EPA 600/R-14/061 September 2014 | www.epa.gov/ord
c/EPA
LEACHING ENVIRONMENTAL ASSESSMENT FRAMEWORK
United States
Environmental Protection
Agency
Leaching Test Relationships, Laboratory-to-
Field Comparisons and Recommendations for
Leaching Evaluation using the Leaching
Environmental Assessment Framework
Office of Research and Developme,
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EPA-600/R-14/061
October 2014
Leaching Test Relationships,
Lab oratory-to-Field Comparisons and
Recommendations for Leaching
Evaluation using the Leaching
Environmental Assessment Framework
[LEAF]
D.S. Kosson1, H.A. van derSloot2, A.C. Garrabrants1 and P.P.A.B. Seignette3
1 Vanderbilt University
Civil and Environmental Engineering
Nashville, TN 37215
2 Hans van der Sloot Consultancy
Langedijk, The Netherlands
3 Energy Research Centre of The Netherlands
Petten, The Netherlands
Category III / Applied Research
Contract No. EP-C-09-027
Work Assignment No. 3-07
Prepared for
Susan A. Thorneloe
U.S. Environmental Protection Agency
Office of Research and Development
National Risk Management Research Laboratory
Air Pollution Prevention and Control Division
Research Triangle Park, NC 27711
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Notice
The U.S. Environmental Protection Agency
through its Office of Research and Development
partially funded and managed the research
described here under Contract Number EP-C-
09-27 coordinated by ARCADIS-US, Inc. This
report has been subjected to the Agency's peer
and administrative review and has been
approved for publication as an EPA document.
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Acknowledgements
This document represents years of work collecting and analyzing data over multiple decades.
We want to thank all of the organizations and individuals providing data and analyses that
made the comparisons in this report possible. Those people include:
Christian Engelsen, SINTEF, Oslo, Norway (Recycled concrete lab and field]
Ole Hjelmar, DHI, H0rsholm, Denmark (Coal fly ash field data, MSWI BA field
data]
Ken Ladwig, Electric Power Research Institute, United States (Coal fly ash landfill
leachate, coal combustion fixated scrubber sludge with lime landfill)
Gerd Spanka, VDZ, Diisseldorf, Germany (Cement mortars and field samples
concrete]
Rudiger Stenger, Holcim, Switzerland (Worldwide cement mortars]
David Bendz, SGI, Linkoping, Sweden (MSWI BA field data]
Andre van Zomeren, ECN, Petten, The Netherlands (MSWI BA Lab and field Nauerna,
Field Stabilized waste field]
Dutch Foundation for Sustainable Landfilling p/a Dutch Waste Management
Association's Hertogenbosch The Netherlands with:
Rob Bleijerveld, Van Gansewinkel Maasvlakte, Maasvlakte, The Netherlands
(Maasvlakte pilot stabilised waste]
Heijo Scharff, Afvalzorg, Nauerna< The Netherlands (Nauerna pilot]
Hans Woelders, Attero, Wijster, The Netherlands (Landgraaf pilot]
We also wish to thank all of the reviewers of the report including:
Craig H. Benson, Ph.D., P.E.
Richard Benware, OSWER/ORCR
Kevin H. Gardner, Ph.D., P.E.
Greg Helms, OSWER/ORCR
Douglas McKinney ORD/NRMRL/APPCD
Constance L. Senior, Ph.D
Richard Shores, ORD/NRMRL/APPCD
Bob Wright, ORD/NRMRL/APPCD
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ABSTRACT
This report presents examples of the relationships between the results of laboratory
leaching tests, as defined by the Leaching Environmental Assessment Framework (LEAF) or
analogous international test methods, and leaching of constituents from a broad range of
materials under disposal and beneficial use scenarios. A framework is defined for
interpretation of laboratory testing results, including approaches for comparison of
laboratory testing of fresh or field aged materials and leachate results from field
applications. This report also illustrates the use of chemical speciation modeling for
interpretation of leaching data and facilitated evaluation of scenarios beyond the conditions
of laboratory testing. This report then provides recommendations for selection and use of
the LEAF test methods, data interpretation, and chemical speciation-based models as tools
for environmental leaching assessment.
Ten field cases were evaluated to illustrate how LEAF results can be used to compare to field
leachate data for either the disposal or beneficial use of seven different materials. The field
data presented in this report include leachate from field lysimeters, pore water from landfill
or use applications, eluates from leaching tests conducted on sample cores taken from field
sites, and leachate collected from landfills. The LEAF laboratory leaching tests in the
comparisons are shown to be effective for estimating the field leaching behavior for a wide
range of materials under both disposal and use conditions.
Interpretation of laboratory leaching test results to the field must be conducted within the
context of the controlling physical and chemical mechanisms of the field scenario (e.g., pH,
L/S, mode of water contact). The effects of field conditions that are beyond the physical-
chemical domain of the laboratory test conditions can be evaluated through a combination
of empirical calculations to extrapolate laboratory results and chemical speciation and
reactive mass transport simulations that are calibrated based on LEAF testing results. Both
direct laboratory testing results and outcomes from chemical speciation and reactive mass
transport simulations can be used to provide a source term for subsequent fate and
transport and risk assessment evaluations.
in
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EXECUTIVE SUMMARY
ES-1 Objectives and Background
The primary objective of this report is to provide an evaluation of the applicability and
limitations of using laboratory leaching tests, as defined by the LEAF and LEAF-analogous
methods, for estimating leaching of constituents of potential concern (COPCs) from a broad
range of materials under field disposal and beneficial use scenarios. This evaluation
compares results from laboratory testing of "as produced" material using LEAF methods,
laboratory testing of "field aged" material, and field leaching studies of the material.
Interpretation of LEAF leaching data is conducted within the context of a defined conceptual
leaching model. Chemical speciation modeling is used as a tool to facilitate evaluation of
scenarios beyond the conditions of common laboratory testing (i.e., normalize the
laboratory data to the field conditions by estimating the impact of factors not practical to
achieve in the laboratory, but which are known to occur and affect leaching). A second
objective of this report is to provide recommendations on the selection and use of LEAF
testing for different types of materials or wastes when evaluating disposal or use scenarios.
The Leaching Environmental Assessment Framework (LEAF) is fundamentally different
than the simulation-based approach to testing, such as used for the toxicity characteristic
leaching procedure (TCLP)1, because it focuses on characterization of intrinsic material-
specific leaching behaviors controlling the release of COPCs from solid materials over a
broad range of test and environmental conditions, with application of the resulting leaching
data to specific disposal or use conditions (Kosson et al., 2002). The framework consists of
four laboratory leaching methods, data management tools, and leaching assessment
approaches developed by Vanderbilt University in conjunction with U.S. EPA and
international partners.
The four leach testing methods described in LEAF have been validated through
interlaboratory studies (Garrabrants et al., 2012a, 2012b) and adopted into SW-846, the
EPA compendium of laboratory tests (EPA, 2013a) as:
Method 1313 - Liquid-Solid Partitioning as a Function of Extract pH using a Parallel
Batch Extraction Procedure
Method 1314 - Liquid-Solid Partitioning as a Function of Liquid-Solid Ratio for
Constituents in Solid Materials using an Up-flow Percolation Column Procedure
Method 1315 - Mass Transfer Rates in Monolithic and Compacted Granular
Materials using a Semi-Dynamic Tank Leaching Procedure
Method 1316- Liquid-Solid Partitioning as a Function of Liquid-Solid Ratio in Solid
Materials using a Parallel Batch Extraction Procedure
These tests may be applied to solid materials to determine fundamental leaching
parameters including liquid-solid partitioning (LSP) of constituents as a function of pH and
i TCLP was designed to simulate a plausible mismanagement scenario of co-disposal in a municipal solid waste
landfill.
IV
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cumulative liquid-to-solid ratio (L/S) as well as the rate of constituent mass transfer from
monolithic and compacted granular materials. Coordinated development of LEAF has
occurred between research laboratories in the United States (U.S.) and the European Union
(EU). The general approach and test methods described in this report also are applicable to
assess release of organic substances, radionuclides and nano-particles. However, additional
consideration is needed with respect to compatibility of the constituents of interest to the
container materials used.
Leaching tests are tools used for estimating the environmental impact associated with
disposal or utilization of materials and wastes on the land (e.g., soils, sediments, industrial
wastes, demolition debris, etc.). Results of leaching assessments based on testing and
interpretive models provide a source term as one part of an evaluation of environmental
safety. In addition to test results, integral factors in applicability assessment or criteria
development for use and disposal include (i) definition and application of appropriate fate
and transport models from the source to the points of compliance and (ii) establishment of
risk-informed constituent concentration thresholds at defined points of compliance.
Characterization of leaching behavior using the LEAF tests along with scenario-specific
information can be used to assemble a leaching "source term" for many environmental
scenarios or levels of environmental assessment including:
screening level assessments at a site-specific, regional or national scale;
detailed site-specific evaluations;
performance comparisons between different materials or treatment processes
under specific disposal or use scenarios;
development of chemical speciation based models to evaluate potential material
leaching behavior under field conditions that may be difficult or impossible to
reproduce in the laboratory.
Assessing the applicability and accuracy of any predictive leaching assessment approach,
however, requires evaluation through the use of pilot- and full-scale field studies in which
leaching predictions for a particular material based on laboratory testing may be compared
to measured leachate concentrations for that material collected under field conditions.
Field studies also provide information regarding the relative importance of natural
processes on leaching of COPCs including water flow patterns, extent of local chemical
equilibrium, and chemical changes due to aging or exposure to the environment.
This report facilitates understanding application and accuracy of the LEAF test methods by
addressing the following important relationships of LEAF test data:
within datasets from the different LEAF test methods conducted on the same
material;
compared to the results of test methods currently in more widespread use,
specifically the Toxicity Characteristic Leaching Procedure (TCLP; EPA Method
1311) and the Synthetic Precipitation Leaching Procedure (SPLP; EPA Method
1312);
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relative to field leaching and material behavior over a wider set of disposal and use
scenarios;
in conjunction with chemical speciation modeling and other knowledge to evaluate
leaching under conditions beyond typical laboratory testing conditions.
Furthermore, this report provides recommendations for how environmental scientists,
engineers and regulators may use LEAF as part of their evaluation programs.
ES-2 Evaluation Cases
In order to illustrate the relationship between laboratory data and field measurements, ten
disposal and beneficial use cases for which both laboratory and field data exist have been
identified and are presented in this report. These ten field evaluation cases consist of
combinations of laboratory testing and field analysis for the following seven materials:
coal fly ash (CFA; 3 cases);
fixated scrubber sludge with lime (FSSL) produced at some coal-fired power plants by
combining coal fly ash with flue gas desulfurization (FGD) scrubber residue and lime (1
case),
municipal solid waste incinerator bottom ash (MSWI-BA; 2 cases);
a predominantly inorganic waste mixture comprised of residues from soil cleanup
residues, contaminated soil, sediments, construction and demolition (C&D) waste and
small industry waste (IND; 1 case);
municipal solid waste (MSW; 1 case);
cement-stabilized municipal solid waste incinerator fly ash (S-MSWI-FA; 1 case);
portland cement mortars and concrete (1 case).
Table 1-1ES-1 provides a summary of the cases and data sets evaluated in this report. In
this table, the types of leaching test data (i.e., laboratory tests conducted on "as produced"
site materials,2 analog materials or field materials), field data (i.e., leachates collected from
the field application) and case conditions are defined for each case. The symbols
representing leaching test data for the cases in Table 1-1 include "pH" for pH dependent
leaching data (e.g., from Method 1313 or equivalent), "L/S" for L/S-dependent leaching data
(e.g., Method 1316 or equivalent), "Perc" for percolation column data (e.g., from Method
1314 or equivalent), and "MT" for mass transfer data (e.g., from Method 1315 or
equivalent). For a few of the field case studies where laboratory test results were not
available for the specific material present in the field, laboratory test results on closely
analogous materials are used for comparison with field measurements. The field data
presented in this report include (i) leachate from field lysimeters, (ii) porewater from
landfill or use applications, (iii) eluate from leaching tests on sample cores taken from field
sites, and (iv) leachate collected from landfills.
2 In this report, "as produced" materials refer to newly processed materials that are ready for disposal or
beneficial use in a field application. This distinction is made relative to aged field materials that have been
retrieved from a field application for testing in the laboratory.
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Table ES-1. Summary of Laboratory-To-Field Comparison Cases.
Report
Section
Case Name (Country)
Leaching Test Data Field Data
Site Analog Field Leachates
Materials Materials Materials
Case Conditions
4.1 Coal Fly Ash Landfill
Leachate (U.S.)
4.2 Coal Fly Ash in Large-Scale
Field Lysimeters (Denmark)
4.3 Landfill of Coal Combustion
Fixated Scrubber Sludge
with Lime (U.S.)
4.4 Coal Fly Ash Used in
Roadbase and Embankments
(The Netherlands)
4.5 Municipal Solid Waste
(MSW) Incinerator Bottom
Ash Landfill (Denmark)
4.6 MSW Incinerator Bottom
Ash Used in Roadbase
(Sweden)
4.7 Inorganic Industrial Waste
Landfill (The Netherlands)
4.8 MSW Landfill
(The Netherlands)
4.9 Stabilized MSW Incinerator
Fly Ash Disposal (The
Netherlands)
4.10 Portland Cement Mortars
and Concrete (Germany,
Norway, The Netherlands)
pH
L/S
Perc
L/S
pH - pH
L/S L/S
MT
L/S
pH
Perc
pH pH
Perc L/S
Perc
pH - pH
Perc L/S
Perc
pH - pH
Perc L/S
Perc
pH - pH
Perc
MT
pH pH pH
(recycled
concrete)
Multiple
landfills
Lysimeters
Landfill
Roadbase,
Embankment
Landfill
Roadbase test
section
Lysimeters,
Landfill
Landfill,
Multiple
landfills
Pilot test cells.
Landfill
Ox-Red,
pH6-13
Ox-Red,
pH 11-13
Ox,
pH 6-12
pH8-12
Reducing,
pH7-ll
Ox-Red,
pH 7-10
Ox-Red,
pH6-9
Strongly reducing.
High DOC,
pH5-9
Oxidizing,
pH8-13
Oxidizing,
Carbonation,
pH8-13
Notes:
pH =
L/S =
Perc =
MT =
pH-dependent leaching data (e.g., EPA Method 1313,PrEN 14429, PrEN 14997).
L/S-dependent data with deionized or demineralized water (e.g., EPA Method 1316, EN 12547).
Percolation column data, up-flow or down-flow (e.g., EPA Method 1314, CEN/TS 14405).
Monolith or compacted granular mass transfer data (e.g., EPA Method 1315, PrEN 15863).
Ox-Red = oxidized to reducing conditions.
i Site Materials refers to "as produced" source materials placed into the field application.
2 Analog Materials refers to comparative materials for cases where source material sample leaching
characterization information was not available.
3 Field Materials refers to materials retrieved from a field application for laboratory testing.
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The field component and laboratory testing comparison for each case is as follows:
Case 1 (ง 4.1) examined the leaching behavior of coal fly ash under landfill disposal
conditions as a class of materials by comparing the leaching concentration ranges and
pH dependent relationships for field leachates and pore water in comparison to
laboratory test results obtained from LEAF testing of a wide range of coal fly ash
samples.
Case 2 (ง 4.2) compared the field leaching from large scale lysimeters over 7 years to
results from laboratory percolation column tests.
Case 3 (ง 4.3) compared field leaching, field pore water samples, and laboratory
leaching test results on landfill core samples, laboratory leaching test results on fresh
"as disposed" material for mixed coal fly ash and FGD scrubber residues, referred to as
fixated scrubber sludge.
Case 4 (ง 4.4) compared the results of field leaching over 2 years from a road base and
embankment constructed with coal fly ash to percolation column results. Laboratory pH
dependent leaching test results from an analogous material were also used for
comparison.
Case 5 (ง 4.5) focused on landfill leaching from combined MSWI bottom ash and MSWI
fly ash that was deposited in layers and monitored for 30 years. Field leaching results
were compared to laboratory leaching of core samples obtained from the landfill and
laboratory pH dependent test and percolation column test results from analogous
materials.
Case 6 (ง 4.6) focused on MSWI bottom ash used as a subbase below an unbound base
course and surface asphalt layers that was cored and evaluated 15 years after the road
construction. Single point leaching was carried out on an extensive set of samples (n=
53) to evaluate the heterogeneity of material and exposure under field conditions.
Case 7 (ง 4.7) focused on comparison of laboratory and field lysimeter results to
leaching from a 12,000 m3 field pilot landfill for a mixture of predominantly inorganic
wastes.
Case 8 (ง 4.8) focused on a 45,000 m3 pilot-scale landfill for MSW in Landgraaf, The
Netherlands, that was filled with a mixture of sewage sludge, construction and
demolition (C&D) waste, MSW, industrial waste, car shredder waste, foundry sand, and
soil cleanup residue. The pilot study was established to evaluate the biodegradation of
organic matter-rich waste by leachate renewal and recycling.
Case 9 (ง 4.9) focused on a pilot-scale field demonstration of near surface disposal of
MSWI fly ash stabilized with a mixture of pozzolonic binders (i.e., multiple ash types).
Initial samples of the stabilized material were subjected to laboratory leaching tests.
Leachate and runoff was collected during that evaluation period of approximately 4
years, after which cores were taken of the stabilized material for laboratory leaching
testing. Comparative results were also available from a full-scale monofill receiving the
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same stabilized waste. In addition, laboratory leaching was carried on cores obtained
from field testing after 10 years from a corresponding full-scale facility.
Case 10 (ง 4.10) compared the leaching of cement and concrete samples with different
aging periods, including 28 days (standard mortar), 4 years (recycled concrete
aggregate), 40 years (field test site) and 2,000 years (Roman cement).
For each evaluation case, the following generalized approach was used to compare
laboratory test results for a material to its field leaching:
(i) LSP Leaching - laboratory leaching results provide an understanding of the LSP for
COPCs as a function of pH (e.g., from Method 1313) or L/S (e.g., from Method 1316
or Method 1314). [Field values for these parameters were also obtained]
(ii) Dynamic Leaching - percolation column leaching test results (e.g., from Method
1314) provide an understanding of percolation-controlled leaching of COPCs under
idealized conditions, and/or mass transport leaching test results (e.g., Method
1315) provide intrinsic COPC release rates.
(iii) Laboratory-to-Field Comparison - laboratory LSP or dynamic leaching results (e.g.,
percolation or mass transport data) and conditions are compared with results and
conditions measured in the field scenario to evaluate whether local equilibrium is
controlling observed leaching under field conditions. If not, this comparison is
used to determine the extent of preferential flow effects in percolation scenarios or
limited water contact in mass transport scenarios.
(iv) Chemical Speciation and Reactive Transport Modeling - a chemical speciation
fingerprint (CSF) for the material of interest and subsequent reactive transport
modeling (i.e., combination of speciation and mass transport models) are used to
explore the extent that non-ideal conditions (e.g., preferential flow) and aging
conditions (e.g., redox changes, carbonation, etc.) influence observed field leaching
behavior.
The broad range of potential uses of environmental leaching assessment implies that there
is a need for a graded or tiered approach that provides for flexible, scenario-based
assessments and allows tailoring of the needed testing and information based on the type of
intended use of the assessment and available prior or related information. Furthermore,
determination of constituent leaching estimates that are greater than or equal to the actual
expected constituent leaching is necessary to maintain environmental protection in the face
of uncertainty (often referred to as a "conservative" approach). The extent of the
assessment bias toward over-estimation of COPC leaching should depend on the nature of
the decision and the uncertainties regarding the available material and scenario
information. However, even when used as a screening test, LEAF methods provide release
estimates that are more accurate, reliable (because of test conditions defined based on
fundamental principles of environmental chemistry and mass transport) and robust (able to
consider multiple or evolving physical-chemical conditions) than are obtainable using any
single-point leaching test. Testing using LEAF is considered to be more accurate because of
the ability to consider the range of anticipated environmental conditions and intrinsic
leaching characteristics of materials.
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ES-3 Leaching Fundamentals and Use of Laboratory Leaching Data
LEAF is described in detail within the report and provides a conceptual framework for
interpreting characteristic leaching behavior and comparing LEAF laboratory test results to
field leaching. Detailed material characterization consists of laboratory measurement (i)
LSP as a function of pH (pH-dependent leaching), (ii) LSP as a function of L/S either by
percolation column or by parallel batch procedures, and (iii) rates of mass transport under
diffusion-controlled conditions.
Equilibrium-based leaching test measure LSP under specified test conditions. For example,
Methods 1313 and 1316 determine the effect of pH and L/S, respectively, on LSP under
batch test conditions which are intended to approximate chemical equilibrium between the
aqueous and solid phases (Garrabrants et al., 2010). Column percolation tests carried out at
relatively slow flow conditions (e.g., residence time ~1 day or less) approximate local
equilibrium between the pore solution and solid phase at any given point in the column.
Column percolation tests also often are considered a surrogate for field leaching conditions
for scenarios where infiltration or groundwater passes through a relatively permeable solid;
however, field conditions are much more likely subject to preferential flow, and therefore
infiltration bypassing the material in question results in lower observed concentrations in
the field than the laboratory.
The following are characteristic responses of LSP observed from equilibrium-based leaching
tests:
Response 1. Total Content vs. Availability. The fraction of the specific constituent that is
not bound in recalcitrant phases and is released over the domain of leaching conditions (i.e.,
L/S=10 mL/g dry and pH between 2 and 13) is considered the available fraction of the total
content in the material, often referred to as "availability." The sum of the constituent
incorporated into recalcitrant phases and the available content of that constituent is equal
to the total content of the constituent in the material.
Response 2. LSP less than Aqueous Solubility. A constituent, or fraction thereof, may be
present in one or more readily soluble solid phases that dissolve fully into the aqueous
phase under the leaching test conditions with the resultant constituent concentration in the
aqueous phase less than the aqueous solubility (i.e., an under-saturated solution based on
chemical thermodynamics). One example of this case is the dissolution of sodium chloride
when the total amount of dissolvable sodium and chloride results in concentrations in the
aqueous phase that are less than the respective solubility for each constituent. In this case,
the available content of a constituent could be the limiting factor in the concentration seen
in laboratory testing (referred to as "availability-limited" leaching).
Response 3. LSP at Aqueous Solubility. A constituent, or fraction thereof, may be present
in one or more solid phases that will only partially dissolve into the aqueous phase under
the leaching test conditions with the resulting constituent concentration in the aqueous
phase at the aqueous solubility (i.e., a saturated solution). This phenomenon is referred to
as "solubility-controlled" release.
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Response 4. Surface Interaction. A constituent, or fraction thereof, may be present as a
readily soluble species that is not initially present in the material as a distinct, precipitated
solid phase. The constituent species may be present at a relatively low concentration and
associated with a reactive solid surface where the LSP is controlled by
adsorption/desorption or ion exchange phenomena. Such reactive surfaces include oxide
minerals (e.g., iron, manganese, or alumina (hydr)oxides), (ii) clay-like minerals, (iii)
particulate organic carbon (such as from decay of plant matter), and (iv) particulate carbon
(such as char from combustion or activated carbon).
For many constituents, the initial speciation (i.e., chemical forms) and distribution in the
solid material are often a combination of two or more of the four phenomena described as
characteristic responses above. Primary factors that can modify the LSP of a particular
constituent are pH, eluate ionic strength and aqueous phase complexation.3 For
constituents with multiple valence states under the range of oxidizing to reducing
conditions observed in the field, the oxidation-reduction potential (ORP) of the pore water
and bulk solutions in contact with solid materials can influence the resulting LSP and
precipitated solid phases. The effect of redox conditions can also extend to constituents
with only single valence state because of precipitation with reduced species (i.e., zinc
precipitation with sulfides).
Laboratory leaching test results from pH dependent leaching (e.g., Method 1313) are used in
this report in conjunction with other information known about a material (e.g., availability
data, total carbon, etc.) to develop a "chemical speciation fingerprint" (CSF). This CSF
includes the set of mineral phases, adsorbing surfaces, organic matter fractionation and the
fraction of the total content of each constituent that is available for leaching. The resulting
CSF may be used in conjunction with the results of L/S-dependence tests to assess the
impact of low L/S ratios (such as those present under field conditions) on LSP or with
results from percolation column tests (e.g., Method 1314) or results from mass transport
(e.g., Method 1315) to calibrate needed mass transport parameters for simulations of
dynamic leaching tests (i.e., mobile-immobile fractions for percolation column tests or
tortuosity for monolith diffusion tests). The resulting combination of the CSF and mass
transport parameters may then be used in conjunction with one or more field conceptual
models (i.e., percolation with preferential flow or diffusion controlled release from a
monolith) and a variety of initial and boundary conditions (e.g., system geometry,
infiltration rate and chemistry, redox state, etc.) to estimate release under a range of field
scenarios. Characterization of uncertainty at each step is needed to understand the accuracy
and limitations of each simulation.
3 The final conditions achieved during a leaching test or field conditions define the LSP, not the initial test
conditions, because these are the conditions that define liquid-solid equilibrium. Thus, the pH of an eluate at the
conclusion of a leaching test defines LSP, not the initial pH of the eluent.
XI
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ES-4 Case Summaries
Each of the cases included consideration of multiple constituents (from 5 up to 29 per
individual case) that illustrated each of the characteristic leaching responses indicated
above and provided the basis for understanding relationships between laboratory test
results and field data as a function of constituent, material and field management scenario.
The observed field pH domain, constituents considered and the primary conclusions for
each of the case studies are presented in Table ES-2. The observed field pH domain
indicated for a specific case may be narrower than what would be considered the applicable
pH domain for the material and field scenario when applied prospectively because (i) the
range of material characteristics may be broader than the specific materials tested in
individual cases (for example, coal fly ash may range from very alkaline to acidic, as
indicated by Case 1 but the specific coal fly ash evaluated in Case 2 was alkaline), and (ii) the
relatively short duration of field testing (i.e., typically less than 10 years) may not fully
re fleet the long-term aging of the materials (for example, strongly alkaline materials are
expected to react with atmospheric or biogenic carbon dioxide to result in slightly alkaline
pHofca. 8-9).
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Table ES-2. The observed field pH domain, constituents considered and the primary conclusions for each of the case studies.
Report Case Name (Country) pH Constituents
Section Domain Considered
Primary Conclusions
4.1
4.2
Coal Fly Ash Landfill
Leachate (U.S.)
Coal Fly Ash in Large-
Scale Field Lysimeters
(Denmark)
4.3 Landfill of Coal
Combustion Fixated
Scrubber Sludge with
Lime (U.S.)
6-13 Al, As, B, Ca, Cd, For a well-defined class of materials, the upper range of constituent
Co, Cr, Cu, F, Fe, K, concentrations from pH dependent testing over the relevant pH domain can be
Li, Mg, Mo, Mn, considered a conservative estimate of the upper limit of field concentrations
Na, Ni, Pb, S, Se, constituents where solubility limits leaching. For highly soluble constituents,
Si, Sr, Tl, V, Zn pH dependent test concentrations should be adjusted based on a correction
factor between laboratory L/S and field pore water L/S. Field leachate
DOC concentrations lower than anticipated may be a consequence of either (i)
reducing conditions (as seen for chromium and selenium) or (ii) common ion
effects (as seen for barium in the presence of sulfate).
11-13 Al, As, B, Ba, Br, Laboratory percolation column testing provide a good estimate of initial
Ca, Cd, Cl, Cr, Cu, leachate concentrations under field conditions. Laboratory percolation column
Fe, Hg, K, Li, Mg, testing also provides a good approximation of the evolution of leaching profiles
Mn, Mo, Na, Ni, P, as a function of L/S that would be expected under field conditions in the
Pb, S, Sb, Se, Sn, absence of preferential flow and establishment of reducing conditions.
Sr,V, Zn;DOC
6-12 Al, As, B, Ba, Ca, Carbonation of samples during field aging had a significant impact on the pH
Cd, Cl, Co, Cr, Cu, dependent leaching behavior of periodic table Group II elements (i.e., calcium,
F, K, Li, Mg, Mn, strontium) and some trace elements (i.e., arsenic). Higher concentrations of
Mo, Na, S, Sb, Se, highly soluble species (i.e., potassium, sodium, chloride) observed in porewater
Si, Sr, Tl, Ti, V, Zn compared laboratory testing can be readily estimated based on the ratio of
laboratory L/S to field porewater L/S.
DOC
8-12 Ca, Cr, Mo, S, Se, The combined use of pH dependent leaching, percolation column leaching and
chemical speciation simulations provided insights into the redox condition in
the material (establishment of reducing conditions), impacts of carbonation,
and the resultant consequences for leaching of oxyanions (e.g., chromium).
Percolation column experiments provided a realistic estimate of the upper
bound concentration for leaching of CO PCs.
4.4 Coal Fly Ash Used in
Roadbase and
Embankments
(The Netherlands)
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Report Case Name (Country) pH Constituents
Section Domain Considered
Primary Conclusions
4.5
Municipal Solid Waste
(MSW) Incinerator
Bottom Ash Landfill
(Denmark)
4.6
4.7
MSW Incinerator Bottom
Ash Used in Roadbase
(Sweden)
Inorganic Industrial
Waste Landfill (The
Netherlands)
7-11 Al, Cd, Ca, Cl, Cr,
Cu, Fe, K, Mg, Mn,
Na, Ni, Pb, P, Zn
7-10
6-9
As, Al, B, Ba, Br,
Ca, Cd, Cl, Cr, Co,
Cu, Fe, K, Li, Mg,
Mn, Mo, Na, Ni, P,
Pb, S, Sb, Se, Si,
Sr, V, Zn
DOC
Concentrations obtained from laboratory batch extractions at L/S of 2 mL/g can
be used as an estimate of peak concentrations in leachate from a heterogeneous
fill material. The L/S of 2 L/kg is greater than the expected porewater L/S of ca.
0.2 to 0.5 L/kg but reflects the impacts of preferential flow through a
heterogeneous material in a landfill. Testing at L/S of 2 mL/g in conjunction
with pH dependent testing (at L/S of 10 mL/g) provides an estimate of
increased concentrations relative to pH dependent testing that would be
expected for highly soluble constituents and resulting from dissolved organic
carbon (DOC) complexation effects at the low L/S values associated with early
leachate from MSW landfills.
Al, As, Ba, Ca, Cd,
Cr, Cl, Cu, Fe, Hg,
K, Mg, Mo, Na, Ni,
P, Pb, S, Se, V, Zn
DOC
Laboratory testing of composite samples from field cores using pH dependent
leaching and percolation column tests showed LSP and column elution
consistent with leaching of MSW incinerator bottom ash from other sources
with respect to both highly soluble constituents (e.g., Na, K, Cl) and constituents
where solubility limits LSP as a function of pH (e.g., Ca, Cu, Pb, Zn). Combined
leaching test results and chemical speciation modeling illustrated (i) the effects
of DOC complexation to increase aqueous concentrations of copper, lead and
zinc, and (ii) the effects of L/S on the expected concentrations of highly soluble
and solubility limited constituents as a function of pH, with lower L/S
conditions resulting in increased aqueous concentrations when the constituent
solubility is not limiting leaching.
Laboratory testing data obtained under oxidizing to mildly reducing conditions
can be used in conjunction with chemical speciation modeling to estimate field
leaching under mildly to strongly reducing conditions. The effects of reducing
conditions include (i) chemical reduction of iron resulting in loss of HFO
sorptive surfaces and increased dissolved iron, (ii) increased biogenic DOC
concentrations, and (iii) increased leaching of some species resulting from
chemical reduction to more soluble species, loss of iron oxide sorption sites,
and/or increased partitioning into the leachate by complexation with DOC. For
several constituents (i.e., arsenic, barium, chromium, copper, iron, phosphorous)
the maximum concentrations observed in the field pilot-scale landfill were
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Report Case Name (Country) pH Constituents
Section Domain Considered
Primary Conclusions
significantly greater than maximum concentrations indicated by the laboratory
column testing. However, leaching of many constituents was not impacted by
the reducing conditions. These differing effects point to the need of a priori
knowledge of the adsorption, solubilization and precipitation chemistry of
different elements to interpret leaching results and the benefits of using
chemical speciation modeling to facilitate interpretation.
4.8 MSW Landfill
(The Netherlands)
5-9 Al, As, Ba, Ca, Cd,
Cl,Cr,Cu, Fe,Hg,
K, Mg, Mo, Na,
Ni, P, Pb, Se, V, Zn
DOC
Peak concentrations for highly soluble species from laboratory percolation
column at L/S 0.5 mL/g agreed well with peak leachate concentrations from the
landfill and were a factor of 20 times greater than observed using pH dependent
leaching test at L/S 10 mL/g. Reducing conditions in the landfill resulted in
higher concentrations in leachate than observed at corresponding pH values
during pH dependent laboratory testing. Chemical speciation modeling based
on laboratory testing under oxidized conditions facilitated understanding of
leaching under expected reducing conditions in the field.
4.9
Stabilized MSW
Incinerator Fly Ash
Disposal (The
Netherlands)
8-13 Al, As, Ba, Ca, Cl,
Cr, Cu, Fe, Hg, K,
Mg, Mn, Mo, Na,
Ni, Pb, S, Se, Sr, V,
Zn
DOC
The observed peak field leachate concentrations of anionic species such as
sulfate and oxyanions of arsenic, molybdenum, selenium, are indicative of pore-
water (L/S ~0.2-0.5 mL/g, based on porosity of ca. 0.2-0.5) and are
approximated as 20 times the concentration observed at corresponding pH in
the pH-dependence test (L/S=10 mL/g). Peak monofill leachate concentrations
of chloride and potassium were approximately a factor of 10 greater than
measured using pH dependent testing on freshly prepared material and
approximately half of peak values from percolation column tests, likely because
of diffusion controlled release and preferential flow. Carbonation at the surface
of the stabilized material from reaction with atmospheric carbon dioxide
resulted in lower pH (6-9) for runoff and leachate samples and characteristic
reductions in leaching of calcium, barium and strontium. Field leachate
concentrations indicate solubility controlled (local equilibrium with the surface)
for several constituents (e.g., copper, chromium, manganese) and were
consistent with pH dependent leaching test results.
in
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Report Case Name (Country) pH Constituents
Section Domain Considered
Primary Conclusions
4.10
Portland Cement Mortars
and Concrete (Germany,
Norway, The
Netherlands)
7-13
Al, As, B, Ba, Ca, I Carbonation results in increased leaching of Ca, Ba, Sr and sulfate, consistent
Cd, Cr, Cu, Fe, K, with loss of the ettringite mineral phase and pH dependent leaching test results.
Li, Mg, Mn, Mo, Increased leaching of oxyanions (e.g., molybdate, arsenate and chromate) also
Ni, P, Pb, S, Sb, Si, occurs with carbonation because of dissolution of the oxyanions substituted for
Sn, Sr, Zn sulfate in ettringite. pH dependent leaching test results on uncarbonated
material can be used to estimate oxyanion leaching from carbonated materials
DOC at pH less than 10.
IV
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ES-5 Recommendations for Use of the LEAF Test Methods for Beneficial Use and
Disposal Decisions
LEAF test results can be used to provide a reasonably conservative (upper-bound) source-
term for a wide range of materials in use and disposal scenarios. The resulting source term
should be used in conjunction with additional assessment steps that include consideration
of dilution and attenuation from the source to receptor, and relevant receptor thresholds.
Information presented in this report supports grouping individual sources of similar
materials based on process origin and leaching behavior into material grouping or classes
(i.e., coal fly ash from combustion of bituminous coal, coal combustion flue gas
desulfurization gypsum, blastfurnace slags, MSWI bottom ash, etc.). Accumulation of LEAF
testing data for a range of materials and over time can provide useful estimates of
uncertainty and variability associated with leaching from specific materials and material
classes. Creation of one or more databases containing leaching data used in regulatory
decision making and monitoring can facilitate efficient use of leaching data in future
assessments, including by reducing testing and evaluation costs for well-studied classes of
materials.
Evaluating New Management Scenarios - Material Combinations and Pilot Studies
Leaching assessment can present two forms of challenges:
1. Evaluating a new use or disposal scenario for a previously evaluated material or
material class; and,
2. Evaluating a new material class or specific material without prior characterization
of materials within the same material class.
Careful consideration should be given to the extent of prior knowledge about both the
material or class of material, and the anticipated use or disposal scenario before proceeding.
Consideration should be given to the potential range and changes that may occur with
respect to water contact, physical integrity of the material, blending or interfaces with other
materials, chemistry within the material and of contacting solutions, and evolution of pH
and redox (e.g., from atmospheric exchange, carbonation, sulfide oxidation, organic matter
degradation, etc.). Insufficient prior leaching characterization data or experience with
sufficiently similar materials under analogous management scenarios should trigger use of
a field pilot demonstration project, when warranted based on a screening assessment that
includes laboratory characterization, to insure that a priori unforeseen conditions do not
result in a significant shift in the phenomena controlling leaching for the material and
scenario under consideration.
The case studies presented in this report provide the basis for recommending specific
components and considerations for initial material characterization and field demonstration
projects.
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Estimating Leaching Source Terms
In Kosson et al. (2002), leaching assessment using a performance or "impact-based
approach" was proposed, that subsequently has been referred to as LEAF. The LEAF testing
methodology allows for both empirical use of testing data for specific scenarios as part of a
screening assessment, and use of the leaching test data in conjunction with chemical
speciation and mass transport models to provide a more realistic and refined, scenario-
specific estimate of constituent leaching that can be used as a source-term for risk
assessment. While the screening assessment is a bounding estimate of leaching potential,
consideration of waste and scenario-specific information allows many conservative
assumptions to be replaced with further testing data and mass transport modeling results.
A tiered-approach was proposed for developing the leaching source term, considering the
type of evaluation being carried out, the level of information available, and the extent of
conservatism embedded in the estimate. Subsequently, the EPA published its Methodology
for Evaluating Encapsulated Beneficial Uses of Coal Combustion Residuals (2013b; also EPA,
2014) which describes a tiered approach that can be applied to a more limited set of uses of
two secondary materials (i.e., coal fly ash use as a cement replacement in concrete and FGD
gypsum use in gypsum board). The observations and information gathered in this report
provides a basis for more detailed recommendations provided on the use of LEAF test
methods, consistent with the initially proposed methodology (2002) and the EPA
methodology (2013). It must be emphasized that these recommendations for use of leach
test data only provide the approach for estimating the leaching source term (i.e.,
concentrations and amounts of a constituents leaching from the material under a specific
scenario). Additional determinations are needed to define or account for (i) the location
that serves as the basis for exposure assessment following constituent leaching release from
a source scenario (e.g., point of compliance), (ii) dilution and attenuation in the vadose zone
and groundwater or surface water from the point of release to the point of compliance, and
(iii) appropriate exposure scenarios or reference thresholds (e.g., human health or
ecological thresholds). These evaluations can be incorporated into a model of constituent
fate and transport leading to possible receptor exposure (e.g., groundwater transport to a
drinking water well, with water ingestion as the exposure pathway).
Scenario Definition
Defining the material use or disposal scenario is the first step to selecting the appropriate
leaching tests and basis for interpreting the resulting data. The extent of information
needed as part of the scenario definition increases as the evaluation seeks to achieve a more
detailed and refined estimate of constituent leaching. The initial scenario definition should
at a minimum include determination of the applicable pH domain, range of oxidation-
reduction conditions, and the primary mode and amount of water contact.
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Screening Assessment (Tier 1)
Recommendations for use of LEAF testing in screening assessment (Tier 1) and equilibrium-
based assessment (Tier 2) are provided in Table ES-3. Note that Tier 1 and Tier 2
assessments are independent of the physical form (i.e., granular or monolithic) of the
material. A leaching screening assessment is based on the estimated maximum leaching
concentration anticipated for each COPC that would leach assuming an infinite source4. At
this tier, maximum LSP is estimated based on the maximum concentration for each COPC
measured over the applicable pH domain as defined by the scenario using the pH dependent
leaching test (i.e., Method 1313) and then adjusted for the anticipated pore water L/S,
unless it can be demonstrated that the specific COPC is solubility controlled throughout the
applicable pH domain.
Equilibrium-based Assessment (Tier 2)
An equilibrium-based leaching evaluation would consider LSP over the applicable pH and
redox domains and the maximum amountof each COPC available for leaching. Method 1313
results in conjunction with Method 1316 at L/S of 2 mL/g would be used to assess whether
LSP for each COPC was constrained by aqueous solubility or availability. If the COPC
exhibits significantly greater concentration at L/S of 2 mL/g (Method 1316) then measured
from Method 1313 at the pH corresponding with the pH measured at L/S of 2 mL/g, then
the Method 1313 results are considered to be availability constrained and the maximum
concentration from Method 1313 over the applicable pH domain that is adjusted to the pore
water L/S is used as the peak source concentration. If the COPC at L/S 2 mL/g is the same
as (within uncertainty) the concentration measured at the corresponding pH from Method
1313, then the COPC is considered solubility constrained and the maximum concentration
over the applicable pH domain from Method 1313 is used as the peak source concentration.
The maximum amount of a COPC that is available to leach per unit mass of material (i.e.,
"finite source") is based on the maximum constituent release (i.e., mg/kg) over the entire pH
domain of Method 1313 (typically pH 2 for cations and pH 9 for oxyanions). The amount of
each COPC that leaches should be estimated based on the amount of contacting water per
unit time (i.e., L/S per year) times the estimated peak concentration.
Initial characterization testing (Tier 2B) should include analysis of both major and trace
constituents in all leaching test eluates because knowledge of the major constituents that
control release of the trace constituents provides insights into the factors that may result in
changes in leaching and allow for calibration of chemical speciation models. However, prior
knowledge from testing of analogous materials may reduce the need for or extent of
characterization testing.
4 For regulatory frameworks based on a source term concentration (typical in the United States), the
maximum estimated leaching concentration is recommended for use in screening assessment. For
regulatory frameworks based on the total mass of constituent potentially leached (as used in some
international jurisdictions), availability is recommended for use in screening assessment.
in
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Table ES-3. Tier 1 Screening Assessment and Tier 2 Equilibrium-Based Assessment - Summary of recommended test methods and analyses.
Assessment Type Leaching
Methods
Tier 1 -
Screening
Assessment1
Method 1313
(applicable pH
range only2)
Eluate Analyses
pH, Electrical
conductivity (EC),
COPCs, DOC
Tier 2 - Equilibrium-based Assessment
Tier 2A
Compliance
Tier 2B
Characterization
Tier 2C
Quality Control
Method 1313
(applicable pH
range + pH=2,
7, 9 if not
included)
Method 1316
(L/S=2 mL/g
or lowest L/S
eluate)
Method 1313
(full set of
eluates)
Method 1316
(full set of
eluates)
Method 1313
atnaturalpH,
andpH=2, 7
and/or 9
pH, EC (natural pH
only), COPCs, DOC
pH, EC &pE6 (natural
pH only)7, COPCs, DOC,
DIG, major and minor
constituents (including
P and S)
pH, EC, relevant COPCs9
(natural pH and for
availability) to meet
environmental
requirements and
additional constituents
to meet beneficial use
requirements
Assessment Basis
Maximum leachate cone.3 estimated as 2Ox or lOx maximum eluate cone, for
highly soluble constituents in granular materials4'5 and the measured maximum
eluate cone, for monolithic materials and solubility controlled constituents (all
materials).
^H
Availability estimated as maximum release at measured pH intervals including
pH=2 and 9; provides basis for finite source by assuming that availability is
maximum cumulative release under field conditions. EC used to estimate ionic
strength. Acid/base neutralization capacity to pH=7. Maximum leachate cone.
estimated as determined from Tier 2B based on Method 1313 results over
applicable pH domain. Method 1316 allows identification of solubility
controlled vs highly soluble constituents.
Availability as indicated in Tier 2A.
Liquid-solid partitioning as a function of pH used for speciation assessment.8
Provides baseline understanding of material leaching behavior. Supports
chemical speciation simulations to understand effects of changes in L/S, pH,
redox, and reactive constituents (e.g., DOC, carbon dioxide, etc.). Maximum
leaching concentration as indicated for Tier 1 or based on simulation results at
L/S of the material pore solution. Method 1316 provides basis for
determination of solubility control and verification of chemical speciation
modeling at low L/S.
Used to verify leaching over "applicable" pH range, acid/base neutralization
capacity to pH=7, and availability of relevant COPCs and other (if applicable)
constituents central to beneficial use application (e.g., Ca, sulfate, etc.). Assumes
definition after completion of Tier 2B and/or analogous prior information.10
Chemical analysis only for determination of leaching at natural pH and
availability (2 or 3 extracts). Further simplification may be possible based on
additional available information.
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Notes for Table ES- 3:
regulatory frameworks based on a source term concentration, the maximum estimated leaching concentration is recommended for
use in screening assessment. For regulatory frameworks based on the total mass of constituent potentially leached, availability is
recommended for use in screening assessment.
2The applicable pH range is determined considering the material's natural pH, changes in pH due to material aging processes, infiltration
conditions, and interfaces or comingling with other materials.
3"conc." is used as an abbreviation for concentration or concentrations.
4Twenty times the maximum eluate concentration is recommended for highly soluble species when the material is homogeneous (e.g., coal
fly ash) and ten times the maximum eluate concentration is recommended for heterogeneous materials (e.g., MSW incinerator bottom
ash) where significant preferential flow is anticipated. Both multipliers are to account for the increased concentrations expected when
estimating pore water concentrations (L/S=0.2 to 0.5 L/kg) from test conditions of L/S=10 mL/g).
5Highly soluble species are Group IA elements (i.e., Na, K), anions (i.e., bromide, chloride, fluoride, nitrate), and oxyanions (i.e., As, B, Cr, Se,
Mo, V.).
6Electron potential as a measure of oxidation reduction conditions (see ง 2.2.3).
Determination of EC and pe is recommended for natural pH eluate only. The sensitivity and uncertainty of pe measurements are
recognized but pe measurement will provide a useful indication of whether or not the material is inherently reducing under abiotic and
anoxic conditions.
8Speciation assessment refers to consideration of the effects of changes in pH, redox conditions, extent of carbonation, complexation with
dissolved organic carbon, etc. which may be accomplished heuristically or in combination with geochemical speciation modeling.
9Relevant COPCs are those constituents that are present in the material and have been found through Tier 2B characterization and/or
prior information to leach at concentrations or release values that approach or challenge regulatory or quality control thresholds.
10Prior information, such as characterization information from similar materials, may reduce or supplant the need for or extent of Tier 2B
characterization.
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Results from Method 1313 also can be used to indicate where increased leachate
concentrations can be anticipated if there is a shift in field pH from the initial pH to other
conditions over the range of pH defined for the specific scenario being evaluated. Chemical
speciation modeling or other knowledge of the system should then be used to determine if
changes in redox or other conditions (i.e., carbonation, infiltration chemistry) are likely to
result in increased or decreased leaching.
For periodic demonstration of compliance with regulatory thresholds, the extent of Method
1313 testing can be reduced to the applicable pH domain and regulatory COPCs, pH and
conductivity5. For quality control purposes, the extent of Method 1313 testing can be
further reduced to only the natural pH value and along with the pH 2 and/or 9 as needed to
measure availability for the relevant COPCs (those that are present and leach at
concentrations that approach thresholds) and conductivity.
Knowledge of the chemical behavior of the COPCs and the scenario should be used to
evaluate if higher leaching concentrations are anticipated because of changes in redox
conditions. Anticipated changes in leaching because of changes in L/S, redox or chemical
conditions can also be evaluated using chemical speciation modeling as demonstrated for
the evaluation cases in this report.
Mass Transport-based Assessment (Tier 3)
Mass transport-based assessment can be divided into two distinct regimes: (i) percolation
through the material as the predominant leaching mechanism, and (ii) mass transport from
monolithic materials where diffusion to the exterior surface of the bulk material and surface
dissolution control constituent leaching. Intermediate conditions between the percolation
and monolith regimes, such as for large aggregates and cracked monolithic materials also
exist, but are beyond the scope of this discussion. Summaries of recommended LEAF testing
and evaluation are provided for percolation mass transport-based assessment and
monolithic mass transport-based assessment in Table ES-4 and Table ES-5, respectively.
Percolation based regimes can be evaluated through use of the pH dependent test (i.e.,
Method 1313) in conjunction with the percolation column test (i.e., Method 1314 or Method
1316 for initial leachate concentrations). Considering the results of Cases 2, 5 and 8
(Sections 4.2, 4.5 and 4.8) initial eluates from Method 1314 or low L/S results from Method
1316 are good indicators of the anticipated COPC concentrations in initial field leachates
and Method 1314 provides the evolution of the leachate concentrations over prolonged
periods based on the progression of the L/S based on the field material geometry and
annual infiltration rates.
5 Measurement of conductivity is recommended as an indicator of total ionic strength and therefore can also
provide an indication if there is a significant change in leaching of total salts over the monitoring interval.
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Table ES-4. Tier 3 Percolation Mass Transport-Based Assessment - Summary of recommended test methods and analyses.
Assessment Type Leaching Eluate Analyses
Methods
Tier 3 - Percolation Mass Transfer Rate-based Assessment
Tier 3A
Compliance
Method 1313
(pH=2, 9,
applicable pH
domain)
Method 1314
(to L/S=2
mL/g)
Tier 3B
Characterization
Tier 3C
Quality Control
Method 1313
(full set of
eluates)
Method 1314
(full set of
eluates)
Method 1316
(L/S=2)
Method 1313
atpH=2, 7
and/or 9 and
Method 1316
at L/S = 2
pH, EC (natural pH
only), COPCs, DOC
pH, EC (natural pH
only), COPCs, DOC, DIG,
major and minor
constituents
pH, EC, COPCs (1313
for availability and
1314 at L/S of peak
release) to meet
environmental
requirements,
additional constituents
to meet beneficial use
requirements
Assessment Basis
Allows verification of liquid-solid partitioning at natural pH and availability
(from Method 1313). Maximum leachate cone, estimated as established by Tier
3B as greater of either i) maximum cone, from Method 1314 up to L/S =2 mL/g,
or ii) maximum cone, from Method 1316, or iii) maximum cone, from Method
1313 over applicable pH domain.
Availability and leaching as a function of pH and evaluation of potential changes
in conditions as indicated for Tier 2 B.
Method 1314 provides leachate evolution as a function of L/S for source term
based on test elution curve. Supports reactive transport simulations to consider
sensitivity to field conditions such as infiltration chemistry, preferential flow
and material aging. Provides basis for verification of chemical speciation
modeling at low L/S.
Method 1313 extractions used to verify acid/base neutralization capacity to
pH=7, and availability of selected COPCs and other (if applicable) constituents
central to beneficial use application (e.g., Ca, sulfate, etc.). Method 1314 extract
at L/S of prior peak concentration to verify maximum leaching cone. Assumes
definition after completion of Tier 3B Characterization. Chemical analysis only
for determination of leaching at peak release cone, and availability (2 or 3
extracts). Further simplification may be possible based on additional available
information.
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Table ES-5. Tier 3 Monolith Mass Transport-Based Assessment - Summary of recommended test methods and analyses1.
Assessment Type Leaching Eluate Analyses
Methods
Tier 3 - Monolith Mass Transport-based Assessment
Tier 3A
Compliance
Tier 3B
Characterization
Tier 3C
Quality Control
Method 1313
(pH=2, 9,
applicable pH
domain)
Method 1315
(to 7 days)
Method 1313
(full set of
eluates)
Method 1314
(full set of
eluates)
Method 1315
(to 64 days)
Method 1313
atpH=2, 7
and/or 9 and
Method 1315
(to 7 days)
pH, EC (natural pH for
Method 1313 and all
Method 1315 eluates),
COPCs, DOC
pH, EC (natural pH only
for Method 1313 and
all Method 1314, and
1315 eluates),
COPCs, DOC, DIG, major
and minor constituents
Assessment Basis
Allows verification of liquid-solid partitioning at natural pH and availability
(from Method 1313). Maximum leachate cone, estimated as established by Tier
3B as greater of either i) maximum cone, from Method 1314 up to L/S =2 mL/g,
or ii) maximum cone, from Method 1316, or iii) maximum cone, from Method
1313 over applicable pH domain.
pH, EC, COPCs (1313
for availability and
1314 at L/S of peak
release) to meet
environmental
requirements,
additional constituents
to meet beneficial use
requirements
Availability and leaching as a function of pH as indicated for Tier 2B.
Method 1314 (crushed material) up to L/S=2 provides estimate of initial pore
water composition.
Method 1315 provides cumulative release as a function of leaching time for
saturated and intermittent wetting conditions. Also provides basis for
estimating reactive transport parameters (e.g., tortuosity) for simulation of
evolving conditions (e.g., low liquid to surface area, external solution chemistry,
carbonation, oxidation, intermittent wetting, etc.). Provides basis for Tier 3C
quality control.
Method 1313 extractions used to verify acid/base neutralization capacity to
pH=7, and availability of selected COPCs and other (if applicable) constituents
central to beneficial use application (e.g., Ca, sulfate, etc.). Method 1315
cumulative release to 7 days to verify consistency with characterization results
(Tier 2B). Assumes definition after completion of Tier 3B Characterization.
Further simplification may be possible based on additional available
information.
xThe cure time prior to testing of monolithic materials is an important consideration because for many cementitious materials, hydration and
microstructure development continues for more than a one year, with initial cure times of 90 days recommended prior to Method 1315 testing.
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Initial percolation characterization testing (Tier 3B) should include analysis of both major
and trace constituents in all leaching test eluates (Methods 1313 and 1314 or 1316)
because knowledge of the major constituents (such as Ca, Fe, DOC or SCU) that control
release of the trace constituents provides insights into the factors that may result in changes
in leaching and allow for calibration of chemical speciation models. For compliance testing
(Tier 3A), Method 1313 can be used as described above (Equilibrium Based Assessment)
and Method 1314 analysis can be simplified to analysis of eluates as prescribed as Option E
in Table 1 of the method (i.e. at L/S=0.2 and along with two composite samples) for COPCs,
pH and conductivity, thus providing peak eluate concentrations and cumulative release.
Monolith regimes can be evaluated based on use of Method 1315 in conjunction with
Method 1313 (Table ES-5). A detailed example of use of this information for evaluation of
use of coal combustion fly ash as a substitute for Portland cement in concrete considering
intermittent water contact via precipitation is available (EPA, 2013a). An example approach
for use of empirical data from Method 1313 (i.e., for availability) and Method 1315 (i.e., for
estimated effective diffusivity) is provided for MSWI bottom ash scenarios in Kosson et al
(1996). These approaches can also be used in conjunction with chemical speciation based
mass transfer models (see Section 3) to provide insights into potential changes in leaching
that may occur in response to changing conditions within or on the external surface of the
material being evaluated.
Initial monolith characterization testing should include analysis of both major and trace
constituents in all leaching test eluates (Methods 1313 and 1315) because knowledge of the
major constituents that control release of the trace constituents provides insights into the
factors that may result in changes in leaching and allow for calibration of chemical
speciation models. For compliance testing, Method 1313 should be used to assess
availability and solubility at the natural pH of the material (i.e., no acid or base addition) and
Method 1315 analysis can be simplified to analysis of eluates at exchange up to 7 days for
COPCs, pH and conductivity. For quality control purposes, Method 1315 reduced to only
analysis of eluates up to 2 days for COPCs, pH and conductivity.
ES-6 Conclusions
This report evaluated the relationships between laboratory leaching tests as defined by the
Leaching Environmental Assessment Framework (LEAF) or analogous EU/international test
methods and leaching of COPCs from a broad range of materials under disposal and
beneficial use scenarios. This evaluation was achieved by defining a framework for
interpretation of laboratory testing results, comparison of laboratory testing on "as
produced" material, laboratory testing of "field aged" material, and results from field
leaching studies, and illustrating the use of chemical speciation modeling as a tool to
facilitate evaluation of scenarios beyond the conditions of laboratory testing.
As identified in table ES-1, ten field cases were evaluated using a combination of laboratory
testing and field analysis for seven different materials: (i) coal fly ash (CFA), (ii) fixated
scrubber sludge typically produced by combining coal fly ash with acid gas scrubber residue
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and lime at some coal fired power plants (FSSL), (iii) municipal solid waste incinerator
bottom ash (MSWI-BA), (iv) a predominantly inorganic waste mixture comprised of
residues from soil cleanup residues, contaminated soil, sediments, C&D waste and small
industry waste(IND), (v) municipal solid waste (MSW), (vi) cement-stabilized municipal
solid waste incinerator fly ash (S-MSWI-FA), and (vii) Portland cement mortars and
concrete. The field data presented in this report include (i) leachate from field lysimeters,
(ii) porewater from landfill or use applications, (iii) eluate from leaching tests on sample
cores taken from field sites, and (iv)leachate collected from landfills. Principal uncertainties
for field data include (i) the extent of preferential flow or dilution that may have occurred
during water contact within the material and in sampling of landfill leachate, and (ii) the
exposure and aging conditions that can occur and are reflected by the field data.
Primary aging processes and reactions that can impact leaching are (i) establishment of
reducing conditions from biogenic processes (i.e., degradation of organic matter), (ii)
oxidation from atmospheric exchange, and (iii) carbonation from either atmospheric
exchange, dissolved carbon dioxide (or carbonates) in contacting water, or reaction with
biogenic carbon dioxide. Other slow mineral formation processes, such as with stabilized
waste after initial curing periods (e.g., 90 days), may result in relative small changes in
leaching relative to freshly prepared material. Constituents in infiltrating or contacting
water, either from natural processes (e.g., DOC in the form of humic substances from leaf
decay) or from anthropogenic origin (e.g., leaching from up gradient disposed materials)
may have a substantial effect on leaching.
Based on the above comparisons and observations along with results discussed in earlier
sections, the following conclusions and recommendations are drawn:
1. The combination of results from pH-dependent leaching tests (i.e., EPA Method 1313
or CEN/TS 14429 or CEN/TS 14997) and percolation column tests (i.e., EPA Method
1314 or CEN/TS 14405) can be used to provide accurate estimates within defined
uncertainty levels of maximum field leachate concentrations, extent of leaching and
expected leaching responses over time and to changes in environmental conditions
under both disposal and use scenarios. Leaching test results should be evaluated
with consideration of the potential for changes in leaching conditions that are
beyond the domain of laboratory test conditions, such as oxidation of reduced
materials, reduction of oxidized material, carbonation and introduction of DOC from
external sources. When field conditions beyond the domain of laboratory test
conditions are plausable, chemical speciation modeling can be used to consider the
magnitude of effects from the postulated changing conditions. Peak leaching
concentrations and availability of COPCs estimated from laboratory testing can be
used to provide a conservative estimate (i.e., reasonable upper bound) of anticipated
field leaching. Results from batch testing at low L/S ratios (i.e., EPA Method 1316 or
EN 12457) can also be used in place of column test results when column testing is
impractical. Thus, the LEAF laboratory leaching tests can be used effectively to
estimate the field leaching behavior of a wide range of materials under both disposal
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and use conditions. Interpretation of the leaching test results should be in the
context of the controlling physical and chemical mechanisms of the field scenario.
2. Field testing of new use or disposal scenarios or new classes of materials to be used
or disposed in new ways is highly beneficial to understanding the factors that
control leaching for the specific scenario. Thereafter, materials within a given class
can be anticipated to behave similarly under the established use or disposal scenario
and the LEAF testing approach can be used to distinguish "acceptable" versus
"unacceptable" materials and use conditions within the general class of materials
and scenario. The EPA guidance on beneficial use of coal fly ash in concrete (EPA,
2014) provides an example of the use of LEAF test results in such decisions.
3. Establishment of a national or international database of LEAF laboratory leaching
test results for materials and leaching observed under field conditions would
provide useful insights for evaluation of new cases and material use and disposal
decisions. The database would allow effective comparison of leaching (i) from
materials produced over time from the same facility, (ii) commonality from similar
materials from a diverse set of facilities, and (iii) from different types of materials
considered for similar beneficial use applications.
4. Field testing should include (i) sampling and leaching characterization of the initial
material, including pH-dependent, column and monolithic mass transfer rate (where
applicable) testing; (ii) field leachate collection and monitoring over extended time
frames (i.e., several years); and (iii) collection and characterization of test materials
after prolonged field exposure (i.e., core samples from field test sites). Sample
collection systems and subsequent handling need to be designed to avoid sample
changes prior to analysis that degrade the representativeness of the samples and
can result in misleading results (e.g., sample oxidation or carbonation during
collection or handling resulting in changes in pH and constituent speciation).
Furthermore, sample analysis should include a full suite of major and trace
constituents that influence and provide a context for understanding COPC leaching.
5. Chemical speciation modeling of liquid-solid partitioning can be used for
understanding the mechanisms (e.g., mineral phases, sorption and aqueous phase
complexation phenomena) controlling leaching of the full range of constituents in
the laboratory and the field, and understanding material leaching under conditions
that are not readily subject to testing. Although the general behavior of many of the
major and trace constituents are reasonably represented in relevant scenarios,
application of chemical speciation modeling to waste management currently is
constrained by the availability of test data for identifying important solid phases and
the range of available thermodynamic data available for model parameters.
Application of chemical speciation modeling as a tool for understanding waste
management should be expanded, along with underlying research to fill data gaps.
6. Single point leaching tests and other common leaching assessment approaches
cannot provide needed insights into the expected leaching performance of materials
in
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under the range of expected field conditions. The LEAF integrated evaluation of
multiple types of leaching test data (i.e., pH dependent LSP along with percolation
and/or monolithic mass transport behavior) and field data within the context of
understanding fundamental leaching behavior (i.e., processes controlling liquid-
solid partitioning and mass transport rates), along with use of chemical speciation
based modeling provides insights into the expected leaching behavior over a range
of field conditions that cannot be obtained otherwise. The resulting estimates of
COPC release reduce the use of conservative assumptions in favor of more complete
data and refined speciation models, and consequently expands alternatives and
provides a sound scientific basis for making decisions about appropriate disposal or
use of secondary materials under environmentally exposed conditions.
IV
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TABLE OF CONTENTS
ABSTRACT Ill
EXECUTIVE SUMMARY IV
ES-1 OBJECTIVES AND BACKGROUND iv
ES-2 EVALUATION CASES vi
ES-3 LEACHING FUNDAMENTALS AND USE OF LABORATORY LEACHING DATA x
ES-4 CASE SUMMARIES xn
ES-5 RECOMMENDATIONS FOR USE OF THE LEAF TEST METHODS FOR BENEFICIAL USE AND DISPOSAL
DECISIONS i
ES-6 CONCLUSIONS i
TABLE OF CONTENTS V
LIST OF FIGURES IX
LIST OF TABLES XIX
ABBREVIATIONS AND ACRONYMS XX
1 INTRODUCTION 1
1.1 THE LEACHING ENVIRONMENTAL FRAMEWORK 1
1.1.1 LEAF Leaching Methods 1
1.1.2 Data Management with LeachXS 2
1.1.3 Leaching Assessment 3
1.1.4 Extension to Field Scenarios 3
1.2 REPORT OBJECTIVES AND APPROACH 4
1.2.1 Field Evaluation Cases 5
1.2.2 Evaluation Approach 7
1.3 DATA QUALITY AND QUALITY ASSURANCE 7
1.4 REPORT LIMITATIONS 8
2 LEACHING TESTS AND CONCEPTUAL INTERPRETATION FRAMEWORK 10
2.1 LEAF AND LEAF-ANALOGOUS LEACHING TESTS 11
2.1.1 pH-dependent Leaching Tests 12
2.1.2 L/S-dependent Leaching Tests. 15
2.1.3 Mass Transport-based Leaching Tests 21
2.2 A CONCEPTUAL FRAMEWORK FOR INTERPRETING LEACHING TEST DATA 24
2.2.1 Liquid-Solid Partitioning at Equilibrium 25
2.2.2 pH, Ionic Strength and Aqueous Phase Complexation as LSP
Modifying Parameters 29
2.2.3 Oxidation-Reduction Considerations for Leaching Tests and Leaching
Assessment 30
2.3 RELATIONSHIPS BETWEEN RESULTS FROM THE LEAF LEACHING TESTS 39
2.3.1 Equilibrium-based Leaching Tests 39
2.3.2 Mass Transfer-based Leaching and pH-dependent Leaching 42
2.4 RELATIONSHIPS BETWEEN LEAF TEST RESULTS AND SINGLE BATCH EXTRACTIONS 44
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2.5 DETERMINATION OF CONSTITUENT AVAILABILITY 45
3 CHEMICAL SPECIATION AND MASS TRANSPORT MODELING AS INTERPRETATION
TOOLS 46
3.1 MODELING AND SIMULATION APPROACH 47
3.2 CHEMICAL SPECIATION AND REACTIVE TRANSPORT MODELING IN LEACHXS 47
3.2.1 Parameterization of ORCHESTRA 48
3.3 SIMULATIONS IN LEACHXS 50
3.3.1 Laboratory Test Simulations 50
3.3.2 LeachXS Field Test Simulations 53
3.3.3 LeachXS Prediction Scenario Models 53
3.4 EXAMPLE OF MODEL DEVELOPMENT FORA STABILIZED WASTE MATERIAL 54
3.5 A COMPARISON OF COPPER AND LEAD SPECIATION IN SEVERAL MATERIALS 61
4 LABORATORY AND FIELD DATA FOR EVALUATION CASES 67
4.1 COAL FLY ASH LANDFILL LEACHATE (UNITED STATES) 67
4.1.1 Case Description 67
4.1.2 Results and Discussion 68
4.1.3 Case Summary 73
4.2 LEACHATE FROM COAL FLY ASH IN LARGE-SCALE FIELD LYSIMETERS (DENMARK) 74
4.2.1 Case Description 74
4.2.2 Results and Discussion 75
4.2.3 Case Summary 76
4.3 LANDFILL OF COAL COMBUSTION FIXATED SCRUBBER SLUDGE WITH LIME (UNITED STATES) ..77
4.3.1 Case Description 77
4.3.2 Results and Discussion 78
4.3.3 Case Summary 83
4.4 COAL FLY ASH USED IN ROADBASE AND EMBANKMENTS (THE NETHERLANDS) 84
4.4J Case Description 84
4.4.2 Results and Discussion 85
4.4.3 Insights Gained from Chemical Spec/at/on of Coal Fly Ash Leaching 86
4.4.4 Case Summary 93
4.5 MUNICIPAL SOLID WASTE INCINERATOR BOTTOM ASH LANDFILL (DENMARK) 94
4.5.1 Case Description 94
4.5.2 Landfill Construction 94
4.5.3 Leachate Quantity and Quality 95
4.5.4 Results and Discussion 96
4.5.5 Case Summary 98
4.6 MUNICIPAL SOLID WASTE INCINERATOR BOTTOM ASH USED IN ROADBASE (SWEDEN) 102
4.6J Case Description 102
4.6.2 Results and Discussion 103
4.6.3 MSWIBA Chemical Spec/at/on Insights. 110
4.6.4 Case Summary 119
4.7 INORGANIC INDUSTRIAL WASTE LANDFILL (THE NETHERLANDS) 120
4.7.1 Case Description 120
VI
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4.7.2 Results and Discussion 122
4.7.3 Chemical Spec/at/on Insights - Predominantly Inorganic Industrial
Waste 127
4.7.4 Case Summary 133
4.8 MUNICIPAL SOLID WASTE LANDFILL (THE NETHERLANDS) 135
4.8.1 Case Description 135
4.8.2 Results and Discussion 136
4.8.3 Chemical Spec/at/on Insights - Municipal Solid Waste Landfills. 145
4.8.4 Case Summary 154
4.9 STABILIZED MUNICIPAL SOLID WASTE INCINERATOR FLY ASH DISPOSAL (THE NETHERLANDS)
155
4.9.1 Case Description 155
4.9.2 Results and Discussion 156
4.9.3 Chemical Spec/at/on Insights - Stabilized Waste 164
4.9.4 Case Summary 172
4.10 PORTLAND CEMENT MORTARS AND CONCRETE 173
4.10.1 Case Description 173
4.10.2 Results and Discussion 174
4.10.3 Chemical Spec/at/on Insights- Cement and Concrete ^77
4.10.4 Case Summary 182
5 RECOMMENDATIONS FOR USE OF THE LEAF TEST METHODS FOR BENEFICIAL USE
AND DISPOSAL DECISIONS 183
5.1 EVALUATING NEW MANAGEMENT SCENARIOS - MATERIAL COMBINATIONS AND PILOT STUDIES
183
5.2 ESTIMATING LEACHING SOURCE TERMS 184
5.3 SCENARIO DEFINITION 186
5.4 SCREENING ASSESSMENT (TIER 1) 187
5.5 EQUILIBRIUM-BASED ASSESSMENT (TIER 2) 187
5.6 MASS TRANSPORT-BASED ASSESSMENT (TIER 3) 190
6 CONCLUSIONS 194
REFERENCES 199
APPENDIX A CHEMICAL SPECIATION MODELS FOR EXAMPLE CASES
APPENDIX B COAL FLY ASH LANDFILL LEACHATE (UNITED STATES)
APPENDIX C LANDFILL OF COAL COMBUSTION FIXATED SCRUBBER SLUDGE WITH
LIME (UNITED STATES)
APPENDIX D MUNICIPAL SOLID WASTE INCINERATOR BOTTOM ASH LANDFILL
(DENMARK)
APPENDIX E MUNICIPAL SOLID WASTE INCINERATOR BOTTOM ASH USE IN
ROADBASE (SWEDEN)
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APPENDIX F INORGANIC INDUSTRIAL WASTE LANDFILL (THE NETHERLANDS)
APPENDIX G MUNICIPAL SOLID WASTE LANDFILL (THE NETHERLANDS)
APPENDIX H STABILIZED MUNICIPAL SOLID WASTE INCINERATOR FLY ASH DISPOSAL
(THE NETHERLANDS)
APPENDIX I PORTLAND CEMENT MORTARS AND CONCRETE
Vlll
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LIST OF FIGURES
Figure 2-1. Example of Method 1313 data in triplicate for arsenic pH-dependent leaching
from a coal combustion fly ash showing measured data (left) and interpolated
data (right). The figures have been modified from those in Garrabrants et al.,
2012a 14
Figure 2-2. Comparison of pH-dependent leaching tests results for testing of a coal
combustion fly ash using Method 1313, CEN/TS 14429 and CEN/TS 14997
(Garrabrants etal., 2012a) 16
Figure 2-3. Example Method 1314 results for arsenic leaching from a contaminated
smelter site soil showing eluate pH in collected fractions from the column,
eluate arsenic concentrations, and cumulative release of arsenic with L/S
(Garrabrants etal., 2012b) 17
Figure 2-4. Example Method 1316 results for arsenic leaching from a contaminated
smelter site soil showing eluate pH in collected fractions from the column,
eluate arsenic concentrations, and cumulative release of arsenic with L/S
(Garrabrants etal., 2012a) 18
Figure 2-5. Comparison of L/S-dependent release for a contaminated smelter site soil
using Method 1314 (percolation), Method 1316 (batch L/S) and CEN/TS
14405 (percolation). Data taken from Garrabrants etal., 2012a, 2012b 20
Figure 2-6. Example Method 1315 test results for barium leaching from a solidified waste
analog material showing pH evolution, eluate concentration, mean interval
flux and cumulative release (Garrabrants et al., 2012b) 22
Figure 2-7. Comparison of mean interval flux release results for testing of a solidified
waste analog using Method 1315, CEN/TS 15863 and NEN 7375. Data taken
from Garrabrants etal., 2012b 24
Figure 2-8. Chloride as an example of a highly soluble species where the observed
leaching concentration is a function of L/S but not a function of pH for an
unwashed gypsum material from coal combustion flue gas desulfurization
(SAU, after Kosson etal., 2009) 27
Figure 2-9. Arsenic as an example of solubility-controlled (saturated solution) leaching as
a function of L/S and pH for a coal combustion fly ash (EaFA; after
Garrabrants etal., 2012a) 28
Figure 2-10. pH-dependent solubility of magnesium and molybdenum for coal fly ash
sample TFA (after Kosson et al., 2009) 29
Figure 2-11. Illustration of the influence of organic matter and DOC on leaching of copper
through three cases: (i) fresh municipal solid waste incinerator (MSWI)
bottom ash, (ii) the same MSWI bottom ash heat treated at 500 ฐC to remove
organic matter, and (iii) the heat-treated MSWI bottom ash from above with
1% compost added to provide organic matter (after van der Sloot et al.,
2008c) 30
Figure 2-12. Predominance diagram for iron (0.1 M) in the presence of sulfate (0.1 M) 35
Figure 2-13. Predominance diagram for sulfate (0.1 M) in the presence of iron (0.1 M) 35
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Figure 2-14. Predominance diagram for sulfate (0.1 M) in the presence of iron (0.1 M) and
calcium 0.1 M) 36
Figure 2-15. Predominance diagram for arsenic (0.1 M) in the presence of sulfate (0.1 M).37
Figure 2-16. Predominance diagram for chromium (0.1 M) 37
Figure 2-17. Predominance diagram for copper (0.1 M) in the presence of sulfate (0.1 M). 38
Figure 2-18 Predominance diagram for vanadium (0.001 M) 39
Figure 2-19. Comparison of eluate concentration (left) and release (right) for a Response 2
highly soluble species from pH-dependent (Method 1313) and L/S dependent
(Method 1314 and Method 1316) leaching tests 41
Figure 2-20. Comparison of eluate concentration (left) and release (right) for a Response 3
aqueous saturation species from pH-dependent (Method 1313) and L/S
dependent (Method 1314 and Method 1316) leaching tests 42
Figure 2-21. Comparison of mass transfer-based leaching data (single points) to pH-
dependent leaching data (continuous series) as a check against equilibrium in
the bulk liquid phase of the mass transfer test. Data is shown for a
contaminated smelter site soil (CFS; top) and a solidified waste analog (SWA;
bottom) 43
Figure 2-22. Comparison of single-batch extractions (i.e., TCLP and SPLP) to pH- and L/S-
dependent leaching results for a contaminated smelter site soil (CFS; top) and
a solidified waste analog (SWA; bottom) 44
Figure 3-1. Mass transport model (laboratory simulation) scenario 51
Figure 3-2. Conceptual model of percolation with mobile and immobile zones shown for
soil aggregates (left; van Genuchten and Dalton, 1986) and as a 1-dimension
approximation in ORCHESTRA (right) 52
Figure 3-3. Conceptual model of percolation with radial diffusion in the immobile zone
(Sarkar et al., 2013) shown as an up-flow column (left) and as flow through
cracks in concrete (right) 53
Figure 3-4. Comparison of laboratory simulation results for a stabilized MSWI residue
(van der Sloot et al, 2007). Multi-element, multi-phase chemical speciation
modeling is shown for pH-dependent leaching data (left), percolation test
data (middle) and mass transport test data (right) 58
Figure 3-5. Comparison of laboratory simulation results for a stabilized MSWI residue
(van der Sloot et al, 2007). Multi-element, multi-phase chemical speciation
modeling is shown for pH-dependent leaching data (left), percolation test
data (middle) and mass transport test data (right) 59
Figure 3-6. Laboratory leaching test simulation shown pH-dependent leaching (model at
L/S=10 L/kg) and percolation leaching (model at L/S=0.5 L/kg) for select
species in a solidified MSWI residue (van der Sloot etal, 2007) 60
Figure 3-7. Chemical speciation and phase descriptions as a function of pH for a stabilized
MSWI residue conducted on fresh material and aged (4 year) cores.
Comparisons include pH-dependent model simulations (upper left), phase
description for fresh material (upper right), phase descript for aged material
(lower left) and liquid phase fraction for fresh material (lower right) 61
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Figure 3-8. Geochemical model description of copper at L/S=10 with prediction to
L/S=0.3 (left) and partitioning (L/S=10) based on multi-element geochemical
speciation modelling (right). Data shown for cement mortar (top), coal fly
ash (middle), and stabilized waste (bottom) 62
Figure 3-9. Geochemical model description of copper at L/S=10 with prediction to
L/S=0.3 (left) and partitioning (L/S=10) based on multi-element geochemical
speciation modelling (right). Data shown for municipal solid waste (top),
predominantly inorganic waste (middle), and MSWI bottom ash (bottom)... 63
Figure 3-10 Geochemical model description of lead at L/S=10 with prediction to L/S=0.3
(left) and partitioning (L/S=10) based on multi-element geochemical
speciation modelling (right). Data shown for cement mortar (top), coal fly
ash (middle), and stabilized waste (bottom) 64
Figure 3-11 Geochemical model description of lead atL/S=10 with prediction to L/S=0.3
(left) and partitioning (L/S=10) based on multi-element geochemical
speciation modelling (right). Data shown for municipal solid waste (top),
predominantly inorganic waste (middle), and MSWI bottom ash (bottom)... 65
Figure 4-1. Comparison of field leachates to pH-dependent leaching for magnesium and
vanadium release from CCRs 69
Figure 4-2. Bimodal behavior of field leaching results compared to pH-dependent
leaching of arsenic, cadmium, chromium and selenium from CCRs 70
Figure 4-3. Comparison of field leachates to pH-dependent leaching for calcium and
sulfate release from CCRs 71
Figure 4-4. Effect of ettringite formation at alkaline pH on the leaching of chromium and
molybdenum 71
Figure 4-5. Comparison of field leachates to pH-dependent leaching for chloride and
sulfate release from CCRs 72
Figure 4-6. Comparison of field leachates to pH-dependent leaching for barium release
from CCRs 73
Figure 4-7. Cross-section of large-scale field lysimeter construction (Hjelmar etal., 1991).
74
Figure 4-8. Comparison of leachate composition from field lysimeters and laboratory
column testing (Column 4, red symbols) for pH, sodium, potassium, calcium
and sulfate 75
Figure 4-9. Comparison of leachate composition from field lysimeters and laboratory
column testing (red symbols) for arsenic, chromium, molybdenum and
selenium 76
Figure 4-10. Comparison of pH-dependence testing of field-cored FSSL and "as produced"
FSSL to field pore water samples showing the impact of aging and partial
carbonation of field materials 79
Figure 4-11. Comparison of chloride and cadmium leaching in field-cored FSSL and "as
produced" FSSL to field pore water samples showing the impact of cadmium
chloride chelation 80
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Figure 4-12. Comparison of dissolved organic carbon and copper leaching in field-cored
FSSL and "as produced" FSSL to field porewater samples showing the impact
of complexation of dissolved organic carbon with copper. 80
Figure 4-13. Comparison of arsenic, boron, molybdenum and selenium leaching in field-
cored FSSL and "as produced" FSSL to field porewater samples 81
Figure 4-14. Comparison of potassium and sodium leaching in field-cored FSSL and "as
produced" FSSL to field porewater samples (upper graphs). Lower four
graphs present Method 1316 results applied to field core (FCM) and
extrapolation to L/S=0.5 L/kg (dashed line) compared to result of 20x result
from Method 1313 at natural pH 83
Figure 4-15. Cross section of roadbase constructed with cement stabilized coal fly ash
(same as for the embankment). The stabilized fly ash (0.8 m thick) is overlain
with an asphalt layer in the road surface area and by clinker material (coarse
aggregate) on the sloped road shoulder area, and underlain with a sloped
sand drainage layer (0.30 m thick). A polyvinyl chloride plastic sheet
underlies the sand drainage layer to ensure leachate collection in a collection
sump (at left) 84
Figure 4-16. Cross-section of embankment constructed with cement stabilized coal fly ash
as the core material and then covered with 0.3 m topsoil for growth of grass.
A drainage sand layer underlies the stabilized coal fly ash, and a polyvinyl
chloride plastic sheet underlies the sand drainage layer to ensure leachate
collection through a drain (center bottom) and diversion to a collection sump
(at left) 85
Figure 4-17. Field leachate concentrations from Dutch embankment and road base
demonstration projects compared to laboratory percolation column
experiments 86
Figure 4-18. Chemical speciation model results for chromium at L/S=10 and L/S=0.3
compared to pH-dependent (CEN/TS 14429) and percolation column
(CEN/TS 14405) leaching results for coal fly ash (the Netherlands) 87
Figure 4-19. Chemical speciation model results for sulfate at L/S=10 and L/S=0.3
compared to pH-dependent (CEN/TS 14429) and percolation column
(CEN/TS 14405) leaching results for coal fly ash (the Netherlands) 88
Figure 4-20. Chemical speciation model results for molybdenum at L/S=10 and L/S=0.3
compared to pH-dependent (CEN/TS 14429) and percolation column
(CEN/TS 14405) leaching results for coal fly ash (the Netherlands) 89
Figure 4-21. Effect of carbonation levels (wt% COs) on calcium model predictions and
partitioning compared to pH-dependent (CEN/TS 14429) and percolation
column (CEN/TS 14405) leaching test results 90
Figure 4-22. Effect of carbonation levels (wt% COs) on nickel model predictions and
partitioning compared to pH-dependence (CEN/TS 14429) and percolation
column (CEN/TS 14405) leaching test results 91
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Figure 4-23. Effect of reducing and oxidizing (redox) conditions on chemical speciation
results for chromium as a function of L/S (left) and chromium partitioning
with depth (right) for coal fly ash (the Netherlands) 93
Figure 4-24. Cross-section of the MSWI residue monofill in Vestskoven, Denmark (Hjelmar
and Hansen, 2005) 95
Figure 4-25. Eluate pH from leachates from the Vestkoven monofill (red circles) compared
to the percolation column pH for comparable bottom ash samples (solid
symbols) 97
Figure 4-26. Arsenic concentration results from the Vestskoven MSWI monofill leachate
samples (red circles). Data are shown for pH-dependent leaching (left) and
percolation column testing (right). These results illustrate typical
relationships between pH-dependent and column testing of cored samples
and leachate measurements 97
Figure 4-27. Chromium, lead and zinc concentration results from testing of cored materials
from the Vestskoven MSWI monofill (grey diamonds) compared to leachate
samples (red circles). Data are shown for pH-dependent leaching (left) and
percolation column testing (right). These results illustrate typical
relationships between pH-dependent and column testing of cored samples
and leachate measurements 100
Figure 4-28. Sodium, potassium and chloride concentration results from testing of cored
materials from the Vestskoven MSWI monofill (grey diamonds) compared to
leachate samples (red circles). Data are shown for pH-dependent leaching
(left) and percolation column testing (right). These results illustrate leaching
behavior of highly soluble species 101
Figure 4-29. Spatial distribution of pH (EN 12457-2) in a section of subbase layer of MSWI
bottom ash. The sampling points are marked as black dots (n=53) while the
x- and y-axes are scaled in centimeters (Bendz et al., 2009) 103
Figure 4-30. Measured pH in reference bottom ash and core samples from Vandora
roadbase 103
Figure 4-31. Cadmium and nickel results from pH-dependent leaching tests (left) and
column leaching tests (right), illustrating consistency of results between field
road subbase samples (16-year-old MSWI bottom ash) and for MSWI bottom
ash reference samples 104
Figure 4-32. Results from pH-dependent leaching test (left) and column leaching tests
(right; chloride and sodium), illustrating higher initial eluate concentrations
for highly soluble species from column tests (i.e., L/S < 0.2 L/kg) compared to
pH-dependent leaching tests 105
Figure 4-33. Potassium and manganese results from pH-dependent leaching test (left) and
column leaching tests (right) illustrating typical results for highly soluble
species (potassium) compared to solubility controlled species (manganese).
106
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Figure 4-34. Calcium and strontium results from pH-dependent leaching test (left) and
column leaching tests (right) illustrating the effects of carbonation to reduce
solubility at alkaline pH 107
Figure 4-35. Aluminum, magnesium and lead results from pH-dependent leaching test
(left) and column leaching tests (right) illustrating the effects of pH-
dependent solubility on the eluate concentrations from column tests (also
refer to Figure 4-30 for pH of column testeluates) 108
Figure 4-36. Copper and DOC results from pH-dependent leaching test (left) and column
leaching tests (right) illustrating the effects of pH-dependent solubility on the
eluate concentrations from column tests 109
Figure 4-37. pH-dependence leaching (CEN/TS 14429) data for MSWI bottom ash
(Netherlands) as "fresh" material (red), MSWI BA after heat treatment at 500
ฐC (blue), and heat-treated MSWI BA with 1% compost added (green) 110
Figure 4-38. Chemical speciation modeling for MSWI bottom ash (Netherlands) as "fresh"
material (upper), MSWI BA after heat treatment at 500 ฐC (middle), and heat-
treated MSWI BAwith 1% compost added (lower) 112
Figure 4-39. Chemical speciation modeling of copper in MSWI bottom ash (Austria)
compared to pH-dependence (CEN/TS 14429) and percolation column
(CEN/TS 14405) data 114
Figure 4-40. Chemical speciation modeling of aluminum from MSWI bottom ash (Austria)
atL/S=10andL/S=0.3 115
Figure 4-41. Chemical speciation modeling of vanadium from MSWI bottom ash (Austria)
atL/S=10andL/S=0.3 116
Figure 4-42. Chemical speciation modeling of zinc from MSWI bottom ash (Austria) at
L/S=10andL/S=0.3 117
Figure 4-43. Chemical speciation modeling at different L/S compared to pH-dependence
(CEN/TS 14429) and percolation column (CEN/TS 14405) data for MSWI
bottom ash (Austria) 118
Figure 4-44. Chemical speciation modeling at different L/S compared to pH-dependence
(CEN/TS 14429) and percolation column (CEN/TS 14405) data for MSWI
bottom ash (Austria) 119
Figure 4-45. Construction of the Nauerna pilot-scale landfill (van Zomeren and van der
Sloot, 2006b) 120
Figure 4-46. Nauerna landfill lysimeters 121
Figure 4-47. Iron and dissolved organic carbon concentrations from Nauerna landfill study.
123
Figure 4-48. Chromium and arsenic concentrations from Nauerna landfill study. 124
Figure 4-49. Barium and phosphorus concentrations from Nauerna landfill study. 125
Figure 4-50. Chloride, magnesium and sodium concentrations from Nauerna landfill study.
126
Figure 4-51. Cadmium and zinc concentrations from Nauerna landfill study. 127
xiv
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Figure 4-52. Chemical speciation modeling of chromium from predominantly inorganic
industrial waste at L/S=10 and 0.3 mL/g compared to pH-dependence and
percolation column data 128
Figure 4-53. Chemical speciation modeling of copper from predominantly inorganic
industrial waste at L/S=10 and 0.3 mL/g compared to pH-dependence and
percolation column data 129
Figure 4-54. Chemical speciation modeling of lead from predominantly inorganic
industrial waste at L/S=10 and 0.3 mL/g compared to pH-dependence and
percolation column data 130
Figure 4-55. Comparing effects of oxidizing and reducing conditions - chemical speciation
modeling of iron from predominantly inorganic industrial waste at L/S=10
mL/g compared to pH-dependent and percolation column laboratory data
and pilot leachates 131
Figure 4-56. Comparing effects of oxidizing and reducing conditions - chemical speciation
modeling of copper from predominantly inorganic industrial waste atL/S=10
mL/g compared to pH-dependent (PrEN 14429) and percolation column
(PrEN 14405) data 132
Figure 4-57. Comparing effects of oxidizing and reducing conditions - chemical speciation
modeling of sulfur from predominantly inorganic industrial waste at L/S=10
mL/g compared to pH-dependent (PrEN 14429) and percolation column
(PrEN 14405) data 133
Figure 4-58. Cross-section schematic layout of the landfill test cell with leachate collection
drains and infiltration pipes 136
Figure 4-59. Eluate pH from leachates from the Landgraaf MSW landfill (red circles)
compared to the pH from percolation column testing for initial material and
landfill cores (solid symbols) 137
Figure 4-60. Comparison of DOC and iron concentrations from Landgraaf landfill leachates
(red circles) with laboratory data (solid symbols) as a function of pH (left)
and L/S (right) 138
Figure 4-61. Concentrations of highly soluble constituents (chloride, potassium and
sodium, upper, middle and lower graphs, respectively) from laboratory test
eluates and leachate from the landfill test cell 139
Figure 4-62. Examples of solubility-controlled leaching whereby the measured
concentration in leachate and laboratory column tests is closely aligned with
results from the pH-dependent leaching test (illustrated by aluminum,
calcium and nickel, upper, middle and lower graphs, respectively) 140
Figure 4-63. Complex interactions as a result of reducing conditions are illustrated by
chromium (DOC complexation) and arsenic (loss of iron adsorption),
resulting in higher leachate concentrations than indicated by pH-dependent
and laboratory column tests 141
Figure 4-64. Potential relationship between barium (upper graph) and phosphorus (lower
graph) solubilization under reducing conditions, resulting in higher leachate
xv
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concentrations than indicated by pH-dependent and laboratory column tests.
142
Figure 4-65. Increased vanadium concentrations under reducing conditions, likely the
result of chemical reduction of V+5, also resulting in higher leachate
concentrations than indicated by pH-dependent and laboratory column tests.
143
Figure 4-66. Decreasing sulfur in leachate from the landfill test cell and lower initial sulfate
concentrations in eluates from laboratory column testing on core samples
after eight years indicates conversion of sulfate to sulfides (top) with
decreased solubility of copper (middle) and cadmium (bottom) 144
Figure 4-67. Chemical speciation modeling under reducing conditions (pH+pE=13) of
municipal solid waste (the Netherlands) compared to pH-dependence data
(CEN/TS 14429) and percolation column data (CEN/TS 14405) 146
Figure 4-68. Chemical speciation modeling under reducing conditions (pH+pE=13) of
municipal solid waste (the Netherlands) compared to pH-dependence data
(CEN/TS 14429) and percolation column data (CEN/TS 14405) 147
Figure 4-69. The effect of oxidation-reduction (redox) on the chemical speciation of iron
from municipal solid waste (the Netherlands) 149
Figure 4-70. The effect of oxidation-reduction (redox) on the chemical speciation of copper
from municipal solid waste (the Netherlands) 150
Figure 4-71. Chemical speciation of copper atpH+pE=13 during degradation of municipal
solid waste (the Netherlands) through loss of POM and DOC under oxidizing
conditions 152
Figure 4-72. Chemical speciation of copper atpH+pE=5.5 during degradation of municipal
solid waste (the Netherlands) through loss of POM and DOC under reducing
conditions 153
Figure 4-73. Comparison of field leachate concentrations (multiple sources) for Fe and Cu
with pH dependence laboratory test data and simulated concentrations at
pH+pE=5.5 and L/S=10 and 0.3 154
Figure 4-74. Schematic illustration of the front view of the pilot scale experiment using
stabilized waste (from van der Sloot et al., 2007). Each test cell was 8 m long,
and the space between test cells was filled with sand to maintain physical
stability 155
Figure 4-75. Conceptual model of processes occurring during the field pilot study of
monolithic waste disposal (from van der Sloot et al., 2007) 157
Figure 4-76. Comparison of pH for laboratory testing of waste materials and landfill cores
to landfill leachate pH for stabilized waste 158
Figure 4-77. Calcium and strontium leaching from laboratory and field materials showing
decrease in concentrations in the pH range 6 < pH < 10 consistent with
carbonate formation 159
Figure 4-78. Lead leaching from laboratory and field materials showing decrease in
concentrations in the pH range 6 < pH < 10 consistent with carbonate
formation 160
xvi
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Figure 4-79. Chloride and potassium leaching from laboratory and field materials showing
washout of highly soluble species 161
Figure 4-80. Vanadium and selenium leaching from laboratory and field materials showing
washout of more soluble oxyanions 162
Figure 4-81. Copper, chromium and manganese leaching from laboratory and field samples
of stabilized waste 163
Figure 4-82. Molybdenum leaching from laboratory and field samples of stabilized waste.
164
Figure 4-83. Chemical speciation modeling at L/S=10 and 0.3 mL/g for copper from
stabilized waste (the Netherlands) compared to field leachate data,
laboratory pH dependence test data (CEN/TS 14429) on fresh stabilized
waste (ca. 28 day cure) and field core samples after 4 years, and percolation
column data on fresh stabilized waste (CEN/TS 14405). Also included is a
comparison of assuming Cu precipitation as Cu(OH)2 and as te no rite [CuO].
165
Figure 4-84. Chemical speciation modeling at L/S=10 and 0.3 mL/g for lead from stabilized
waste (the Netherlands) compared to field leachate data, laboratory pH
dependence test data (CEN/TS 14429) on fresh stabilized waste (ca. 28 day
cure) and field core samples after 4 years, and percolation column data on
fresh stabilized waste (CEN/TS 14405) 166
Figure 4-85. Chemical speciation modeling at L/S=10 and 0.3 mL/g for sulfate from
stabilized waste (the Netherlands) compared to field leachate data,
laboratory pH dependence test data (CEN/TS 14429) on fresh stabilized
waste (ca. 28 day cure) and field core samples after 4 years, and percolation
column data on fresh stabilized waste (CEN/TS 14405) 167
Figure 4-86. Chemical speciation modeling for calcium from stabilized waste (the
Netherlands) at different carbonate levels compared to pH-dependence data
(CEN/TS 14429) and percolation column data (CEN/TS 14405) for cement
stabilized fly ash (the Netherlands) 168
Figure 4-87. Chemical speciation modeling for copper from stabilized waste (the
Netherlands) at different carbonate levels compared to pH-dependence data
(CEN/TS 14429) and percolation column data (CEN/TS 14405) 169
Figure 4-88. Chemical speciation modeling for chromium from stabilized waste (the
Netherlands) at different carbonate levels compared to pH-dependence data
(CEN/TS 14429) and percolation column data (CEN/TS 14405) 170
Figure 4-89. Chemical speciation modeling for magnesium from stabilized waste (the
Netherlands) at different carbonate levels compared to pH-dependence data
(CEN/TS 14429) and percolation column data (CEN/TS 14405) 171
Figure 4-90. Chemical speciation modeling for zinc from stabilized waste (the
Netherlands) at different carbonate levels compared to pH-dependence data
(CEN/TS 14429) and percolation column data (CEN/TS 14405) 172
Figure 4-91. Aluminum, antimony, copper and zinc as example results from pH-dependent
leaching tests on field core samples of concrete of different ages and exposure
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conditions in comparison with reference mortars. LSP was consistent
between reference materials cured for short times (i.e., 28 days) and
materials exposed to field conditions for extended time periods 175
Figure 4-92. Arsenic and chromium results from pH-dependent leaching tests on field core
samples of concrete of different ages and exposure conditions in comparison
with reference mortars 176
Figure 4-93. Calcium and strontium results from pH-dependent leaching tests on field core
samples of concrete of different ages and exposure conditions in comparison
with reference mortars. The effect of carbonation to decrease leaching at
neutral to alkaline pH is evident 176
Figure 4-94. Chemical speciation modeling of the impacts of carbonation on solubility of
Ca and the resulting solid and aqueous phase speciation compared to pH-
dependence leaching test data on portland cement CEM I standard mortar
after 28-day cure 178
Figure 4-95. Leaching of CEM I mortar (56-day cure) with recycled concrete aggregate
(field aged 4 years) and Roman cement (field aged 2,000 years) indicative of
different extents of carbonation compared to chemical speciation modeling of
the impacts of carbonation on solubility of Ca and pH-dependence leaching
test data on portland cement CEM I standard mortar after 28-day cure 180
Figure 4-96. Chemical speciation modeling of the impacts of carbonation on solubility of
Ca, S04, Mo and Cr compared to pH dependence leaching test data on
portland cement CEM I standard mortar after 28-day cure 182
Figure 5-1. A tiered framework for evaluating leaching (Kosson et al, 2002) 186
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LIST OF TABLES
Table ES-1. Summary of Laboratory-To-Field Comparison Cases vii
Table ES-2. The observed field pH domain, constituents considered and the primary
conclusions for each of the case studies i
Table ES-3. Tier 1 Screening Assessment and Tier 2 Equilibrium-Based Assessment -
Summary of recommended test methods and analyses i
Table ES-4. Tier 3 Percolation Mass Transport-Based Assessment - Summary of
recommended test methods and analyses i
Table ES-5. Tier 3 Monolith Mass Transport-Based Assessment - Summary of
recommended test methods and analyses1 ii
Table 1-1. Summary of Laboratory-To-Field Comparison Cases 6
Table 2-1. LEAF Test Methods and Analogous European/International Methods 12
Table 2-2. Comparison of Method 1315 and EU Mass Transfer Test Parameters 23
Table 3-1. Model Parameters for CSF Definition for Stabilized MSWI waste 55
Table 3-2 Chemical Availability Values for CSF Definition of Stabilized MSWI Waste 55
Table 3-3. Mineral Phases in CSF Definition for Stabilized MSWI Waste 56
Table 4-1. Summary of field sites and field data for calcium 68
Table 4-2. Physical information about the Vestkoven MSWI monofill 95
Table 4-3. Waste composition of the landfilled material in the test cell at Landgraaf
(Luningetal., 2006) 135
Table 5-1. Tier 1 Screening Assessment and Tier 2 Equilibrium-Based Assessment-
Summary of recommended test methods and analyses 188
Table 5-2. Tier 3 Percolation Mass Transport-Based Assessment - Summary of
recommended test methods and analyses 191
Table 5-3. Tier 3 Monolith Mass Transport-Based Assessment - Summary of recommended
test methods and analyses1 192
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ABBREVIATIONS AND ACRONYMS
BOD biological oxygen demand
C&D construction and demolition
CCR(s) coal combustion residue(s)
CEN Comite Europeen de Normalisation, Brussels, Belgium
CFA coal fly ash
COD chemical oxygen demand
COPC(s) constituent(s) of potential concern
CSF chemical speciation fingerprint
DOC dissolved organic carbon
DNV Det Norske Veritas (a Norwegian classification society)
ECN Energy Research Centre of The Netherlands, Petten, The Netherlands
EPA U.S. Environmental Protection Agency
EPRI Electric Power Research Institute, Palo Alto, CA
ESP(s) electrostatic precipitator(s)
EU European Union
FGD flue gas desulfurization
FSSL fixated scrubber sludge with lime
HFO hydrous ferric oxide
IND small industry waste
ISO International Standards Organization, Geneva, Switzerland
LEAF Leaching Environmental Assessment Framework
L/A liquid-to-surface area ratio (mL/cm2)
L/S cumulative liquid-to-solid ratio (mL/g-dry or L/kg-dry; dry mass basis)
L/Si interval liquid-to-solid ration (mL/g-dry or L/kg-dry; dry mass basis)
LSP liquid-solid partitioning
meq milli-equivalents
MSW municipal solid waste
MSWI municipal solid waste incinerator
MSWI-BA municipal solid waste incinerator bottom ash
MW megawatt
NEN Nederlands Normalisatie Instituut, Delft, The Netherlands
NOK National Research Program Coal (The Netherlands)
ORD Office of Research and Development (U.S. EPA)
ORP oxidation-reduction potential
POM particulate organic matter
RCA recycled concrete aggregate
SHA solid humic acid
S-MSWI-FA stabilized municipal solid waste incinerator ash
SPLP Synthetic Precipitation Leaching Procedure (EPA Method 1312)
TCLP Toxicity Characteristic Leaching Procedure (EPA Method 1311)
U.S. United States
VU Vanderbilt University, Nashville, TN
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1 INTRODUCTION
Leaching tests are tools typically used to estimate the environmental impact associated with
disposal or utilization of materials and wastes on the land (e.g., soils, sediments, industrial wastes,
demolition debris, etc.). However, the results of leaching tests are often used without sufficient
consideration of the type of data available or the applicability of the available data for the chosen
disposal or utilization scenario. Furthermore, results of leaching assessments based on testing and
interpretive models only provide a source term as one part of an evaluation of environmental safety.
In addition to test results, integral factors in applicability assessment or criteria development for
use and disposal include (i) definition and application of appropriate fate and transport models and
(ii) establishment of risk-informed constituent concentration thresholds at defined points of
compliance.
The assumption that is often made, consciously or not, is that the leaching test "simulates" the
release of constituents of potential concern (COPCs) as would happen in the application scenario
and, therefore, the leaching test results represent the leachate that would occur in the field. Since
many of the current leaching test methods are based on simulation of a particular pre-defined
release scenario, the relevance of the leaching test results is restricted to the scenario being
simulated. Furthermore, no single leaching test can encompass the range of conditions that a
material or waste may be subjected to over the duration of use or disposal. Therefore, the
applicability of the results of simulation-based leaching tests is often quite limited to the defined
test conditions and relatively short assessment intervals. In order to address these limitations, a
more robust science-based approach is needed for environmental leaching assessment that
considers the impact on leaching of the chemical and physical characteristics of the tested materials
and the range of environmental conditions likely to be encountered during disposal and utilization.
These needs have been strongly articulated by the Science Advisory Board of the United States
Environment Protection Agency (EPA) during reviews of regulatory leaching approaches (EPA,
1991,1999).
1.1 The Leaching Environmental Framework
The Leaching Environmental Assessment Framework (LEAF) is fundamentally different than the
defined simulation-based approach because it focuses on characterization of material-specific
leaching behaviors controlling the release of COPCs from solid materials over a broad range of test
and environmental conditions with application of the leaching data to specific disposal or use
conditions (Kosson et al., 2002). The framework consists of four laboratory leaching methods, data
management tools, and leaching assessment approaches developed by Vanderbilt University in
conjunction with U.S. EPA and international partners.
1.1.1 LEAF Leaching Methods
The four leach testing methods described in LEAF have been validated through interlaboratory
studies (Garrabrants et al., 2012a, 2012b) and adopted into SW-846, the EPA compendium of
laboratory tests (EPA, 2013a) as:
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Method 1313 - Liquid-Solid Partitioning as a Function of Extract pH using a Parallel Batch
Extraction Procedure
Method 1314 - Liquid-Solid Partitioning as a Function of Liquid-Solid Ratio for Constituents
in Solid Materials using an Up-flow Percolation Column Procedure
Method 1315 - Mass Transfer Rates in Monolithic and Compacted Granular Materials using
a Semi-Dynamic Tank Leaching Procedure
Method 1316 - Liquid-Solid Partitioning as a Function of Liquid-Solid Ratio in Solid
Materials using a Parallel Batch Extraction Procedure
These tests may be applied to solid materials to determine fundamental leaching parameters
including liquid-solid partitioning (LSP) of constituents as a function of pH and cumulative liquid-
to-solid ratio (L/S) as well as the rate of constituent mass transfer from monolithic and compacted
granular materials. Coordinated development of LEAF has occurred between research laboratories
in the United States (U.S.) and the European Union (EU). Thus, LEAF analogous test methods have
been or are being developed within the EU with minor differences intended to address the different
regulatory contexts (e.g., quality control requirements, method description requirements, etc.)
1.1.2 Data Management with LeachXS
Typically, only those chemical species of environmental concern (e.g., heavy metals and select
organic compounds) are measured under the current regulatory leaching structure, often for
compliance purposes. However, the understanding of COPC leaching can be significantly increased
if the release of major and minor species not typically studied are measured. For example, arsenic
retention is often influenced by calcium and carbonate concentrations, while copper leaching
concentrations are often influenced by dissolved organic carbon. Thus, examination of species that
are not COPCs or other usual environmental analytes may provide insight into release mechanisms
and the potential for changes in those release mechanisms for environmental COPCs. In addition,
quantification of a broader range of constituents allows for chemical speciation modeling (see
Section 3) and facilitates more fully descriptive leaching behavior modeling approaches. Therefore,
the LEAF approach for environmental assessment is designed to provide a more complete
evaluation of the leaching behavior which benefits from the analysis and evaluation of major and
minor components of the solid matrix in addition to the typical species posing direct environmental
concern.
However, the combination of multi-point leach testing and more comprehensive chemical analysis
results in a considerable amount of data to be assessed, compared and reported. The leaching
assessment and data management program, LeachXS, has been developed to facilitate leaching
data management. The database driven program is integrated with the LEAF methods through
Microsoft Excel spreadsheets used to upload laboratory and analytical data into the LeachXS
materials database. In addition, display tools allow for comparison of leaching results for multiple
materials and facilitated reporting of the large amount of data required for full characterization.
LeachXS also serves as an interface for statistical evaluations of leaching results, chemical
speciation modeling using ORCHESTRA (Meeussen, 2003), and advanced reactive transport
modeling for several pre-defined release scenarios. LeachXS Lite is a freely-licensed, limited
capability version of the full LeachXS program (van der Sloot et al., 2003; van der Sloot et al., 2008b)
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focused primarily on uploading, comparing, and display of leaching data between materials and test
types.6 The Lite version of LeachXS was developed, in part, to facilitate EPA characterization of coal
combustion residues (CCRs) and associated reports (Sanchez et al., 2006, 2008; Kosson et al., 2009),
but also is applicable to management and evaluation of LEAF data from a wide range of materials.
1.1.3 Leaching Assessment
Assessments based on the results of characterization-based leaching methods, such as LEAF and
LEAF analogous methods, are more flexible than those from simulation-based tests because the
data generated focus on relevant intrinsic leaching behavior independent of the disposal or
utilization scenario. Characterization of leaching behavior using the LEAF tests along with scenario-
specific information can be used to assemble a leaching "source term" for many environmental
scenarios or levels of environmental assessment including:
screening level assessments at a site-specific, regional or national scale;
detailed site-specific evaluations;
performance comparisons between different materials or treatment processes under
specific disposal or use scenarios;
development of chemical speciation based models to evaluate potential material leaching
behavior under field conditions that may be difficult or impossible to reproduce in the
laboratory.
However, it must be recognized that leaching assessment only provides that source-term as part of
the overall evaluation process, which also must consider dilution and attenuation from the source to
the point of exposure or compliance, and the relevant risk-informed decision or compliance human
health and ecological thresholds.
1.1.4 Extension to Field Scenarios
The robustness of the LEAF approach comes from using laboratory data that includes a range of
limiting conditions (i.e., LSP and maximum leaching mass transport rates) in conjunction with
models for estimating release under a range of field conditions and scenarios. Assessing the
applicability and accuracy of any predictive leaching assessment approach, however, requires
evaluation through the use of pilot- and full-scale field studies in which leaching predictions for a
particular material based on laboratory testing may be compared to measured leachate
concentrations for that material collected under field conditions. Field studies also provide
information regarding the relative importance of natural processes on leaching of COPCs including
water flow patterns, extent of local chemical equilibrium, and chemical changes due to aging or
exposure to the environment. For example, leaching of alkaline materials such as some cement-
stabilized materials may be altered by reaction with atmospheric carbon dioxide, resulting in a less
6 LeachXS Lite, which is a collaboration of Vanderbilt University (VU), Energy Research Centre of The Netherlands (ECN),
EPA Office of Research and Development (ORD) and ARCADIS-U.S., Inc., does not include the advanced formatting,
statistical calculations, or chemical speciation and reactive transport modeling capabilities native to the full LeachXS
version. The LEAF methods. Excel data templates and LeachXS Lite are available free of charge at
www.vanderbilt.edu/leaching.
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alkaline pH for leaching and altered chemical speciation for some constituents (e.g., formation of
lead carbonate from lead hydroxide).
This report facilitates understanding application and accuracy of the LEAF test methods by
addressing the following important relationships of LEAF test data:
within datasets from the different LEAF test methods conducted on the same material;
compared to the results of test methods currently in more widespread use, specifically the
Toxicity Characteristic Leaching Procedure (TCLP; EPA Method 1311) and the Synthetic
Precipitation Leaching Procedure (SPLP; EPA Method 1312);
relative to field leaching and material behavior over a wider set of disposal and use
scenarios;
in conjunction with chemical speciation modeling and other knowledge to evaluate leaching
under conditions beyond typical laboratory testing conditions.
Furthermore, this report provides recommendations for how environmental scientists, engineers
and regulators may use LEAF as part of their evaluation programs.
In this report, the liquid phase resulting from a laboratory leaching test is referred to as an "eluate"
whereas liquid phase samples collect from field leachate samples are referred to as "leachate." The
term "constituent" refers to a component of a substance in the liquid or solid phase and is the
analytical summation of the various speciation forms of that constituent in that phase. In contrast, a
"species" refers to the chemical unit or speciation of an element in the solid or liquid phases. Thus,
the measured concentration of a constituent (e.g., lead or Pb) in an eluate or solid material may
result from the presence of multiple species containing that element in the designated eluate,
leachate, or solid (e.g., Pb+2, Pb(OH)3-, PbCl2 or organo-Pb species). The "release" of a constituent is
defined as the mass of a constituent leached per mass of solid material (mg/kg) and is calculated by
multiplying the measured COPC eluate concentration (mg/L) by the associated extract or leaching
L/S (L/kg) represented by the volume of liquid in contact with a unit mass of solid. Release is
therefore on a solid phase unit basis and is used to represent the amount of a constituent that has or
potentially may leach, rather than the more familiar liquid phase unit basis that is used to describe
leachate or eluate concentrations.
1.2 Report Objectives and Approach
The primary objective of this report is to provide results from an evaluation of the applicability and
limitations of using laboratory leaching tests, as defined by the LEAF and LEAF-analogous methods,
for estimating leaching of COPCs from a broad range of materials under field disposal and beneficial
use scenarios. This evaluation is achieved by comparison of LEAF laboratory testing of "as
produced" material using LEAF methods, laboratory testing of "field aged" material, and results
from field leaching studies of the material. Interpretation of LEAF leaching data is conducted within
the context of a defined conceptual leaching model and chemical speciation modeling is used as a
tool to facilitate evaluation of scenarios beyond the conditions of common laboratory testing (i.e.,
normalize the laboratory data to the field conditions by estimating the impact of factors not
practical to achieve in the laboratory, but which are known to occur and affect leaching). A second
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objective of this report is to provide recommendations on the selection and use of LEAF testing for
different types of materials or wastes when evaluating disposal or use scenarios.
1.2.1 Field Evaluation Cases
In order to illustrate the relationship between laboratory data and field measurements, ten disposal
and beneficial use cases for which both laboratory and field data exist have been identified and are
presented in this report. These ten field evaluation cases consist of combinations of laboratory
testing and field analysis for the following seven materials:
coal fly ash (CFA; 3 cases);
fixated scrubber sludge with lime (FSSL) produced at some coal-fired power plants by
combining coal fly ash with flue gas desulfurization (FGD) scrubber residue and lime (1
case),
municipal solid waste incinerator bottom ash (MSWI-BA; 2 cases);
a predominantly inorganic waste mixture comprised of residues from soil cleanup residues,
contaminated soil, sediments, construction and demolition (C&D) waste and small industry
waste (IND; 1 case);
municipal solid waste (MSW; 1 case);
cement-stabilized municipal solid waste incinerator fly ash (S-MSWI-FA; 1 case);
portland cement mortars and concrete (1 case).
Table 1-1 provides a summary of the cases and data sets evaluated in this report. In this table, the
types of leaching test data (i.e., laboratory tests conducted on "as produced" site materials,7 analog
materials or field materials), field data (i.e., leachates collected from the field application) and case
conditions are defined for each case. The symbols representing leaching test data for the cases in
Table 1-1 include "pH" for pH dependent leaching data (e.g., from Method 1313), "L/S" for L/S-
dependent leaching data (e.g., Method 1316), "Perc" for percolation column data (e.g., from Method
1314), and "MT" for mass transfer data (e.g., from Method 1315). For a few of the field case studies
where laboratory test results were not available for the specific material present in the field,
laboratory test results on closely analogous materials are used for comparison with field
measurements. The field data presented in this report include (i) leachate from field lysimeters, (ii)
porewater from landfill or use applications, (iii) eluate from leaching tests on sample cores taken
from field sites, and (iv) leachate collected from landfills.
7 In this report, "as produced" materials refer to materials newly processed materials that are ready for disposal or
beneficial use in a field application. This distinction is made relative to aged field materials that have been retrieved from
a field application for testing in the laboratory.
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Table 1-1. Summary of Laboratory-To-Field Comparison Cases
Report
Section
4.1
4.2
4.3
4.4
4.5
4.6
4.7
4.8
4.9
4.10
Case Name (Country)
Coal Fly Ash Landfill
Leachate (U.S.)
Coal Fly Ash in Large-Scale
Field Lysimeters (Denmark)
Landfill of Coal Combustion
Fixated Scrubber Sludge
with Lime (U.S.)
Coal Fly Ash Used in
Roadbase and Embankments
(The Netherlands)
Municipal Solid Waste
Incinerator Bottom Ash
Landfill (Denmark)
Municipal Solid Waste
Incinerator Bottom Ash Used
in Roadbase (Sweden)
Inorganic Industrial Waste
Landfill (The Netherlands)
Municipal Solid Waste
(The Netherlands)
Stabilized Municipal Solid
Waste Incinerator Fly Ash
Disposal (The Netherlands)
Portland Cement Mortars
and Concrete (Germany,
Norway, The Netherlands)
Leaching Test Data
Site Analog Field
Materials Materials Materials
123
pH
L/S
Perc
L/S
PH
L/S
PH
L/S
MT
L/S
pH
Perc
PH
Perc
PH
Perc
PH
Perc
MT
PH
(recycled
concrete)
PH
Perc
PH
PH
L/S
Perc
PH
L/S
Perc
PH
L/S
Perc
PH
PH
Field Data
Leachates
Multiple
landfills
Lysimeters
Landfill
Roadbase,
Embankment
Landfill
Roadbase test
section
Lysimeters,
Landfill
Landfill,
Multiple
landfills
Pilot test
cells.
Landfill
Case Conditions
Ox-Red,
pH 6-13
Ox-Red,
pH 11-13
Ox,
pH 6-12
pH 8-12
Reducing,
pH7-ll
Ox-Red,
pH 7-10
Ox-Red,
pH6-9
Strongly Reducing,
High DOC,
pH5-9
Oxidizing,
pH8-13
Oxidizing,
Carbonation,
pH8-13
Notes:
pH = pH-dependent leaching data (e.g., EPA Method 1313,PrEN 14429, PrEN 14997).
L/S = L/S-dependent data with deionized or demineralized water (e.g., EPA Method 1316, EN 12547).
Perc = Percolation column data, up-flow or down-flow (e.g., EPA Method 1314, CEN/TS 14405).
MT = Monolith or compacted granular mass transfer data (e.g., EPA Method 1315, PrEN 15863).
Ox-Red = oxidized to reducing conditions.
i Site Materials refers to "as produced" source materials placed into the field application.
2 Analog Materials refers to comparative materials for cases where source material sample leaching characterization
information was not available.
3 Field Materials refers to materials retrieved from a field application for laboratory testing.
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1.2.2 Evaluation Approach
For each evaluation case, the following generalized approach is used to compare laboratory test
results for a material to its field leaching:
(v) LSP Leaching - laboratory leaching results provide an understanding of the LSP for COPCs
as a function of pH (e.g., from Method 1313) or L/S (e.g., from Method 1316 or Method
1314). [Field values for these parameters were also obtained]
(vi) Dynamic Leaching - percolation column leaching test results (e.g., from Method 1314)
provide an understanding of percolation-controlled leaching of COPCs under idealized
conditions, and/or mass transport leaching test results (e.g., Method 1315) provide
intrinsic COPC release rates.
(vii) Laboratory-to-Field Comparison - laboratory LSP or dynamic leaching results (e.g.,
percolation or mass transport data) and conditions are compared with results and
conditions measured in the field scenario to evaluate whether local equilibrium is
controlling observed leaching under field conditions. If not, this comparison is used to
determine the extent of preferential flow effects in percolation scenarios or limited water
contact in mass transport scenarios.
(viii) Chemical Speciation and Reactive Transport Modeling - a chemical speciation fingerprint
(CSF) for the material of interest and subsequent reactive transport modeling (i.e.,
combination of speciation and mass transport models) are used to explore the extent that
non-ideal conditions (e.g., preferential flow) and aging conditions (e.g., redox changes,
carbonation, etc.) influence observed field leaching behavior (see Section 3).
1.3 Data Quality and Quality Assurance
Two laboratories, Vanderbilt University (VU) and The Energy Research Centre of The Netherlands
(ECN), were responsible for the laboratory leaching characterization of fly ash, cement mortars and
concrete discussed in this report. VU carried out the leaching characterization of CBP fly ash,
mortar and concrete samples, as well as the cement admixture paste sample (MBD2) as part of
research on behalf of the Department of Energy, Office of Environmental Management. At VU,
leaching procedures and chemical analyses were carried out under the same quality assurance and
quality control procedures specified in the Quality Assurance Project Plan for characterization of
CCRs for research carried out on behalf of USEPA (Kosson etal, 2009).
ECN carried out all leaching characterization of European cement and concrete samples included in
this report. For more than two decades, ECN has been a national and international leader in
developing and implementing leaching characterization methods. Since 1983, ECN has been actively
involved in the development of leaching tests in support of national (The Netherlands) and European
legislation (European Landfill Directive, 2002; Requirement 3 on Health and Environment in the
Construction Products Directive, 1989; End of Waste Directive; in development) through chairmanship
of working groups in the national standardisation body (Nederlands Normalisatie Instituut, NEN) and
the European standardisation organisation CEN. ECN is a qualified laboratory for chemical analysis
and for leaching tests under the Dutch quality assurance program RvA (Raad voor de Accreditatie) with
annual external independent audits on the basis of NEN-EN-ISO 17025. ECN operates under ISO 9000
practice and has an ISO 9001 as well as an ISO 14001 certificate. ECN has participated in many
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interlaboratory comparison (round-robin) studies for leaching characterization methods which has
demonstrated its proficiency (van der Slootetal., 1994,1995, 2001b; Hohberg et al., 2000; de Groot
et al., 1996). The interlaboratory validation studies for the LEAF test methods (Garrabrants et al.,
2012a, 2012b), in which ECN participated and conducted LEAF-analogous European leaching
methods in parallel demonstrated ECN's proficiency in leaching characterization as well as the
comparability of results between USEPA Method 1313 and the European pH-dependence methods,
CEN/TS 14429 and CEN/TS 14497.
DHI works in accordance with the quality management system standard: ISO 9001 as certified by
DetNorske Veritas (DNV). The certificate is covering the following products or services: Consulting,
software, research & development and laboratory testing, analysis & products within the area of
water, environment & health
1.4 Report Limitations
This report focuses primarily on the leaching behavior of inorganic constituents, along with the
influences of solid phase and dissolved organic carbon on inorganic constituent leaching. This
report does not include evaluation of the leaching of organic substances (e.g., polycyclic aromatic
hydrocarbons, pesticides, Pharmaceuticals, etc.) or radionuclides. Future work is needed to include
organics contaminants, radionuclides, and nanoparticles into LEAF although some work is already
progressing in Europe and the U.S. through commercial labs to include organic contaminants and
radionuclides.
The cases evaluated in this report are based on studies carried out over approximately the last two
decades. All the data presented herein should be considered "secondary data." As such, the data
were likely generated for purposes not specifically in support of this analysis. Nonetheless, these
data are useful and broadly appropriate for use in this analysis with some limitations:
Over the time period that is covered by these cases, the knowledge base for leaching
assessment has grown considerably. Thus, if some of these studies were designed and
carried out today, more extensive testing would be completed if necessary resources were
available. However, many of the studies included complete characterization of the initial
material, careful sampling and extensive laboratory leaching characterization in addition to
carefully monitored field lysimeters and field, pilot-scale testing.
Laboratory test methods have evolved since some of these studies were conducted with
several of the most recent test methods standardized or in the process of being
standardized in the U.S. and EU, respectively. In some cases, these studies were conducted
using precursor methods that retain the objectives and general approaches of the
standardized leaching tests. The results of analogous leaching tests (i.e., methods intended
to determine the same leaching characteristic) have been shown to provide similar and
directly comparable results despite minor variations in the procedure or test parameters
(Garrabrants etal., 2012a; 2012b; Lopez-Mezaetal., 2008; van der Slootetal., 1995,1997;
van der Sloot 2010a; Hjelmar et al., 2012). Thus, the fundamental information and
knowledge to be gained from past studies discussed in this report is still valid.
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In some cases, the collection and analysis of field data contain principal uncertainties
including (i) the extent of preferential flow or dilution that may have occurred in sampling
of landfill leachate, and (ii) the exact exposure and aging conditions that contribute to the
field data. Therefore, for each case, the relevant attributes of each sample are summarized
to the extent known or previously reported.
The studies discussed in this report have been carried out by research groups in at least five
countries, each with their own quality assurance and quality control requirements. These
requirements are summarized in Section 4 and are discussed in more detail as part of the
primary documents from which the cases are taken. However, all studies have been
previously independently peer-reviewed as part of required publication processes.
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2 LEACHING TESTS AND CONCEPTUAL INTERPRETATION FRAMEWORK
Leaching is defined as the release of constituents from a solid material to the aqueous phase when
contacted with water. Release to the aqueous phase can be determined by constituent liquid-solid
partitioning (including consideration of solubility, adsorption the solid phase, content available for
leaching, aqueous complexation, etc.), the physical properties of the material that limit mass
transport, the degree to which equilibrium is achieved, and the properties of the contacting liquid.
The solid materials of interest may be soils or sediments (with or without known contamination),
wastes (from municipal, industrial, construction, or nuclear material processing), treated wastes or
waste forms (e.g., cement-stabilized wastes, vitrified wastes or products from a range of
physical/chemical/thermal treatment processes), secondary materials under consideration for
beneficial use (e.g., slags, flue gas desulfurization gypsum, coal fly ash), or construction materials.
The contacting water may be from percolation through porous materials, flow around porous or
nonporous (or fractured) monolithic materials, or from condensation processes. The material may
be water-saturated or unsaturated. The source and fate of the water (and any leached constituents)
may include precipitation, runoff, groundwater, surface water or collected leachate.
The goal of environmental leaching assessment is to provide an estimate of constituent leaching
potential for materials under possible management scenarios that is as accurate as practical or
needed, but also does not under-estimate release ofCOPCs. The intended use of assessments may be
to evaluate the environmental safety of specific management options for a class of materials (e.g.,
beneficial use or disposal scenarios for coal combustion residues), evaluate a specific or set of use
or disposal scenarios for a material (e.g., use of a particular coal fly ash in construction of a roadway,
embankment or structural fill), establish classes or performance characteristics of materials that
may be acceptable for use in defined use scenarios, compare the effectiveness of treatment
processes for specific waste types (such as may be needed for regulatory determinations of
equivalent treatment), delisting of materials categorized as hazardous wastes based on the
material's origin, or to determine remediation goals for contaminated soils or sediments. The
constituents identified as COPCs will be specific to the material being evaluated, with specific COPCs
usually considered because of their inherent human or aquatic toxicity (e.g., arsenic, mercury, etc.).
However, it is important to recognize that leaching of COPCs most often is strongly influenced by the
leaching of other major and trace constituents in the material being evaluated and the constituents
present initially in the contacting water, the general chemical state (e.g., pH, oxidation-reduction
potential, and ionic strength) of the leachantin contact with the solid, and the physical
characteristics of the material that impact water contact. All of the above factors influence the LSP
of COPCs and the rate and extent to which equilibrium between the solid and liquid phase is
approached.
The broad range of potential uses of environmental leaching assessment implies that there is a need
for a graded or tiered approach that provides for flexible, scenario-based assessments and allows
tailoring of the needed testing and information based on the type of intended use of the assessment
and available prior or related information. Furthermore, determination of constituent leaching
estimates that are greater than or equal to the actual expected constituent leaching is necessary to
maintain environmental protection in the face of uncertainty (often referred to as a "conservative"
10
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approach). The extent of the assessment bias toward over-estimation of COPC leaching should
depend on the nature of the decision and the uncertainties regarding the available material and
scenario information. However, even when used as a screening test, LEAF methods provide release
estimates that are more accurate and reliable (i.e., less conservative, or less of an over-estimate) and
robust (able to consider multiple or evolving physical-chemical conditions) than are obtainable
using any single-point leaching test. Testing is considered to be more accurate because of the
tailoring to the range of potential environmental conditions and intrinsic leaching characteristics of
materials inherent in the design of LEAF.
Several physical-chemical factors such as preferential flow and reducing conditions are known to
significantly impact leaching and observed leachate conditions under field conditions but are not
readily reproduced through routine laboratory testing (i.e., using standardized commercial test
methods). As a consequence, while the LEAF test methods directly incorporate many of the
important factors that impact leaching, additional factors such as reducing conditions and
preferential flow are considered through chemical speciation and reactive mass transport
simulations as discussed in later sections of this report.
2.1 LEAF and LEAF-analogous Leaching Tests
The LEAF test methods are presented in Table 2-1 by EPA method number along with a listing of
analogous EU leaching methods. The LEAF methods are designed to measure fundamental leaching
parameters including:
LSP as a function of eluate pH;
LSP as a function of L/S under percolation (column flow) or batch extraction testing;
mass transfer rates from COPC leaching from monolithic or compacted granular materials.
Method 1313 and Method 1316 are parallel batch procedures intended to characterize the LSP at
conditions approaching equilibrium as a function of final extract pH and liquid-to-solid ratio (L/S),
respectively. Method 1314 and Method 1315 are test methods intended to measure the rate of
constituent release under percolation or diffusive/dissolution mass transfer conditions,
respectively. The test parameters and values specified in these methods have been described in a
background information document on the LEAF leaching methods with fully validated methods
available (Garrabrants etal., 2010; Garrabrants etal., 2012a; 2012b).
LEAF-analogous methods, also shown in Table 2-1, include leaching methods from the EU which are
similar in structure and intent to the LEAF methods. Many of these EU methods have only minor
deviations in test structure (e.g., the number of test fractions taken) or in test parameters (e.g.,
specified targets or time durations) from their LEAF counterparts. Documentation supporting the
development and use of the EU test methods is available in the public literature (van der Sloot et al.,
2012; Hjelmar etal., 2012).
The following sections contain brief description of LEAF and LEAF-analogous methods, example
outputs from LEAF testing, and comparison of the results of analogous EU and EPA method results
using the same test material. More detailed comparison and information relevant to the precision
of these methods also has been documented (Garrabrants etal., 2012a; 2012b).
11
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Table 2-1. LEAF Test Methods and Analogous European/International Methods.
EPA
Method
1313'
1314
1315'
1316'
Method Name
Liquid-Solid Partitioning as a Function of
Extract pH using a Parallel Batch Extraction
Procedure
Liquid-Solid Partitioning as a Function of
Liquid-Solid Ratio for Constituents in Solid
Materials using an Up-Flow Percolation
Column Procedure
Mass Transfer Rates of Constituents in
Monolithic or Compacted Granular
Materials using a Semi-dynamic Tank
Leaching Procedure
Liquid-Solid Partitioning as a Function of
Liquid-Solid Ratio in Solid Materials using a
Parallel Batch Extraction Procedure
Short Name
pH-dependence Test
Column Test or
Percolation Test
Monolith Leach Test or
Compacted Granular Leach Test
(generally "Tank Leaching Test")
Batch L/S-dependence Test
Analogous EU and
International
Methods
PrENa 14429
PrEn 14997
ISO/TS 2 1268-4
CEN/TSt 14405
CEN/TC 351-TS-3
ISO/TS 2 1268-3
NEN 7343
NEN7373
PrEN 15863
Compacted Granular
Leach Testc
CEN/TC 351-TS-2
NEN 7345
NEN 7375
EN 12457-2
Notes:
*In Kosson et al. (2002) and other previous works, precursor methods with slightly different test conditions were
used. These precursor methods include:
SR002 as a precursor to Method 1313 without specific target pH values.
MT01 (monolithic materials) and MT02 (compacted granular materials) as precursors to Method 1315 with
minor interval duration changes.
SR003 as a precursor to Method 1316 with no significant changes.
a The "PrEN" designation denotes a preliminary CEN standard method that has been approved by a CEN technical
committee and has completed interlaboratory validation, but is in the final approval process for "EN" designation.
b The "TS" designation denotes a "technical specification" which is a test method resulting from multi-national
consensus and approved by a CEN technical committee, but has not yet completed interlaboratory validation or the
final approval process for "EN" designation.
c Specifications for the Compacted Granular Leach Test are under development.
2.1.1 pH-dependent Leaching Tests
The concentration of hydrogen ion in solution (i.e., pH) has a major influence on the dissolution of
COPC-containing mineral phases as well as on the COPC speciation in aqueous solution and the
extent of adsorption onto or ion exchange with reactive surfaces. Thus, pH is a master variable in
leaching assessment and reporting of pH in the eluate or leachate (i.e., pH at the leaching test end
point) is of critical importance because pH at the approximated chemical equilibrium conditions
controls the observed liquid-solid partitioning behavior for many constituents. Tests that measure
COPC leaching with respect to pH are an important class of equilibrium-based test methods where
the pH of the final extract is controlled as an independent variable in order to characterize leaching
over a broad range of pH values. The pH-dependent leaching tests tend to be parallel batch
extraction tests (i.e., multiple batch extraction conducted at different test conditions) with specific
target pH values intended for the final eluate pH. Control of pH typically is obtained either by initial
acid addition or by automated acid/base addition. The resultant eluate COPC concentrations are
12
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plotted as a function of final eluate pH and are interpreted as a continuum pH-dependent leaching
curve.
Method 1313: Liquid-Solid Partitioning as a Function of pH using a Parallel Batch Extraction Procedure
Method 1313 consists of nine parallel batch extractions at targeted pH values and one extraction at
the natural pH8 of the material. The solid material may require particle size reduction by crushing
in order to facilitate the approach to solid-liquid equilibrium within a reasonable extraction
timeframe. Dilute acid or base in deionized water is added to each extraction according to a pre-test
titration in order to achieve final extract pH values at specified target values ranging between 2 and
13 at an L/S of 10 mL/g-dry The extraction contact time ranges from 24 to 72 hours based on the
grain size of the "as tested" material (i.e., the material after any particle size reduction or air drying
required to improve the handling of the "as received" material). The pH and conductivity of the final
extract solution are recorded and vacuum- or pressure-assisted filtration is used to separate the
liquid and solid phases prior to chemical analysis of the eluate. This method also provides a
titration curve of the solid material defined as the eluate pH response to additions of acid or base
expressed in milli-equivalents (meq) of acid per gram of material with base additions shown on the
x-axis as acid additions less than zero.
Eluate concentrations for constituents of interest are plotted as a function of eluate pH allowing for
comparison to quality control and assessment values (e.g., quantitation or detection limits and
waste disposal or utilization criteria). Eluate concentrations may also be interpolated to the target
pH values to provide a uniform basis for comparison of results as the recorded eluate pH is likely to
differ slightly from target values within specified pH tolerances. Example results for Method 1313
are shown in Figure 2-1 for arsenic leaching from a coal combustion fly ash, both as measured
arsenic concentrations plotted as at measured eluate pH values (left) as well as arsenic
concentrations interpolated to Method 1313 target pH values (right). In the figure, concentrations
for the different parallel batch extractions of the test are connected with a line; however, this line
should not be used as a functional trendline showing pH-dependent leaching between data points.
A large circle is used to denote the natural pH extraction data.
8 The natural pH, also referred to as "own pH", is the final eluate pH response of a deionized water extraction of a solid
material (i.e., no acid or base added) conducted at an L/S 10 mL/g-dry.
13
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I
0.1 -r
0.01
PH
Figure 2-1. Example of Method 1313 data in triplicate for arsenic pH-dependent leaching from a
coal combustion fly ash showing measured data (left) and interpolated data (right). The figures
have been modified from those in Garrabrants et al., 2012a.
EU pH-dependent Methods PrEN 14429 and PrEN 14997
PrEN914429 and PrEN 14997 are European pH-dependent leaching tests developed by the Comite
Europeen de Normalisation (CEN) which are analogous to EPA Method 1313. Although initially
designed to test waste materials, the approach of these methods has been adapted as ISO/TS
21268-4 under the International Standards Organization (ISO) program for soils and soil materials
(ISO, 2007).
Separate sample portions are extracted in parallel at a fixed L/S ratio of 10 mL/g in dilute acid or
base solutions in order to reach stationary pH values at the end of the extraction period. Sample
portions of 15, 30, or 60 g (depending on sample heterogeneity and volumes of extractant required
for chemical analysis) are prepared to have a grain size with 95% (m/m) less than 1 mm. Any
particle size reduction is conducted by crushing. At least eight final pH values are required,
covering at the minimum the range pH 4-12 (including the lowest value <4 and the highest value
>12). The maximum pH differential between final pH points shall not exceed 1.5 pH units. The
amounts of acid or base needed to cover the pH range can be derived from the results of a
preliminary titration, from available experimental data on the material to be tested or from an
arbitrary division of the predetermined maximum consumption of acid and base. The tests are
carried out at a fixed contact time of 48 hours at which time equilibrium conditions are assumed for
most constituents. The equilibrium condition is verified by a pH difference of less than 0.3 pH units
between measurements taken after 44 hours and 48 hours. The results are expressed in mg/L of
constituents for each final pH value. The quantity of acid or base that is added is recorded for each
final pH value in mol H+/kg of dry material with base additions expressed as negative values.
9 The PrEN designation denotes that a draft method which is in the final process for approval as a European standard
(EN). PrEN methods have been developed from a multi-national consensus process, approved by a CEN technical
committee, and completed interlaboratory validation studies to assess method precision. The PrEN designation does not
carry the status of an EN, but the method may be adopted as national standard. With regard to LEAF-analogous methods,
the U.S. EPA interlaboratory validation study on EPA Method 1313 (Garrabrants etal., 2012a) has been accepted by CEN
as the basis for validation for PrEN 14429 and PrEN 14997.
14
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The primary difference between these two EU methods is how the extraction solution is introduced
to the test portion:
PrEN 14429 (2005) - Test portions are contacted with extraction solutions in a closed
vessel with acid/base introduction through initial addition of extraction fluid. At the start of
the test, the extraction solutions are prepared and divided evenly into three fractions. A
fraction of extraction solution is added to the extraction bottle at the start of the test, after
30 minutes, and after 2 hours.
PrEN 14997 (2005) - Test portions are placed into an open vessel with reagent water and
acid/base is introduced via automated pH control. The method specifies that acid or base
addition between cumulative extraction times of 44 and 48 hours shall not exceed 2% of
maximum of the total acid/base addition at 48 hours.
Comparison of pH-dependent Leaching Test Results
The interlaboratory validation program for Method 1313 (Garrabrants etal., 2012a) allowed for a
comparison of leaching test results between Method 1313 and the precursor "technical
specifications" of PrEN 14429 and PrEN 14997 (denoted as CEN/TS 14429 and CEN/TS 14997,
respectively). A sample of the results for testing of a coal combustion fly ash is shown in Figure 2-2
for selected COPCs.
In general, all pH-dependence leaching tests characterize the LSP behavior of fly ash; however, in
Figure 2-2, minor differences were observed in the pH range 6 < pH < 12. These differences are
most likely attributed to kinetic effects where the approximate equilibrium in some tests may not be
established over the test duration to the same degree.
2.1.2 L/S-dependent Leaching Tests
The amount of liquid in contact with a solid sample (i.e., L/S) is another critical parameter
controlling the leaching of COPCs. At low L/S, liquid-solid partitioning and ionic effects in the
aqueous solution control the release of COPCs while such solution chemistry effects are not
significant at high L/S values where the mass of a COPC released into solution may be indicative of
the total amount of COPC in the solid that is leachable. L/S-dependent leaching tests may be
designed as batch extractions over a duration of time required to approach equilibrium or as
percolation column tests at a flow rate low enough to approximate liquid-solid equilibrium. Eluate
concentrations typically are expressed as a function of extraction L/S (for batch tests) or as
cumulative L/S (for percolation tests).
Method 1314: Liquid-Solid Partitioning as a Function of Liquid-Solid Ratio using an Up-Flow Percolation
Column Procedure
Method 1314 is an up-flow percolation column procedure used to evaluate the release of
constituents from solid materials as a function of cumulative L/S.10 Relative to field conditions, L/S
1ฐ Cumulative liquid-to-solid ratio will be denoted as L/S whereas the liquid-to-solid ratio for individual leaching intervals
or test fractions will be denoted as L/Si where the value / represents the endpoint cumulative L/S. For example, L/So.2
refers to first fraction of Method 1314 starting at L/S=0 mL/g-dryand endingatanL/S=0.2 mL/g-dry while L/Sio refers
to the last fraction of the test starting at L/S=9.5 mL/g-dry ending at L/S=10 mL/g-dry.
15
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can be a useful surrogate measure for time when infiltration rates are considered. In the context of
the column test, L/S is defined as the volume of liquid passing through the column relative to the
dry equivalent mass of test material in the column bed and is expressed in units of mL/g-dry A
sample of the solid material of approximately 300-600 grams is packed under moderate effort into a
0.1
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0.001 -
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--Method 1313
CEN/TS 14429
CEN/TS 14997
10
12
14
PH
Figure 2-2. Comparison of pH-dependent leaching tests results for testing of a coal combustion fly
ash using Method 1313, CEN/TS 14429 and CEN/TS 14997 (Garrabrants et al., 2012a).
5-cm diameter x 30-cm long column. Layers of clean silica sand are used at the top and bottom of
the column to provide flow regulation on the inlet side and coarse filtration at the outlet. Leaching
solution (eluent) is pumped upward through the material and eluate is collected as nine discrete
volume fractions of the continuous elution volume. The up-flow percolation mode is intended to
minimize air entrapment and flow channeling. The pump flow rate is adjusted to provide a volume
of eluent equivalent to 0.75ฑ0.25 L/S per day. For primarily inorganic materials, deionized water is
used as the eluent for testing; however, a 1 mM solution of CaCl2 may be used when testing certain
materials (e.g., organic soils, clayey materials) where deflocculation of clay layers or dissolution of
organic carbon may be a concern.
Method 1314 specifies nine eluate fractions collected at L/S values of 0.2, 0.5,1.0,1.5, 2.0, 4.5, 5.0,
9.5, and 10 mL/g-dry. The eluate pH, conductivity and optionally oxidation-reduction potential
(ORP) are recorded for each fraction prior to filtration through a 0.45-|im membrane and
preservation of an analytical sample. After chemical analysis of analytical samples, cumulative
16
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release from the column at the specified L/S values is calculated from eluate concentrations and
interval liquid-solid ratios (L/Si). Thus, the measured eluate concentration for a given fraction
represents the composite or integrated concentration over the designated cumulative L/S interval.
Depending upon the intended use of the test results (e.g., when only cumulative release at specified
L/S values is a concern), analytical samples may be composited to minimize analytical costs, but
typically all eluate collections are analyzed for COPCs. For display purposes, eluate concentrations
are typically graphed as a function of L/S, with the concentration of each individual fraction plotted
at the cumulative L/S at the end of the fraction interval.11 A second useful representation of
percolation test data is the cumulative release for each constituent (i.e., the cumulative amount of a
constituent leached per mass of material tested) as a function of cumulative L/S. Cumulative
release is accurately plotted at the end-point cumulative L/S for each fraction interval. Example
outputs from Method 1314 testing of a contaminated soil from a smelter site are presented in
Figure 2-3 and include the pH of the collected eluate fractions, the graphs of eluate COPC
concentration, and cumulative release of the COPC.
I
0.0001
0.01 -;
0.001 -r
100
0.01
0.1 1 10
L/S (L/kg)
100
0.001
0.01
10
100
L/S (L/kg)
Figure 2-3. Example Method 1314 results for arsenic leaching from a contaminated smelter site
soil showing eluate pH in collected fractions from the column, eluate arsenic concentrations, and
cumulative release of arsenic with L/S (Garrabrants et al., 2012b).
n Since the eluate concentration represents a mean concentration, a more accurate representation would be obtained by
plotting the COPC concentration at the geometric mean L/S over the fraction interval.
17
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Method 1316: Liquid-Solid Partitioning as a Function of Liquid-Solid using a Parallel Batch Extraction
Procedure
Method 1316 is an equilibrium-based leaching test intended to provide eluates over a range of L/S
values from 10 to 0.5 mL/g-dry using five parallel batch extractions in DI water. No acid or base is
added to the extractions so that the results can indicate changes in eluate pH with L/S. Particle size
reduction of the solid material may be required in order to facilitate the approach to solid-liquid
equilibrium. The contact time for the extractions ranges from 24 to 72 hours based on grain size in
a similar manner. The pH and conductivity of the final extract solution are recorded. Solid and
liquid phases are separated by vacuum- or pressure-assisted filtration and prepared for chemical
analysis. This method provides data on the changes in equilibrium chemistry (i.e., ionic strength,
constituent concentrations) as the L/S value approaches that are found within the solid phase pore
solution. Method 1316 output (see example in Figure 2-4) is similar to the output of Method 1314
with eluate pH, eluate COPC concentration and COPC release plotted as functions of L/S. COPC
release results are similar to the results of Method 1316; however, eluate concentrations are
typically higher in Method 1316 due of the natural of batch extraction process.
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EU Percolation Method CEN/TS 14405
CEN/TS 14405 (2004) is an up-flow percolation column test method designated as a "technical
specification"12 by CEN for characterization of waste and has been adopted by ISO under ISO/TS
21268-3 for soils and soil materials (ISO, 2007). A very similar column test, CEN/TC351-TS-3,
sponsored through the CEN Technical Committee 351 is undergoing robustness testing (Hjelmar et
al., 2012). The Dutch standards NEN 7343 (1995) and NEN 7373 (2004) from the Nederlands
Normalisatie Instituut (NEN), are precursors of the CEN/TS 14405 method.
The procedure for CEN/TS 14405 is similar in intent and procedure to Method 1314 with minor
differences in the number of eluates collected and, hence, the prescribed L/S values. CEN/TS 14405
allows for collection of an eluate at 0.1 mL/g-dry that is not specified in Method 1314 due to
limitations of eluate volume at this low L/S. In addition, while Method 1314 specifies a flow rate
based on L/S passing through the column which is dependent on the mass of solid in the column,
CEN/TS 14405 specifies flow rate in terms of eluate volume per time, which is independent of the
solid mass. The CEN/TS 14405 method determines the release of constituents from granular
material packed into a column with a leachant percolating through the column packing. The test
conditions, including the flow rate of the leachant, enable conclusions to be drawn from the results
as to which components are rapidly washed out and which components are released under the
influence of interaction with the matrix.
Test material, with or without particle size reduction, is packed into either a 5-cm or a 10-cm
diameter plastic or glass column that is 30-cm long. Packing is achieved in a standardized manner
with a plastic rammer. Demineralized water leachant is percolated in up-flow through the column
at a specified flow rate of 12 mL/h for a 5-cm diameter column or 48 mL/h for 10-cm diameter
column. The eluate is collected at seven fixed values of cumulative liquid-to-solid ratio or L/S (i.e.,
0.1, 0.2, 0.5,1.0, 2.0, 5.0 and 10.0 mL/g-dry). Each eluate is characterized physically and chemically
for pH, conductivity and concentrations of constituents of interest according to existing standard
methods. In the test procedure, equilibrium conditions at the outlet of the column are verified after
an equilibration period by measuring a pH deviation. The results of the test are expressed as a
function of L/S, in terms of both eluate concentration (mg/L) and cumulative mass release (mg/kg-
dry).
EU Batch L/S Method EN 12457
EN 12457 is a European Standard consisting of a four-part batch leaching procedure in which
particle size-reduced material is extracted with deionized or demineralized water at room
temperature. Parts 1, 2 and 4 of the standard are single-batch extractions at difference L/S ratios
and particle size requirements. Part 3 consists of a two-step test with re-extraction of the recovered
12 The "TS" designation denotes a CEN "technical specification" which is a method that has resulted from a multi-national
consensus process and has been accepted by a CEN technical committee, but has not completed interlaboratory validation
studies and final CEN approval. TS methods may be used as national standards. The U.S. EPA validation data for Method
1314 has been accepted as the basis for validation of CEN/TS 14405, but this method has not yet received the "PrEN"
designation.
19
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material from the first L/S 2.0 mL/g extraction in a second extraction step at L/S of 8.0 mL/g
(cumulatively the L/S is equal to 10 mL/g). In comparison to the LEAF methods, EN 12457-2 is
most similar to the L/S 10 target extractions in Method 1316 and the natural pH extraction of
Method 1313.
Comparison of L/S-dependent Leaching Test Results
The results of Method 1314 and CEN/TS 14405 were compared during validation of the EPA
percolation column test (Garrabrants et al., 2012b). In Figure 2-5, this comparison is shown for
selected COPCs leached from a smelter site soil in terms of mass released from the column tests.
Also include in this figure are the release values resulting from the batch L/S test, Method 1316,
performed on the same material (Garrabrants, et al., 2012a). The three L/S-dependence tests result
in very similar cumulative release data with all tests showing the same general behavior for each
COPC. Differences in the cumulative release from these test methods were considered within the
reproducibility values calculated for the individual LEAF tests (see Garrabrants etal., 2012a, 2012b
for details on performance measurements).
0.1 -:
0.01 -:
0.001
01
IB
CD
0.001
0.01
10
100
0.01 -f
0.01
L/S (L/kg)
10
01
I
\
I
1 -
0.1
/ slope = 1
10
100
L/S (L/kg)
3
i
IB
0)
02
E
3
'E
n 1 -
Method 1314 / slope = 1
Method 1316 .'
A CEN/TS 14405 J-
/
; / A
/t-H**^
0.01
0.1
10
100
0.01
0.1
10
100
L/S (L/kg)
L/S (L/kg)
Figure 2-5. Comparison of L/S-dependent release for a contaminated smelter site soil using
Method 1314 (percolation), Method 1316 (batch L/S) and CEN/TS 14405 (percolation). Data taken
from Garrabrants et al., 2012a, 2012b.
20
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2.1.3 Mass Transport-based Leaching Tests
For materials with low hydraulic conductivity relative to their surroundings, the majority of any
infiltrating water will not percolate through the material but will be diverted to "flow around" the
material. Examples, of such material would be clays and compacted granular materials and
monolithic material derived from solidification/stabilization. When flow-around conditions exist,
constituents must travel through the porous structure of the material to the bulk material surface in
order to be release. Often, this mass transport through the material is the rate limiting factor in
leaching assessments. The rate of mass transport may be characterized using tank leaching tests
where a sample of monolithic or compacted granular material is suspended in a tank of leaching
fluid over a specified leaching interval. The fluid is refreshed in order to maintain a concentration
gradient between the material surface and the pore structure. This gradient is related the driving
force for mass transport through the material. Refreshment of the leaching solution often is semi-
dynamic, occurring in accordance with a specified refresh schedule, such that the leaching method
appears as a large scale, sequential batch leaching procedure consisting of several leaching intervals
that comprise a total or cumulative leaching time.
Method 1315: Mass Transfer Rates in Monolithic and Compacted Granular Materials using a Semi-
dynamic Tank Leaching Procedure
Method 1315 is a semi-dynamic tank leaching procedure used to determine the rate of mass
transport from either monolithic materials (e.g., concrete materials, bricks, tiles) or compacted
granular materials (e.g., soils, sediments, fly ash) as a function of time. Monolithic test specimens
may be cylinders or parallelepipeds, cast in molds or cut/cored to size from larger samples.
Granular materials are compacted into cylindrical molds at optimum moisture content by Proctor-
type compaction methods such as ASTM D698 (2007)orASTMD1557 (2009). Test specimens are
leached in intervals in a series of tanks containing deionized water with each leaching interval
having a specified duration. The volume of deionized water in each tank is based on the surface
area of the test specimen at a liquid-to-surface area ratio (L/A) of 9 mL/cm2. At the end of each
leaching interval, the test specimen is removed from the tank, the mass of the test specimen is
recorded, and the specimen is submerged into another new tank containing fresh deionized water.
The cumulative times corresponding to the end of the nine leaching intervals are 2, 25, 48 hours, 7,
14, 28, 42, 49, and 63 days. For each tank eluate, the pH, conductivity, and optionally ORP are
recorded prior to filtration through a 0.45-urn membrane and preservation of an analytical sample.
After chemical analysis, the mean flux of constituents in each interval (i.e., mass released per
surface area per unit time of the leaching interval) and the cumulative release of constituents (total
mass released per unit surface area as a function of time) are calculated from the eluate
concentration, the volume of eluate collected for each interval, the geometry and mass of the test
specimen, and the duration of each interval. In addition, mass transfer characteristics (e.g.,
diffusivity, tortuosity) may be calculated using assumed mathematical models. An example of the
outputs of Method 1315 conducted on sample of a solidified waste analog (i.e., cement, coal water
matrix spike with metal oxide powders) is shown in Figure 2-6 and include (i) the evolution of pH in
test fractions, (ii) eluate concentrations for a selected COPC, (iii) the mean interval mass flux
21
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(mg/m2 s) of the COPC as a function of cumulative leaching time, and (iv) the cumulative mass
release (mg/m2) of the COPC as a function of cumulative leaching time. This test is used to assess
the combined effects of pore water chemistry (e.g., dissolution, adsorption) and diffusion through a
monolithic or compacted granular material.
12.5
0.
11.5
10.5
11 -
0.01
1E-02
1E-03
1E-04
IE-OS
1E-06
1E-07
IE-OS
0.01
0.1 -;
0.01 -:
0.001
10
100
0.01
Time (days)
1000
100 -:
01
_
&
a
m
ML
MDL
0.1
10
100
Time (days)
0.1
10
100
0.01
10
100
Time (days)
Time (days)
Figure 2-6. Example Method 1315 test results for barium leaching from a solidified waste analog
material showing pH evolution, eluate concentration, mean interval flux and cumulative release
(Garrabrants et al., 2012b).
EU Mass Transport Methods PrEN 15863 and NEN 7375
The EU mass transfer leaching test, PrEN 15863 (2009) and the Dutch standard mass transfer test,
NEN 7375 (NEN, 2004), are similar in intent and procedure to Method 1315. Differences include
the total testing duration, the number and duration of the testing intervals, and the basis for
determination of the amount of liquid used in each leaching interval as shown in Table 2-2.
Currently, a similar procedure, CEN/TC 351-TS-2, is undergoing robustness testing for use with
construction products under CEN Technical Committee 351 (Hjelmar etal., 2012). Dutch standards
NEN 7345 (1995) and NEN 7375 (2004) are precursors of the PrEN 15863 method while CEN/TS
15863 is the technical speciation designation for PrEN 15863.
22
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NEN 7375 Procedure
NEN 7375 is a test intended to define leaching from molded or monolithic materials under mass
transfer conditions as a function of time. The test determines the nature and properties of the
material matrix by placing a complete sample in a leaching fluid of demineralized water and
replenishing the eluate at eight specified cumulative times of 0.25,1, 2.25, 4, 9,16, 36, and 64 days.
Test specimens should have a minimum dimension of 40 mm and a geometric surface area of at
least 75 cm2. The volume of eluent for each leaching interval is based on the test specimen volume
with 2-5 mL of eluent for every cm3 of test specimen. From analytical samples of each eluate
collection, the composition of the eluate is determined using standard methods, and the leached
quantity per unit area is calculated for each constituent. Parameters that can be deduced from the
development of release of constituent over time include the extent of surface rinsing and the
effective diffusion coefficient which can be used to estimate leaching over longer periods.
PrEN 15863 Procedure
PrEN 15863 is a procedure for leaching of a solid monolithic material in a similar manner as NEN
7375 or Method 1315. The test specifies that a regular shaped test specimen is prepared by cutting
or coring in accordance with standard sampling methods. The test specimen is submerged in a tank
of demineralized or deionized water for specified interval durations for a series of eight leaching
intervals (see Table 2-2). Leachant is refreshed at cumulative times of 0.08,1, 2.25, 8,14,15, 28,
and 36 days. For each eluate, pH and conductivity are measured and recorded prior to preparation
for chemical analysis using standard methods. The results of the test are the cumulative mass
release (mg/m2) expressed as a function of time.
Table 2-2. Comparison of Method 1315 and EU Mass Transfer Test Parameters.
Parameter Method 1315 PrEN 15863 NEN 7375
Total Test Duration (d)
Eluate Volume Basis
Liquid Volume
Number of Intervals
Refresh Exchanges at
Cumulative Times (d)
63
specimen
surface area
9ฑ1 mL/cm2
9
0.08
1.1
2.0
7
14
28
42
49
63
51
specimen
surface area
8ฑ1 mL/cm3
8
0.08
1.0
2.25
8
14
15
28
36
64
specimen
volume
2-5 cm3/cm3
8
0.25
1.0
2.25
4
9
16
36
64
23
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Comparison of Mass Transport Test Results
Figure 2-7 shows the comparison of interval mean flux for mass transport of selected COPCs in a
solidified waste analog for EPA Method 1315, NEN 7375 and CEN/TS 15863 (the technical
specification of PrEN 15863). This figure shows that the general trend of the interval flux is
consistent despite the different interval durations of the tank leaching tests.
I
5
1E-02
1E-03
O 1E-04 -
IE-OS
1E-06
1E-07
1E-02
0.01
0.1 1
Time (days)
100
1E-06
1E-07 -
IE-OS
0.01
0.1 1
Time (days)
100
1E-07
Ol
0.01
0.1 1
Time (days)
100
1E-07
0.01
0.1 1
Time (days)
100
Figure 2-7. Comparison of mean interval flux release results for testing of a solidified waste
analog using Method 1315, CEN/TS 15863 and NEN 7375. Data taken from Garrabrants et al.,
2012b.
2.2 A Conceptual Framework for Interpreting Leaching Test Data
Detailed material characterization consists of laboratory measurement (i) LSP as a function of pH
(pH-dependent leaching), (ii) LSP as a function of L/S either by percolation column or by parallel
batch procedures, and (iii) rates of mass transport under diffusion-controlled conditions. Data sets
from the currently-specified LEAF, EU and respective precursor test methods (Table 2-1) are the
laboratory test results used in this report for comparison with field data. Laboratory leaching test
results are used here primarily to illustrate a conceptual framework for the relationships between
test method results and field data because more complete testing information is available for the
24
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laboratory tests, including a wider range of test method results and constituents analyzed, than is
available from reported field data and studies.
2.2.1 Liquid-Solid Partitioning at Equilibrium
Equilibrium-based leaching test measure LSP under specified test conditions. For example,
Methods 1313 and 1316 determine the effect of pH and L/S, respectively, on LSP under batch test
conditions which are intended to approximate chemical equilibrium between the aqueous and solid
phases (Garrabrants et al., 2010). Similarly, column percolation tests carried out at relatively slow
flow conditions (e.g., residence time ~1 day or less) approximate local equilibrium between the
pore solution and solid phase at any given point in the column. Therefore, eluates collected
between two L/S values indicate the average release over that L/S interval. The primary
distinguishing feature of a percolation test over that of a batch L/S procedure is the column test
captures the effects of different elution rates of COPCs into the pore solution at different L/S values
with the result that the local composition of the system changes as the amount of liquid passes
through the column. Under the assumption of a constant flow rate, the cumulative L/S (e.g., the
volume eluted from the column divided by the dry mass of solid material in the column) is used as a
surrogate for elution time.13 Column percolation tests also often are considered a surrogate for field
leaching conditions for scenarios where infiltration or groundwater passes through a relatively
permeable solid; however, field conditions are much more likely subject to preferential flow, and
therefore infiltration bypassing the material in question results in lower observed concentrations in
the field than the laboratory14
For all equilibrium-based leaching tests, the approximation of local equilibrium is the result of
pragmatic choices in selection of appropriate contact times, because attaining true chemical
thermodynamic equilibrium would, in most cases, require test durations far longer than practical
for routine implementation in a decision-making framework.
Chemical Phenomena Affecting LSP
The resulting LSP of constituents in a material at chemical equilibrium can be the result of several
chemical phenomena that occur either individually, with one phenomenon dominant in the
observed behavior, or with multiple phenomena occurring simultaneously with different
phenomena controlling the observed behavior under different pH or L/S conditions.
To illustrate this concept, the several response types are used to describe dominant leaching
mechanisms under common partitioning behaviors. Most of these response types can be
distinguished based on examination of the results from one or more of the LEAF test methods,
however, for some situations, chemical speciation may be needed to clarify the contributing
13 In many column test procedures, the number of pore-volumes eluting from the material is used as the comparison basis
rather than cumulative L/S. Cumulative L/S was selected as the basis for comparison for Method 1314 because it is not
dependent on system porosity and provides a convenient basis for comparing results of Method 1314 with Methods 1313
and 1316.
i4 The extent of preferential flow during percolation can be evaluated based on the observed concentrations and elution
profiles for highly soluble constituents such as sodium, potassium, chloride and nitrate. Greater extents of preferential
flow result in lower peak concentrations and longer tailing of elution curves.
25
-------
mechanisms (i.e., distinguishing between precipitation and adsorption at low constituent
concentrations).
Response 1. Total Content vs. Availability
A constituent, or fraction thereof, may be incorporated into one or more solid phases or mineral
structures that do not readily dissolve in water, thereby rendering that fraction of the
constituent not available for leaching under reasonable environmental conditions and relevant
time frames (e.g., years to decades). Although the solid phase or mineral structure containing
the constituent may be dissolved over geologic time frames due to weathering and aging which
may allow for leaching of the constituent in the long term, these time frames typically are long
enough that leaching may have little impact on groundwater when carried through a risk
assessment. One example of this response is the incorporation of lead into stable alumina-
silicate phases where the alumina silicate phases must be dissolved to release the lead and have
been found to be stable over geologic time frames (i.e., amorphous glassy phases and other
mineral phases). The fraction of lead not bound in these recalcitrant phases is considered the
available fraction of the total content in the material, often referred to as "availability." The sum
of the lead incorporated into recalcitrant phases and available content of lead is the total lead
content in the material. Comparison of total content to maximum leaching concentration for a
wide range of CCRs illustrated that total content and available content are not correlated
(Thorneloeetal., 2010).
Response 2. LSP less than Aqueous Solubility
A constituent, or fraction thereof, may be present in one or more readily soluble solid phases
that dissolve fully into the aqueous phase under the leaching test conditions with the resultant
constituent concentration in the aqueous phase less than the aqueous solubility (i.e., an under-
saturated solution). One example of this case is the dissolution of sodium chloride when the
total amount of dissolvable sodium and chloride results in concentrations in the aqueous phase
that are less than the respective solubility for each constituent. In this case, the available
content of a constituent could be the limiting factor in the concentration seen in laboratory
testing (referred to as "availability-limited" leaching).
For many of these highly soluble species, the LSP curve is not a strong function of pH, and eluate
concentrations remain relatively constant across the pH range. When availability-limited
release is dominant, eluate concentrations increase with decreasing L/S (i.e., the same mass of
constituent is released into less liquid), but mass release is independent of L/S (i.e., when
normalized to the mass of the solid material tested, mass of the constituent release is relatively
constant with changes in L/S). An illustration of availability-limited leaching as a function of pH
and L/S is shown in Figure 2-8 using chloride release from a sample of unwashed flue gas
desulfurization (FGD) gypsum with material code SAU (Kosson etal., 2009).
26
-------
o
4=
O
u
a
a
z
o
I
1
+1
2
ง
I
c
f
u
c
1
)
<
? i.
\ e
---_
>
I
--
;
)H
.
-
-Unwashed FGD Gypsum
(SAU, SR02)
i 10 12 1
^^^
-Unwashed FGD gypsum
(SAU, SR03)
10000
oi 1000
ฅ
_S 100
8.
a
TO
2
f
u
10 -:
10
* '
I, 4
1
Unwashed FGD gypsum
(SAU, SR02)
10000
1000 -
2. 100
8.
z
o
10 -
10 12 14
PH
Unwashed FGD gypsum
(SAU, SR03)
10
L/S (L/kg)
L/S (L/kg)
Figure 2-8. Chloride as an example of a highly soluble species where the observed leaching
concentration is a function of L/S but not a function of pH for an unwashed gypsum material
from coal combustion flue gas desulfurization (SAU, after Kosson et al., 2009).
Response 3. LSP at Aqueous Solubility
A constituent, or fraction thereof, may be present in one or more solid phases that will only
partially dissolve into the aqueous phase under the leaching test conditions with the resulting
constituent concentration in the aqueous phase at the aqueous solubility (i.e., a saturated
solution). This phenomenon is referred to as "solubility-controlled" release. An example of this
case is the dissolution of arsenic from a highly alkaline coal fly ash under neutral to alkaline pH
(Figure 2-9).
When this phenomenon is dominant in leaching, eluate concentrations typically are strong
functions of pH and are constant with decreasing L/S (i.e., the dissolution of the partial soluble
solid phase controls the eluate concentration). As long as pH remains relatively constant with
decreasing L/S, the constituent mass release will decrease with decreasing L/S at a rate
approximately proportionate to the decrease in L/S (e.g., a reduction in L/S from 10 to 0.5
mL/g-dry will result in a 2 Ox decrease in constituent). However, the greater ionic strength at
lower L/S may also impact the amount leached. In addition, trace constituents may also co-
precipitate with major element solid phases, resulting in solid solutions and more complex
behavior where the observed liquid concentration for the trace species is proportional to the
content of that species in the solid solution.
27
-------
_ 100
Ol
o
u
I
u
U
5
ซ
0.1 -:
0.01
--Coal fly ash (EaFA, M1313)
O own pH
0.1 -
n m -
--Coal fly ash (EaFA, M1316)
i-
10
Oi
E
100
10 -:
1 -r
0.1 -:
0.01
3
0.01
7
--Coal fly ash (EaFA, M1313)
O own pH
2 4 6 8 10 12 14
PH
L/S (L/kg)
L/S (L/kg)
Figure 2-9. Arsenic as an example of solubility-controlled (saturated solution) leaching as a
function of L/S and pH for a coal combustion fly ash (EaFA; after Garrabrants et al., 2012a).
Response 4. Surface Interaction
A constituent, or fraction thereof, may be present as a readily soluble species that is not initially
present in the material as a distinct, precipitated solid phase. The constituent species may be
present at a relatively low concentration associated with a reactive solid surface where the LSP
is controlled by adsorption/desorption or ion exchange phenomena. Such reactive surfaces
include oxide minerals (e.g., iron, manganese, or alumina (hydr)oxides), (ii) clay-like minerals,
(iii) particulate organic carbon (such as from decay of plant matter), and (iv) particulate carbon
(such as char from combustion or activated carbon). When adsorption/desorption or ion
exchange phenomena control constituent leaching, the constituent species of interest is
fractionally distributed between the aqueous and solid phases at equilibrium, with the
fractional distribution influenced by (i) the total available amount of the constituent in the
liquid-solid system, (ii) the nature and amount of reactive solid surface in the system, and (iii)
the aqueous solubility of the species at the test conditions.
For many constituents, the initial speciation (i.e., chemical forms) and distribution in the solid
material are often a combination of two or more of the four phenomena described above. Examples
include (i) chloride present both in a relatively insoluble alumina-silicate phase and as sodium
28
-------
chloride crystals (Responses 1 and 2, above; Figure 2-8), (ii) lead present both in a relatively
insoluble alumina-silicate phase and as a lead molybdate phase (Responses 1 and 3, above), or (iii)
arsenic present as several species with the resultant leaching behavior a combination of Responses
1, 2 and 4, as described above (Figure 2-9).
2.2.2 pH, Ionic Strength and Aqueous Phase Complexation as LSP Modifying Parameters
The above phenomena and resulting observed leaching behavior is further complicated by the
following modifying factors:
Eluate pH
The solubility of some constituents, such as periodic table Group IA elements (e.g., sodium,
potassium) and anions (e.g., chloride and nitrate), is not strongly affected by pH and, therefore,
tends to have leaching characteristic behavior consistent with Response 2, above (Figure 2-8).
In contrast, the solubility of some constituents is strongly dependent on pH and can exhibit
behavior consistent with Response 2 over some pH domains and Response 3 over the remaining
pH domains. For the example of a coal fly ash in Figure 2-10, magnesium is very soluble atpH <
8 (Response 2) while forming a saturated solution atpH > 9 (Response 3). Conversely,
molybdenum is very soluble atpH > 8 while forming a saturated solution atpH < 6. This
phenomenon allows the availability of many constituents to be estimated based on the
maximum or asymptotic release over the domain of 2 < pH < 13.
.2 in -
E
s .
z?
o "ฑ: n 1 -
ฃ.ง
1 o.oi -
g
S1 o.ooi
n nnm -
! ป-^_^
^-o --ป_,
r
[
v
*\
\
--Coal fly ash (TFA, SR02)
O own pH
\
\
-A
Si~
10 12 14
PH
Figure 2-10. pH-dependent solubility of magnesium and molybdenum for coal fly ash sample
TFA (after Kosson et al., 2009).
Ionic Strength
The presence of other constituents in the aqueous and solid phases often influences the solid
phases present for the constituent of interest (speciation of precipitated solids) and resultant
solid phase solubility in the aqueous phase. One effect of the presence of highly soluble
constituents is reflected in changes in ionic strength, which impacts solubility through changes
in chemical activity (i.e., activity coefficients). Another effect might be precipitation of a
constituent phase due to dissolution of a related phase through the presence of a common ion.
29
-------
An example of the common ion effect is that barium will precipitate as barium sulfate as calcium
sulfate dissolves, leading to apparent chemical interactions between calcium and barium
leaching in the presence of sulfate.
Complexation and Chelation
Some constituents in solution may complex or chelate with a constituent of interest, shifting
equilibrium toward the aqueous phase and increasing the LSP eluate concentration over the
aqueous solubility afforded only by mineral dissolution. Examples of this include (i)
complexation of cadmium by chloride at neutral to moderately alkaline pH, and (ii) the
chelation of copper with DOC (e.g., humic and fulvic substances, especially in MSW landfill
leachate) at moderately acid to alkaline pH (Figure 2-11).
a.
a.
o
u
1 .
n
X
v
\
N,
^\50
\
QฐC
*-.
k.
- "^
,>
30C
>
-MSWI Bottom Ash (fresh)
-MSWI Bottom Ash (reheated to 500 C)
-Reheated MSWI Bottom Ash with 1 wt% Compost
10
12
14
PH
Figure 2-11. Illustration of the influence of organic matter and DOC on leaching of copper
through three cases: (i) fresh municipal solid waste incinerator (MSWI) bottom ash, (ii) the
same MSWI bottom ash heat treated at 500 ฐC to remove organic matter, and (iii) the heat-
treated MSWI bottom ash from above with 1% compost added to provide organic matter
(after van der Sloot et al., 2008c).
In most cases, only the total concentration of a constituent, rather than the chemical speciation of a
constituent, is measured in a leaching test eluate or leachate and in the solid material being
evaluated because of analytical method limitations or cost. Thus, chemical speciation of individual
constituents is most often only inferred based on empirical observations (i.e., characteristic liquid-
solid partitioning behavior) or assessed by chemical speciation modeling (see Section 3).
2.2.3 Oxidation-Reduction Considerations for Leaching Tests and Leaching Assessment
For constituents with multiple valence states under the range of oxidizing to reducing conditions
observed in the field, the oxidation-reduction potential (ORP) of the pore water and bulk solutions
in contact with solid materials can influence the resulting LSP and precipitated solid phases. In the
context of the case studies evaluated in this report, the most relevant constituents for reduction/
30
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oxidation (redox) are Fe and S as species that control the LSP of other constituents and As, Cr, Cu
and V as redox sensitive species that frequently are considered COPCs in environmental systems.
In order to provide context for redox relationships with respect to leaching and geochemical
speciation modeling (Manahan, 1991):
where pE is the -logjelectron activity} or redox of the aqueous system at the stated
conditions,
Fis Faraday's constant,
R is the ideal gas law constant,
7Ms the absolute temperature, and
EH is the measured half-cell potential against a standard hydrogen electrode (in
contrast to use of a saturated calomel reference electrode15 as typically measured in
the laboratory).
If the oxidized and reduced species (i.e., Fe3+ and Fe2+) are both at unit activity16, than E=Eฐ and
pE=pEฐ at the stated temperature (usually 25 C). Values for pEฐ are available in standard
tabulations (Pourbaix, 1963; Sillen and Martell, 1964). For conditions where the oxidized and
reduced species are not at unit activity (which is typically the situation for leachates and other real
aqueous solutions), then the value for pE can be calculated as follows:
1 [oxidized species}a
pE = pEฐ +-log - - - -
n {reduced species}"
where a and b are the reaction stoichiometric coefficients for the redox half reaction and n is the
number of electrons transferred.
The redox conditions for water are limited by the following oxidation and reduction reactions and
resultant constraints:
Oxidation
2H2o 02 + 4H++4e-
y402 + H+ + e-o %H20 pEฐ = 20.75 (at 25 C)
/ 1 \
pE = pEฐ + log! P* [H+] I , assuming the partial pressure of oxygen, P02 = I
pH + pE = 20.75
is In the laboratory, EH=Emeasmed + EKfcieuce electrode where Reference electrode is dependent on the type of
reference electrode used.
i6 Activity is the thermodynamic effective concentration in solution considering ion-ion interactions.
In dilute solutions, activity is approximately equal to concentration, and unit activity is equal to a
concentration of 1 mole/L.
31
-------
However, in equilibrium with atmospheric oxygen, P02 = 0.21 and therefore
pH + pE = 20.59 (at 25 C)
Reduction
H++e-o i/2 H2 pEฐ = 0.00(at25C)
pE = pEฐ + log([H+])
pH + pE = 0(at25C)
The oxidation and reduction constraints imposed by the stability of water impose a plausible
domain of pH + pE between 0 (fully reduced) and 20.75 (fully oxidized) as illustrated in Figure 2-12.
The actual redox of a system results from the combined effects of oxygen supply (i.e., atmospheric
exchange, often limited by diffusion or barometric changes), oxygen consumption by microbial
respiration and oxidation of organic matter (i.e., POM and DOC), anaerobic microbial respiration
and fermentation (i.e., nitrate reduction (pฃ'0=21.05), iron reduction, sulfate reduction (pฃ'0=4.13)
and carbonate reduction (pEฐ=2.87], and/or the presence of reducing inorganic solid phases (i.e.,
sulfides, iron) which often result from high temperature processing (i.e., in slags from steel and iron
production). Thus, reducing conditions in the field can result as a consequence of either the
material being managed or imposed as a consequence of microbial processes and limited oxygen
supply. Organic matter (i.e., POM and DOC) that provides the substrate (i.e., food source) for
microbial processes can either originate from the material being managed (i.e., MSW, MSWI bottom
ash, soils) or from external sources (i.e., decay of leaf litter or commingling of materials). During
laboratory pH dependent testing (i.e., Method 1313), oxidizing to mildly reducing conditions (i.e.,
pH+pE > 13) are most often present because of aerobic handling of materials and use of nitric acid
to adjust pH, although more reduced conditions may result from highly reducing materials such as
blast furnace slag. Percolation column testing (i.e., 1314) can result in an evolving redox condition
as the test progresses for materials containing significant amounts of organic matter because initial
conditions are oxic while microbial activity can deplete oxygen and produce reducing conditions as
the test progresses over several days. The potential for redox changes should be considered when
evaluating laboratory testing results and field scenarios. Consideration of potential effects of
reducing conditions is most readily accomplished through sensitivity evaluation as part of chemical
speciation modeling because accurate control of redox conditions in the laboratory presents many
challenges that go beyond the capabilities of many commercial laboratories. Examples of using
sensitivity analysis as part of chemical speciation modeling (i.e., varying the simulated conditions
over a range of pH+pE values) is included in the discussion of many of the laboratory to field
comparison cases in subsequent sections.
The relationship between pH and pE that results in the formation of a particular mineral phase
depends on the stoichiometry of the reaction, and whether or not H+ (or OH-) is involved in the
reaction as well as electron transfer (which is inherent in a redox reaction). For example, the
reduction of iron according the reaction
32
-------
Fe(OH)3Cs) + 3H+ + e- o Fe2+Caq) + 3H20
includes the reduction reaction of Fe3++ e- -> Fe2+, pEฐ=13.2 (at25 C).
This results in the relationship for the observed Fe activity in solution (where activity is
approximately equal to concentration in dilute solutions),
3pH + pE = 17.16 -[Fe2+].
Within the discussion included in this report, the following redox reactions are important:
1. Iron reduction from Fe3+ to Fe2+ because Fe3+ in the form of hydrous ferric oxide (HFO)
provides adsorptive surfaces for many species, thus impacting LSP. Fe2+ is relatively soluble
at neutral to mildly acidic pH, while Fe3+ is essentially insoluble over the same pH range, so
reduction of Fe3+ to Fe2+ results in increased solution concentrations of Fe and loss of
adsorption of other constituents from solution to HFO surfaces, increasing the solution
concentrations of these constituents. A predominance diagram, which is a presentation of
the predominant speciation of a constituent (solid phases or dissolved phases as indicated
by charged species) as a function of pH (x-axis) and pE (y-axis), is provided for iron (0.1 M)
in the presence of sulfate (0.1 M) in Figure 2-12. The precise speciation, precipitated
phases and transitions reflected in a predominance diagram is dependent on the presence
and overall content of multiple constituents in the simulated system (i.e., iron, sulfate,
carbonate, calcium, etc. usually reflected as a molar concentration (M) in the unit solid plus
liquid simulated volume) and therefore simple systems are used here to illustrate general
phenomena. HFO predominates as the solid phase controlling iron solubility transitions to
other phases between pH+pE between 5.5 and 4 at neutral to alkaline pH (orange region),
becomes soluble Fe2+ between pH+pE between 5.5 and 13 and pH less than 7 (aqua region)
and become completely solubilized atpH+pE greater than 4 and pH less than ca. 2.5. Iron
precipitates with sulfide (produced from the concurrent reduction of sulfate) begins to form
at pH+pE of 5.5 and predominates at pH+pE below approximately 4.
2. Sulfate reduction to sulfide (i.e., S22- to S2- or S042- to HS-) results in the precipitation of other
constituents (i.e., Fe, Cu) as sulfide minerals that are relatively insoluble. The relationship
between the sulfur species can be written as (Stumm and Morgan, 1996)
S042- + 9H+ + 8e- o HS- + 4H20
which results in the relationship
1.125pH + pE = l/81og[SOf-] - l/81og[HS~]
Figure 2-13 presents a Pourbaix diagram for sulfate (0.1 M) in the presence of iron (0.1 M).
The aqua region (pH+pE greater than 5.5 and pH greater than ca. 3 indicates dissolved
sulfate as the predominant speciation, while the red region that begins at pH less than 7
indicates a domain where reduced iron (Fe2+) precipitates as iron sulfate (FeS04). AtpH+pE
less than 5.5 sulfate becomes reduced to sulfide and precipitates as iron sulfide species. In
contrast, Figure 2-14, presents a predominance diagram for sulfate (0.1 M) in the presence
of iron (0.1M) and now also with calcium (0.1 M). The addition of calcium to the system
results in the formation of anhydrite (CaS04 or gypsum, indicated by a blue region) which
33
-------
limits the availability of sulfate to precipitate with iron (iron sulfate now only forms in a
very small region indicated in orange).
3. Figure 2-15 presents a predominance diagram for arsenic (0.1 M) in the presence of sulfate
(0.1 M). Arsenic is present in aqueous solutions as As(v) in the form of HzAsCU-, HAsCU2- or
AsCU3- (aqua, light green and light blue regions) and as As(III) in the form of I-bAsO3- or
HAs032- (dark green regions), depending on the pH and pE of the system. At pH+pE less than
5.5, arsenic speciation transitions to As(III) precipitated with sulfide as the mineral
orpiment (brown-gray region). Arsenic also precipitates with calcium and is adsorbed onto
HFO surfaces when present (not included in Figure 2-15).
4. Figure 2-16 presents a predominance diagram for chromium (0.1 M). Reduction of Cr6+
(usually as Cr042' in solution, light aqua region) to Cr3+ dramatically changes Cr solubility at
slightly acid to slightly alkaline pH, where Cr3+ as Cr(OH)3 is relatively insoluble near neutral
pH (dark green region) while Cr042- is very soluble. Cr3+ is soluble at both alkaline pH (as
CrO2-, light green region) and acidic pH (as Cr(OH)2+, light olive region, or Cr3+, light green
region).
5. Figure 2-17 presents a predominance diagram for copper (0.1 M) in the presence of sulfate
(0.1 M). Copper redox reactions result with complex set of potential solid phases with the
primary Cu reduction being:
Cu2+ + e- -> Cu+ pEฐ = 2.59
6. AtpH+pE greater than 13, copper precipitates as tenorite (CuO) from over a wide pH range
(dark blue region) or atpH+pE between approximately 5.5 to 13 as cuprite (Cu20).
However, Figure 2-17 can be misleading because copper readily forms solution complexes
with dissolved organic carbon (i.e., humic substances) and therefore much higher solution
concentrations of copper are observed at near neutral pH in systems with significant
amounts of organic carbon (i.e., soils and wastes) as discussed in later sections of this
report. AtpH+pE less than ca. 6, copper precipitates as sulfide mineral phases such covellite
(CuS) and as Blaublei II (mix of CuS and Cu2S).
7. For vanadium, multiple valence states and complex solution species are possible, with V(V)
being the dominant valence state and present in solution as HV042~, HV073-, H3V207- and V02+
over alkaline to acidic pH, respectively (Figure 2-18). V(IV) as V02+ (gray region) and V(III)
as V3+ (light gray region) also can be present in solution at acidic reducing conditions.
34
-------
Figure 2-12. Predominance diagram for iron (0.1 M) in the presence of sulfate (0.1 M).
13.0
Figure 2-13. Predominance diagram for sulfate (0.1 M) in the presence of iron (0.1 M).
35
-------
1.0
PH
7,0
13.0
Figure 2-14. Predominance diagram for sulfate (0.1 M) in the presence of iron (0.1 M) and calcium 0.1
M).
36
-------
pH+pE=13
H3As042
' 1,0
7.0
13.0
PH
Figure 2-15. Predominance diagram for arsenic (0.1 M) in the presence of sulfate (0.1 M).
pH+pE=0
H
1.0
7.0
13.0
PH
Figure 2-16. Predominance diagram for chromium (0.1 M).
37
-------
13.0
Figure 2-17. Predominance diagram for copper (0.1 M) in the presence of sulfate (0.1 M).
38
-------
.4jH+pE=13
HV073
13.0
Figure 2-18 Predominance diagram for vanadium (0.001 M).
2.3 Relationships Between Results from the LEAF Leaching Tests
2.3.1 Equilibrium-based Leaching Tests
Eluate constituent concentrations from batch equilibrium-based leaching tests (e.g., Method 1313,
Method 1316) should be consistent under the same test conditions within the range of documented
inherent test variability (see Garrabrants et al., 2012a, 2012b). Therefore, COPC concentrations in
the pH-dependent extraction at natural pH and L/S=10 mL/g are expected to be the same as COPC
concentrations in an L/S-dependent extraction of the same material at L/S=10 mL/g. This can be
demonstrated by plotting both pH- and L/S-dependent results as a function of eluate pH as shown
in Figure 2-19 for leach testing of a contaminated smelter plant soil using Method 1313 and Method
1316.
The results of percolation tests may represent equilibrium between the solid and liquid phases or
mass transfer of constituents from solid particles depending on test conditions (e.g., flow rate,
column geometry, etc.). Initial interpretation of column percolation test results can be made based
on the following:
The two first eluate fractions collected as part of a percolation test, at cumulative L/S=0.2
and 0.5 mL/g-dry, provide a good estimate of constituent concentrations in the material
porewater because of the pre-equilibration of the system prior to beginning eluent flow.
39
-------
These two fractions also provide a useful estimate of the maximum expected initial leachate
concentrations and porewater composition under field monofill conditions.17 The
constituent release measured in the first two eluate fractions collected as part of a
percolation test (i.e., Method 1314) also are comparable to the L/S=0.5 mL/g-dry eluate
collected as part of the L/S dependence test (i.e., Method 1316), while the integrated
concentrations measured in the first two eluate fractions of Method 1314 are comparable to
the L/S=0.5 mL/g-dry eluate collected as part of Method 1316. For both tests, the system
composition is similar because little elution has occurred from the column at low L/S.
For constituents that follow Response 2 LSP (i.e., highly soluble constituent), the cumulative
release from the percolation test at cumulative L/S=10 mL/g-dry should be comparable to
the release observed at the natural pH of the material from the pH-dependence test (i.e.,
Method 1313; see Lopez Meza, 2008) and at L/S=10 mL/g for the L/S dependence test (i.e.,
Method 1316) because the system is relatively dilute under the batch conditions of the pH-
dependence test and the L/S dependence test at L/S=10 mL/g and, therefore, interactions
with other ions (e.g., ionic strength effects) often are not significant18. Furthermore, the
eluate concentration curve should follow "first flush" phenomena with a large decrease (i.e.,
one or more orders of magnitude) in eluate concentration by cumulative L/S=2 mL/g.
For many Response 2 constituents, the release curve of the L/S-dependent leaching test
appears to gradually approach a constant value. Often, the level of this asymptotic behavior
roughly corresponds with the available content derived from the maximum of the pH-
dependent leaching curve (see example boron release in Figure 2-19). Such behavior
indicates a release-limiting case where the available content, or majority of the available
content, has been released from the solid material.
For constituents that follow Response 3 LSP (i.e., aqueous saturation), the percolation test
eluate concentration is approximately constant as a function of cumulative L/S if the eluate
pH is constant. The percolation test eluate concentration also should correspond with the
pH-dependence test eluate concentrations at the corresponding eluate pH values. The
resulting percolation test cumulative release curve has a slope of approximately 1.
For constituents that follow Response 4 LSP (i.e., surface interaction), the percolation test
eluate concentration profile will be variable between the profile observed for Response 2
and Response 3 LSP as described above because of adsorption-desorption partitioning
which may result from either a linear or non-linear isotherm depending on the constituent,
concentration and competing constituents. Similarly the slope for the cumulative release
will be between that of Response 2 LSP and less than 1.
17 Lower initial field leachate concentrations may be observed because of a greater extent of preferential flow or flow
channeling under field conditions.
18 According to the Davies equation for activity coefficients (Sawyer et al, 2003), the impact of ionic strength effects will
be less than 20 percent of the measured concentration for an individual constituent if the ionic strength of the solution is
less than 0.06 M for monovalent ions and less than 0.002 M for divalent ions.
40
-------
10
1 -r
01
^ 0.1
2
o
CD
0.01 - :
0.001
L/S^O.ZmL/g
1
-*t"
^.
* CFS-M1316
' A CFS-M1314
' -0-CFS-M1313
X
4
\
' L/S =
L/S = 1C
-
L/S9 -
).5mL/g
mL/g
-^
10 m L/g
*ป
ML
MDL
10 12 14
PH
10 12 14
10
2
o o.oi
0.001
0.001
ป CFS-M1316
-A-CFS-M1314
CFA-M1313 (Nat pH)
10
0.1
10
L/S (L/kg)
L/S (L/kg)
Figure 2-19. Comparison of eluate concentration (left) and release (right) for a Response 2
highly soluble species from pH-dependent (Method 1313) and L/S dependent (Method 1314
and Method 1316) leaching tests.
41
-------
100 -
^^
I
"Si 10
ฃ
o 1
'E
2 o.i
0.01
0.001
[
[
\
\
', L/S! = 0.2 mL/g O*-. *
3fe
L/S9 = 10mL
;
h-
'g ^
0 CFS-M1316
A CFS-M1314
--CFS-M1313
L/b -
U.J
-
^L/S = 1C
'
02468
mL/g
^,-^
^-^^
mL/g
^
MDL
10 12 1
1000
PH
100 -
0.01 -
0.001 -
n nnm -
r
* * S
r
ML
i MDL
0 CFS-M1316
-A-CFS-M1314
CFS-M1313 (Nat pH)
U-^J. * 1
01
w
I
n nnm -
M1313Availablity
[
slope=l ^ . -5
--J^J^-TlC
[
-""""'""""''"" ^-ฃfi
0 CFS-M1316
CFS-M1313(NatpH)
0.1
10
0.1
10
L/S (L/kg)
L/S (L/kg)
Figure 2-20. Comparison of eluate concentration (left) and release (right) for a Response 3
aqueous saturation species from pH-dependent (Method 1313) and L/S dependent (Method
1314 and Method 1316) leaching tests.
Further interpretation of percolation test results can be divided into understanding (i) the mass
transfer behavior and (ii) the LSP behavior of constituents in the material during elution. The mass
transfer behavior of a column is most easily determined based on the elution behavior of
constituents that are highly soluble and have little pH-dependent leaching behavior (i.e., Response 2
from above). Thus, sodium, potassium or chloride often is the constituent selected to evaluate the
mass transfer behavior observed based on results of a column test.
2.3.2 Mass Transfer-based Leaching and pH-dependent Leaching
Mass transfer-based leaching tests (e.g., Method 1315) are designed to measure the rate of mass
transfer through the solid material to the bulk solid-liquid interface. Slow surface dissolution
and/or internal resistance to constituent migration to the surface of the monolithic material
reduces the leaching rate, which can be further reduced because of different chemical conditions
within the matrix (i.e., pH, composition) than present at the surface-leaching fluid interface.
Method 1315 is intended to assess the rate at which this occurs. A critical aspect of these tests is
that the driving force for mass transfer (i.e., the concentration gradient between the solid and the
bulk liquid phase) is maintained. Therefore, COPC concentrations in the bulk liquid phase should
not approach equilibrium at the eluate pH value.
42
-------
A first-order evaluation of whether or not the bulk liquid phase of a mass transfer-based leaching
tests is at equilibrium is to compare eluate concentrations to the pH-dependent leaching data for
the same material as a function of pH (Figure 2-21). Mass transfer data visually below the pH-
dependent leaching curve indicates that equilibrium is not achieved during the leaching intervals of
the mass transfer test. For most constituents of environmental concern, the example data shown
for arsenic, cadmium, and boron in Figure 2-21 are typical when the leaching intervals specified in
Method 1315 are followed. This comparison for constituents of the primary mineral phases of the
material (e.g., calcium in the cement-based stabilized waste analog as shown in Figure 2-21) may
appear to indicate that concentrations in the bulk liquid approach equilibrium; however, the results
may reflect dissolution of minerals at the surface rather than mass transport through the material.
12
14
PH
Figure 2-21. Comparison of mass transfer-based leaching data (single points) to pH-dependent
leaching data (continuous series) as a check against equilibrium in the bulk liquid phase of the
mass transfer test. Data is shown for a contaminated smelter site soil (CFS; top) and a solidified
waste analog (SWA; bottom).
43
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2.4 Relationships between LEAF Test Results and Single Batch Extractions
Many of the current leaching tests used to assess leaching from solid materials are single-batch
extraction tests in structure. Thus, each test yields a single result for each COPC so that the result is
limited to the test conditions under which the data point was derived.19 However, under the
assumption that the single batch extraction obtains equilibrium over the extraction interval and if
the pH of the final eluate solution is recorded, the results of single-batch tests may be compared to
LEAF test results by plotting the results as a function of pH. In Figure 2-22, the results of Method
1313 and Method 1316 testing for a contaminated smelter site soil (CFS) and a solidified waste
analog (SWA) are compared to the results of EPA leaching tests that are currently used for leaching
evaluation, TCLP and SPLP. In order to compare these data, the procedure for TCLP (EPA Method
1311) and SPLP (EPA Method 1312) had to be modified to include recording of the final eluate pH.
Ol
Ol
PH
10
10
100
10
1
0.1
0.001
n nnm .
[
[
!
!
\
\
S
?fv
D CFS-SPLP
D CFS-TCLP
CFS-M1316
--CFS-M1313
ซ-*
--
*
ML
MD
12
14
100 -
10 -
1
0.1
0.001 -
n nnm -
|
n s
s
o s
--s
*--ซ
WA-SPLP
WA-TCLF
WA-M13
^
\
16
13
N*
9*
r*^.
/ฐ
-^
ML
MDL
12
14
1 -
* 0.1
^ 0.1 -
2
&
1
^
0
J
0 2 4 6 J
D CFS-SPLP
CFS-TCLP
O CFS-M1316
--CFS-M1313
*ป
ML
MDL
! 10 12 1
PH
1 -
0.1 -
nm -
-
n SWA-SPLP
SWA-TCLP
O SWA-M1316
-S-SWA-M1313
^**
""-*--
ป~A
"^~m
?4
w
ML
MDL
10
12
14
PH
PH
Figure 2-22. Comparison of single-batch extractions (i.e., TCLP and SPLP) to pH- and L/S-
dependent leaching results for a contaminated smelter site soil (CFS; top) and a solidified
waste analog (SWA; bottom).
19 For example, TCLP specifies contacting particle size reduced material with a maximum particle size of 9.5 mm with
either a NaOH buffered or unbuffered acetic acid leaching solution at an L/S of 20 mL/g-dry over an 18 hour period while
SPLP specifies a similar particle size, L/S and duration conditions with a dilute nitric/sulfuric acid solution.
44
-------
When compared to the LEAF test results, single-batch extraction results (e.g., TCLP and SPLP) often
appear as another point along the pH-dependent trendline. For Response 2 species, TCLP and SPLP
concentrations plot slightly below the pH-dependent trendline and are consistent with the
increased L/S of the single batch tests. Species that follow solubility-controlled release (i.e.,
Response 3 species) have TCLP and SPLP data consistent with the pH-dependent trendline.
Although the comparisons between single batch extractions and characteristic leaching tests are
useful in interpreting COPC behavior, the single batch extraction data alone do not provide enough
information to support such observations and therefore limit the ability to provide insight into
leaching behavior for the broad set of disposal or utilization scenarios.
2.5 Determination of Constituent Availability
As discussed in Section 2.1.1, the amount of a constituent that partitions into the aqueous phase can
be limited either by (i) the solubility of the constituent at the test conditions (resulting in a
saturated solution at solid-liquid equilibrium), (ii) adsorption-desorption equilibrium partitioning
between the aqueous solution and solid phases (i.e., sorption onto particulate organic matter or
hydrous ferric oxide (HFO) surfaces), or (iii) the maximum leachable amount of the constituent.
The maximum leachable amount may be either the total content, or often only a limited fraction of
the total content because of constituent sequestration in relatively non-leachable phases such as
durable glass phases or very poorly soluble alumina-silicate phases. Here, the maximum leachable
quantity is referred to as the constituent availability. To measure or estimate constituent
availability, test conditions must be established such that the aqueous phase solubility and
adsorption processes do not limit leaching. Conditions to estimate availability can be established in
test conditions either through (i) very large liquid-to-solid ratio, (ii) multiple extractions, (iii) use of
chelating agents (e.g., EDTA) to increase aqueous solubility, or (iv) use of fundamental pH-solubility
properties to select conditions of high solubility. Each of these approaches have been used with
comparable results (NEN 7371, 2004; Garrabrants and Kosson, 2000; van der Sloot et al., 1997;
Lopez Meza et al, 2008). From a practical perspective, it has been useful to integrate determination
of constituent availability with pH dependence leaching (i.e., Method 1313). Constituent availability
can be estimated from Method 1313 by selecting the maximum mass leached of each constituent
over the pH domain from pH of 2 to 13. Most cationic elements will reach a plateau in leaching as
pH decreases between pH 4 and 2. AtpH 2, HFO phases are dissolved, resulting in leaching of
adsorbed constituents. Most metal hydroxides (amphoteric constituents) will have a maximum
solubility either at pH of 2 or approximately 13. Oxyanionic species (e.g., arsenate, molybdate,
chromate) will have maximum solubility at mildly alkline pH (i.e., pH 9 - 10). Thus, the pH value at
which availability is estimated will be constituent dependent.
45
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3 CHEMICAL SPECIATION AND MASS TRANSPORT MODELING AS
INTERPRETATION TOOLS
Often, leaching tests are used to characterize samples of materials that are either to be placed into a
field scenario or material samples that are obtained from a field test location. However,
understanding of field leaching behavior frequently requires consideration of the changes in
material leaching over time due to aging of the material and/or due to release conditions that are
representative of the field scenario, but are not readily reproduced in the laboratory. Material aging
phenomena may include reaction with species from the surrounding environment (e.g., oxygen,
carbon dioxide, sulfate), depletion of primary species through leaching (e.g., loss of calcium
hydroxide from cementitious materials), and changes in the physical nature of the material (e.g.,
cracking). Scenario conditions that cannot be easily reproduced in the laboratory but may affect
leaching include low L/S ratios, changes in chemical oxidation-reduction state (e.g., from either
biotic or abiotic processes), and the presence/extent of preferential flow pathways.
One approach toward integrating aging phenomena and scenario conditions into the understanding
of material leaching behavior is through the use of numeric models designed to simulate chemical
speciation or reactive transport of COPCs for defined release conditions. Chemical speciation
models simultaneously solve the chemical thermodynamic and kinetic equations representing the
material mineralogy/adsorption/aqueous interaction reactions that allow for evaluation of
equilibrium liquid-solid partitioning as a function of material and fluid phase composition, pH and
redox state. The effects of physical parameters (e.g., monolithic nature of materials that divert
infiltration or preferential flow during percolation) may be evaluated through coupling of the
results of chemical speciation models with mass transport models, often called reactive transport
models. Thus, chemical speciation and reactive transport models can be useful tools to
prospectively or retrospectively evaluate (i) conditions not practically achievable in the laboratory
on material leaching behavior, (ii) the aging of materials under factors that historically control
leaching in the field, and (iii) integration between laboratory and field leaching data.
Using these tools, useful simulations of LSP and mass transport leaching are achievable for a wide
range of materials to evaluate the impacts of varying laboratory and field conditions using idealized
conceptual models. Interpretation of leaching data using chemical speciation and reactive transport
models has been advanced by the development of extended thermodynamic databases and the
evolution of descriptions of chemical interactions with reactive surfaces. However, like all numeric
models, the results of these models are limited by the state of current knowledge or the availability
of accurate data for the materials being tested (e.g., see Sarkar et al, 2012). For leaching assessment
purposes, areas where limits in current knowledge or available data may increase uncertainty in
chemical speciation and reactive transport model results include:
chemical speciation of solid phases in materials and wastes;
aqueous solution characteristics (e.g., dissolved or colloidal organic matter);
thermodynamic data for solid mineral phases;
adsorption onto solid surfaces;
solution conditions (e.g., very high ionic strength solutions);
46
-------
physical mass transport conditions.
3.1 Modeling and Simulation Approach
Laboratory leaching test results from pH dependent leaching (i.e., Method 1313 or PrEN 14429) is
used in conjunction with other information known about a material (e.g., availability data, total
carbon, etc.) to develop a "chemical speciation fingerprint" (CSF). This CSF includes the set of
mineral phases, adsorbing surfaces, organic matter fractionation and the fraction of the total
content of each constituent that is available for leaching (often referred to as "availability"). The
resulting CSF may be used in conjunction with the results of L/S-dependence tests (e.g., Method
1316, EN 12457) to assess the impact of low L/S ratios onLSP or with percolation column tests
(e.g., Method 1314, CEN/TS 14405, CEN/TS 16337-3) or mass transport (e.g., Method 1315, PrEN
15863, CEN/TS 16337-2) to calibrate needed mass transport parameters for simulations of
dynamic leaching tests (i.e., mobile-immobile fractions for percolation column tests or tortuosity for
monolith diffusion tests). The resulting combination of the CSF and mass transport parameters may
be used in conjunction with one or more field conceptual models (i.e., percolation with preferential
flow or diffusion controlled release from a monolith) and a variety of initial and boundary
conditions (e.g., system geometry, infiltration rate and chemistry, redox state, etc.) to estimate
release under a range of field scenarios. Characterization of uncertainty at each step is needed to
understand the accuracy and limitations of each simulation.
3.2 Chemical Speciation and Reactive Transport Modeling in LeachXS
Recent developments in chemical speciation codes such as ORCHESTRA (Meeussen, 2003),
MINTEQA2 (Allison etal., 1991), PHREEQC (Parkhurst, 1995), Geochemist's Workbench (Lee and
Goldhaber, 2011) allow calculation of multi-element equilibrium concentrations based on available
thermodynamic data and may include coupling with mass transport models.
The software package LeachXS, used for data management and chemical speciation based
simulations in this report, has the ORCHESTRA code embedded as the chemical speciation and
reactive transport code for modeling experimental results and the chemical behavior of materials in
specific application scenarios. ORCHESTRA can calculate chemical speciation in thermodynamic
equilibrium systems using the same thermodynamic database format as PHREEQC or MINTEQA2,
but also contains state-of-the-art adsorption models for oxide and organic surfaces as well as the
ability to handle dissolution/precipitation of solid solutions.
Underlying chemical speciation models incorporate current knowledge about the chemical
interactions between major, minor trace elements, such as mineral dissolution/precipitation, ion
exchange, sorption and incorporation in solid solutions that result in the concentrations of elements
in solution at liquid-solid equilibrium as a function of pH or L/S based on initial solid and liquid
phase composition and redox state. A set of solid phases (i.e., minerals, solid solutions, adsorptive
surfaces) and reactions (i.e., dissolution/precipitation, adsorption/desorption, reaction with carbon
dioxide) in the form of reaction equations with corresponding thermodynamic equilibrium
constants are solved simultaneously to calculate liquid-solid partitioning of major, minor and trace
constituents including COPCs. Several books are available that describe the fundamentals of
47
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chemical speciation and reactive mass transport modeling (Stumm and Morgan 1996; Appelo and
Postma2005).
In ORCHESTRA, ion adsorption onto organic matter is calculated with the NICA-Donnan model
(Kinniburgh etal., 1999) using generic adsorption reactions (Milne etal., 2003). Adsorption of ions
onto iron and aluminum oxides was modeled according to the generalized two layer model of
Dzombak and Morel (1990). Aqueous speciation reactions and selected minerals were taken from
the MINTEQA2 database (Allison et al., 1991). The MINTEQA2 database is internally consistent
through use of a common set of primary entities and thermodynamic reference state; additional
mineral reactions taken from literature were transformed into the same format by rewriting the
reactions using primary entities in LeachXS-ORCHESTRA. For example, more recent
thermodynamic data on solid phases relevant to cement, concrete and cement-stabilized waste
forms has been obtained from Lothenbach, et al. (2008) and incorporated into the LeachXS-
ORCHESTRA models used here. More detail on the use of the chemical speciation code can be found
elsewhere (Dijkstra et al., 2006a, 2006b, 2008; Engelsenetal., 2009, 2010, 2012; Carter etal., 2008,
2009; van der Slootetal., 2000, 2007, 2009, 2011; van der Sloot and van Zomeren, 2012; Sarkar et
al., 2010; Sarkar etal., 2011; Sarkar etal., 2012).
3.2.1 Parameterization of ORCHESTRA
The input to the ORCHESTRA model to form a material-specific CSF consists of (i) element
availability values, (ii) selected possible solubility-controlling minerals, (iii) definition of the
reduction-oxidation state of the material, (iv) description of active Fe - and Al-oxide sites, and (v) a
fractionation of organic matter between particular organic matter (POM) and reactive DOC
concentration as a function of pH.
Availability
The maximum leached amount (mg of COPC/kg material) derived from pH-dependent leaching
test concentrations between pH 2 and 13 is used as the concentration available for interaction
under environmental conditions.
Possible Solubility-controlling Minerals
The chemical speciation model is used to generate saturation indices (Sis) for relevant mineral
phases based on the eluate concentrations from pH-dependent leaching tests. From these Sis
and prior knowledge of the material (e.g., previously identified mineral phases from speciation
modeling or from published literature), solubility-controlling minerals are selected for possible
inclusion in the definition of a CSF.
Reduction-oxidation State
The reduction-oxidation (redox) state of the material is specified as the sum of the electron
activity (pE), which indicates the tendency for a solution to donate or accept a proton and pH.
The numerical range for the sum pH+pE is based on the stability of water with values at
between 0-20.75 for maximum reducing and oxidizing conditions (Stumm and Morgan, 1996).
In pe vs. pH stability charts, this sum defines the upper and lower stability limits. For example,
a pH+pE value of 10 represents slightly reducing conditions while a value of 15-16 represents
48
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oxidizing conditions. The values for pH+pE selected for simulation may be either (i) based on
measured laboratory or field values (with appropriate care taken to avoid sample changes
during measurement and correction for the reference electrode used; see Section 2.2.3), (ii)
based on observation of liquid-solid partitioning of iron, manganese and/or chromium as
indicator species from field data and laboratory testing, or (iii) treated as a variable that is
varied over a plausible range as part of a sensitivity study.
Reactive Surfaces Description
The surface area of reactive surfaces present in the solid is required in order to account for
sorption of COPCs onto the solid surface. Reactive surface fractions are estimated from
independent determinations of the test material or through selective chemical extractions on
comparable materials. For example, the amount of amorphous and crystalline iron (hydr)oxide
may be determined by a dithionite extraction (Kostka and Luther III, 1994), while amorphous
aluminum (hydr)oxide may be determined by an oxalate extraction (Blakemore et al., 1987). In
the CSF model, the extracted amounts of Fe and Al were summed and used as a surrogate for
hydrous ferric oxides (HFO) as described by Meima and Comans (1998). Determination of HFO
by ascorbic acid extraction has been standardized as ISO 12782-1 (2012).
Organic Matter and Inorganic Carbon Descriptions
POM and carbonate/bicarbonate content are either measured directly through total carbon
analysis or estimated from the titration curve results of pH-dependent leaching tests. The total
organic carbon in a solid can be divided into a solid fraction (POM) and a fraction that dissolves
as a function of pH (DOC). DOC is available for interaction with COPCs in the eluate; however,
the direct analysis of eluate DOC does not completely representthe reactive part of the
dissolved organic matter. Based on experience with soil materials where the quantification
between the hydrophilic fulvic, and humic acid fraction in DOC was estimated (van Zomeren and
Comans, 2007), the reactive fraction of DOC is defined either as a constant value independent of
pH or as a function of pH (i.e., with the lowest proportion of reactive forms at neutral pH and
increasing towards both low and high pH). In the latter situation, a polynomial fit is created
through eight data points to allow quantification of the reactive DOC at intermediate pH values
in modeling (van Zomeren and Comans, 2007). Thus, the reactive component of the DOC used
in chemical speciation modeling is parameterized as the solid humic acid (SHA) which
represents the sum of the fulvic and humic fractions. In accordance with van Zomeren and
Comans (2007), SHA is either (i) quantified by fractionation POM or (ii) assumed to be 20% of
the total DOC, in case no data for the particular material were available.
Using the information specified above in conjunction with available prior knowledge of the material
(such as previously identified mineral phases from speciation modeling or from published
literature), the speciation of all elements is calculated in one problem definition in the Laboratory
Simulation pH-Dependence Leaching Test model with the same parameter settings. This method of
calculation limits the degrees of freedom in selecting parameter settings considerably, as
improvement of the model description for one element may deteriorate the outcome for other
elements.
49
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3.3 Simulations in LeachXS
3.3.1 Laboratory Test Simulations
Laboratory testing results are used to calibrate and verify models (i.e., "laboratory simulations")
that then can be used for estimating system responses under anticipated field conditions. The
specific types of simulation models currently included in LeachXS are as follows:
Chemical Speciation and Solubility Indices
Solubility index for possible minerals are evaluated in comparison to LSP data obtained from
pH-dependent tests or L/S-dependent test for initial identification of relevant mineral phases
based on LSP data.
pH-dependence Test and LSP Simulation
Based on identified mineral phases and other parameters (e.g., availability values, carbon
fractionation, etc.), a CSF is developed to simulate results obtained from pH dependence tests.
The parameters of this model can be varied to assess changes to LSP due to L/S (e.g., low L/S
ratios found in field conditions), solution chemistry (e.g., high ionic strength solutions in
cementitious materials), redox conditions (e.g., oxidation of reductive materials), the amount of
iron hydr(oxide) and clay surfaces available for sorption, and the amount/fractionation of
particulate organic matter (POM) and DOC.
Monolith Leaching and Mass Transport Rate Test Simulation
The CSF may be combined with diffusion models to determine mass transport parameters (e.g.,
effective tortuosity values, diffusivity) based on results from mass transport tests. The mass
transport model segments a monolithic solid (i.e., a true monolithic form or a compacted
granular material compacted to act like a monolith) into a series of layers from the external
boundary to the interior core (Figure 3-1). Within each layer, the monolith segment is divided
into aqueous and solid phases defined by the CSF. Local equilibrium between phases in the
segment is calculated at each time step to account for changes in pH and local composition
based on dissolved constituent mass transport between the layers by diffusion through the
liquid phase. The external surface of the monolith is simulated as being in contact with a well-
mixed bath of finite volume which is refreshed at time intervals defined by the leaching test
conditions (e.g., Method 1315). This laboratory simulation model also can be used to evaluate
the impacts to release rates from changes in eluate volume, eluate chemistry (e.g., influx of acid
or sulfate attack), and layering of material composition and properties within a monolith (e.g., a
carbonated surface layer with an un-carbonated core).
50
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Monolith
Bath
local equilibrium
based on CSF model
Leachant refresh
at scheduled times
Figure 3-1. Mass transport model (laboratory simulation) scenario.
Percolation Test Simulation (mobile-immobile zones)
The CSF and percolation parameters may be used to evaluate the results of percolation column
tests using the conceptual model of mobile and immobile zones. The conceptual model (Figure
3-2) consists of two zones segmented along the flow path, with one zone containing a mobile
fluid phase in local equilibrium with the solid phase and the second zone containing an
immobile fluid phase in local equilibrium with the solid phase. Within each column segment,
each of the mobile and immobile zones are well mixed (i.e., uniform distribution of constituents
within each of the solid phase and liquid phase orthogonal to the flow direction), and the mobile
and immobile zones exchange dissolved constituents based on a mass transfer coefficient that
can be considered an effective diffusion distance (van Genuchten and Dalton, 1986). This model
is insensitive to percolation flow rate because homogeneity within the immobile zone is
assumed. This model can be used for a first-order approximation of the effects of preferential
flow in a percolation system, as well as the impacts of changes in redox and influent solution
chemistry on the leaching of constituents.
51
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Inflow
Outflow
Micropores
Mobile
Fluid
Immobile
Fluid and Solid
(well-mixed within
each segment)
Outflow
Inflow
Figure 3-2. Conceptual model of percolation with mobile and immobile zones shown for soil
aggregates (left; van Genuchten and Dalton, 1986) and as a 1-dimension approximation in
ORCHESTRA (right).
Percolation Test Simulation (percolation-radial diffusion)
The CSF and percolation parameters also may be used for evaluation of percolation column test
results using the conceptual model of percolation with radial diffusion from porous solid
particles. The conceptual model (Figure 3-3) consists of two zones segmented along the flow
path, with one zone containing a mobile fluid phase in local equilibrium with the solid phase
and the second zone containing porous spheres with an immobile fluid phase (in contrast to the
previous model using an immobile zone which was well mixed). Mass transport within the
spheres occurs by diffusion through the fluid phase with the boundary condition of equal fluid
composition at the interface between the sphere surface and the mobile zone, and no diffusion
at the center of the spheres (van Beinum et al., 1999; Sarkar et al., 2013). Thus, fluid phase
constituents can diffuse into and out of the spheres based on concentration gradients, and
within the spheres local solid-liquid equilibrium is maintained at each radial layer within the
sphere. Within each column segment, each of the phases in the mobile zone are well mixed (i.e.,
uniform distribution of constituents within each of the solid phase and liquid phase orthogonal
to the flow direction) and in local equilibrium between the solid and liquid phases. This
approach is more accurately reflective of systems where the diffusion gradients within the
immobile zone control release to the mobile zone. Thus, this model is sensitive to overall
percolation flow rate and can be used to reflect the impact of fast infiltration that does not reach
complete equilibrium between mobile and immobile zones. This model can also be used to
evaluate leaching under the effects of preferential flow, cracking in monoliths, varying flow
conditions (e.g., intermittent flow, different flow rates), and solution chemistry.
52
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Outflow
Inflow
Contact
volume
(liquid)
Length
Immobile
Fluid and Solid
Inflow
Outflow
Figure 3-3. Conceptual model of percolation with radial diffusion in the immobile zone (Sarkar et
al., 2013) shown as an up-flow column (left) and as flow through cracks in concrete (right).
3.3.2 LeachXS Field Test Simulations
In the different cases of laboratory to field evaluation data obtained from the field after a certain
time of exposure to leaching under field conditions can be modeled just as was done for the
laboratory test data. Results from laboratory testing and simulations described above can be used
to parameterize the simulations for field scenarios and thus form a predictive estimate of field
leaching under a range of conditions (i.e., "prediction scenarios"). Simulations of field scenarios
illustrate the extent to which differences in field conditions compared to laboratory testing (i.e.,
contact water amounts and composition, and preferential flow) and changes in field conditions as a
result of aging impact observed field leaching behavior. An illustration of this approach follows a
description of prediction scenarios. For the illustration, the field data obtained in the pilot study on
stabilized municipal solid waste incinerator (MSWI) scrubber residues (see Section 4.9) have been
modelled using the same CSF as derived from the lab data. The main difference in this case is the
higher carbonate level in the field exposed samples.
3.3.3 LeachXS Prediction Scenario Models
Monolithic Diffusion Prediction Scenarios
Leaching - one dimensional diffusion from a monolith where system size, material layers,
time frames, water contact and composition at the boundary can be varied to represent field
scenarios. Unsaturated cases also can be simulated but without consideration of gas phase
transport and reaction processes (e.g., oxygen or carbon dioxide gas phase transport and
reaction).
Leaching with Carbonation and Oxidation - analogous to the Leaching model above, but also
allows for consideration of gas phase transport and reaction processes to consider impacts
of carbonation and oxidation (Brown etal., 2013).
53
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Sulfate Attack with Leaching - this simulation allows coupling of physical degradation
through sulfate attack on cementitious materials with leaching (Sarkar etal, 2010, 2012).
Percolation Prediction Scenarios
Mobile-Immobile Zones Dual Regime Leaching - this simulation is analogous to the
percolation column test (mobile-immobile zones) model but with adaptation appropriate
for evaluating field scenarios (van Genuchten and Dalton, 1986).
Percolation with Radial Diffusion Leaching - this simulation is analogous to the percolation
column test (percolation with radial diffusion) model but with adaptation appropriate for
evaluating field scenarios (Brown etal., 2013; Sarkar etal., 2013).
3.4 Example of Model Development for a Stabilized Waste Material
The chemical speciation and reactive transport models described earlier are illustrated through
application to cement-stabilized MSWI bottom and fly ash as described in Section 4.9. The data
used in laboratory simulation and field simulation modeling is shown in Table 3-1 through Table 3-
3 and includes (i) the model parameters from the pH-dependence, percolation and monolith models
(Table 3-1), (ii) the availability data used to parameterize the CSF (Table 3-2), and (iii) the CSF
mineral phases derived from saturation indices in conjunction with pH-dependent leaching test
data (Table 3-3). Extensive literature on cement-stabilized materials and cements is available (van
der Sloot et al., 2007; van der Sloot et al., 2011) and provides initial indications of the solid mineral
phases that are applicable to the major components of the stabilized waste. However, most often
very limited, if any information, is available with respect to identification based on direct
measurements of the mineral phases controlling release of the trace constituents because they are
present below the detection limits of available analytical instruments. As a result, the controlling
mineral phases for COPCs must be inferred from the LSP as a function of pH and L/S.
54
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Table 3-1. Model Parameters for CSF Definition for Stabilized MSWI waste
Parameter
L/S
Fraction DOC
pH+pE
Clay [kg/kg]
HFO [kg/kg]
SHA (kgsHA/kgxoc)
Porosity
Density (kg/L)
Initial pH of Solid
Initial pH of Leachant
Column Length (cm)
Relative Stagnant Volume (%)
Effective Diffusion Distance (cm)
Tortuosity
Specimen Length (cm)
Specimen Width (cm)
Specimen Height (cm)
pH-dependent
Model
10
0.2
15
0
IxlO-4
2xlO-4
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Percolation
Model
varies
0.2
15
0
1x1 0-4
2xlO-4
0.3
1.9
12.1
7
25
20
2
NA
NA
NA
NA
Monolith
Model
NA
0.2
15
0
IxlO-4
2xlO'4
0.4
2.4
12.4
7
NA
NA
NA
1.5
10.9
9.57
9.57
Note: NA=data not applicable for the type of model.
Table 3-2 Chemical Availability Values for CSF Definition of Stabilized MSWI Waste
Species
Name
Al+3
H3As04
HsBOs
Ba+2
Br
Ca+2
Cd+2
ci-
Cr04-2
Availability Species
(mg/kg) Name
4,456
0.15
59
19
830
84,000
180
54,000
9.7
tCu+2 360
F- 1,900
Fe+3
H2COs
K+
74
10,000
34,000
Li+ 25
Mg+2
Mn+2
Mo04-2
Na+
Ni+2
P04-3
Pb+2
S04-2
Sb(OH)6-
Se04-2
H2Si04
Sr+2
V02+
Zn+2
Availability
(mg/kg)
3,900
170
7.7
26,000
9.3
4.7
960
11,000
4.9
0.46
3600
210
0.58
8000
55
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Table 3-3. Mineral Phases in CSF Definition for Stabilized MSWI Waste
Chemical Formula*
Common Name Chemical Formula*
Common Name
2CaO-AI2O3-8H2O [s]
2CaO-AI2O3-SiO2-8H2O [s]
2CaO-Fe2O3-8H2O [s]
2CaO-Fe2O3-SiO2-8H2O [s]
3CaO-AI2O3[Ca(OH)2]0.5-(CaCO3)0
.5-11.5H2O [s]
3CaO-AI2O3-6H2O [s]
3CaO-AI2O3-CaCO3-llH2O [s]
3CaO-AI2O3-CaSO4-12H2O [s]
3CaO-Fe2O3[Ca(OH)2]0.5(CaCO3)0
t3CaO-Fe2O3-6H2O [s]
3CaO-Fe2O3-CaCO3-llH2O [s]
3CaO-Fe2O3-CaSO4-12H2O [s]
5-11.5H2O [s]
4CaO-AI2O3-13H2O [s]
4CaO-Fe2O3-13H2O [s]
AI(OH)3 [amorphous]
CaSO4
Mg(OH)2
CaCO3
Gibbsite
Anhydrite
Brucite
Calcite
CaO-AI2O3-10H2O [s]
Mg6AI2(C03)(OH)16.4H20
Fe(OH)3 [microcrystalline]
AI(OH)3
CaSO4ป2H2O
1.67CaO-SiO2-2.1H2O
MgC03
Ca(OH)2
SiO2 [am]
K2Ca(SO4)2ปH20
Hydrotalcite
Ferric hydroxide
Gibbsite
Gypsum
Jennite
Magnesite
Portlandite
Silica gel
Syngenite
2CaO-2.4SiO4-3.2H2O
0.83CaO-SiO2-1.3H2O
Tobermorite-l
Tobermorite-ll
Tricarboaluminate
Ca3(P04)2
alpha-TCP
Ba[S,Cr]O4[77%SO4]
Ba,SrSO4 [50% Ba]
Ca3(AsO4)2ป6H2O
CaMoO4 [c]
Cd(OH)2 [C]
Cr(OH)3 [A]
Cu(OH)2 [s]
FeVO4
Fe2O3ป0.5H2O
CaF2
MgCO3
MnO(OH)
Iron Vanadate
Ferrihydrite
Fluorite
Magnesite
Manganite
Ni(OH)2[s]
Ni2SiO4
Pb(OH)2 [C]
Pb2V2O7
Pb3(V04)2
PbCrO4
PbMoO4 [c]
MnCO3
SrCO3
CuO
Zn2SiO4
ZnO
Rhodochrosite
Strontianite
Tenorite
Willemite
Zincite
Note: * - chemical formulae presented in cement-based notation or standard chemical format
For this illustration, the CSF that was developed from the pH-dependent model applied to pH-
dependent test data subsequently was used in the percolation model (mobile-immobile zones) and
the monolith model to simulate leaching under the conditions of respective percolation column and
monolith diffusion tests. Results of the model simulations are provided in Figure 3-4 and Figure
3-5. The initial step toward assessing the simulation accuracy is the ability of the CSF to simulate
the system response with respect to eluate pH, a master variable controlling leaching (see Section
2), for the pH dependent test, percolation column test and mass transport tests. In these figures, the
pH titration curve is simulated to a high degree using the derived CSF and the eluate pH values for
both percolation column and monolith leaching are well represented. For simulation of pH in the
column test, peak pH response from the percolation model occurs at a lower L/S value than is
indicated from the experimental data, most likely because of a greater amount of axial dispersion in
the laboratory column which is not fully accounted for in the model. For the selected COPCs shown
56
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in Figure 3-4 and Figure 3-5, the simulations provide a good representation of the experimental
data for all three models, especially considering the uncertainties associated with both
experimental data and simulations.
The effect of L/S on the pH-dependent model is shown in Figure 3-6. The results of the initial pH-
dependent leaching test simulation at L/S of 10 mL/g-dry (solid, red line) are compared with
results of the same CSF and model used to simulate LSP at 0.5 mL/g-dry (blue, dashed line). Also on
the same graph, the simulation results are compared with experimental data from the pH-
dependence test and percolation column test. Simulation results for Ca with an L/S of 10 mL/g-dry
support the pH-dependent leaching data and indicate pH domains where Ca leaching is controlled
by solubility (i.e., pH > 12) and by availability (i.e., pH < 12) as explained in Section 2. When the L/S
decreases to 0.5 mL/g-dry, a similar pattern with a higher availability but the same solubility
control is indicated. In Figure 3-6, this can be observed as the same Ca response for both
simulations atpH greater than 12 while the simulation asymptotically approach different
concentration values atpH less than 11. The difference in the concentration-based asymptote
values is related to the L/S conditions under which the models were conducted (i.e., a similar mass
released into less liquid at L/S 0.5 would result in a higher concentration). In contrast, potassium
shows the behavior of a highly soluble species that exhibits LSP independent of pH and, therefore, a
constant concentration as a function of pH. The pH-dependent model conducted at L/S 10 mL/g-
dry is in good agreement with the pH-dependent test data and the simulation at the lower L/S of 0.5
mL/g-dry is in good agreement with the initial fraction observed from the percolation column test
(i.e., the fraction collected at a cumulative L/S of 0.5 mL/g-dry). For selenium and molybdenum, the
simulation and experimental results illustrate the more complex behaviors that can result as a
function of pH and L/S.
For the four COPCs, experimental results for all eluates from the column test, ranging from L/S of
0.5 to 10 mL/g, are presented with the simulation results. When the eluate concentrations fall on
the pH dependence curve for a range of L/S values this indicates that aqueous saturation of the
constituent is controlling leaching within the column, as is the case for Ca. When initial percolation
column test eluate concentrations correspond with the simulated values for the low L/S value (i.e.,
0.5 mL/g) followed by continuous decrease in eluate concentration as is indicated for K and Se, this
behavior is indicative of constituent release that is controlled by availability and depletion of the
available fraction of the constituent as the percolation column test progresses.
57
-------
Calcium (mol/L)
o
ง 1 P o
0 0 0 P
o
Potassium (m
1 P
1 I-1
Selenium (mol/L)
o o o o o
0
-i
pH-dependence Test
pH-dependence Mode
)
0
2
4 6
i
f
^
.
\
\
\
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A Percolation Test
Percolation Model
. . .
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.2 1,000 -
5
' r-' ""'
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Mass Tra nsport Test
Monolith Mode
. -
8 10 12 14 0.01 0.1 1 10 0.1 1 10 1C
pH L/S (L/kg) Time (days)
pH-dependence Test
pH-dependence Model
246
PH
2
o
ฅ o.i -
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8
-x
i
V
A Percolation Test
Percolation Mode
A
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ra
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Mass Transport Test
Monolith Model
8 10 12 14 0.01 0.1 1 10 0.1 1 10 1C
L/S (L/kg) Time (days)
pH-dependence Test
pH-dependence Model
w "
4 6
PI
V_?
S~
j" l.E-05
'E' l.E-06
1
V
'x
\
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A A
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nium Release (mg/m2)
i-* i
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, Mass Tra nsport Test
V
W ---- Monolith Mode
l.E-08 H 1 1 1 "-J- ' '
8 10 12 14 Oi01 Oil ! 10 0.1 1 10 1C
H L/S (L/kg) Time (days)
Figure 3-4. Comparison of laboratory simulation results for a stabilized MSWI residue (van der Sloot et al, 2007). Multi-element, multi-phase
chemical speciation modeling is shown for pH-dependent leaching data (left), percolation test data (middle) and mass transport test data
(right).
58
-------
2 l.E-0
E l.E-0
3
C
a
a
S- l.E-0
0
l.E-0
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10 1C
ys)
,ปi *'
i
i
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i
i
i
i
0.1 1 10 0.1 1 10 1C
L/S (L/kg) Time (days)
Figure 3-5. Comparison of laboratory simulation results for a stabilized MSWI residue (van der Sloot et al, 2007). Multi-element, multi-phase
chemical speciation modeling is shown for pH-dependent leaching data (left), percolation test data (middle) and mass transport test data
(right).
59
-------
10 -F-
1^1
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i "-1-
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E
_0
U
0
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,
pH-dependence Test
Model at L/S=10
Model at L/S=0.5
246
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pendence Test
pendenceTest
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at L/S=0.5
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8 10 12 1
PH
Figure 3-6. Laboratory leaching test simulation shown pH-dependent leaching (model at L/S=10 L/kg)
and percolation leaching (model at L/S=0.5 L/kg) for select species in a solidified MSWI residue (van
der Sloot et al, 2007).
60
-------
N
1 E-04 -
l.E-05
l.E-06 -
l.E-07 -
l.E-08 -1
C
!
L
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pH Data (fresh)
^-^ Model at L/S=10 (fres
A L/S Data (fresh)
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Zn Fractionation in Solution
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123
1234567
10 11 12 13 14
PH
Figure 3-7. Chemical speciation and phase descriptions as a function of pH for a stabilized MSWI
residue conducted on fresh material and aged (4 year) cores. Comparisons include pH-dependent
model simulations (upper left), phase description for fresh material (upper right), phase descript for
aged material (lower left) and liquid phase fraction for fresh material (lower right).
3.5 A Comparison of Copper and Lead Speciation in Several Materials
Figure 3-8 through Figure 3-11 present chemical speciation modeling compared to experimental
results of pH dependent leaching for copper and lead from cement mortar, coal fly ash, stabilized
waste, municipal solid waste, predominantly inorganic waste, and municipal solid waste incinerator
bottom ash. For all cases, the left graph compares the experimental results from pH dependent
leaching at L/S=10 mL/g (red dots) and percolation column results, with L/S ranging from 0.2 to 10
mL/g (blue dots), to the modeled aqueous phase concentration at L/S=10 and 0.3 mL/g (red line
and blue dashed lines, respectively). The right graph for each case presents the distribution of the
constituent concentration in the liquid phase between the amount complexed with dissolved
organic matter (DOC-bound, bright green) and other dissolved species (i.e., the sum of free and
other complexed species, "Free" indicated in light blue-green), while the remaining colored areas
indicate speciation in the solid phase. For the graphs on the right side, the units (y-axis) are moles
per liter of the total unit volume (i.e., total volume of solid and liquid phases). The sum of the DOC-
bound and the "Free" species is equal to the total dissolved concentration (for either Cu or Pb) as
61
-------
CEM I Cement Mortar
CEM I Partioning of Cu
l.E
l.E
^ l.E
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ฃ l.E
f LE
v
S 1.E
5 1.E
l.E
l.E
:-oi
02
03
04
05
06
07
08
-09
\
pH-dependence
[Cu+2] L/S=10
Percolation Column
[Cu+2] L/S=0.3
I ' I
I ' I ' I ' I
I ' I
7 8
pH
9 10 11 12 13 14
Coal Fly Ash
l.E-02 -
1 E 03
l.E-06 -
l.E-07 -
1 F no .
!
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[Cu+2] L/S=10
Percolation Column
[Cu+21 L/S=0.3
J^~
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PH
Stabilized Waste
l.E-02 -
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l.E-05 -
l.E-08 -
1 F-flQ -
1
i
' pH-dependence
[Cu+2] L/S=10
r Percolation Column
fCu+21 L/S=0.3
\
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X
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^
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9 10 11 12 13 14
10 11 12 13 14
Coal Fly Ash Partitioning of Cu
10 11 12 13 14
Stabilized Waste Partitioning of Cu
pH
10 11 12 13 14
Figure 3-8. Geochemical model description of copper at L/S=10 with prediction to L/S=0.3 (left) and
partitioning (L/S=10) based on multi-element geochemical speciation modelling (right). Data shown
for cement mortar (top), coal fly ash (middle), and stabilized waste (bottom).
62
-------
Municipal Solid Waste
MSW Partitioning of Cu
l.E
l.E
l.E
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5 1.E
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^^
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10 11 12 13 14
pH
Predominantly Inorganic Waste
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MSWI Bottom Ash
10 11 12 13 14
l.E-01
l.E-09
Pred. Inorganic Waste Partitioning of Cu
l.E-01
o
n.
3
10 11 12 13 14
MSWI Bottom Ash Partitioning of Cu
10 11 12 13 14
Figure 3-9. Geochemical model description of copper at L/S=10 with prediction to L/S=0.3 (left) and
partitioning (L/S=10) based on multi-element geochemical speciation modelling (right). Data shown
for municipal solid waste (top), predominantly inorganic waste (middle), and MSWI bottom ash
(bottom).
63
-------
CEM I Cement Mortar
o
l.E-02 -
l.E-03 -
l.E-04 -
l.E-05 -
l.E-06 -
l.E-07 -
l.E-08 -
l.E-09 -
l.E-10 -
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9 10 11 12 13 14
pH
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10 11 12 13 14
Stabilized Waste
l.E-02 -
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l.E-05 -
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l.E-06 -:
l.E-07 -
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l.E-10 -
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l.E-01
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
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l.E-09
l.E-10
l.E-11
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E-02
E-03
E-04
E-05
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E-07
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E-09
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E-ll
pH
Coal Fly Ash Partitioning of Pb
D Free n DOC-bound
ROM-bound BFeOxide
DClay DPb(OH)2[c]
DPb2V207 DPbMoQ4[c]
9 10 11 12 13 14
pH
Stabilized Waste Partitioning of Pb
9 10 11 12 13 14
pH
pH
Figure 3-10. Geochemical model description of lead at L/S=10 with prediction to L/S=0.3 (left) and
partitioning (L/S=10) based on multi-element geochemical speciation modelling (right). Data shown
for cement mortar (top), coal fly ash (middle), and stabilized waste (bottom).
64
-------
Municipal Solid Waste
l.E-02 -
l.E-03 -
^ l.E-04 -
2, l.E-05 -
1 l.E-06 -
l.E-07 -
l.E-08 -
1 F-na -
i
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sv
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[Pb+2] L/S=10
Percoation Column
rPb+21 L/S-0.3
^
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,ซ
~r*
*~
i
/
/
/-
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1234567
9 10 11 12 13 14
pH
Predominantly Inorganic Waste
pH-dependence
[Pb+2] L/S=10
Percolation Column
[Pb+2] L/S=0.3
10 11 12 13 14
MSWI Bottom Ash
l.E-01
l.E-02
l.E-03
l.E-04
5 l.E-06
l.E-07
l.E-08
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1
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9 10 11 12 13 14
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2
MSW Partitioning of Pb
l.E-01
l.E-02 -
,-, l.E-04 -'
10 11 12 13 14
Pred. Inorganic Waste Partitioning of Pb
l.E-01
,E-02
,E-03
,E-04 -
,E-05
,E-06
,E-07
,E-08
,E-09
,E-10
a Free a DOC-bound
POM-bound FeOxide
OHinsdalite-2 OPb(OH)2[c]
gPbMoOt [c]
I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I
9 10 11 12 13 14
pH
MSWI Bottom Ash Partitioning of Pb
l.OE-01
pH
123
10 11 12 13 14
Figure 3-11. Geochemical model description of lead at L/S=10 with prediction to L/S=0.3 (left) and
partitioning (L/S=10) based on multi-element geochemical speciation modelling (right). Data shown
for municipal solid waste (top), predominantly inorganic waste (middle), and MSWI bottom ash
(bottom).
65
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modeled at L/S=10 mL/g and indicated on the red line on the respective left side graph. In each
right side graph, the remaining colored areas indicate the relative amount of the Cu or Pb associated
with specific solid phases over the indicated pH range. For example, dark green indicates
adsorption with particulate organic matter and red indicates adsorption onto iron oxide surfaces.
For the graphs of Cu partitioning, yellow indicates precipitation as tenorite or copper hydroxide
[Cu(OH)2] depending on the material, while for the lead graphs, yellow indicates precipitation as
lead hydroxide [Pb(OH)2]. Purple indicates co-precipitation with ettringite and red indicates
adsorption onto iron (hydr)oxide surfaces.
Examination of Figure 3-8 through Figure 3-11 elucidates several important phenomena:
The specific chemical species that control LSP varies as a function of pH (as well as pE, as
discussed in Section 2.2.3) and material type.
Comparison of LSP as a function of pH and at different L/S values (i.e., 10 and 0.3 mL/g, left
side graphs) provides clear indication of when solubility in solution (i.e., a saturated
solution) vs. the amount of a constituent that is available for leaching (i.e., availability)
controls the observed aqueous phase concentration. For example the aqueous phase
concentration of Cu in most of the materials is controlled by solubility at pH greater than 4,
while a plateau in aqueous concentration is present at lower pH values. Saturated solutions
are typically indicated when the simulated LSP at L/S=0.3 and 10 mL/g coincide. Materials
leaching in the pH domain where the simulated LSP at L/S= 0.3 mL/g results in substantially
higher aqueous concentrations than the simulated LSP at L/S=10 mL/g can be expected to
higher leachate concentrations at low L/S values (i.e., initial percolates) than observed from
the pH dependent leaching test carried out at L/S=10 mL/g.
Complexation with dissolved organic matter and adsorption onto solid organic matter is
more important for Cu than Pb LSP, and plays a critical role between pH 6 to 12. The
presence of more DOC increases the amount of Cu in solution.
The same set of phenomena and solid phases (i.e., organic matter complexation, precipitated
solid phases, adsorption onto iron surfaces) are responsible for a significant fraction of the
LSP behavior in multiple materials, albeit to different extents.
-------
4 LABORATORY AND FIELD DATA FOR EVALUATION CASES
4.1 Coal Fly Ash Landfill Leachate (United States)
The burning of coal for energy production results in several forms of CCRs, including (i) fly ash,
which is the fine material entrained in combustion gases and typically collected by an electro-static
precipitator (ESP) in the first stage of air pollution control; (ii) scrubber residues, usually collected
in the second stage of air pollution control, which may include processes for removal of gaseous
sulfur oxides in the form of calcium, sodium or magnesium sulfides and sulfates (depending on
facility configuration), and mercury removal by adsorption onto activated carbon; (iii) FGD gypsum,
which is produced when the scrubber is designed and operated to force sulfidic gas oxidation to
sulfates and precipitation with calcium; and (iv) bottom ash, which is the post-combustion residue
removed from the combustion grates or chamber. In addition, preprocessing of coal prior to
combustion can result in the production of a "coal milling reject" stream often including pyrite
minerals that have high concentrations of reduced sulfur species and are difficult to size reduce.
Specific CCR streams from a coal combustion power plant may be managed separately (e.g., for
beneficial use of one or more streams, such as fly ash or FGD gypsum) or together for disposal. The
specific leaching characteristics of individual CCRs are a function of the coal type combusted and the
combustion system design and operating conditions. Extensive discussion is available on coal
combustion facilities and the leaching characteristics of individual CCRs (Sanchez et al., 2006, 2008;
Kossonetal., 2009).
4.1.1 Case Description
Landfill leachates, porewater and lysimeter samples20 have been collected from multiple landfills
and surface impoundments in the U.S. containing CCRs under an Electric Power Research Institute
(EPRI) program (EPRI, 1988; 1998; 2006a; 2006b), and also by a U.S. EPA sampling program (EPA,
2000). The resulting set of field data was filtered to focus only on landfills receiving coal fly ash
from coal combustion facilities without FGD scrubbers and not receiving coal milling rejects. In this
way, the resulting set of data would reflect the range of landfill leachates produced from disposal
environments where the fly ash predominated. It would not be possible to identify all disposal sites
that receive only fly ash because most facilities co-dispose coal combustion bottom ash, although
this waste stream is considered relatively inert. The resulting set of field data is compared to the
range of pH-dependent leaching measured as part of a U.S. EPA study to characterize CCR leaching
(Kosson et al., 2009) and a reference sample from an interlaboratory leaching test methods
validation study (Garrabrants et al., 2012a; 2012b).
As part of the laboratory CCR characterization program, 35 fly ash samples were subjected to
laboratory pH-dependent leaching by EPA Method 1313 and the corresponding precursor method
SR002, as well as laboratory L/S dependent leaching by Method 1316 and the corresponding
20 Leachate samples typically are taken from leachate collection systems, which may include sumps, collection wells
and/or drainage above liner systems. Porewater samples typically are collected under suction from porous sampling
devices embedded in the field material or by taking core samples and then using centrifugation, compression or suction to
express pore water from the solid samples. Lysimeters typically are small-scale (e.g., on the order of 1 to 10 m3) field test
cells with liners and leachate collection intended to mimic larger field conditions.
67
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precursor method SR003. Results of the laboratory testing program are summarized for each
constituent as a function of pH or L/S based on the 5th, 50th, and 95th percentiles of the resulting
data based on interpolation to common pH or L/S points (Garrabrants et al., 2012a) and graphed as
either dashed (5th, 95th percentiles) or continuous lines (50th percentile). Field data are graphed as
individual observations as a function of the measured sample pH along with the statistical
(percentile) representation of the laboratory data.
4.1.2 Results and Discussion
A complete set of figures illustrating results from the field measurements in comparison to the
statistical representation of the laboratory data is provided in Appendix A. The field sites and
samples included can be summarized in Table 4-1. The field data includes core samples, pore water
samples, leachates from lysimeter tests, leachates from well and leachate collection systems. The
number of observations shown in Table 4-1 for calcium represents a high number of data points and
full coverage of each site. The actual number of sites and data points for each COPC varies; thus, the
ten total disposal sites are represented to various degrees.
Table 4-1. Summary of field sites and field data for calcium.
Sponsor Site Solid Core Lysimeter Well Leachate Pore water
Leachate Leachate Collection
EPRI 38575
EPRI 49003B
EPRI 50207
EPA 14093
EPA 23214
EPA 27413
EPA 50211
EPA 50212
EPA 50213
EPA SX-BAG
17
18
21
2
104
3
3
1
3
1
1
1
5
Totals 10 17 25 35 8 5
The following are notable relationships between field leaching and leaching test results:
Field leaching results for many constituents were well represented by the concentration as a
function of pH domain of the laboratory leaching tests, considering the variability associated
with the leaching behavior of fly ash from different facilities (Kosson etal., 2009). These
constituents included aluminum, boron, calcium, copper, iron, potassium, magnesium,
silicon, strontium, vanadium and zinc. Figure 4-1 illustrates this behavior for magnesium
and vanadium. In most cases, there were a few data points that fell outside the laboratory
distribution. For potassium, the laboratory distribution is skewed at alkaline pH because of
the addition of potassium hydroxide during testing to achieve test pH values greater than
the natural pH of the material.
-------
12 14
* EPRI-38575 Core
O EPRI-49003B Leachate
EPA-14093 Well Leachate
EPA-50211 Leachate Collection
X EPA-SX-BAG Porewater
EPRI-38575 Leachate
A EPRI-50207 Lysimeter
EPA-23214 Leachate Collection
O EPA-50212 Leachate Collection
EPA Lab - All CFAs - 5th, 95th %
A EPRI-38575 Lysimeter
D EPRI-50207 Well Leachate
EPA-27413 Well Leachate
A EPA-50213 Lysimeter
EPA Lab - All CFAs - Median
Figure 4-1. Comparison of field leachates to pH-dependent leaching for magnesium and
vanadium release from CCRs.
The range of pH observed for field leachate samples is in agreement with the range of
natural pH observed during laboratory testing of fly ash from multiple sources. However,
more acidic natural pHs were observed during laboratory testing (Kosson et al., 2009), but
probably were not present in the field samples because of exclusion of sites containing
pyrites (coal mill rejects) which also would correlate with high sulfur coals.
For several constituents (e.g., arsenic, cadmium, chromium, manganese, nickel, and
selenium), field leaching results exhibited bimodal behavior where one-third to one-half of
the field results were well-represented by the domain of the laboratory concentrations as a
function of pH domain, while the remaining data were significantly less than the laboratory
testing results. Field concentrations that were less than the laboratory domain were also
typically near detection limit values. Insufficient information was available to discern the
cause of this response which may have been a result of relatively high detection limits,
preferential flow or intrusion of dilution water. This bimodal behavior is illustrated in
Figure 4-2 for arsenic, cadmium, chromium and selenium.
69
-------
0.1 -
0.01 -
0.001
S o-1 -r
01
E 0.01
3
I
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u o.ooi
0.0001
^ /v^>m\n~n~i ii ii ii n n
| i i i I i i i I i i i |_^_
10 12 14
10 12 14
PH
100
10
1
0.1
0.01
0.001
0.0001
X
\
;H
A*^A
D /^m\n~fc
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2T A
CSSiaOCNU
10
12
14
PH
* EPRI-38575 Core
O EPRI-49003B Leachate
EPA-14093 Well Leachate
EPA-50211 Leachate Collection
X EPA-SX-BAG Porewater
EPRI-38575 Leachate
A EPRI-50207 Lysimeter
EPA-23214 Leachate Collection
O EPA-50212 Leachate Collection
- EPA Lab - All CFAs - 5th, 95th %
A EPRI-38575 Lysimeter
D EPRI-50207 Well Leachate
EPA-27413 Well Leachate
A EPA-50213 Lysimeter
^^ EPA Lab - All CFAs - Median
Figure 4-2. Bimodal behavior of field leaching results compared to pH-dependent leaching of
arsenic, cadmium, chromium and selenium from CCRs.
The upper range of field leaching concentrations for calcium and sulfate (Figure 4-3) reflects
the solubility of calcium sulfate within the uncertainty of temperature and co-dissolved ions
in solution (Marshall and Slusher, 1966). Note the 5th percentile dashed line for the
laboratory extracts between pH 9 and 13 indicates a steep decrease in sulfate concentration
with increasing pH. The decrease in sulfate at pH > 9 is consistent with the formation of
ettringite, Ca6Al2(S04)3(OH)i2-26H20, in some high calcium fly ash samples (e.g., material
codes XFA, ZFA in Figure 4-4 as compared to material codes EaFA or UFA). The formation of
ettringite results in decreased sulfate solubility at alkaline pH as well as a similar decrease
in chromium and molybdenum leaching resulting from anion inclusion and isomorphic
substitution into ettringite.
70
-------
en
Calcium
h
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0 2 4 6 8 10 12 14 0 2 4 6 8 10 12 14
pH pH
* EPRI-38575 Core EPRI-38575 Leachate A EPRI-38575 Lysimeter
O EPRI-49003B Leachate A EPRI-50207 Lysimeter D EPRI-50207 Well Leachate
EPA-14093 Well Leachate EPA-23214 Leachate Collection EPA-27413 Well Leachate
O EPA-50211 Leachate Collection O EPA-50212 Leachate Collection A EPA-50213 Lysimeter
X EPA-SX-BAG Porewater -EPA Lab - All CFAs - 5th, 95th % EPA Lab - All CFAs- Median
Figure 4-3. Comparison of field leachates to pH-dependent leaching for calcium and sulfate
release from CCRs.
pH dependent concentration of Ca
10000 -F_
pH dependent concentration of SO4
I
pH dependent concentration of Cr
100 -i
pH dependent concentration of Mo
-EaFA
-XFA
USEPA All Fly Ash Median
! UFA
1ZFA
- USEPA All Fly Ash 5th & 95th %
Figure 4-4. Effect of ettringite formation at alkaline pH on the leaching of chromium and
molybdenum.
71
-------
The upper range of field leaching concentrations for chloride (ca. 290 mg/L) is
approximately 15 times greater than the chloride concentrations at the 95th percentile for
chloride based on laboratory testing at L/S 10 L/kg (Figure 4-5, left). For sodium, the upper
range of field leaching concentrations (2,900 mg/L) is approximately 17 times the
concentration at the 95th percentile for the laboratory testing at L/S 10 L/kg (Figure 4-5,
right). These observed field values are reasonable given that the field porosity21 is ca. 0.3
and a resulting multiplier of 33 is calculated if the assumption is made that all of the
chloride or sulfate remains in solution (considering the porewater L/S would be
approximately equal to the porosity, or 0.3 mL/g and the laboratory testing is at L/S = 10
mL/g, so the resulting correction factor would be 10/0.3=33. The results are also consistent
with results of batch leaching as a function of L/S by Method 1316 and its precursor method
SR003 (Kosson et al., 2002).
1000
^> 100 -r
01
-------
_l
Ol
E 1
_3
^
N
~~ ^^
*- .
i
/
^ ^^
|ฃ
_/
^**V-
1^1
0)
+i
"5
<^-^
_
B^^C^^^^ffin
^i ^^~n.__, Cn_
- \ T^-
\
A \
\
\
1
f
'
0 2 4 6 8 10 12 14 0 2 4 6 8 10 12 14
pH pH
* EPRI-38575 Core EPRI-38575 Leachate A EPRI-38575 Lysimeter
O EPRI-49003B Leachate A EPRI-50207 Lysimeter D EPRI-50207 Well Leachate
EPA-14093 Well Leachate EPA-23214 Leachate Collection EPA-27413 Well Leachate
O EPA-50211 Leachate Collection O EPA-50212 Leachate Collection A EPA-50213 Lysimeter
X EPA-SX-BAG Porewater -EPA Lab - All CFAs - 5th, 95th % EPA Lab - All CFAs- Median
Figure 4-6. Comparison of field leachates to pH-dependent leaching for barium release from
CCRs.
4.1.3 Case Summary
Case 1 examined the leaching behavior of coal fly ash under landfill disposal conditions as a class of
materials. The study compares the leaching concentration ranges and pH dependent relationships
for field leachates and pore water in comparison to laboratory test results obtained from LEAF
testing of a wide range of coal fly ash samples. The applicable field leachate pH domain was from 6
to 13. Results of this case indicate that laboratory leaching characterization from a wide range of
samples within a class of materials (i.e., coal fly ash) can be used to define the characteristic
leaching behavior anticipated under field conditions (leachate concentration response as a function
of pH and the anticipated ranges of concentrations, or bandwidth), associated with the response at
specific pH values. The upper range of constituent concentrations from pH dependent testing (i.e.,
Method 1313) at a specific pH can be considered a conservative estimate of the upper limit of field
concentrations, but laboratory concentrations of highly soluble constituents (i.e., availability
limited) must be adjusted based on a correction factor between laboratory L/S and field pore water
L/S. Field leachate concentrations lower than anticipated from laboratory pH dependent testing
may be a consequence of either (i) reducing conditions (as seen for chromium and selenium) or (ii)
common ion effects (as seen for barium in the presence of sulfate).
73
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4.2 Leachate from Coal Fly Ash in Large-scale Field Lysimeters (Denmark)
4.2.1 Case Description
Large-scale lysimeter tests were carried out with coal fly ash in Denmark over the period of 1983 to
1990 (Hjelmar et al., 1991; Hjelmar, 1990). Individual lysimeters were 3m x 3m x 1.5 m deep (10
units) or 2.5 m deep (4 units) and used for a series of experiments, including those used for coal fly
ash studies (Figure 4-7). Each lysimeter had a low density polyethylene liner and separate leachate
collection. Filled lysimeters contained between 0.81 and 1.05 tonnes of fly ash and had 8-9 m2 of
surface area exposed to the atmosphere and natural precipitation. Two different fly ash materials,
identified as HF1 and BF2, were obtained from different Danish power plants, each burning a
different mixture of coal types. Results from BF2 as used in Lysimeters 4, 9 and 14 are the focus of
the case comparison presented here. Similar results were obtained for HF1 and are available in
Hjelmar (1990).
Fly ash samples HF1 and BF2 were also tested using laboratory percolation columns (Hjelmar et al.,
1991). At the time of the testing, column test methods had not yet been standardized. For BF2, the
column experimental conditions (identified as Column 4) were column diameter of 0.145 m, height
of fly ash packing of 0.58 m for a total of 8.1 kg dry weight, and an influent velocity of 44-145
mm/day (up-flow). Similar column conditions were used for HF1. Column influent was a synthetic
rainwater comprised of 0.5 mg/L NaCl, 0.19 mg/L NaHC03, 0.25 mg/L CaCl2-2H20 and 0.27 mg/L
Na2S04. However, the report also concludes, "Therefore, it makes little difference whether artificial
rainwater (with limited buffering capacity, as above), demineralized water or slightly acidified
demineralized water is used in leaching experiments, except perhaps at very high L/S values"
(Hjelmar etal., 1991, p. 26).
METERS i
2,5
20
1,5
1.0
0.5
3 METERS
COMBUSTION RESIDUE
AUTOMATIC PUMPING
OF LEACHATE TO
STORAGE TANKS
^7/twwr/,-
CONCRETE WALL
0.5 mm REINFORCED
LDPE LINER
DRAINAGE LAYER
(QUARTZ SAND)
PVC TUBING
LEACHATE
BUFFERING
TANK
Figure 4-7. Cross-section of large-scale field lysimeter construction (Hjelmar et al., 1991).
74
-------
4.2.2 Results and Discussion
Only a limited set of analytes was measured in field leachate and laboratory column eluates; only
one data point (at L/S ~0.002) was available for Lysimeter 4. A comparison of leachate composition
from field lysimeters and laboratory column testing (Column-4) is provided in Figure 4-8 for pH and
major constituents and in Figure 4-9 for trace constituents.
13
12
11
10
- Lysimeter-4
- Lysimeter-9
Lysimeter-14
-Column-4
0,001
0,01
0,1
L/S (L/kg)
pH
10
_ 10000
E
^ 1000 -
o
1 100 -
ฃ> 10 -
re
Lysimeter-4
Lysimeter-9
Lysimeter-14
Column-4
1
0,001 0,01 0,1
L/S (L/kg)
10
10000
_ง
o 1000
8
3
15
100
10
K
0,001 0,01 0,1 1
L/S (L/kg)
10
_ 1000
_ง
c 100
ol 10 -
o
c
8
s 1
0,1
Ca
0,001 0,01 0,1 1
L/S (L/kg)
10
_ 10000
13)
2 1000
8
01
100
10
0,001
0,01 0,1
L/S (L/kg)
Sulfate
10
Figure 4-8. Comparison of leachate composition from field lysimeters and laboratory column testing
(Column 4, red symbols) for pH, sodium, potassium, calcium and sulfate.
75
-------
Leachate pH values were lower for Lysimeter 14 than for Lysimeter 9 and Column 4, along with
somewhat higher calcium and somewhat lower arsenic concentrations in Lysimeter 14 than the
other results. Leachate constituent concentrations from Lysimeter 9 and eluate concentrations
from Column 4 were nearly identical for all constituents and consistent with the single observation
reported for Lysimeter 4. This information indicates that preferential flow was not a major factor in
the field lysimeter performance. In addition, the common behavior between laboratory and field
conditions for oxyanions (i.e., chromium and selenium) suggests that establishment of strongly
reducing conditions in the field was not a consideration for the material tested.
0,1 -
g 0,01
o
c
8
01
3 0,001
100
10
0,1
ฃ
3 0,01
Cr
0,001
0,01 0,1
L/S (L/kg)
10
0,001
0,01 0,1
L/S (L/kg)
10
100
13)
.ง 10
0,1 4
0,01
Mo
_ 1
f
c
ฃ 0,1 -
8 0,01 -I
0,001
0,001
0,01 0,1
L/S (L/kg)
10
0,001
0,01 0,1
L/S (L/kg)
10
Figure 4-9. Comparison of leachate composition from field lysimeters and laboratory column testing
(red symbols) for arsenic, chromium, molybdenum and selenium.
4.2.3 Case Summary
Case 2 compared the field leaching from large scale lysimeters over 7 years to results from
laboratory percolation column tests. The observed field leachate pH was between 11 and 12.8.
Results of this case indicate that laboratory percolation column testing (e.g., Method 1314) can
provide a good estimate of initial leachate concentrations under field conditions established in
lysimeters. Initial concentrations from field lysimeters at very low L/S (i.e., <0.01 L/kg) of some
76
-------
species may be somewhat greater than observed from initial eluates of laboratory percolation
column tests (i.e., molybdenum). Laboratory percolation column testing also provides a good
approximation of the evolution of leaching profiles as a function of L/S that would be expected
under field conditions in the absence of preferential flow and establishment of strong reducing
conditions.
4.3 Landfill of Coal Combustion Fixated Scrubber Sludge with Lime (United States)
4.3.1 Case Description
FGD filter cake and fly ash are typical CCRs requiring environmental characterization in conjunction
with material management. Plant 14090 served as a test case for comparison of laboratory leaching
tests of produced blended CCRs, laboratory leaching of core samples from the disposal landfill site
for the blended CCRs, and field leachate samples (EPRI, 2012).
Plant 14090 is a 1,000+ megawatt (MW) power plant. The plant burns pulverized eastern
bituminous coal in a boiler. Cold-side electrostatic precipitators (ESPs) are used on all units for
particulate control. Selective catalytic reduction is used at the plant but was not active during
collection of the materials used in this study. The wet FGD systems on two units are used to reduce
S02 emissions via limestone slurry sorbents and an inhibited oxidation process. The FGD solids,
consisting primarily of calcium sulfite, are pumped from the absorber to a thickener. Liquid
overflow from the thickener is recycled back into the FGD system, and the thickened sludge is
pumped to a series of drum vacuum filters for further dewatering. Water removed by the drum
vacuum filters is recycled back into the FGD system, and the filter cake (FC) is taken by conveyor
belt to a pug mill, where it is mixed with dry fly ash and dry quicklime for stabilization. The
resulting FSSLs are taken by conveyor to a temporary outdoor stockpile and then transported by
truck either to a utilization site or to an on-site landfill. After setting, the stabilized solid forms a
weak monolithic material that has some degree of compressive strength and moderately high
alkalinity.
"As produced" FSSL was sampled from Plant 14090 and evaluated as part of an EPA program on
leaching characterization of CCRs and identified by material code "MAD" (Sanchez et al., 2008) and
testing for pH-dependent leaching following method SR002 and L/S dependent leaching using
method SR003.22 Core samples from the FSSL disposal landfill (designated "FCM") also were
characterized for pH-dependent leaching using SR002 and L/S dependent leaching using SR003.
Porewater was collected from two locations in the landfill (designated "SCS-1" and "SCS-2")
between 2001 and 2007.
The concentrations of constituents in porewater samples collected from the FSSL landfill at Plant
14090 was compared as a function of pH to the equilibrium data from SR002 and SR003 tests.
22 SR002 (abbreviated in figures as SR02) and SR003 (abbreviated in figures as SR03) are Vanderbilt University
precursors of EPA Method 1313 and Method 1316, respectively. Although the general procedures and utilization of
results are the same, these precursors differ from the current tests in the number of extracts and the exact target values
(e.g., pH or L/S) required in each test.
77
-------
Porewater was collected at two locations in the landfill (i.e., SCS-1 and SCS-2) from November 2001
through May 2007, providing 25 independent samples for analysis.
4.3.2 Results and Discussion
A complete set of figures illustrating results from the field porewater measurements in comparison
to the laboratory leaching test results of "as produced" FSSL (i.e., MAD) and landfill core samples
(i.e., FCM) is provided in Appendix B. The following are notable relationships among the testing
results from the three types of samples:
The average natural pH of the MAD material is approximately 11.9 and of the FCM material
is 9.1 (based on replicate samples), whereas the average SCS sample pH is 7.4 with a span
from pH 6-10. The high natural pH of the freshly mixed FSSL is due to addition of quicklime
and the dissolution of Ca(OH)2 atapH of approximately 12.5. The decrease in natural pH
from ca. 12.0 for MAD to 9.0 for FCM is consistent with the consumption of Ca(OH)2 during
carbonation of alkaline materials, including slower reactions with fly ash (natural pH 11.3)
and scrubber solids (natural pH 8.9). Nominally, the natural pH of the field cored material
should agree closely with the pH of landfill leachates. The discrepancy in pH readings may
be caused by carbonation during handling and processing of landfill leachates. Based on the
titration curve of FCM, approximately 0.5 milli-equivalents of acid per gram of material
(meq/g) would be required to lower the pH of the FCM material to the mean leachate pH of
7.4. Considering the mass of FCM in the landfill, a significant amount of acid would be
required to overcome the buffering capacity of the FCM material. However, considerably
less acid (in the form of carbonation) would be needed to neutralize the porewater samples
once they were no longer in contact (and therefore near equilibrium) with the solid phase.
Therefore, porewater samples were likely neutralized through reaction with atmospheric
carbon dioxide during collection and handling prior to analysis.
The impact of aging and partial carbonation of field cores (FCM) in comparison to the "as
produced" material (MAD) is apparent in the response of barium, calcium, magnesium and
strontium between pH of 8 and 13, where FCM indicates decreased solubility relative to
MAD (illustrated for barium, calcium and strontium in Figure 4-10). Porewater
concentrations of these constituents are similar to or less than the concentrations measured
for field core material. This is a typical response to carbonation and is consistent with other
results for other materials presented in this report.
Field porewater concentrations of barium are lower than measured in laboratory extracts of
field cores and "as produced" material. This phenomena is similar to that observed for coal
fly ash (see Section 4.1) and likely results from elevated concentrations of sulfate at the low
L/S associated with porewater, thereby reducing barium sulfate solubility by common ion
effects.
78
-------
100
10000
,-> 1000
I
Isi
.3
100
10
0.01
10 12 14
10 12 14
PH
1
3
1
S
ft
1 .
A
A
4
6>
9D c
t
cP1
"bo,n
Wp
T\
Riซ^
) AA
^CC
0
FSSL - "as produced" (MAD)
A FSSL-Field Core (FCM)
ป Landfill Porewater
10 12 14
PH
Figure 4-10. Comparison of pH-dependence testing of field-cored FSSL and "as produced"
FSSL to field porewater samples showing the impact of aging and partial carbonation of field
materials.
When "as produced" and field core samples are compared, the coupling between chloride
and cadmium leaching is evident (Figure 4-11). The higher chloride concentrations in the
unaged "as produced" samples result in increased cadmium concentrations relative to the
field cores. However, this effect of elevated chloride concentration increasing cadmium
leaching is not evident when porewater samples are compared to laboratory results.
79
-------
Chloride (mg/L)
1 P S i
' (-* h-^ O O C
A
*t
f AA ,
^
f/A
0 2 4 6 J
PH
FSSL -"as produced" [MAD)
A FSSL -Field Core (FCM)
* Landfill Porewater
> *
V
*
A"
A
O
_l U.I
1
ฃ 0.01 -
o
ra
A
M.
*
A
S^oc
&&;
A
! 10 12 14 0 2 4 6 J
PH
A?*
A
>
O
! 10 12 1
Figure 4-11. Comparison of chloride and cadmium leaching in field-cored FSSL and "as
produced" FSSL to field porewater samples showing the impact of cadmium chloride
chelation.
The effect of dissolved organic carbon (DOC) concentrations resulting in increased copper
concentrations is evident when comparing laboratory testing on the "as produced" material
to field cores and porewater analysis at pH 6 to 8 (Figure 4-12).
c
o
.Q
1_
a
U
23
100
10
1
0.01
0.001
00
10
01
a.
a.
0.1 -r
0.01 -r
0.001
cP
C*AA
10 12 14
10 12 14
PH
PH
FSSL - "as produced" (MAD)
A FSSL -Field Core (FCM)
* Landfill Porewater
Figure 4-12. Comparison of dissolved organic carbon and copper leaching in field-cored FSSL
and "as produced" FSSL to field porewater samples showing the impact of complexation of
dissolved organic carbon with copper.
80
-------
Concentrations of oxyanions are either similar to or less than the concentrations measured
by the laboratory pH-dependent leaching test at the corresponding pH. These leachate
concentrations are more closely related to the laboratory testing of the field cores (i.e., aged
FCM material) than to the concentrations from laboratory testing of the unaged "as
produced" material (MAD). This relationship is observed for several analytes including
arsenic, boron, antimony, molybdenum, selenium and vanadium (illustrated for arsenic,
boron, molybdenum and selenium in Figure 4-13). Molybdenum is the only oxyanion for
which aging of the material resulted in increased concentrations relative to the "as
produced" material (at pH less than 8.
nซn
_l
1 '
o
'c n 1 .
s ^
<
n nm -
A
A
V
0ฐ
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di^
v;
RA
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(
A
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4
01
ฃ i-
c
1
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: A
Q&c
^A^c(
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<
oo
AUk
AA
3 8
4
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0 2 4 6 8 10 12 14
PH
0246
10 12 14
PH
J.U
J1
01
^
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3 1
C
ID
o
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O
S
n 1 -
A
4^
e0c
o
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A^A
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*
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<3OIO-
A
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A A
P
10
01
*
0 1
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2 1
PH
FSSL - "as produced" (MAD)
A FSSL-Field Core (FCM)
* Landfill Porewater
Figure 4-13. Comparison of arsenic, boron, molybdenum and selenium leaching in field-cored
FSSL and "as produced" FSSL to field porewater samples.
Concentrations of highly soluble species, including chloride, potassium, lithium and sodium,
are greater by up to a factor of 20 in the porewater (L/S less than 0.5 L/kg) than when
measured by the pH-dependent leaching test at L/S of 10 L/kg. However, the porewater
concentrations for these constituents are closely estimated by the laboratory batch L/S
81
-------
dependent leaching test (i.e., SR03 or Method 1316; illustrated for potassium and sodium in
G1
01
E
S'~
IB
2
0.
E
3
in mn
A
A A
A
A
A
_
^
01
E
3
o
A
A
A
A
A
A
4:
t
1 1 10 0.1 1 1
L/S (L/kg) L/S (L/kg)
mnnn
L/S=0.5 L/kg;
Conc=20*40 mg/L=800 mg/L
1
-k NX^-.
T " "-.,_ .
\i^
~--_ A
^~A
L/S=10 L/kg; Conc=40 mg/L ^ ,
^^
Ol
E
3
' mn
M
h
0.1 1 10 0
L/S (L/kg)
1/5=0.5 L/kg;
Conc=20*30 mg/L=600 mg/L
1 ^>c^
~^1
"**. A
^--^
^~-~4
L/S=10 L/kg; Conc=30 mg/L ^~~,
.111
L/S (L/kg)
Figure 4-14).
^
"5 100 -
^>
E
3
U)
i io-
Q.
4
- A ^A A AJ^^ A^
rtlTl ^-^ rt-A?"V^-A /^-* O O
O-^*-ปCXJป (jฃ>
OFSSL- as produced (MAD)
AFSSL-FieldCore(FCM)
* Landfill Porewater
01
E
^ 100
E
3
o
ซ 10
0 2 4 6 8 10 12 14
AA
*^U' ^ A
<5$
.
; .
: A cstrc^ ^A4^^5^P ^po OCS>D
0 2 4 6 8 10 12 1
pH pH
82
-------
J.UUU
^^
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en
"*-*"
Emn -
1UU
'ซ
(0
re
s
Q.
m -
A
A A
A
A
A
i
0.1
10
L/S (L/kg)
10000
01 1000
E
3
ซ
a 100
10
L/S=0.5 L/kg;
Conc=20*40 mg/L=800 t
L
7
L/S=10 L/
ng/L
'""---. A
~~A,
"^-^ A
-------
4.4 Coal Fly Ash Used in Roadbase and Embankments (The Netherlands)
4.4.1 Case Description
In the framework of the National Research Program Coal (NOK), studies were done to evaluate
beneficial coal fly ash uses (Spee and Reintjes, 1986). Two applications were studied in full scale - a
roadbase made with bound fly ash covered by asphalt and sintered paving bricks (road sections of
100 m long and 8 m wide) with cement-stabilized fly ash used as a base for an embankment (100 m
long). Cross-sections for the roadbase and the embankment applications are presented in Figure
4-16 and Figure 4-15, respectively. Measurements were carried out over a 2 year period, starting in
1984.
Coarse Sand
Paving Blocks -
Fly Ash Cement Stahiliied
- ^ - ' ' ' '- -'
_T" **Ta50 m: ^Drainage Sand
Drainage Channels* 80 cm dia.
Drainage Channels* 100 cm dia.
Asphalt Pavement 0.09 mm
fly Ash - Ftuidized Bed Combustion -Stabilized
Mirror View
Sand Foundation
8.50m
8.50 m
'Drainage channels through the fly ash stabilization layer
filled with a 2cm/6cm mix of coarse granular aggregate
Figure 4-15. Cross section of roadbase constructed with cement stabilized coal fly ash (same as for
the embankment). The stabilized fly ash (0.8 m thick) is overlain with an asphalt layer in the road
surface area and by clinker material (coarse aggregate) on the sloped road shoulder area, and
underlain with a sloped sand drainage layer (0.30 m thick). A polyvinyl chloride plastic sheet underlies
the sand drainage layer to ensure leachate collection in a collection sump (at left).
Leachate obtained from collection wells at the side of the road and at the foot of the embankment
was analyzed for a selection of substances. The coal fly ash used was stabilized with addition of 5%
cement. This mixture was tested separately in a column experiment.
84
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4.4.2 Results and Discussion
Results for calcium, chromium, molybdenum and selenium from leachate collected from the
roadbase, embankment and laboratory percolation column studies are presented in Figure 4-17.
The set of data (dots) with the lowest L/S values represents concentrations in the leachate collected
from the embankment, while the continuous lines represent concentrations obtained from the
laboratory percolation column experiments.
Grass-covered compost
0.30m
Mirror View
trainage Sand PVC Foil
_Drain 100 cm
Figure 4-16. Cross-section of embankment constructed with cement stabilized coal fly ash as the core
material and then covered with 0.3 m topsoil for growth of grass. A drainage sand layer underlies the
stabilized coal fly ash, and a polyvinyl chloride plastic sheet underlies the sand drainage layer to
ensure leachate collection through a drain (center bottom) and diversion to a collection sump (at left).
Leachate concentrations emanating from the embankment initially have relatively low
concentrations that increase significantly at L/S of ca. 0.005 L/kg. This delayed release reflects
displacement of initial porewater in the underlying sand drainage layer and retardation by partial
adsorption by the sand drainage layer. Similarly, there is an offset as a function of L/S of ca. 0.5 L/kg
for the concentrations of constituents in leachates emanating from the roadbase in comparison to
the percolation column results. This offset is attributed to the collection of samples at much lower
L/S for the field conditions and integration of sample volumes over the collection intervals for the
laboratory columns. This effect has been further confirmed through independent tracer studies
(van der Sloot et al, 1991). Although this data set is sparse, it does indicate that the laboratory
column experiments conservatively approximate the peak leachate concentrations observed in the
field.
85
-------
100000
0.00001 0.0001 0,001 0.01 0.1 1
L/S (L/kg)
0.01 0.1
L/S(L/kg)
0.00001 0.0001 0.001 0.01 0.1
L/S(L/kg)
10 100
-CF A/cement (95/5) Column D Road side collection well 2
Road side collection well 3 x Road side collection well 4
Road side collection well 1 Embankment well 6
Embankment well 7 CFA ML Column
I .
3 ,
\
ฐ*
0.00001 0.0001 0.001 0.01 0.1 1
L/S(L/kg)
Figure 4-17. Field leachate concentrations from Dutch embankment and road base demonstration
projects compared to laboratory percolation column experiments.
4.4.3 Insights Gained from Chemical Speciation of Coal Fly Ash Leaching
The following examples illustrate the impact of three common phenomena which strongly influence
retention and leaching of COPCs - oxyanion substitution for sulfate in ettringite, carbonation due to
uptake of C02, and oxidation/reduction. These phenomena are shown through comparison of
leaching test data from a European coal combustion fly ash (pH-dependent and percolation column,
material code CFA) to chemical speciation model results conducted at various L/S values. The
presentation of chemical speciation results in these examples is similar to that used in comparison
of materials.
In Figure 4-18 through Figure 4-20, leaching test results are presented along with chemical
speciation modeling of LSP and associated phase partitioning of Cr, S04, and Mo. For each figure, the
first panel compares pH-dependent leaching data (red dots) and percolation column data (blue
triangles) to CSF model results at L/S 10 (red solid line) and L/S 0.3 (blue dashed line). The latter
two panels of each figure show the relative contributions of mineral, carbon, and aqueous species
86
-------
that are responsible for the shape and magnitude of the CFS model results at L/S 10 and L/S 0.3. In
particular, these figures for Cr, S04, and Mo in CFA fly ash illustrate the importance of oxyanion
substitution for sulfate in ettringite, (CaO)6(Al203)(S03)3-32H20, as a retention mechanism for
oxyanions such as molybdate and chromate in the pH range between 9 and 13.
Coal Fly Ash (the Netherlands)
l.E-05 -
l.E-06 -
1 F-H7 -
V.
/
ป
pH-dependence
[Cr04-2] L/S=10
A Percolation Column
[Cr04-2] L/S=0.3
\
\
\
h
* /
>
/
^
1234567
9 10 11 12 13 14
PH
Partitioning of Cr at L/S=10
l.E-03
l.E-04
l.E-05
l.E-06
1 P-H7 .
DFree ROM-bound
FeOxide DClay
D Ettringite
:
VT
l.E-02 T
*3 l.E-03 -I
l.E-04 -
E l.E-05 -r
o
l.E-06 -
l.E-07
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Partitioning of Cr at L/S=0.3
V
234567
9 10 11 12 13 14
PH
Figure 4-18. Chemical speciation model results for chromium at L/S=10 and L/S=0.3 compared to pH-
dependent (CEN/TS 14429) and percolation column (CEN/TS 14405) leaching results for coal fly ash
(the Netherlands).
87
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Coal Fly Ash (the Netherlands)
~^
^
ฃ l.E-03 -
ฃ
ฃ l.E-04 -
(A
l.E-06 -t
1
1 C-01
l.E-02 -
2 l.E-03 -
s
ฃ l.E-04 -
3
W
l.E-05 -
1 F-flfi -
*
O
A
'
s
w
pH-dependence
-[S04-2] L/S-10
Percolation Column
[S04-2] L/S=0.3
*,
\
\
V ,
\A
v\
v /
\/ 1
t
A
A
/
A/
J
7
I
I
i
s
2 3 4 5 6 7 8 9 10 11 12 13 14
:
PH
Partitioning of S04
at L/S=10
Partitioning S04 at L/S=0.3
FeOxide OClay
DEttringite n[Ba,Sr]S04 (50%Ba)
1
\
/
/
\J
S
^ l.E-02
"3
E l.E-03 -
^a
.2 l.E-04
3
l.E-05
/
^ /
DFree \ /
DDOC-bound \ /
POM-bound \ /
FeOxide \ /
DClay \^ /
Ettringite ^V/
DAA_Gypsum
D[Ba,Sr]S04(50%Ba)
2 3 4 5 6 7 8 9 10 11 12 13 14 2 3 4 5 6 7 8 8 9 10 11 12 13 1
PH
PH
Figure 4-19. Chemical speciation model results for sulfate at L/S=10 and L/S=0.3 compared to pH-
dependent (CEN/TS 14429) and percolation column (CEN/TS 14405) leaching results for coal fly ash
(the Netherlands).
-------
Coal Fly Ash (the Netherlands)
^
o
^>
0)
o
.a
>.
"S 1 F-flfi -
z
A
pH-dependence
[Mo04-2] L/S=10
Percolation Column
[Mo04-2] L/S=0.3
*
\
\
\
\
\
\
IJ
A
/
*'
/
r
k
1 2 3 4 5 6 7 8 9 10 11 12 13 1
PH
Partitioning of Mo at L/S=10
o
l.E-05 -
l.E-06 -
1 F-PI7 .
DFree DDOC-bound
POM-bound BFeOxide
OClay DEttringite
OPbMo04[c]
^^\/
Partitioning of Mo at L/S=0.3
l.E-04 -?
O
*-* l.E-05
E
01
S
>,
o
l.E-06 -:
l.E-07
I ' I ' I ' I ' I ' I ' I ' I
1234567
9 10 11 12 13 14
234567
9 10 11 12 13 14
PH
PH
Figure 4-20. Chemical speciation model results for molybdenum at L/S=10 and L/S=0.3 compared to
pH-dependent (CEN/TS 14429) and percolation column (CEN/TS 14405) leaching results for coal fly ash
(the Netherlands).
Figure 4-21 and Figure 4-22 illustrate the impact of reaction with atmospheric carbon dioxide (i.e.,
carbonation) on the shift controlling mineral species. The two upper panels compare CSF model
results at increasing degrees of carbonation (determined by C02 uptake between 1 and 7 wt %) to
the leaching data for Ca and Ni. The lower figures show the phase partitioning that creates the CSF
model LSP result. Figure 4-21 clearly demonstrates that increasing extent of carbonation yields a
loss of ettringite and formation of calcite, CaCOs, with a concurrent decrease in Ca solubility atpH
greater than 7. In the case of Ni (Figure 4-22), increased carbonation increases the partitioning Ni
into the aqueous phase due to the loss of oxyanion substituted ettringite and competition with
carbonate adsorption onto HFO surfaces.
89
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L/S=10 at Different Carbonate Levels
L/S=0.3 at Different Carbonation Levels
1 l.E-03
E
3 1 E-04
^
l.E-05
\V. * *"~^-Ji^
\ -^ f)
\ \\
\ A N;\._
A_. VAV
pH-dependence * V
[Ca+2] 2.85 wt% COS . . ^
[Ca+2] 3.45 wt% COS \ S
[Ca+2] 7 wt% COS -^ S
l.E+OO -
"3
E l.E-02 -
I l.E-03 -
ju
51 F-fl4 -
l.E-05 -
1 1 1 1 I 1 l.b-Ub H
1 2 3 4 5 6 7 8 9 10 11 12 13 14 ]
X>\ ~^-^.
\ ^i^ X^
' """ V^ tt y"\
v * ^Bn
' ^"*x i ^y
\ \\
r ' ' A \ \
> A \
pH-dependence % \
[Ca+2] 2.85 wt% COS \
[ [Ca+2] 3.45 wt% COS . '
[Ca+2] 7 wt% COS V. ./
2 3 4 5 6 7 8 9 10 11 12 13 1
pH pH
l.E-01 -|
l.E-02 -
^ l.E-03 -
O
E
"ฑ l.E-04 -
ฃ l.E-05 -
ID
U
l.E-06 -
1
Partitioning of Ca; L/S=10, 1 wt% C03
^^c^
2 3 4 5 6 7 8 9 10 11 12 13 1
1 E-01 -i
1 E-02 -
^ l.E-03 -
E
"T" l.E-04 -
!a i.E-os -
5
l.E-06 -
4 2
Partitioning of Ca; L/S=10, 2.85 wt% C03
^ " ^ r
\--_
^^ปT.
XxN
3 4 5 6 7 8 8 9 10 11 12 13 1*
PH pH
l.E-01 -
l.E-02 -
^ l.E-03 -
0
E
"ฑ l.E-04 -
3
ฃ l.E-05 -
ID
U
l.E-06 -
Partitioning of Ca; L/S=10, 3.45 wt% C03
>^
^t
V__^_
^^x:
1 E-01 -
l.E-02 -
^- l.E-03 -
O
E
"T" l.E-04 -
3
5 l.E-05 -
ID
U
l.E-06 -
Partitioning of Ca; L/S=10, 7 wt% C03
! \
\ f\
\ \\
\ /"^
W^-
; V^ ^^
\ *s
V S
^*^
\
2 3 4 5 6 7 8 8 9 10 11 12 13 14 1 2 3 4 5 6 7 8 9 10 11 12 13 1
PH pH
DFree DDOC-bound BPOM-bound
FeOxide DClay DEttringite
DAA_2CaO_AI203_Si02_8H20 [s] DAA_3CaO_AI203_6H20 [s] DAA_3CaO_Fe203_6H20 [s]
DAA Calcite BAA Tobermorite-I D beta-TCP
BFIuorite BWairakite
Figure 4-21. Effect of carbonation levels (wt% CO3) on calcium model predictions and partitioning
compared to pH-dependent (CEN/TS 14429) and percolation column (CEN/TS 14405) leaching test
results.
90
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L/S=10 at Different Carbonation Levels
o
^>
"3
S 1.1
l.E-07
l.E-08
1 F-riQ .
:
r
i
pH-ds
O own
A Perco
[Ca+
[Ca+
[Ca+
A
V
pendence
H
ation Column
2] 1 wt% COS
2] 2.85 wt% COS
2] 3.45 wt% COS
21 7 wt% COS
~^~
^
i
V
\
~~
^s
(
-\
y
/
ป \
y
ฃ
/
L/S=0.3 at Different Carbonation Levels
^ l.E-05 -
E
J l-E-06 -
Z l.E-07 -
l.E-08 -
1 F-nQ .
ฐ
V
*
**""
^
pH-dependence
O own pH
A Percolation Column
[Ca+2] 1 wt% COS
[Ca+2] 2.85 wt% COS
[Ca+2] 3.45 wt% COS
[Ca+2] 7wt% COS
\
\
i
\
\
is^
<
/
ป i
\
\
/
a
y
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
1 2 3 4 5 6
7 8
PH
9 10 11 12 13 14
l.E-04 T
Partitioning of Ni; L/S=10, 1 wt% C03
l.E-05
?*
_i
^ l.E-06
^>
S l.E-07 -r
o
'z
l.E-08 -
l.E-09
l.E-04
l.E-05
Partitioning of Ni; L/S=10, 2.85 wt% C03
O l.E-06 -
E
l.E-07 ;
l.E-08 - r
l.E-09
l.E-04
l.E-05
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Partitioning of Ni; L/S=10, 3.45 wt% C03
234567
9 10 11 12 13 14
PH
5 l.E-06 -
ฃ
"g l.E-07 -
l.E-08 -
l.E-09
l.E-04
Partitioning of Ni; L/S=10, 7 wt% C03
l.E-05 -
^. l.E-06
O
TZ l-E-07 -t
v
o
Z l.E-08 -
l.E-09
2 3 4 5 6 7 8 8 9 10 11 12 13 14
PH
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
DFree BDOC-bound ROM-bound
FeOxide DClay DNi[OH]2[s]
Figure 4-22. Effect of Carbonation levels (wt% CO3) on nickel model predictions and partitioning
compared to pH-dependence (CEN/TS 14429) and percolation column (CEN/TS 14405) leaching test
results.
Figure 4-23 illustrates the impact of reduction/oxidation on the percolation leaching of Cr. The
panels on the left side of the figure show the results of percolation column leaching tests (blue
symbols) and model results conducted at three levels of pH+pE. For the model results, the orange
91
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symbols indicate data points at target L/S values while the orange dashed line indicates continuous
elution as a function of L/S. The right hand panels present the phase partitioning at each level of
pH+pE. Figure 4-23 illustrates that as the reducing conditions (i.e., higher values of pH+pE) results
in a decrease in Cr leaching due is the reduction of Cr(VI) to Cr(III) and the low solubility of Cr(OH)3
at mildly alkaline pH. Comparison of the field embankment samples with the simulations indicates
pH+pE in the embankment between 12 and 12.8 with Cr(OH)3 as the controlling solid phase.
92
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Coal Fly Ash; pH+pE=15
Chromium (mol/L)
_i i_i i_i i_i i_i i_
n m m m m r
D O O O O C
-J Oi UJ h
'. """ NH
i
\
\ i
A Percolation Column
[Cr04-2] (continuous)
D [Cr04-2] (fraction average)
1
A V*
I
k \'l
0.01
0.1
10
100
l.E-02
l.E-03
l.E-04
L/S (L/kg)
Coal Fly Ash; pH+pE = 12.8
E
1 l.E-05 -f
0 l.E-06 -f
l.E-0
I
A Percolation Column
[Cr04-2] (continuous)
[Cr04-2] (fraction average)
\.
\
n
l
*-\vi*
L
0.01
0.1 1
L/S (L/kg)
10
100
Coal Fly Ash; pH+pE = 12
Chromium (mol/L)
_L |_L |_L |_L |_L |_
Ti m m m m r
D 0 0 0 0 C
vi o> LH -i^ l.E-03
~0
& l.E-04
E
| l.E-05
V l.E-06
OFree
POM-bound
FeOxide
0.00 3.33 6.67 10.00
Depth (m)
13.33
Partitioning Profile; L/S=1.3, pH+pE=12.8
l.E-07
DFree
POM-bound
FeOxide
DCr(OH)3 [A]
0.00 3.33 6.67 10.00
Depth (m)
13.33
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06 -;
Partioning Profile; L/S=1.3, pH+pE = 12
l.E-07
0.00 3.33 6.67 10.00
Depth (m)
13.33
Figure 4-23. Effect of reducing and oxidizing (redox) conditions on chemical speciation results for
chromium as a function of L/S (left) and chromium partitioning with depth (right) for coal fly ash (the
Netherlands).
4.4.4 Case Summary
Case 4 compared the results of field leaching over 2 years from a road base and embankment
constructed with coal fly ash to percolation column results. Laboratory pH dependent leaching test
results from an analogous material were also used for comparison. Results of this case illustrate the
93
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benefits of the combined use of pH dependent leaching and percolation column leaching in
combination with chemical speciation simulations to understand field performance. Specifically,
insights from the combined use of these tools provided insights into the redox condition in the
material (establishment of reducing conditions), potential impacts of carbonation, and the resultant
consequences for leaching of oxyanions (e.g., chromium). Percolation column experiments
provided a realistic estimate of the upper bound concentration for leaching of COPCs, however, an
initial delay was observed in the field before peak leaching concentrations were observed. The
initial delay was attributed to the mass transport delay and attenuation associated with drainage
materials (i.e., sand) underlying the primary fly ash fill. This highlights the need to carefully design
and understand field monitoring strategies and their impact on field measurements.
4.5 Municipal Solid Waste Incinerator Bottom Ash Landfill (Denmark)
4.5.1 Case Description
A relatively small MSWI residue landfill, established between 1973 and 1976, has been monitored
periodically for more than 30 years. The landfill is situated at Vestskoven in the western part of
Greater Copenhagen in Denmark and contains approximately 10,000 m3 of bottom ash and fly ash
from a nearby MSW incinerator (Hjelmar and Hansen, 2005; Hjelmar et al., 1991). During the initial
period of operation, the amount and quality of the leachate generated was monitored. In December
2003, two borings were made into the site and several samples of the landfilled material were
collected from different depths of the site. In addition, leachate was collected from one of the two
borings. Solid samples obtained from the borings were subjected to leach testing in accordance
with technical specification EN 12457-1, a single batch extraction leaching test with deionized
water at L/S of 2 L/kg. Field leachate samples and leaching test extracts were then analyzed for
constituents of interest.
4.5.2 Landfill Construction
In June 1973, a circular site was dug a few meters into the ground with the excavated soil used to
construct a dike at the perimeter of the hole. The site was lined with reinforced PVC on top of which
a protective 0.3 m drainage layer of sand was placed. The bottom liner slopes towards the center
where a leachate collection tank was installed. Access to the collection tank was afforded by a well
shaft, allowing the removal of leachate by pumping. The well shaft was adjusted in height as
landfilling progressed until the landfill reached its final height. During the period July 11 to August
29,1973, the site was filled to the top of the dike with approximately 6000 m3 of MSWI bottom ash
and fly ash. The top of the site was then left open and exposed until 1976.
During the period January to June of 1976, an additional 4000 m3 of bottom and fly ash was placed
on top of the site, forming a circular mound. Aim layer of topsoil was placed directly on top of the
MSWI residues. Self-sown grass and bushes soon covered the surface of the site. Figure 1 shows a
cross-section of the closed site while Table 4-2 provides some physical details on the size and shape
of the site.
94
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Leachate collection well
Top cover
1 m of topsoil
Protective layer: 0.3 m of sand
Leachate collection tank
Bottom liner:
Reinforced PVC
Figure 4-24. Cross-section of the MSWI residue monofill in Vestskoven, Denmark (Hjelmar and
Hansen, 2005).
The landfilled material has been estimated to consist of approximately 85% of MSWI bottom ash
and 15 % of MSWI fly ash. Observations made during the drilling of boreholes in 2003 revealed that
a substantial amount of scrap metal was also present and that the fly ash was deposited in distinct
layers. Although the exact bulk density is unknown, the dry bulk density of the landfilled material
was estimated to be 1000 kg/m3 in previously published information on the leachate development
at the site (e.g. Hjelmar, 1989; Hjelmar, 1996; IAWG, 1997). Based on the information obtained in
2003, the estimate of the dry bulk density of the material in the monofill has been adjusted to 1,200
kg/m3. The calculated values of the L/S used in this report are based on the revised value of the dry
bulk density. The landfill is thus estimated to contain approximately 12,000 tonnes of MSWI
residues (dry weight).
Table 4-2. Physical information about the Vestkoven MSWI monofill.
Parameter Value
Amount of MSWO residues
Diameter of the site at the upper edges of the dike
Diameter of the site at the inner bottom of the dike
Surface area at the upper edge of the dike
Surface area at the inner bottom of the dike
Elevation of the bottom of the leachate collection tank
Elevation of the bottom liner
Elevation of the upper edge of the dike
Elevation at the top of the site
Maximum height of the MSWI at center
10,000 m3 (approximately)
52.4m
40m
2,157m2
1,257m2
13.4 m above sea level
15.0 - 15.4 m above sea level
18.4 m above sea level
25.4 m above sea level
9.2 m (approximately)
4.5.3 Leachate Quantity and Quality
Since the landfill was established in 1973, the leachate produced has been pumped from the
leachate tank at regular intervals. During the period from 1973 to 1977, the leachate was sprayed
95
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onto the top of two adjacent MSWI residue landfills. From 1977 to 1980, the leachate was allowed
to accumulate within the site. From 1980 to the present, the leachate has been pumped into tank
trucks and removed from the site. The quantity of all leachate removed from site has been
registered throughout its existence, and the leachate has been subjected to chemical analysis once a
year (in the beginning more often). Water balances for the site have been calculated each year since
1980 and compared to precipitation data obtained from a nearby weather station (Hjelmar and
Hansen, 2005). The results of the water balance calculations have shown that for the seven-year
interval between 1998 and 2005, the leachate production has corresponded to 33% of the
measured precipitation.
Leaching data were not available for the MSWI bottom ash and fly ash that was originally used in
the MSWI landfill project. Therefore, a selection of leaching pH-dependent and percolation column
test results from testing of MSWI bottom ash from Germany (Berger etal., 2005) and the
Netherlands (van der Sloot et al., 2008c) are used as reference materials for this case.
4.5.4 Results and Discussion
A complete set of figures is provided in Appendix C for the comparison of Vestkoven monofill
leachate concentrations (red circles) to laboratory results on Vestkoven core samples (grey
diamonds) and off-site comparable materials from Germany, Italy, Austria, The Netherlands and the
United Kingdom (solid symbols with lines). Laboratory data include (i) single batch extraction test
results from EN 12457-1 testing of landfill cores and (ii) pH-dependent leaching test results for the
reference materials, and (iii) percolation column testing for reference materials (Susset and Leuchs,
2008). Comparisons are shown as a function of pH (left) and L/S (right). Although the comparison
materials represent the same class of materials placed into the Vestkoven landfill, the materials
were not sampled from the monofill and, therefore, the results for comparison materials are
provided only as an indication of expected leaching behavior.
The following are notable relationships between leaching test results for specific constituents:
The batch extractions of cored samples at L/S 2 L/kg ranged from 7.6 to 11.6 which is
consistent with the range of leachate pH values (Figure 2-5). Lower upper bound values of
pH from field samples is expected because of reaction with carbon dioxide, either generated
from decomposition of residual carbon in the fill material or from atmospheric exchange
during leachate accumulation and sampling.
96
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14
12 -
O O o
0.01
0.1 1
L/S (L/kg)
10
- MSWI Bottom Ash (Germany)
- Hi - MSWI Bottom Ash (Italy)
--*-- MSWI Bottom Ash (Austria)
- ป- - MSWI Bottom ash (the Netherlands)
A MSWI Bottom Ash (UK)
O MSWI Monofill Leachate (Denmark)
Figure 4-25. Eluate pH from leachates from the Vestkoven monofill (red circles) compared to the
percolation column pH for comparable bottom ash samples (solid symbols).
Analysis of batch extractions of core samples for arsenic was not available. Figure 4-26
presents the field leachate data in comparison to pH dependent test results and percolation
column test results for the analogous reference materials. Maximum field leachate
concentrations were approximately 10 times greater than anticipated based on pH
dependent testing but consistent with column test results for the reference materials.
Collectively, these results indicate that the fraction of arsenic not adsorbed to iron (the most
likely retention mechanism for MSWI bottom ash) behaves as a highly soluble species,
exhibiting higher concentrations at lower L/S.
o.oooi
0.1 1
L/S (L/kg)
- - MSWI Bottom Ash (Germany)
--- MSWI Bottom Ash (Italy)
-ป-- MSWI Bottom Ash (Austria)
-*- - MSWI Bottom ash (the Netherlands)
4 MSWI Bottom Ash (UK)
O MSWI Monofill Leachate (Denmark)
Figure 4-26. Arsenic concentration results from the Vestskoven MSWI monofill leachate samples (red
circles). Data are shown for pH-dependent leaching (left) and percolation column testing (right).
These results illustrate typical relationships between pH-dependent and column testing of cored
samples and leachate measurements.
97
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The constituent concentration ranges from batch extractions of cored samples at L/S 2 L/kg
also were consistent with the concentration ranges measured in the leachate samples
obtained over several years of operation of the landfill (Figure 4-27). For many constituents
(i.e., chromium, lead, potassium, sodium, chloride) the upper bound for extract
concentrations from the core samples was greater than or similar to the upper bound for
leachate concentrations, although both data sets exhibit considerable variability most likely
resulting from heterogeneous water flow patterns through the landfill over the period of
observation and the heterogeneity of the fill material. For zinc, the peak laboratory
extractions at L/S 2 L/kg were up to an order of magnitude lower than the peak leachate
concentrations at pH greater than 9; there is no clear explanation for this effect.
Increasing zinc concentration in leachate as a function of L/S reflects the concurrent
decrease in pH and increased zinc solubility with decreasing pH (Figure 4-27). Other
constituents that exhibit similar behavior include aluminum, cadmium, calcium, chloride,
chromium, copper, iron, potassium, magnesium, manganese, sodium, nickel, lead,
phosphorus, sulfur, and sulfate. In many cases, comparisons for many constituents cannot
be made since data from the batch extractions of the core samples did not include analytical
results for arsenic, mercury and selenium while leachate sample results did not include
analytical results for barium, bromide, cobalt, lithium, molybdenum, antimony, selenium,
silicon, tin, strontium, or vanadium.
Field leachate and core extract concentrations are consistent with pH dependent laboratory
testing for chromium (apparently present predominantly as Cr(VI)) but were greater than
pH dependent laboratory testing for lead and zinc because of DOC complexation at lower
L/S but diluted at higher L/S (i.e., L/S of 10 mL/gusedinpH dependent testing).
The L/S of 2 L/kg used in the batch extractions provides an accurate estimate, within
approximately 2x uncertainty, of peak initial leachate concentrations of highly soluble
species such as sodium, potassium and chloride (Figure 4-28). This observation is
consistent with the earlier explanation (see Sections 2.1.2 and 2.3.1) that concentrations of
highly soluble constituents can be substantially greater than measured at L/S of 10 L/kg as
used in the pH-dependent leaching tests. Higher concentrations of highly soluble
constituents (i.e., concentrations consistent with approximate porewater L/S of 0.2-0.5
L/kg) were most likely not observed because of material heterogeneity and preferential
flow The leachate concentrations for highly soluble constituents also follow the expected
elution curve as a function of L/S as typified by the comparison materials (e.g., high initial
concentrations that decrease by more than one order of magnitude prior to L/S of 2 L/kg.
4.5.5 Case Summary
Case 5 focused on landfill leaching from combined MSWI bottom ash and MSWI fly ash that was
deposited in layers and monitored for 30 years. Field leaching results were compared to
laboratory leaching of core samples obtained from the landfill and laboratory pH dependent test
98
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and percolation column test results from analogous materials. The resulting applicable pH
domain based on laboratory testing and field leachate samples is approximately pH 7 to 11.
Results of this case illustrate that concentrations obtained from laboratory batch extractions at
L/S of 2 mL/g can be used as an estimate of peak concentrations in leachate from a
heterogeneous fill material. The L/S of 2 L/kg is greater than the expected porewater L/S of ca.
0.2 to 0.5 L/kg but reflects the impacts of preferential flow through a heterogeneous material in
a landfill. Testing at L/S of 2 mL/g in conjunction with pH dependent testing (at L/S of 10
mL/g) provides an estimate of increased concentrations relative to pH dependent testing that
would be expected for highly soluble constituents and resulting from DOC complexation effects
at the low L/S values associated with early leachate from landfills.
99
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12
14
1
2
0.
1
o
ra
* n m -
0.
I
_n
0.
*
0 ฐฐl
31 0
0
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31 0
" 0ฐ0 0^
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31 0
's.
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L/S (L/kg)
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1
L/S (L/kg)
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L/S (L/kg)
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O Landfill Leachate (DK)
-- MSWI BA (AT)
--- MSWI BA(IT)
A MSWI BA (UK)
ป Landfill Cores (DK)
--MSWI BA(DE)
4- -MSWI BA(NL)
Figure 4-27. Chromium, lead and zinc concentration results from testing of cored materials
from the Vestskoven MSWI monofill (grey diamonds) compared to leachate samples (red
circles). Data are shown for pH-dependent leaching (left) and percolation column testing
(right). These results illustrate typical relationships between pH-dependent and column
testing of cored samples and leachate measurements.
100
-------
100000
O Landfill Leachate (DK)
-- MSWI BA (AT)
-- MSWI BA(IT)
A MSWI BA (UK)
Landfill Cores (DK)
-MSWI BA(DE)
ซ--MSWI BA(NL)
0.1 1
L/S (L/kg)
10
Figure 4-28. Sodium, potassium and chloride concentration results from testing of cored
materials from the Vestskoven MSWI monofill (grey diamonds) compared to leachate samples
(red circles). Data are shown for pH-dependent leaching (left) and percolation column testing
(right). These results illustrate leaching behavior of highly soluble species.
101
-------
4.6 Municipal Solid Waste Incinerator Bottom Ash Used in Roadbase (Sweden)
4.6.1 Case Description
MSWI bottom ash has been evaluated extensively and demonstrated to have consistent, systematic
leaching of individual constituents as a function of pH (IAWG, 1997; Sabbas et al., 2003; Dijkstra et
al., 2006a; 2006b). The extensive use of MSWI in Europe has provided considerable focus on the
potential for beneficial use of bottom ash, which is the heterogeneous material that is discharged
from the incinerator grate and is the largest residue stream from MSWIs (the other large residue
stream being air pollution control residues). Thus, the evaluation case described here is the result
of evaluation of the use of MSWI bottom ash as a roadbase material in Sweden, referred to as
Vandora (Bendz et al., 2009).
The test road was constructed in 1987 in Linkoping, Sweden (Lundgren and Hartlen, 1991) and was
15 years old at the time when the samples were taken (Bendz etal., 2009). Other studies were
performed on this road in 1998 (Andersson et al., 1999) and in 2002 (Flyhammar and Bendz,
2006). In two of the test sections, MSWI bottom ash was used as a subbase below an unbound base
course and surface asphalt layers. The bottom ash was poorly separated and contained large pieces
of incineration residues (e.g., larger than a few decimeters). The test road has been in a rather bad
condition during periods of time in its lifetime, with longitudinal cracks along the centerline of the
road. Therefore, infiltration through the pavement is likely to have taken place.
This field study, Vandora Q4-241, was carried out in September 2003 (Bendz et al., 2006). The
unbound base course and asphalt layers were removed and three sample collection trenches were
excavated into the road construction in different sections. In this report, results are discussed from
the characterization of the subbase layer (bottom ash) as presented in Lundgren and Hartlen
(1991) while the complete set of field data is presented in Bendz etal. (2006).
Fifty-three solid samples of approximately 250 mL each were collected from the subbase layer in a
checker board pattern. One-step batch tests in deionized water at L/S 10 L/kg were conducted on
all 53 samples according to the standard EN 12457-2. The minimum pH-value of the samples in
deionized water at L/S 10 L/kg was 7.4 and the maximum pH value was 10.0 (Figure 4-29).
The collected samples were formed into four groups based on the range of pH values measured in
single batch extractions. These four groups were 7.4-8.0 (n=16), 8.0-8.5 (n=21), 8.5-9.0 (n=12), and
9.0-10.0 (n=4). Samples within each group were mixed together to form composite samples for pH-
dependent leaching and percolation column leaching (material codes Vandora 1, 2, 3 and 4,
respectively). Samples in the pH range 7.4 to 8.5 are indicative of a significant amount of natural
carbonation during the road use. Leaching tests as a function of pH were carried out at L/S 10 L/kg
on the four grouped samples according to technical specification CEN/TS 14997. For Vandora
composites from the first three pH intervals, extraction pH values of 2, 4, 5, 6, 7, 8,10,11 and 12
were tested. For the composite from the fourth pH interval, due to the smaller sample size,
extraction pH values of pH 2, 4, 6, 8,10 and 12 only were measured. Percolation tests were
conducted on the grouped samples Vandora 1, 2 and 3 according to technical specification CEN/TS
14405. The sample amount for Vandora 4 did not allow for a percolation test. Sampling for Vandora
1 and 2 was at L/S 0.1, 0.5,1.0 and 2.0 L/kg (cumulative), and for Vandora 3 at L/S 0.2,1.0 and 2.0
L/kg (cumulative).
102
-------
100 200
300 dOO
aoo 1000
Figure 4-29. Spatial distribution of pH (EN 12457-2) in a section of subbase layer of MSWI bottom
ash. The sampling points are marked as black dots (n=53) while the x- and y-axes are scaled in
centimeters (Bendz et al., 2009).
Leaching data were not available for the MSWI bottom ash that was originally used in the Vandora
project. Therefore, a selection of pH-dependent leaching and percolation column test results from
testing of MSWI bottom ash from Germany (Berger et al., 2005) and the Netherlands (van der Sloot
et al., 2008c) are used as reference materials for this case.
4.6.2 Results and Discussion
A complete set of figures illustrating results from the single extraction batch tests (deionized water
at L/S of 10 L/kg), pH-dependent leaching tests and column tests for the comparison materials is
provided in Appendix D.
Measured pH values from laboratory testing of reference bottom ash materials from Germany and
The Netherlands are compared to pH measured in core samples from the Vandora Roadbase in
Figure 4-30. The lower field material pH shows the effect of carbonation in the field with pH values
between 8 and 8.5, approximately equal to the saturation pH for calcium carbonate.
0.01
0.1 1
L/S (L/kg)
+ Vandora - Core Composite 1 (Sweden)
A Vandora - Core Composite 2 (Sweden)
Vandora - Core Composite 3 (Sweden)
Vandora - Core Composite 4 (Sweden)
O Vandora - Individual Cores (L/S 10)
-A--MSWI Bottom Ash (The Netherlands)
- MSWI Bottom Ash 2 (The Netherlands)
O MSWI Bottom Ash (Germany)
-- MSWI Bottom Ash (Austria)
- -A - MSWI Bottom Ash (UK)
Figure 4-30. Measured pH in reference bottom ash and core samples from Vandora roadbase.
103
-------
For the comparison of leaching test eluates to field leachates, measured concentrations are
displayed as functions of pH (left) and L/S (right). Single batch extraction test results (n=53, black
circles) are plotted along with pH-dependent leaching test results for the four composite samples
from the road subbase (red data sets) and the three reference materials (blue data sets); a sample
key is provided Figure 4-30. In general, LSP was consistent between the single point extraction
tests and the pH-dependent tests for the individual subbase samples, the composite subbase
samples and the reference MSWI samples (Figure 4-31).
As expected, the individual subbase samples exhibit greater variability in pH and extract
concentration because of differences in the extent of air exposure (i.e., carbonation, oxidation) and
for more soluble species (i.e., chloride, potassium) different amounts of water contact because of
preferential flow paths.
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0.0001
0.01
0.1 1
L/S (L/kg)
ป Vandora - Core Composite 1 (Sweden)
-AVandora - Core Composite 2 (Sweden)
-Vandora - Core Composite 3 (Sweden)
-Vandora - Core Composite 4 (Sweden)
O Vandora - Individual Cores (L/S 10)
-A- - MSWI Bottom Ash (The Netherlands)
- - MSWI Bottom Ash 2 (The Netherlands)
- MSWI Bottom Ash (Germany)
MSWI Bottom Ash (Austria)
A MSWI Bottom Ash (UK)
Figure 4-31. Cadmium and nickel results from pH-dependent leaching tests (left) and column leaching
tests (right), illustrating consistency of results between field road subbase samples (16-year-old MSWI
bottom ash) and for MSWI bottom ash reference samples.
104
-------
The following are notable relationships between leaching test results for specific constituents:
The effect of low liquid to solid ratio resulting in higher concentrations in initial column
eluates as compared to pH-dependent leaching at L/S of 10 L/kg for highly soluble species is
apparent for chloride and sodium (Figure 4-32). When estimating percolation
concentrations at low L/S from batch extractions (typically at L/S of 10 L/kg), the upper
bound for the expected concentration can be calculated by the ratio of the batch L/S to the
initial column L/S or pore water L/S, whichever is greater. Thus, for a batch L/S of 10 L/kg
and an initial column L/S of 0.5 L/kg, the initial column eluate concentration would be
expected to be up to 20 times greater than the batch concentration (L/S 10 L/kg divided by
L/S 0.5 L/kg). In many cases, this theoretical upper bound is not realized because of either
preferential flow or the aqueous phase becoming saturated with respect to the constituent
of interest.
^ 10000 -
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* Vandora - Core Composite 1 (Sweden) A- -MSWI Bottom Ash (The Netherlands)
6 Vandora -Core Composite 2 (Sweden) -MSWI Bottom Ash 2 (The Netherlands)
Vandora - Core Composite 3 (Sweden) -MSWI Bottom Ash (Germany)
Vandora - Core Composite 4 (Sweden) ~ -- MSWI Bottom Ash (Austria)
O Vandora - Individual Cores (L/S 10) A MSWI Bottom Ash (UK)
^^Sr^
>J\
A^
1 1
Figure 4-32. Results from pH-dependent leaching test (left) and column leaching tests (right;
chloride and sodium), illustrating higher initial eluate concentrations for highly soluble species
from column tests (i.e., L/S < 0.2 L/kg) compared to pH-dependent leaching tests
105
-------
The effect of washout and depletion of highly soluble species during column testing or
percolation compared with solubility controlled leaching during column testing is evident
when comparing column test results for potassium and manganese (Figure 4-33).
10000 -r
0.00001
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ป Vandora - Core Composite 1 (Sweden)
-AVandora - Core Composite 2 (Sweden)
-Vandora - Core Composite 3 (Sweden)
-Vandora - Core Composite 4 (Sweden)
O Vandora - Individual Cores (L/S 10)
A--MSWI Bottom Ash (The Netherlands)
-MSWI Bottom Ash 2 (The Netherlands)
O MSWI Bottom Ash (Germany)
-- MSWI Bottom Ash (Austria)
A MSWI Bottom Ash (UK)
Figure 4-33. Potassium and manganese results from pH-dependent leaching test (left) and
column leaching tests (right) illustrating typical results for highly soluble species (potassium)
compared to solubility controlled species (manganese).
As indicated earlier, potassium is a highly soluble species with initial column eluate
concentrations significantly higher than measured from the batch pH-dependence test at
L/S of 10 L/kg, and with eluate concentrations from the pH-dependence test essentially
constant as a function of pH. As the column test progresses, potassium eluate concentration
decreases rapidly with increasing cumulative L/S, decreasing by more than an order of
magnitude by cumulative L/S of 2 L/kg. In contrast, the pH-dependent leaching test results
indicate highly pH-dependent solubility for manganese between pH 5 and 13 with
consistent results for the subbase composite samples (red symbols and lines) and reference
materials (blue symbols and lines). However, column test results for manganese indicate
106
-------
much higher concentrations for the subbase samples, consistent with manganese solubility
at pH~8 compared with the concentrations for the reference samples where the column
eluate concentrations are consistent with manganese solubility atpH 10-12.5. For
manganese, changes in column eluate concentrations as a function of L/S are consistent
with manganese LSP with the changes in eluate pH, rather than the rapid decrease in
concentration noted for potassium.
The effect of carbonation of field samples is evident in pH-dependent leaching of barium
(not shown), calcium and strontium at pH greater than 7 by comparison of reference
samples to the field subbase composites (Figure 4-34).
10000
O 1000
1000
100
ซ^>
I
'^
K
0.1 1
L/S (L/kg)
ป Vandora -Core Composite 1 (Sweden) A--MSWI Bottom Ash (The Netherlands)
-AVandora -Core Composite 2 (Sweden) -MSWI Bottom Ash 2 (The Netherlands)
-Vandora -Core Composite 3 (Sweden) O MSWI Bottom Ash (Germany)
-Vandora - Core Composite 4 (Sweden) --- MSWI Bottom Ash (Austria)
O Vandora - Individual Cores (L/S 10) A MSWI Bottom Ash (UK)
Figure 4-34. Calcium and strontium results from pH-dependent leaching test (left) and
column leaching tests (right) illustrating the effects of carbonation to reduce solubility at
alkaline pH.
The effect of pH-dependent solubility on percolation results is evident for aluminum,
magnesium, lead (Figure 4-35), and boron, manganese and zinc (not shown). Higher
concentrations of lead at neutral pH than observed during pH dependent testing is likely the
107
-------
result of complexation with DOC that was present in some individual samples and masked
in the composites used for pH dependent testing (see Figure 4-36).
0.1 1
L/S (L/kg)
10
ป Vandora -Core Composite 1 (Sweden) A--MSWI Bottom Ash (The Netherlands)
-AVandora -Core Composite 2 (Sweden) -MSWI Bottom Ash 2 (The Netherlands)
-Vandora -Core Composite 3 (Sweden) O MSWI Bottom Ash (Germany)
-Vandora - Core Composite 4 (Sweden) p. MSWI Bottom Ash (Austria)
O Vandora - Individual Cores (L/S 10) A MSWI Bottom Ash (UK)
Figure 4-35. Aluminum, magnesium and lead results from pH-dependent leaching test (left)
and column leaching tests (right) illustrating the effects of pH-dependent solubility on the
eluate concentrations from column tests (also refer to Figure 4-30 for pH of column test
eluates).
108
-------
For aluminum, all of the column eluates for the reference materials are greater than for the
subbase composites because the pH-dependent leaching indicates the same leaching as a
function of pH, but the column eluates for the reference materials are between pH 10 and
12.5, where aluminum solubility is much greater than at the subbase column eluates
between pH 8 and 8.5. A less pronounced but similar effect is observed for lead when
comparing the single reference material that had column eluate with pH 12.5 (blue squares)
in contrast to the other materials. The effect is less pronounced for lead than aluminum
because of the column eluate pH values in comparison with the minimum in LSP that occurs
at pH 8 to 10 for lead but at pH 6 to 8 for aluminum. Conversely, for magnesium, the column
eluate concentrations for subbase composites are much greater than for the reference
materials because magnesium solubility is much greater atpH 8-8.5 than atpH 10-12.5.
-J 10
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ป Vandora -Core Composite 1 (Sweden) A- -MSWI Bottom Ash (The Netf
A Vandora -Core Composite 2 (Sweden) -MSWI Bottom Ash 2 (The Ne
Vandora - Core Composite 3 (Sweden) - MSWI Bottom Ash (Germany
Vandora - Core Composite 4 (Sweden) p. MSWI Bottom Ash (Austria
O Vandora - Individual Cores (L/S 10) A MSWI Bottom Ash (UK)
lerlands)
therlands)
1)
Figure 4-36. Copper and DOC results from pH-dependent leaching test (left) and column
leaching tests (right) illustrating the effects of pH-dependent solubility on the eluate
concentrations from column tests.
109
-------
The effect of complexation leading to increased aqueous solubility is evident for copper
leaching from the reference materials during the column tests when viewed in context with
the DOC concentrations in column eluates (Figure 4-36).
Copper has been previously demonstrated to complex strongly with DOC from bottom ash
(van Zomeren and Comans, 2004). Higher concentrations of copper are associated with
higher DOC concentrations during column tests, with higher concentrations at low L/S
decreasing with increasing cumulative L/S.
The single batch extractions for the individual subbase samples have anomalous results
reported for arsenic, when compared to the composite samples, in that the individual
samples indicate higher arsenic concentrations at the measured pH, however increased
levels of carbonation can result in displacement of arsenic adsorbed to HFO.
4.6.3 MSWI BA Chemical Spec/at/on Insights
Figure 4-37 presents data for pH dependence leaching of copper from MSWI BA (from The
Netherlands) from a series of experiments (van der Sloot et al., 2001, van der Sloot et al., 2008).
The uppermost red data series results from testing fresh MSWI BA, the lowest blue data series
results after heat treating the same MSWI BAto 500 ฐC to remove organic carbon, and the middle
green data series results after 1 wt% organic compost is added to the heat treated MSWI BA to add
organic matter back into the material. Clearly, removal or addition of organic matter alters the
concentration of copper in solution based on complexation with DOC.
01
a.
ง
u
0.01 -
1
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2 1
3 1
-MSWI Bottom Ash (fresh)
-MSWI Bottom Ash (reheated to 500 C)
-MSWI Bottom Ash (reheated to 500 C + 1% compost)
Figure 4-37. pH-dependence leaching (CEN/TS 14429) data for MSWI bottom ash (Netherlands) as
"fresh" material (red), MSWI BA after heat treatment at 500 ฐC (blue), and heat-treated MSWI BA with
1% compost added (green).
Figure 4-38 presents the experimental results of the same set of experiments along with results of
using largely the same CSF for all three conditions, but varying the amount of organic matter in the
system to correspond with experimental measurements of TOC and DOC for each experimental
condition. Partitioning between POM and DOC plays a significant role in LSP between pH 7 to 13,
110
-------
with increasing amounts of DOC responsible for increased Cu in solution. At a pH between 6 and
9.5, adsorption onto HFO surfaces represents a significant amount of Cu in the solid phase, while
tenorite [CuO] or Cu(OH)2 is present as a precipitated phased at pH greater than 7. Note that
availability controls the observed Cu in solution at pH less than 6 based on simulation results, but
experimental results indicate that the maximum available amount of Cu partitions into solution only
at pH 3. This difference between simulation and experimental results suggests that either Cu
dissolution is kinetically controlled during the test conditions, i.e., long enough leaching time is not
provide to achieve equilibrium at low pH (Dijkstra et al., 2006) or a solid phase that is important
between pH 3 and 6 has not been included in the simulation.
Ill
-------
l.E-02
MSWI Bottom Ash (the Netherlands)
MSWI BA Partitioning of Cu
l.E-06
l.E-07 -p
l.E-08
pH-dependence
[Cu+2] L/S=10
A Percolation Column
-4-
I ' I ' I ' I ' I ' I
1234567
9 10 11 12 13 14
PH
Reheated MSWI BA
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Reheated MSWI BA Partitioning of Cu
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Reheated MSWI BA + Compost
10 11 12 13 14
Reheated BA + Compost Partitioning of Cu
o
u
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Figure 4-38. Chemical speciation modeling for MSWI bottom ash (Netherlands) as "fresh" material
(upper), MSWI BA after heat treatment at 500 ฐC (middle), and heat-treated MSWI BA with 1%
compost added (lower).
Figure 4-39 presents laboratory test data and simulations for pH dependent leaching of Cu from
MSWI BA from Austria (van der Sloot et al., 2000). For this figure, the uppermost compares
simulation of L/S=0.3 L/kg with experimental data obtained at L/S=10 mL/g, while the middle
series provides simulation results at L/S=10 mL/g. This comparison indicates that increased Cu
concentrations can be anticipated at lower L/S values because the same amount of Cu is available
112
-------
for leaching but increased DOC in solution at low L/S values results in increased Cu solubilization
between pH 7 and 10, while the same mass of Cu in solution at low pH values results in increased Cu
concentrations that are constrained by Cu availability. The bottommost two graphs present the
fraction of dissolved Cu complexed with DOC (left graph) and the percent distribution between
different solid phases as a function of pH (right graph). Dissolved Cu is predominantly complexed
with DOC between pH 7.5 and 11.5, while uncomplexed Cu ("Free") is present in solution outside of
this pH range. Precipitated Cu(OH)2 predominates between pH 8.5 and 13.5, while sorption to iron
(hydr)oxide surfaces is important between pH 5.5 and 8.5.
Figure 4-40 through Figure 4-42 provide analogous information for Al, V and Zn, respectively, and
provide similar insights into expected changes in observed LSP at L/S=0.3 vs. 10 mL/g and
speciation in the solid and aqueous phases as a function of pH and L/S. Note that between pH 7 and
11, a significant amount of the Zn is present in solution as complexed with DOC (Figure 4-42, bright
green area). Thus, increased amounts of DOC results in increased Zn concentrations in solution
over this pH domain. Similar effects are observed for lead (not shown) and these effects are
consistent with the field leachate concentrations observed in this case and the prior case (i.e.,
Figure 4-27 and Figure 4-35)
113
-------
o
u
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
MSWI Bottom Ash (Austria) at L/S=0.3
*ซ
I
\
\
pH-dependence
[ A Percolation Column
[Cu+2] L/S=0.3
\
\
n
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A
A
t
1
1
1
1
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
MSWI Bottom Ash (Austria) at L/S=10
l.E-07
l.E-08
pH-dependence
- [Cu+2] L/S=10
A Percolation Column
I I I ' I ' I ' I I I
100%
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Liquid Phase Partitioning of Cu at L/S=10
l.E-02 -i
l.E-03
Partitioning of Cu at L/S=0.3
o
u
l.E-08
l.E-02
2 3
Partitioning of Cu at L/S=10
1 2 3 4 5 6 7 8 9 10 11 12 13 14
l.E-08
Solid Phase Partitioning of Cu at L/S=10
100%
Si
ID
80% -
60% -
s.
a.
o
u
40%
20%
9 10 11 12 13 14
Figure 4-39. Chemical speciation modeling of copper in MSWI bottom ash (Austria) compared to pH-
dependence (CEN/TS 14429) and percolation column (CEN/TS 14405) data.
114
-------
MSWI Bottom Ash (Austria) at L/S=0.3
_3
l.E-01
l.E-02
l.E-03
l.E-04
l.E-05 -
l.E-06
l.E-07
1 F-flR .
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A Percolation Column
[AI+3] L/S=0.3
i ill i i
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234567
9 10 11 12 13 14
pH
MSWI Bottom Ash (Austria) at L/S=10
l.E+00
l.E-01
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l.E-06
l.E-07
l.E-08
1
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; [AI+3]L/S = 10
A Percolation Column
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10 11 12 13 14
pH
l.E+00
l.E-01
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
Partitioning of Al at L/S=0.3
D Free D DOC-bound
ROM-bound OEttringite
DAA_3CaO_AI203_6H20 [s] DAA_AI[OH]3[am]
Wairakite
I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I
1234567
9 10 11 12 13 14
pH
l.E+00
l.E-01
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
Partitioning of Al at L/S=10
D Free D DOC-bound
ROM-bound DEttringite
n3CaO_AI203_6H20[s] DAI(OH)3 [am]
DWairakite
I ' I ' I ' I ' I
I ' I ' I ' I
9 10 11 12 13 14
PH
Figure 4-40. Chemical speciation modeling of aluminum from MSWI bottom ash (Austria) at L/S=10
and L/S=0.3.
115
-------
0
E
,3
5
ID
1
_J
"5
E
.3
ID
>
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
MSWI Bottom Ash (Austria) at L/S=0.3
N
\
>*.
^
\
^
1 1 1 1 1
xซ
X
I i I i
pH-dependence
A Percolation Column
[V02+] L/S=0.3
0 0
l\
^'
1 1 1 1 1 1 1
0
\
V,
! i !
V
ป
/
t
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I
1
1
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1 1 1 1 1 1
1234567
9 10 11 12 13 14
PH
MSWI Bottom Ash (Austria) at L/S=10
i
^
^\
1
V
\
\
\/
/
t
pH-depen
[V02+] L
A Percolatio
dene
'S-1
n Cc
e
0
lumn
^
y
/
"\
o
\
V
/
4
A
/
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9 10 11 12 13 14
PH
l.E-03
Partitioning of V at L/S=0.3
9 10 11 12 13 14
l.E-03
l.E-04
Partitioning of V at L/S=10
DFree DDOC-bound
POM-bound FeOxide
Ettringite DPb2V207
9 10 11 12 13 14
Figure 4-41. Chemical speciation modeling of vanadium from MSWI bottom ash (Austria) at L/S=10
and L/S=0.3.
116
-------
MSWI Bottom Ash (Austria) at L/S=0.3
o
^>
u
c
N
l.E-02
1 F-04 -
1 F-flR -
1 F-flfi -
l.E-07
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l.E-09
f
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r
r
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pH-dependence
A Percolation Column
[Zn+2] L/S=0.3
.
\
A
.X"
/
/>
A
AX
^
/
/
2 3 4 5 6 7 8 9 10 11 12 13 1
Partitioning of Zn at L/S=0.3
PH
MSWI Bottom Ash (Austria) at L/S=10
123
10 11 12 13 14
o
^>
u
c
N
l.E-02
l.E-05 -
l.E-06 -
1 E-07
l.E-08
l.E-09
1 . E- 1 0
r
r
r
i
\
s
\
\
pH-dependence
[Zn+2] L/S=10
A Percolation Column
0
y
A
f
1
Partitioning of Zn at L/S=10
o
^>
u
c
N
123456
7 8 9 10 11 12 13 14
PH
2 3
10 11 12 13 14
Figure 4-42. Chemical speciation modeling of zinc from MSWI bottom ash (Austria) at L/S=10 and
L/S=0.3.
Figure 4-43 and Figure 4-44 present pH dependent leaching data obtained at L/S=10 mg/L and
percolation column data obtained from 0.3 to 10 mg/L for a group of selected COPCs. Simulation
results are used to illustrate the effect of L/S on expected leaching. For example, sulfate is solubility
controlled throughout the pH domain, as indicated by the overlap of simulation curves over the
range of simulated L/S values. In contrast, K is availability controlled over the entire pH domain, as
indicated by parallel simulation results at increased concentration with decreased L/S
corresponding to the same mass of K partitioning into solution. Finally, Ca, Mg, and Mn are
solubility controlled atpH greater than 12.5, 9.5 and 8.5 respectively, while they are availability
controlled at lower pH values. When percolation column results align with pH dependence test
results and simulated LSP, solubility control during percolation column leaching is indicated (e.g.,
for Ca, Mg, sulfate, Mn, Cu, Mo, Pb, Sb and Zn). However, percolation column results for K (a highly
soluble species) indicates washout and depletion by the initial eluate concentration that
corresponds with simulation results at L/S=1 (which is consistent with a loose packing for a course
material such as bottom ash) and subsequent rapidly decreasing concentrations (also
corresponding with decreasing eluate pH).
117
-------
MSWI Bottom Ash (Austria)
MSWI Bottom Ash (Austria)
1 2
l.E+00
MSWI Bottom Ash (Austria)
e
l.E-02
l.E-0
2 3 4 5 6 7 8 9 10 11 12 13 14
PH
MSWI Bottom Ash (Austria)
ID
Ol
C
ID
23
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ID
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v
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1
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ir
^
1 2 3 4 5 6 7 8 9 10 11 12 13 1
PH
MSWI Bottom Ash (Austria)
l.E-01 -
S-^
^ l.E-02
O
V l-E-03
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w
l.E-05
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1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
pH-dependence
Model at L/S=10
A Percolation Column
Model at L/S=1
Model at L/S=0.5 Model at L/S=0.3
Figure 4-43. Chemical speciation modeling at different L/S compared to pH-dependence (CEN/TS
14429) and percolation column (CEN/TS 14405) data for MSWI bottom ash (Austria).
118
-------
MSWI Bottom Ash (Austria)
MSWI Bottom Ash (Austria)
l.E-02
^ l.E-03 -
O
^^ 1 F-fl4 -
01
a.
0 1.E05
b.
r
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i
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tr
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
pH pH
MSWI Bottom Ash (Austria) MSWI Bottom Ash (Austria)
l.E-03 -
5 l.E-04 -
O
E l.E-05
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l.E-08
i
ir.n.Tiir
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i
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l'
^
1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
pH pH
MSWI Bottom Ash (Austria)
1 E 01 j
l.E-02
_j 1 E-03
"o
u
N
1 F-na .
f
- x \
xv.
V A v
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0
^v
rS~
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7
A
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f
f
i
f
pH-depen
Model at L
dence
./S=10
_/S=0.5
A Pe
Mo
rcolation Column
del at L/S=1
del at L/S=0.3
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Figure 4-44. Chemical speciation modeling at different L/S compared to pH-dependence (CEN/TS
14429) and percolation column (CEN/TS 14405) data for MSWI bottom ash (Austria).
4.6.4 Case Summary/
Case 6 focused on MSWI bottom ash used as a subbase below an unbound base course and surface
asphalt layers that was cored and evaluated 15 years after the road construction. The resulting
applicable pH domain was approximately pH 7 to 10. Single point leaching of an extensive set of
samples (n= 53) illustrates the heterogeneity of material and exposure under field conditions.
119
-------
Laboratory testing of composite samples from field cores using pH dependent leaching and
percolation column tests showed LSP and column elution consistent with descriptions for other
materials with respect to both highly soluble constituents (e.g., Na, K, Cl) and constituents where
solubility limits LSP as a function of pH (e.g., Ca, Cu, Pb, Zn). A general CSF for MSWI bottom ash has
been shown to provide a good description of release behavior of multiple major, minor and trace
elements from MSWI bottom ash from several sources and indicates likely solubility controlling
phases. Combined leaching test results and chemical speciation modeling illustrated (i) the effects
of DOC complexation to increase aqueous concentrations of copper, lead and zinc, and (ii) the effects
of L/S on the expected concentrations of highly soluble and solubility limited constituents as a
function of pH, with lower L/S conditions resulting in increased aqueous concentrations when the
constituent solubility is not limiting leaching.
4.7 Inorganic Industrial Waste Landfill (The Netherlands)
4.7.1 Case Description
In the framework of a Dutch national research project on sustainable landfills, a landfill site in
Nauernasche Polder, Nauerna, The Netherlands was the subject of a pilot scale demonstration
project and lysimeters studies (van der Sloot et al., 2003; van Zomeren and van der Sloot, 2006b).
In addition to the lysimeter and pilot landfill, laboratory experiments on landfill materials were
conducted using the CEN/TS 14405 (2004) percolation column test and the CEN/TS 14429 (2005)
pH-dependence test.
The filling of a 12,000 m3 pilot-scale landfill started in April 2000 and was completed in November
2001 (Figure 4-45). The pilot cell was isolated from the rest of the landfill site by a high-density
polyethylene membrane. Leachate was collected in the lower corner of the test cell and the amount
of leachate pumped out of the test cell was measured. A vertical drain (filled with coarse granular
material) was installed in the center of the pilot cell to enhance the drainage of rainwater and to
minimize the contact of rainwater with the waste material.
Figure 4-45. Construction of the Nauerna pilot-scale landfill (van Zomeren and van der Sloot, 2006b).
120
-------
The material placed into the pilot cell was subject to more stringent acceptance criteria than
currently required by waste regulation. The disposed material, characterized as "primarily
inorganic waste" because it did not contain any municipal solid waste, included wastes from drilling
mud (2.8 wt %), wastewater treatment sludge (0.1 wt %), foundry waste (0.5 wt %), blasting waste
(1.7 wt %), residues from mechanical soil cleaning (10.2 wt%), contaminated soils, gravel and
construction debris (7.2 wt%), mineral production waste (55.4 wt%), filter cake from waste
processing (8.2 wt%), sludge from soil cleaning (11.4 wt%), waste from street cleaning (0.4 wt%)
and miscellaneous materials (2.1 wt%) as reported in van der Sloot et al. (2003).
Samples were taken from all waste streams deposited in the cell and the landfilled weight of each
stream was recorded. From all waste samples collected, a representative waste mixture was
prepared by proportionately taking the waste sample mass per waste mass placed into the landfill
into account. The resulting inorganic waste composite was used for the laboratory testing of pH-
dependent leaching (CEN/TS 14429) and percolation column testing (CEN/TS 14405). In October
2001, representative waste samples were also used to fill three 1.5 m3 lysimeters with a
representative waste mixture (Figure 4-46).
Figure 4-46. Nauerna landfill lysimeters.
The lysimeters were plastic containers of approximately 1 m height, open at the top surface to the
atmosphere in order to receive natural precipitation. Leachates from the lysimeters were collected
through a system of tubes and subsurface collection vessels. The lysimeters were located adjacent
to the pilot landfill. The lysimeters were filled with test material as follows:
Lysimeter 1 - disposal of wastes in order of delivery as practiced at Nauerna;
121
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Lysimeter 2 - encapsulation of more contaminated wastes in relatively low permeability
wastes (soil cleaning residues); and,
Lysimeter 3 - disposal of wastes in order of delivery as practiced at Nauerna with addition of
5 wt% each of sewage sludge and car shredder waste to increase organic matter loading.
The material placed into Lysimeter 1 and 2 were not significantly different and, therefore, leachate
results are presented together for this evaluation. Lysimeter 3, however, contained a sufficiently
different waste composition due to addition of organic matter. Therefore, the results from
Lysimeter 3 are not considered for the purposes of this report. The studies at field, lysimeter and
laboratory scale represent different time scales through the L/S to which the waste was exposed.
4.7.2 Results and Discussion
A complete set of figures illustrating results from the laboratory pH-dependent leaching tests and
column tests of a sample of solid waste material (red solid dots) along with results from the
combined Lysimeter 1 and 2 (orange open squares) and the pilot-scale landfill (purple open
diamonds) is provided in Appendix E. Field lysimeter and pilot-scale landfill results are graphed
both as a function of pH with the laboratory pH-dependent leaching test results (left) and as a
function of L/S with the laboratory column test results (right).
An important distinction in redox within the material existed between the laboratory column tests,
field lysimeters and pilot-scale landfill. Laboratory column leaching tests exhibited an initial ORP of
-100 mV (pE -1.69) that increased to +250 mV (pE 4.23), presumably as a result of using oxygen-
saturated water as the column eluent. The leachates from the field lysimeters had an initial ORP of-
200 mV (pE -3.38) which increased to a stable value of approximately +200 mV (pE 3.38) after 1.5
years of testing. In contrast, the pilot-scale landfill maintained a relatively constant redox potential
of-200 mV (pE -3.38) throughout the observation period of approximately 4 years (vanZomeren et
al., 2005).
The following are notable relationships between leaching test and field results for specific
constituents:
There is a difference in the oxidation conditions for (i) the laboratory leaching tests and the
field lysimeters where leaching occurs under oxidizing conditions, and (ii) the pilot-scale
landfill where leaching occurs under reducing conditions. The difference in these
conditions is most easily seen for iron leaching concentrations due to the increased iron
solubility under reducing conditions (Figure 4-47, top). Unless a highly reducing material is
being tested, oxidizing conditions prevail for most laboratory tests as materials are handled
in open to laboratory atmosphere and the CEN/TS 14429 pH-dependent test uses mildly
oxidizing nitric acid for pH adjustment. In the case of field lysimeters, the construction of
the lysimeter most likely partially limited diffusion and barometric exchange of atmospheric
oxygen into the system under unsaturated conditions. Reducing conditions in the pilot-
scale landfill were most likely induced by microbial degradation of the limited amount of
organic matter introduced with the waste because no reducing waste types (i.e., pyrites,
slags) were included with the disposed materials. Furthermore, biogenic reducing
conditions are consistent with the observed increase in DOC landfill leachates compared to
122
-------
the DOC concentrations in laboratory column eluates and lysimeter leachate (Figure 4-47,
bottom).
1000
0.1
12
14
0.00001
0.001 0.1
L/S (L/kg)
10000
1000 -
1 -r
1000 -I
10
0 1
0.01 -
T nm -
Predominantly Inorganic Waste
: O Pilot Study Leachate
Lysimeter Leachate
: ฐ ^
!
D
<
<
O
nm T
>o<
1
1
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/>
1-
1 1
*
1
1
10
0.1
0.00001
-Predominantly Inorganic Waste
O Pilot Study Leachate
Lysimeter Leachate
"""1 !
0.001 0.1
L/S (L/kg)
10
Figure 4-47. Iron and dissolved organic carbon concentrations from Nauerna landfill study.
Increased concentrations of chromium in leachate from the pilot-scale landfill are most
likely the result of Cr(III) complexation with DOC (Figure 4-48, top); a similar effect is
indicated for copper. Increased concentrations of arsenic in leachate from the pilot-scale
landfill are most likely the result of loss of arsenic adsorption sites on hydrated iron oxide
surfaces because of reduction and solubilization of iron (Figure 4-48, bottom).
123
-------
10 -|
1 -
Chromium (mg/L]
I b P
j. l_i l_i
^
\
V
Predominantly norganic Waste
O Pilot Study Leachate
Lysimeter Leachate
f
^njjffi.
uUjj^P /
.*
f
/
2 4 6 8 10 12
PH
1 -
J1 0.1 -
01
1
5 o.ooi -
D
n
n
Predominantly Inorganic Waste
O Pilot Study Leachate
Lysimeter Leachate
^ <
DOD IXT
O
>ocJI
ฃ
im^
iF*
-
14 0.00001 0.001 0.1 10
L/S (L/kg)
Ol
0.01 -
0.001 -;
0.0001
-Predominantly Inorganic Waste
O Pilot Study Leachate
Lysimeter Leachate
Ol
0.01 -
0.001 -;
0.0001
-Predominantly Inorganic Waste
O Pilot Study Leachate
D Lysimeter Leachate
I
10
12
14
0.00001
PH
0.001 0.1
L/S (L/kg)
I
10
Figure 4-48. Chromium and arsenic concentrations from Nauerna landfill study.
In contrast, increased barium leachability in leachate from the pilot-scale landfill is most
likely linked to increased solubilization of phosphate (shown as phosphorus) under
reducing conditions (Figure 4-49). Vanadium also had higher concentrations in leachate
from the pilot scale landfill under reducing/carbonated conditions than observed from the
lysimeters and the laboratory column tests. For these constituents, the maximum
concentrations observed in the field pilot-scale landfill were significantly greater than
maximum concentrations indicated by the laboratory column testing. These differing effects
point to the need of a priori knowledge of the adsorption, solubilization and precipitation
chemistry of different elements to interpret leaching results and the benefits of using
chemical speciation modeling to facilitate interpretation.
124
-------
01
o.oi
01
^>
10
O
f
0.
to
O
f
Q.
10 -F
1 -:
0.01
-Predominantly Inorganic Waste
O Pilot Study Leachate
D Lysimeter Leachate
10
12
PH
14
0.1 -
0.01
o.oc
D
Predominantly Inorganic Waste
O Pilot Study Leachate
Lysimeter Leachate
<*>&
0 ซj|
o
10
O
f
0.
to
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f
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0.00001
0.001
0.1
L/S (L/kg)
10 -
i -
0.1 -
m .
Predominantly Inorganic Waste
O Pilot Study Leachate
D Lysimeter Leachate
_ * o<
a
.
D
o
o
DLThDna]
1
n
1 i 1 i
>*
ฐX
^
<. '*--
n
^
1 i
10
Figure 4-49. Barium and phosphorus concentrations from Nauerna landfill study.
Increased concentrations at low L/S indicated for chloride, magnesium, potassium, and
sodium (illustrated for chloride, magnesium and sodium in Figure 4-50) are observed for
leachates from the field lysimeters and the pilot-scale landfill, as well as the laboratory
column tests when compared to pH-dependent test results at L/S of 10 L/kg. Peak pilot
concentrations for chloride are consistent with laboratory column testing L/S of 0.5 mL/g
and a peak concentration 20 times that observed from pH dependent testing at L/S of 10
mL/g. For these constituents, the concentrations in eluates at low L/S from laboratory
column tests provide a reasonable indicator of the maximum field leachate concentrations.
125
-------
^ 1000 -
01
V 100 -
o
c
o
5 10 -
1 .
0
f
dB
ฐ
Predominantly Inorganic Waste
O Pilot Study Leachate
Lysimeter Leachate
10
12
PH
1000
O 100
01
IB
0.01
-Predominantly Inorganic Waste
O Pilot Study Leachate
Lysimeter Leachate
10
12
PH
10000
^> 1000 -;
01
100 -r
14
14
-Predominantly Inorganic Waste
O Pilot Study Leachate
D Lysimeter Leachate
10
12
14
10000
^> 1000 -;
Predominantly Inorganic Waste
O Pilot Study Leachate
Lysimeter Leachate
"+-
0.00001
0.001 0.1
L/S (L/kg)
1000 -F
01
01
(0
100 -T
10 -:
-Predominantly Inorganic Waste
O Pilot Study Leachate
Lysimeter Leachate
I
0.00001
0.001
0.1
L/S (L/kg)
10000
^> 1000 -;
Ol
100 -:
10 -
0.00001
10
D
nm
P-b \
D * \
n ^
10
Predominantly Inorganic Waste
O Pilot Study Leachate
Lysimeter Leachate
PH
0.001 0.1
L/S (L/kg)
Figure 4-50. Chloride, magnesium and sodium concentrations from Nauerna landfill study.
Field lysimeter and pilot-scale landfill leachate concentrations for cadmium and zinc are
indicated by initial solubility control followed by rapid washout of the fraction of the
constituent available for leaching (Figure 4-51). The initial concentrations are similar to the
laboratory pH-dependent leaching test results followed by a rapid decrease in concentration
with increasing L/S.
126
-------
edominantly Inorganic Waste
O Pilot Study Leachate
D Lysimeter Leachate
0.00001
0.001 0.1
L/S (L/kg)
Predominantly Inorganic Waste
O Pilot Study Leachate
Lysimeter Leachate
01
U
c
N
12
14
0.00001
0.001 0.1
L/S (L/kg)
100 -
10 -
1 -
0.1 -
0.01 -
0.001 -
nnm .
D
! S
1 i
O Pilot Study Leachate
Lysimeter Leachate
^ <
> *~
o
!
1 1
>^v
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1
10
Figure 4-51. Cadmium and zinc concentrations from Nauerna landfill study.
4.7.3 Chemical Speciation Insights - Predominantly Inorganic Industrial Waste
Figure 4-52 through Figure 4-54 compare chemical speciation modeling results for Cr, Cu and Pb,
respectively, with pH dependence and percolation column test results. In the left side of each figure,
the chemical speciation results are compared to pH-dependent and percolation column test data
(red circles and blue triangles, respectively) are compared to chemical speciation model results at
L/S 10 mL/g and L/S 0.3 mL/g. The right side panels in each figure show the associate partitioning
for controlling solid and aqueous phases. The phase partitioning panels for Cr (Figure 4-52)
indicate that adsorption onto solid carbon or POM (dark green area) and complexation in solution
with DOC (light green area) dominate the LSP atpH less than 10. This is consistent with the
laboratory and field results presented in Figure 4-48 AtpH greater than 10, amorphous chromium
hydroxide [Cr(OH)s(a)] is the prevalent solid phase. The effect of changing L/S from 10 to 0.3 mL/g
on the Cr model result is relatively minor compared to other species.
127
-------
Predominantly Inorganic Waste at L/S=10
l.E-05 -
l.E-06 -
l.E-07
1 F-flR -
1 F-flQ -
1 E-10 -
l.E-11
\
~
(
s,
^
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Low
M-
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1T
ctio
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n
^
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pH-dependence
[Cr04-2] L/S=10
A Percolation Column
1 2 3 4 5 6 7 8 9 10 11 12 13 1
PH
Partitioning of Cr at L/S=10
Predominantly Inorganic Waste at L/S=0.3
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
l.E-10
l.E-11
l.E-12
[
<
V
1
(
^,
\
._
-OW
M.-
L/S
i
*
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if
-'
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pH-dependence
[Cr04-2] L/S=0.3
A Percolation Column
1234567
9 10 11 12 13 14
PH
O
I
u
O
SMI*
E
3
E
u
123
Partitioning of Cr at L/S=0.3
9 10 11 12 13 14
Figure 4-52. Chemical speciation modeling of chromium from predominantly inorganic industrial
waste at L/S=10 and 0.3 mL/g compared to pH-dependence and percolation column data.
In an analogous manner to Cr, Cu LSP behavior (Figure 4-53) is driven by association with POM and
DOC; however, the role of DOC is significantly diminished at low L/S.
128
-------
Predominantly Inorganic Waste at L/S=10
5 l.E-04
"3
E l.E-05 -
SMI*
1_
a.
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i
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pH-dependence
-[Cu+2] L/S=10
Percolation Column
:tior
>
1
/
1
^s
,/
/
f-
1 2 3 4 5 6 7 8 9 10 11 12 13 1
PH
Predominantly Inorganic Waste at L/S=0.3
o
0.
a.
o
u
l.E-02 -
l.E-03
l.E-04 -
1 F-flR -
1 F-flQ -
!
N
[
^
<
^
)
1
1
)
^
nw
pH-dependence
[Cu+2] L/S=0.3
A Percolation Column
^ ^ _,-\
L/S Fraction ^
/
ฎ
s
/
/
E/
1234567
9 10 11 12 13 14
PH
l.E-02
^ l.E-03
^
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
Partitioning of Cu at L/S=10
o
01
a.
a.
DFree ODOC-bound
POM-bound BFeOxide
DCu(OH)2 [s]
123
10 11 12 13 14
Partitioning of Cu at L/S=0.3
1 2
10 11 12 13 14
Figure 4-53. Chemical speciation modeling of copper from predominantly inorganic industrial waste
at L/S=10 and 0.3 mL/g compared to pH-dependence and percolation column data.
Lead LSP (Figure 4-54) is dominated by formation of crystalline lead hydroxide [Pb(OH)2(c)] (light
yellow area) and hinsdalite [(Pb,Sr)Al3(P04)(S04)(OH)6] (pink area) at acidic and alkaline pH,
respectively. Additionally Pb LSP is affected by adsorption onto HFO surfaces (red area) and POM
which playing significant roles at 6 < pH < 11.
129
-------
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
Predominantly Inorganic Waste at L/S=10
pH-dependence
[Pb+2] L/S=10
A Percolation Column
I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I
2 3 4 5 6 7 8 9 10 11 12 13 14
f-^
J
1
o
SM'
o
s
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
Partitioning of Pb at L/S=10
DFree DDOC-bound BPOM-bound
FeOxide DHinsdalite[2] DPb[OH]2[c]
OPb2V207 DPbMo04[c]
123
Predominantly Inorganic Waste at L/S=0.3
l.E-03
l.E-04 -
l.E-05
1 F-flR -
1 F-flQ -
r
f
[
!
-.
<
\
>i
LI
r\
,v
_ov\
^
pH-dependence
[Pb+2] L/S=0.3
A Percolation Column
L/S Fra
1
^\
ctio
i
n
i
^
/
1
1
i
Partitioning of Pb at L/S=0.3
1234567
9 10 11 12 13 14
PH
123
10 11 12 13 14
Figure 4-54. Chemical speciation modeling of lead from predominantly inorganic industrial waste at
L/S=10 and 0.3 mL/g compared to pH-dependence and percolation column data.
The impact of redox condition on LSP is illustrated for Fe, Cu and total sulfur in Figure 4-55 through
Figure 4-57. In each figure, chemical speciation model results are presented for mildly oxidizing
(pH+pE=13), reducing (pH+pE=6) and strongly reducing (pH+pE=4) conditions. Comparison of
simulations with experimental results from the pH dependence test suggests that the material is
mildly reducing to slightly oxidized, most likely closer to pH+pE of 13 than 6 which is reasonable for
the laboratory conditions and test method; however, the effect of increasing the reducing condition
on the chemical speciation in this material is clear, as would occur to a limited extend during
percolation column testing and to a greater extent under field conditions (i.e., between pH+pE of 4
and 6). As conditions become more reducing, Fe solubility increases at neutral to slightly acid pH
with a corresponding loss of adsorptive surface area (see loss of ferrihydrite in Figure 4-55) while
metal precipitation with sulfides (e.g, pyrite [FeS2], blaublei [Cuo.6So.s], galena [PbS]) becomes
evident. Comparison of simulations with measurements for redox must be treated with a high
degree of uncertainty because of the errors that may be introduced during sampling collection and
measurement (these errors would bias experimental measurements towards more oxidizing
conditions through the unintentional introduction of atmospheric oxygen).
130
-------
Predominantly Inorganic Waste; pH+pe=13
Liquid-Solid Partitioning of Fe; pH+pH=13
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
;-oe
07
08
09
pH-dependence
[Fe+3] pH+pe=13
A Percolation Column
O Leachate (Pilot)
I ' I ' I
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Predominantly Inorganic Waste; pH+pe=6
E-01
E-02
E-03
E-04
E-05
E-06
E-07
E-08
E-09
E-10
1
p
[F
A P
1
4
t
H -dependence
e+3] pH+pe
;rcolation Col
v
V
-. VK>
2t
a
=b
imn
O Leachate (Pilot)
L 2 :
i <
1 i i i
t 5 6 /
J
V
N
i <
**
^^^
(
-X*
) /
S
1 i i i
} 10 11 12 1
/
/
3 1
O
123
9 10 11 12 13 14
Liquid-Solid Partitioning of Fe, pH+pe=6
PH
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
O
Predominantly Inorganic Waste; pH+pe=4
l.E-03 -
l.E-04 -
l.E-05 -
l.E-06 -
l.E-07 -
l.E-08
l.E-09
ซ
!
!
I
i
i
,
4
>
; pH-dependenc(
1 ^ [Fe+3] pH+pe
: A Percolation Col
! O Leachate (Pilot
.IkS
=4
umn
)
D
v
\
V
^^
_*
4
^^
iX
9s
'
123456
7 8
PH
9 10 11 12 13 14
O
Partitioning Fe, pH+pe=4
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Figure 4-55. Comparing effects of oxidizing and reducing conditions - chemical speciation modeling of
iron from predominantly inorganic industrial waste at L/S=10 mL/g compared to pH-dependent and
percolation column laboratory data and pilot leachates.
131
-------
Predominantly Inorganic Waste; pH+pe=13
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
Liquid-Solid Partitioning of Cu; pH+pe=13
l.E
l.E
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
pH-dependence
[Cu+2] pH+pe=13
A Percolation Column
O Leachate (Pilot)
I ' I ' I ' I ' I ' I ' I ' I
I ' I
123456
7 8
PH
9 10 11 12 13 14
Predominantly Inorganic Waste; pH+pe=6
;-03
04
05
06
07
08
09
10
11
12
13
1-14
pH-dependence
[Cu+2] pH+pe=6
A Percolation Column
O Leachate (Pilot)
I ' I
I ' I ' I
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
o
^>
0.
a.
o
u
o
o
u
Liquid-Solid Partitioning of Cu; pH+pe=6
1 2 3 4 5 6
7 8 9 10 11 12 13 14
PH
Predominantly Inorganic Waste; pH+pe=4
Liquid-Solid Partitioning of Cu; pH+pe=4
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
l.E-10
l.E-11
l.E-12
l.E-13
l.E-14
!
1
i
!
!
h^
I
O
f
^
O
>,
.1
! pH-dependence
! A Percolation Column
L ;
1 ' 1 ' 1 ' 1 ' 1 '
53456;
*
^
6
^-"
|
.X"
k
**'
[Cu+2] pH+pe=4
O Leachate (Pilot)
+s
1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1
' 8 9 10 11 12 13 1
PH
DFree ODOC-bound BPOM-bound DBIaubleill OCuprite
1 2 3
9 10 11 12 13 14
Figure 4-56. Comparing effects of oxidizing and reducing conditions - chemical speciation modeling of
copper from predominantly inorganic industrial waste at L/S=10 mL/g compared to pH-dependent
(PrEN 14429) and percolation column (PrEN 14405) data.
132
-------
Predominantly Inorganic Waste; pH+pe=13
Liquid-Solid Partitioning of S; pH+pe=13
o
3
W
l.E-02
l.E-04
l.E-05 -
l.E-06 -
l.E-07
l.E-08 -
h ซ-*-
i
i
!
!
__
f
' pH-dependence
! [S04-2] pH+pe=13
: A Percolation Column
! 0 Leachate (Pilot)
L 2 3 4
*
9
A
5 6 7 8 <
-*
-ป
(
t-r
ง-
} 10 11 12 13 1
PH
Predominantly Inorganic Waste; pH-i-pe=6
l.E-01
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
pH-dependence
[S04-2] pH+pe=6
A Percolation Column
O Leachate (Pilot)
I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
1 F-07 -
l.E-03 -
l.E-04 -
l.E-05 -
1 E-06 -
l.E-07 -
l.E-08 -
1 p-na -
I
| " ^
f
F
f
! DFree
r DAIOHS04
: DAnhydrite
[ BaSrS04[50%Ba]
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Liquid-Solid Partitioning of S; pH-i-pe=6
f-^
_l
1
o
SM'
b.
.3
Total Su
1 P-fl? -
l.E-03 -
l.E-04 -
l.E-05 -
l.E-06 -
l.E-07 -
l.E-08 -
1 p-na .
r
[
[
[
[
[
_
DFree
DAIOHSO4
DAnhydrite
DBaSrSO4[50%Ba]
DBIaubleill
123456
7 8 9 10 11 12 13 14
PH
Predominantly Inorganic Waste; pH+pe=4
Liquid-Solid Partitioning of S; pH+pe=4
o
w
"a
l.E-02 -
l.E-03 -
l.E-06
l.E-07
1 p.na .
!
|
!
|
!
Is
<
\
3 C
>
,
O
^
'
f
X
0
1
/
! "^^^^
k y
/
r
pH-dependence
[S04-2] pH+pe=4
A Percolation Column
O Leachate (Pilot)
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
o
w
1
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Figure 4-57. Comparing effects of oxidizing and reducing conditions - chemical speciation modeling of
sulfur from predominantly inorganic industrial waste at L/S=10 mL/g compared to pH-dependent
(PrEN 14429) and percolation column (PrEN 14405) data.
4.7.4 Case Summary
Case 7 focused on comparison of laboratory and field lysimeter results to leaching from a 12,000 m3
field pilot landfill for a mixture of predominantly inorganic wastes. The applicable pH domain for
the material tested was 6.5 to 8.5. In summary, these results emphasize the importance of
133
-------
understanding the potential impacts of reducing conditions in the field that cannot be captured
adequately during laboratory testing (but can be inferred by knowledge and simulation of chemical
speciation under reducing conditions). Laboratory test conditions are likely to be oxidizing to
mildly reducing, while field conditions for the same material can be mildly to strongly reducing
depending on the extent of reducing constituents in the material, biogenic processes and exclusion
of atmospheric oxygen. Reducing conditions in the pilot-scale landfill were most likely induced by
microbial degradation of the limited amount of organic matter introduced with the waste because
no reducing waste types (i.e., pyrites, slags) were included with the disposed materials. The effects
of reducing conditions include (i) chemical reduction of iron resulting in loss of HFO sorptive
surfaces and increased dissolved iron, (ii) increased biogenic DOC concentrations, and (iii)
increased leaching of some species resulting from chemical reduction to more soluble species, loss
of iron oxide sorption sites, and/or increased partitioning into the leachate by complexation with
DOC. For several constituents (i.e., arsenic, barium, chromium, copper, iron, phosphorous) the
maximum concentrations observed in the field pilot-scale landfill were significantly greater than
maximum concentrations indicated by the laboratory column testing. These differing effects point
to the need of a priori knowledge of the adsorption, solubilization and precipitation chemistry of
different elements to interpret leaching results and the benefits of using chemical speciation
modeling to facilitate interpretation. However, also shown in this case study is that leaching of
many constituents was not impacted by the reducing conditions. This case also demonstrates that
laboratory testing data obtained under oxidizing to mildly reducing conditions can be used in
conjunction with chemical speciation modeling to provide an estimate of expected field leaching
under mildly to strongly reducing conditions.
134
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4.8 Municipal Solid Waste Landfill (The Netherlands)
4.8.1 Case Description
The pilot-scale landfill for MSW in Landgraaf, The Netherlands, was established to evaluate the
biodegradation of organic matter-rich waste by leachate renewal and recycling. The test cell had a
volume of 45,000 m3 and was filled with a mixture of sewage sludge, construction and demolition
(C&D) waste, MSW, industrial waste, car shredder waste, foundry sand, and soil cleanup residue
(Table 4-3). Samples of all the wastes accepted at the landfill were sampled proportionally to obtain
a representative mixture of the waste in the test cell for laboratory studies. The material collected
was homogenized and reduced in volume to manageable quantities by cone and quartering. During
the filling of the test cell, lateral infiltration pipes were placed to facilitate the efficient wetting of the
waste. During the entire operation of the test cell, leachate samples were collected and analyzed for
major, minor and trace elements, as well as parameters to monitor the degradation of waste, for
example gas composition, chemical oxygen demand (COD), biological oxygen demand (BOD), DOC.
Preparation for the pilot program started in 2000. The actual leachate collection started when the
pilot was completely filled in May 2002 (Luning et al., 2006; van der Slootetal., 2008a).
Table 4-3. Waste composition of the landfilled material in the test cell at Landgraaf (Luning et al.,
2006).
Material
Eural Fraction Quantity Fraction- Dry
Code* of Total (tonnes) on dry Matter
fo/~1 basis (%) (tonnes)
Water as
moisture
content
(tonnes)
MSW
Industrial Waste
Shredder Waste
Cleaning Residue
Foundry Sand
C&D Waste
Sewage Sludge
Total
20.30.01
20.03.01
19.10.04
19.12.09
10.09.08
19.12.09
19.08.12
34.4%
11.5%
18.3%
6.9%
18.3%
7.3%
3.2%
100%
9,000
3,000
4,800
4,700
1,300
1,900
380
36%
12%
19%
19%
5%
8%
2%
25,200 100%
5,300
1,400
3,800
3,700
1,300
1,600
260
17,400
3,700
1,600
1,100
1,000
13
330
120
7,800
Note: * European waste code
The shape and layout of the drains and infiltration pipes is given in Figure 4-58. Nine leachate
drainage pipes were installed in the bottom of the test cell, which drained into six collection wells.
A buffer tank was used for recirculation of leachate, which was connected with the lateral
infiltration pipes located at two depths in the landfill test cell. Different cycles of infiltration and
discharge of leachate were used during the operation of the cell.
The pH-dependence test (CEN/TS 14429) and the percolation column test (CEN/TS 14405) were
carried out on subsamples of the waste mixtures collected and homogenized during initial filling of
the test cell. After eight years of operation, core samples of the waste in the landfill were obtained
and composited into a sample subjected to pH-dependence and percolation testing using the same
135
-------
procedures. In addition to the core composite, material from individual cores taken after eight
years of operation were subjected to a single step batch leaching procedure in demineralized water
atL/S 10 L/kg (EN 12457-2).
Figure 4-58.Cross-section schematic layout of the landfill test cell with leachate collection drains and
infiltration pipes.
4.8.2 Results and Discussion
A complete set of figures illustrating results from the laboratory pH-dependent leaching tests and
column tests along with results from the pilot-scale landfill test cell is provided in Appendix F.
Comparisons are presented between laboratory test results and field results for the following
datasets:
initial composited waste sample (green triangles with a dashed line) using pH-dependence
and percolation column tests,
field materials composited from landfill cores taken after eight years (blue squares with
solid line) using pH-dependence and percolation column tests,
individual core samples (grey diamonds) using single batch extraction in deionized water at
L/SoflOL/kg
leachate collected from the landfill (red, open circles).
For each analyte, data are presented as a function of pH (left) and as a function of L/S (right).
Leachate concentrations are plotted as a function of leachate pH or as a function of the cumulative
L/S of leachate from the landfill (based on collected leachate volumes).
In the context of the other cases discussed in this report, the MSW landfill has the greatest
proportion of biodegradable organic matter and therefore has the greatest amount of DOC in the
leachate as well as the most chemically reducing conditions within the test material. Interpretation
of the constituent concentrations in the landfill test cell leachate is complicated by the recirculation
of collected leachate back into the landfill. Leachate recirculation induces higher rates of microbial
biodegradation, furthering reducing conditions, and also results in accumulation of soluble
constituents in the leachate, rather than washing them out and observing declining concentrations
as leaching from the system progresses.
136
-------
The following are notable relationships between leaching tests and field results for specific
constituents:
Results for pH, DOC and iron are presented in Figure 4-59 and Figure 4-60. The pH as a
function of L/S for the column test on the initial composite material indicates near neutral
pH (i.e., 7.5) initially followed by a temporary increase to 8.0, followed by a decrease to 7.0,
indicative of the onset of acetogenesis as part of MSW biodegradation. In contrast, the
column test on the composite of core samples after eight years was initially near neutral and
then increased to pH 8.5 followed by a slight decrease in pH. This behavior was most likely
the result of washout of accumulated biogenic volatile fatty acids. DOC and iron
concentrations in the eluates further support this assumed behavior (note the increase in
dissolved iron at L/S of 10 L/kg for the column test on the initial composite material,
signaling the onset of strictly anaerobic biodegradation and strongly reducing conditions).
10
-A MSW Organic Waste (initial)
- MSW Landfill - Core Composite (8 yr)
ป MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
0.001
0.01
0.1
L/S (L/kg)
10
Figure 4-59. Eluate pH from leachates from the Landgraaf MSW landfill (red circles) compared
to the pH from percolation column testing for initial material and landfill cores (solid symbols).
137
-------
10000
10000
0.1
L/S (L/kg)
-A MSW Organic Waste (initial)
- MSW Landfill - Core Composite (8 yr)
* MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
Figure 4-60. Comparison of DOC and iron concentrations from Landgraaf landfill leachates
(red circles) with laboratory data (solid symbols) as a function of pH (left) and L/S (right).
Maximum chloride, potassium and sodium concentrations in the initial column test eluates
were good indicators of maximum landfill leachate concentrations, which were a factor of
approximately 20 greater than observed in laboratory pH-dependenttest eluates (Figure
4-61). This phenomenon was expected because the concentrations measured in leachate
and laboratory test eluates reflect a similar mass per volume of constituent dissolved but at
different L/S conditions. Unlike the values observed for other cases in this report, the
landfill leachate concentrations did not decrease with increasing L/S because of leachate
recirculation.
138
-------
10000
1000 - :
01
V 100 -
_o
u 10
I ' ' ' I
10000
6 8
pH
' I ' ' ' I ' '
10 12 14
0.001
0.01
0.1
L/S (L/kg)
0.001 0.01 0.1
L/S (L/kg)
* MSW Organic Waste (initial)
MSW Landfill - Core Composite (8 yr)
ป MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
J
10
Figure 4-61. Concentrations of highly soluble constituents (chloride, potassium and sodium,
upper, middle and lower graphs, respectively) from laboratory test eluates and leachate from
the landfill test cell.
Aluminum, calcium, nickel and zinc concentrations in landfill leachate were consistent with
concentrations measured in pH-dependent test eluates, indicating solubility controlled
139
-------
leaching (i.e., a saturated solution with respect to the constituent at the leachate pH); results
for aluminum, calcium and nickel are provided in Figure 4-62).
0.001
10 12 14
-A MSW Organic Waste (initial)
- MSW Landfill - Core Composite (8 yr)
* MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
10
01 1
! o.i
0.01
10000
^ 1000
^
E
100
_o
5
10 -;
0.001
10 T
Ol
^>
"3
o
0.01
0.001
0.001
'"V.
0.001 0.01 0.1
L/S (L/kg)
10
0.01 0.1
L/S (L/kg)
10
0.01 0.1
L/S (L/kg)
Figure 4-62. Examples of solubility-controlled leaching whereby the measured concentration
in leachate and laboratory column tests is closely aligned with results from the pH-dependent
leaching test (illustrated by aluminum, calcium and nickel, upper, middle and lower graphs,
respectively).
140
-------
Increased concentrations of chromium in leachate from the landfill test cell are most likely
the result of complexation of Cr+3 with DOC (Figure 4-63, top). Increased concentrations of
arsenic in leachate from the pilot-scale landfill are most likely the result of loss of arsenic
adsorption sites on hydrated iron oxide surfaces because of reduction and solubilization of
iron (Figure 4-63, bottom).
Dl
E o.l
0.01 -:
0.001
I
<
0.0001
"^
KM*
P n 1
1 ฐ'1
1
n nm -
n
A-
1
CO
o
-* *.
""""^
sf
**ป
5
0.001 0.01 0.1 1
L/S (L/kg)
0.01 -
0.001 -
Dl
I
<
0.1 -;
0.01 -
0.001 -;
0.0001
0.001
-A MSW Organic Waste (initial)
- MSW Landfill - Core Composite (8 yr)
* MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
10
ccP
0.01 0.1
L/S (L/kg)
10
Figure 4-63. Complex interactions as a result of reducing conditions are illustrated by
chromium (DOC complexation) and arsenic (loss of iron adsorption), resulting in higher
leachate concentrations than indicated by pH-dependent and laboratory column tests.
In contrast, increased barium leachability (Figure 4-64, top) in leachate from the pilot-scale
landfill is most likely linked to increased solubilization of phosphate under reducing
conditions (Figure 4-64, bottom).
141
-------
5 i
01
^>
1
= n 1 .
m
%
O
-
V
OQ
Mi
m cc
V?
5
V
fe
>*
-^A
0 2 4 6 8 10 12 1
PH
5
"" 1 -
ฃ l
ซ
3
1_
o
f
9- n 1 -
o
f
Q.
\>
\
o
^
X
1
V
o
1*
"* ฃ
oJ
s'
/
"'
-/
0 2 4 6 8 10 12 1
PH
A MSW Organic Waste (initial)
MSW Landfill - Core Composite (8 yr)
* MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
Dl
n
CQ
10
1 -:
0.1 -;
0.01
CD
0.001
0.01 0.1
L/S (L/kg)
10
10
0.01 0.1 1
L/S (L/kg)
Figure 4-64. Potential relationship between barium (upper graph) and phosphorus (lower
graph) solubilization under reducing conditions, resulting in higher leachate concentrations
than indicated by pH-dependent and laboratory column tests.
Vanadium also had higher concentrations in the leachate from the pilot scale landfill under
reducing conditions than observed from the lysimeters and the laboratory column tests
(Figure 4-65). High vanadium is likely due to a shift in oxidation state from V+5 to V+4 (see
Section 2.2.3).
142
-------
01
a
n nnnni .
i
o
[
tc
0ฐ
o
JH
\
o
&
K:
10 12 14
0.001
0.01 0.1
L/S(L/kg)
10
A MSW Organic Waste (initial)
MSW Landfill - Core Composite (8 yr)
* MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
Figure 4-65. Increased vanadium concentrations under reducing conditions, likely the result
of chemical reduction of V+5, also resulting in higher leachate concentrations than indicated by
pH-dependent and laboratory column tests.
For these constituents, the maximum concentrations observed in the field pilot-scale landfill
were significantly greater than maximum concentrations indicated by the laboratory
column testing. These differing effects point to the need of a priori knowledge of the
adsorption, solubilization and precipitation chemistry of different elements to interpret
leaching results, and the benefits of using chemical speciation modeling to facilitate
interpretation (see Section 2.2.3 and Section 3).
The strongly reducing conditions existing in the MSW landfill also favor the conversion of
sulfate to sulfides with the concurrent precipitation of some metal sulfides. Decreasing
sulfur in solution and leachable sulfur from composite samples is a reflection of conversion
from sulfate (soluble) to sulfide (insoluble) as a result of biodegradation processes (Figure
4-66, top). The effect of these processes competing with increased solubilization by either
DOC complexation for copper or chloride complexation for cadmium results in decreasing
concentrations with increasing L/S when leachate results and laboratory column results on
eight-year-old material to laboratory (pH-dependent and column testing) on the initial
landfill composite (Figure 4-66, middle and bottom).
143
-------
1000
5
ฐ> 100 -
a
"5
1 -
0
100 -
10 -
1 1-
KM*
1_
<0
a 0.1-
3
0.01 -
0.001 -
It
5
"5 o.
ฃ
E o.o
_3
1 0.00
n
U
0.000
0.0000
-*
1
m-f-i
o
0 |
08'
^-A
-
2 4 6 8 10 12 1
PH
^.
^
^
k_ -X.
\
V
O
/
****
s
^f
,-J
X
D 2 4 6 8 10 12 1
PH
1 '!
1 '!
A-A
!:^
"T
O
:ป
N|^^'
\Qsฃ~
sir
i
S
**
0 2 4 6 8 10 12 1
PH
A MSW Organic Waste (initial)
MSW Landfill - Core Composite (8 yr)
ป MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
_
o
n
U
100 -
0.0
100 -
10 -
1 -
0.1 -
0.01 -
0.001 -
o.t
It
0.
0.0
0.00
0.000
0.0000
O
J
-
^L^l-,
\
i
o
o
^o
^
0.001 0.01 0.1 1 1
L/S (L/kg)
Figure 4-66. Decreasing sulfur in leachate from the landfill test cell and lower initial sulfate
concentrations in eluates from laboratory column testing on core samples after eight years
indicates conversion of sulfate to sulfides (top) with decreased solubility of copper (middle)
and cadmium (bottom).
144
-------
4.8.3 Chemical Speciation Insights - Municipal Solid Waste Landfills
An extensive review MSW leachate compositions is available (Robinson, 1995). MSW is anticipated
to initially be at oxidizing (i.e., pH+pE=13-15) because of open air handling combined with initial
biodegradation processes. However, under landfill conditions gradients from mildly reducing to
strongly reducing conditions (i.e., pH+pE=5.5 as indicated by sulfate reduction) are present. Thus,
chemical speciation modeling of pH dependent test results are simulated at pH+pE=13 (Figure 4-67
and Figure 4-68), while percolation column conditions can rapidly evolve from oxidizing to reducing
conditions because of inherent microbial activity (initially aerobic to sulfate reducing or
methanogenic) and field conditions are simulated at reducing conditions. Figure 4-67 (Cd, Ni, Pb,
Zn) and Figure 4-68 (sulfate, Ca, Cr, F) left side graphs compare simulation of pH dependent
leaching at L/S=10 (red line) and 0.3 mL/g (blue dashed line) with pH dependent leaching test data
(red dots) and percolation column data (blue triangles) and simulated speciation at L/S=10 mL/g.
As indicated with earlier examples, areas where the simulated results at L/S=10 and 0.3 mL/g
coincide are anticipated to be solubility controlled pH domains for the indicated element. Domains
where simulated concentrations L/S=0.3 mL/g are much greater than simulated concentrations at
L/S=10 mL/g can be expected to exhibit higher concentrations in initial percolation column eluates,
as indicated for sulfate results. Decreasing concentrations of Cd, Ni, Pb and Zn during the
progression of column leaching is a consequence of depletion of the soluble species at near neutral
pH, either because of limited available content or transformation under reducing conditions such as
formation of a metal sulfide precipitate (i.e., Cd, Ni, Pb, Zn).
145
-------
Municipal Solid Waste (the Netherlands)
Partitioning of Cd at L/S=10
l.E-04 -
5 l-E-05 -
o
E
5
l.E-09 -
i
!
-
-N
""-
\
\
**
*A
^"
pH-
A Perc
[Cd
^
depen
(-2] L
olatic
(-21 L
^
dene
n Co
S=0
_^
e
0
umn
3
l.E-04 -
i- l.E-05
o
.ง. l.E-06
E
.5 l.E-07
l.E-09 -
! DFree BDOC-bound
ROM-bound BFeOxide
! DClay
1 X7
l.E 10 I i i i i i i i i i i i i i i.t-iu 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 2 3 4 5 6 7 8 9 10 11 12 13 1
pH pH
Municipal Solid Waste (the Netherlands) Partitionina of Ni at L/S-10
_ l.E-04 -
u
Z
-N
[Ni+2] L/S-10
A Percolation Co umn
[Ni+2] L/S-0.3
\
\
\
"^N\
1^4'
4 ฐ
^
>
f"
^ l.E-04 -
1
1 E 05 -
DFree DDOC-bound
ROM-bound BFeOxide
DClay
1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 2 3 4 5 6 7 8 9 10 11 12 13 1
pH pH
Municipal Solid Waste (the Netherlands) Partitioning of Pb at L/S=10
1 E 02 i i- ^-i
l.E-03 -
j] l.E-04 -
a i F nfi -
ro -L-t uo
V
l.E-08 -
r
f
r
---^
N
-^v.
s
\
\
x r^
^T^^
^
AA pH-
A A Perc
[Pb
/
*
depen
1-2] L
olatic
1-2] L
/
/
den
n Co
S=0
e
0
umn
3
l.E-03
3 l.E-04 -
| l.E-05
~ฐ l.E-06 -
l.E-07 -
l.E-08 -
\
r-=^^^~~"^ jT
; >y J
: DFree ^^ ^^^ 1
, DDOC-bound ^O^^. /
! ROM-bound \^ /
, BFeOxide ^v /
: DClay N. /
f DAnglesite ^S. /
\ D PbMoO4 [c] ^^_/
l.E 09 iii ii l.t-U9 1 1 1 1 1 1 1 1 ' 1 ' 1 1 1 1 1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 2 3 4 5 6 7 8 9 10 11 12 13 1
PH pH
Municipal Solid Waste (the Netherlands) Partitioning of Zn at L/S=10
1 r i nn 1 pj-nn 3
l.E-01
3" l.E-02
Q
N
l.E-05 -
l.E-06 -
!
f
[
f
\
\
pH-depende
A Perco s
[Zn+2
~^-
.\
^ss^^-
A
A
A
tion
L/S=
,. i -
nee
10
Column
0.3
/
0 l.E-03 -
* l.E-05 -
l.E-06 -
DFree DDOC-bound ROM-bound
FeOxide OClay OCa2Zn[PO4]2
Dhydrozincite DZn[OH]2 [B]
"^^^r Oi /
\ ^
v^_^---^~""/
1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 2 3 4 5 6 7 8 9 10 11 12 13 1
pH pH
Figure 4-67. Chemical speciation modeling under reducing conditions (pH+pE=13) of municipal solid
waste (the Netherlands) compared to pH-dependence data (CEN/TS 14429) and percolation column
data (CEN/TS 14405).
146
-------
Municipal Solid Waste (the Netherlands)
5
(0
u
|
u
l.E-01 -
1 E 02 -
1 F r\^ .
\
*
ft
s
i
0
rs
o
A
pH-
[SO
Perc
fSO
Jepe
4-2]
olati
4-2]
dene
sn Co
_/S=C
e
0
umn
.3
1234567
9 10 11 12 13 14
PH
Municipal Solid Waste (the Netherlands)
l.E-04
l.E-05
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
l.E-10
l.E-11
l.E-01
^ l.E-02
C. l.E-03
a
a
Municipal Solid Waste (the Netherlands)
pH-dependence
[CrO4-2] L/S=10
A Percolation Column
[Cr04-2] L/S=0.3
23
9 10 11 12 13 14
PH
Municipal Solid Waste (the Netherlands)
l.E-04 -
l.E-05
!
--
--
*
'
I
\
pH
A Pe
[F
\\
\
I
^
od
^
-depe
]L/S
colat
I L/S
ndence
on Column
=0.3
>
''
t
/
s
-
23
9 10 11 12 13 14
l.E-02
Partitioning of SO4 at L/S=10
O
a
4J
fc
3
(/I
l.E-03
; -^=
nFree
1 BPOM-bound
DClay
D[Ba,Sr]SO4(50%Ba)
nOrpiment
nDOC-bound
FeOxide
DAnglesite
DBIaublei II
1 2 3 4 5
6 7 8 9 10 11 12 13 14
PH
l.E+01
Partitioning of Ca at L/S=10
ปW
g l.E-02 - r
u
l.E-04 r
DFree DDOC-bound BPOM-bound
FeOxide DClay OCa2Zn[PO4]2
DCalcite DDiopside DFIuorite
6 7 8 9 10 11 12 13 14
PH
Partitioning of Cr at L/S=10
ง
E
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Partitioning of F at L/S=10
l.E-02 -
1 E-03
l.E-04
1 F rt^ .
OFree DDOC-bound POM-bound
FeOxide DClay DFIuorite
234567
9 10 11 12 13 14
PH
PH
Figure 4-68. Chemical speciation modeling under reducing conditions (pH+pE=13) of municipal solid
waste (the Netherlands) compared to pH-dependence data (CEN/TS 14429) and percolation column
data (CEN/TS 14405).
147
-------
The upper panels of Figure 4-69 and Figure 4-70 present the changes in simulated Fe and Cu LSP,
respectively as a function of pH+pE between 13 and 4. The left side panels show the model
conducted at L/S=10 while the right side panels shown the model conducted at L/S=0.3. In Figure
4-69, Fe solubility increases at neutral to slightly acid pH values with progressively more reducing
conditions in response to the greater solubility of Fe2+ compared to Fe3+. Cu solubility (Figure 4-70)
decreases with more reducing conditions because of the formation of blaublei [Cuo.eSo.s] and cuprite
[Cu20]. The lower panels in these figures present simulated LSP at L/S=10 indicating dominant
speciation in aqueous and solid phases (left side) and fractional distribution of controlling solid
phases (right side). POM and DOC association are important contributors to overall observed LSP
for both Fe and Cu. Pyrite is an important Fe solid phase at strongly reducing conditions, while the
demarcation between the formation of blaublei and cuprite shifts to a higher pH as more strongly
reducing conditions are simulated.
148
-------
l.E-01
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
Municipal Solid Waste at L/S=10
Municipal Solid Waste at L/S=0.3
1
r_T
\
\
*
^
pH-depen
[Fe] pH +
[Fe] pH +
FFe] pH +
\
\
*
dene
pE=}
pE=.
^ \\
V
V
e
L3
i.5
^c.ii
A
...
-s
Percolatio
[Fe] pH+
;Fe] pH+
[Fe] pH+
s*
n Co
:>E=6
:>E=4
umn
v
l.E+OO
l.E-01
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
)H-dependence
Fe] pH+pE=13
Fe] pH+pE=7
Fel pH+pE=5.5
rcolation Column
Fe] pH+pE=9
:Fe] pH+pE=6
:Fe1 pH+pE=4
4 5 6
9 10 11 12 13 14
PH
1234567
PH
9 10 11 12 13 14
Partitioning of Fe; L/S=10, pH+pE=7
Solid Phase Partioning of Fe; pH+pE=7
o
(/I
2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Partitioning of Fe; L/S=10, pH+pE=5.5
80% -
60% -
40% -
20% -
0% -
1
/^
^
23456
POM-bound
DClay
DFerrihydrite
^
7 8 9 10 11 12 13 1
PH
Solid Phase Partitioning of Fe; pH+pE=5.5
l.E-01
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Partitioning of Fe; L/S=10, pH+pE=4
10 11 12 13 14
100%
Solid Phase Partitioning of Fe; pH+pE=4
1234567!
PH
9 10 11 12 13 14
0%
10 11 12 13 14
Figure 4-69. The effect of oxidation-reduction (redox) on the chemical speciation of iron from
municipal solid waste (the Netherlands).
149
-------
o
u
o
u
o
u
Municipal Solid Waste at L/S=10
1 E 04 -
l.E-05 -
l.E-06 -
1 E-07 -
l.E-10 -
l.E-11 -
1 F 1 "> -
!
h^
[ ___
"
!
!
i
[ n~i
^
pH-d
pH +
pH +
pH +
Q
epen
pE =
pE =
Si
:
--*ป
k
.
ซ
. '
,,
A
ฑ
dent
13
7
5.5
A
.-
Perco ation
-pH + pE =
PH + pE =
^,
Column
9
6
4
-
!$
1234567
9 10 11 12 13 14
PH
Partitioning of Cu at L/S=10; pH+pE = 7
Partitioning of Cu; L/S=10, pH+pE = 5.5
1234567 8 9 10 11 12 13 14
PH
Partitioning of Cu; L/S=10, pH+pE = 4
2 3
Municipal Solid Waste at L/S=0.3
A Percolation Co
pH + pE = 9
pH + pE = 6
pH + pE =
l.E-12
100%
9 10 11 12 13 14
Solid Phase Partitioning of Cu; pH+pE = 7
o% -I
100%
12 3 4 5 6 7 8 9 10 11 12 13 14
PH
Solid Phase Partitioning of Cu; pH+pE=5.5
80% -
o
ฃ
40% -
20% -
0%
1234 567
9 10 11 12 13 14
PH
Solid Phase Partitioning of Cu; pH+pE = 4
80% -
60% -
20% -
1234 567
10 11 12 13 14
PH
DFree
D DOC-bound
I ROM-bound
DClay DBIaubleill D Cuprite
Figure 4-70. The effect of oxidation-reduction (redox) on the chemical speciation of copper from
municipal solid waste (the Netherlands).
150
-------
Figure 4-71 and Figure 4-72 illustrate that impact of biodegradation that results in removal of POM
and DOC from the system under initially oxidizing conditions (pH+pE=13) and under reducing
conditions (pH+pE=5.5), respectively. Progressive loss of DOC decreases DOC-associated Cu in
solution and overall Cu solubility, shifting increasing amounts of Cu to adsorption to TOC and HFO
under oxidizing conditions (Figure 4-71) while resulting in amounts of blaublei and cuprite under
reducing conditions (Figure 4-72). Also note that initial percolation column eluate concentrations
coincide with the simulation under oxidizing conditions with high POM and DOC concentrations
while the final percolation column eluate concentrations coincide with reducing conditions where
POM and DOC have been substantially depleted.
151
-------
POM=96 g/kg, DOC=957 mg/L at L/S=10
Partitioning of Cu; pH+pE=13
l.E-04 -
^^
_i
1 E-05 -
0
E
01
a.
O. 1 F-(17 -
o
u
i N
/
~--^* ^ >*"
\
^J^""
pH-dependence
A Percolation Column
[Cu+2] L/S=10
[Cu+2] L/S=0.3
1 2 3 4 5 6 7 8 9 10 11 12 13 1
PH
POM =60 g/kg, DOC=96 mg/L at L/S=10
123
Partitioning of Cu; pH+pE=13
pH-dependence
A Percolation Column
[Cu+2] L/S=10
- -[Cu+2] L/S=0.3
I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I
1 2
POM=48 g/kg, DOC=9.6 mg/L at L/S=10
Partitioning of Cu; pH+pE=13
pH-dependence
A Percolation Column
[Cu+2] L/S=10
- -[Cu+2] L/S=0.3
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Figure 4-71. Chemical speciation of copper at pH+pE=13 during degradation of municipal solid waste
(the Netherlands) through loss of POM and DOC under oxidizing conditions.
152
-------
POM=96 g/kg, DOC=957 mg/L at L/S=10
o
u
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
l.E-
a
o
u
i-03
04
05
06
07
08
09
10
11
'.-12
1
!
!
|
1
!
^-
*r
_
ฃ-
!
: A
i
! "V
______ .
!^L^* *CL>
^fr ^x
pH-dependence
Percolation Column
[Cu+2] L/S=10
[Cu+2] L/S=0.3
MSW Landfill Leachate (NL)
1234567
9 10 11 12 13 14
PH
POM=60 g/kg, DOC=95 mg/L at L/S=10
E-10
E-ll
E-12
pH-dependence
A Percolation Column
[Cu+2] L/S=10
[Cu+2] L/S=0.3
O MSW Landfill Leachate (NL)
1 I ' I ' I ' I
123456
I I I ' I I ' I
7 8 9 10 11 12 13 14
PH
POM=48 g/kg, DOC=9.6 mg/L at L/S=10
l.E-03
l.E-04 -
l.E-08 -
l.E-09 -
l.E-10 -
l.E-11 -
l.E-12
pH-dependence
Percolation Column
[Cu+2] L/S=10
[Cu+2] L/S=0.3
O MSW Landfill Leachate (NL)
I I ' I I I ' I I I
1 2 3 4 5 6
7 8
PH
9 10 11 12 13 14
01
a.
a.
o
u
o
u
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
l.E-10
l.E-11
l.E-12
Partitioning of Cu; pH+pE=5.5
DFree BDOC-bound
POM-bound BFeOxide
DClay DBIaubleill
D Cuprite
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Partitioning of Cu; pH+pE=5.5
S.
a.
o
u
DFree DDOC-bound
POM-bound BFeOxide
DClay DBIaubleill
DCuprite
1 2 3
9 10 11 12 13 14
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
l.E-10
l.E-11
l.E-12
Partitioning of Cu; pH+pE=5.5
DFree DDOC-bound
POM-bound BFeOxide
DClay DBIaubleill
D Cuprite
I ' I I ' I I I ' I ' I I I ' I I
1234567
9 10 11 12 13 14
PH
Figure 4-72. Chemical speciation of copper at pH+pE=5.5 during degradation of municipal solid
waste (the Netherlands) through loss of POM and DOC under reducing conditions.
Figure 4-73 presents field leachate data in comparison with simulated aqueous concentrations of Fe
and Cu based on laboratory testing. The observed field leachate concentrations correspond well
with simulations at pH+pE=5.5, with the results for Cu also reflect a range in the amount of DOC
present to complex with Cu and increase overall Cu solubility (ranging from coincidence with initial
pH dependent leaching test results to orders of magnitude lower concentrations as DOC is
depleted).
153
-------
Municipal Solid Waste
100000
Municipal Solid Waste
Ul
0.00001
0.001
o
D
pH-dependence (MSW Pilot)
Percolation Column (MSW Pilot)
MSW Pilot - Landfill Leachate
MSW Landfills (NL)
Model-pH+pE, L/S=10
Model - pH+pE=5, L/S=10
A Bioreactor (NL)
D MSW Landfills (UK)
-Composite pH-dependence (MSW Pilot; 8 yrs)
O Field Samples (MSW Pilot; 8 yrs)
Model - pH+pE=5.5, L/S=0.3
Model - pH+pE=5, L/S=0.3
Figure 4-73. Comparison of field leachate concentrations (multiple sources) for Fe and Cu with pH
dependence laboratory test data and simulated concentrations at pH+pE=5.5 and L/S=10 and 0.3.
4.8.4 Case Summary
Case 8 focused on a 45,000 m3 pilot-scale landfill for MSW in Landgraaf, The Netherlands, that was
filled with a mixture of sewage sludge, construction and demolition (C&D) waste, MSW, industrial
waste, car shredder waste, foundry sand, and soil cleanup residue. The pilot study was established
to evaluate the biodegradation of organic matter-rich waste by leachate renewal and recycling. The
applicable pH domain was between 5.5 and 8.5 based on laboratory testing and field results. Peak
concentrations for highly soluble species from laboratory percolation column at L/S 0.5 mL/g
agreed well with peak leachate concentrations from the landfill and were a factor of 20 times
greater than observed using pH dependent leaching test at L/S 10 mL/g. Reducing conditions in the
landfill resulted in higher concentrations in leachate than observed at corresponding pH values
during pH dependent laboratory testing. These effects were entirely consistent with those observed
for the predominantly inorganic landfill (Section 4.7) and were consistently estimated using a
chemical speciation model for municipal solid waste. These results further support the use of
chemical speciation-based simulations based on laboratory test results for evaluating the effects of
reducing conditions established in the field. Chemical speciation modelling and experimental
results also illustrated the importance of particulate organic matter and dissolved organic carbon
on the leaching of several trace and major constituents in MSW.
154
-------
4.9 Stabilized Municipal Solid Waste Incinerator Fly Ash Disposal (The Netherlands)
4.9.1 Case Description
A pilot experiment with four stabilized waste compartments has been carried out in The
Netherlands using cement solidified/stabilized municipal solid waste incinerator fly ash (van
Zomeren and van der Sloot, 2006a; van der Sloot et al., 2007). Details of the stabilization formula
are proprietary but the formulation included portland cement and fuel ash derived pozzolans.
Results are also available for the full-scale landfill receiving the same materials after ten years of
operation (Keulen, 2010; van Zomeren etal., 2011). Laboratory results from pH-dependence
testing and percolation testing on "as produced" cured and crushed material, along with laboratory
monolith testing is compared to field pilot results based on leachate and testing of core samples
after four years and full-scale landfill leachate and testing of core samples. Laboratory testing
consisted of pH-dependent leaching using CEN/TS 14429, up-flow percolation testing using CEN/TS
14405, and monolith mass transfer rate using (NEN 7375, 2004). A full-scale landfill received the
same material as the pilot system and was subject to core sampling after ten years of operation.
Individual core samples were leached according to EN 12457-2 using single point batch extractions
at L/S of 10 L/kg with demineralized water.
A schematic showing the design of the field pilot system is presented in Figure 4-74. Four
hydraulically isolated test cells (Cells A to D) were used for the solidified/stabilized waste to
examine the effects of waste depth, carbonation and mixing of stabilization formulations.
B
Geotextile to ensure
minimal water contact
Run-off water
collection \
D
Cell with mixed
1m
5m
I I
1 I
\
ง
A
A
3m
ป
\\
\
ง
B
b
C
ell packed in foil
\
Four
percolate
water
samplers
ง:
c
\
d
\
S:
D
Figure 4-74. Schematic illustration of the front view of the pilot scale experiment using stabilized
waste (from van der Sloot et al., 2007). Each test cell was 8 m long, and the space between test cells
was filled with sand to maintain physical stability.
155
-------
The waste was stabilized in situ in layers of approximately 0.5 m. Geotextile membrane was placed
vertically at 1.5 m intervals to create preferential flow channels through the stabilized fly ash,
facilitating infiltration flow around the monolith at the waste-geotextile interface rather than
percolation through the material and thus establishing a "flow around" with diffusion to the
interface scenario. A portion of the rainwater that falls on top of the stabilized waste evaporated
because of the relatively high porosity of the surface layer and the low permeability (possibly even
partial pore sealing) of the deeper layers in the stabilized waste monofill. A layer of mildly
contaminated soil underlies the stabilized waste layer for protection of the bottom liner system.
This soil layer also had the potential to neutralize the alkaline percolate water and possibly bind
leached contaminants (Rietra etal., 2001).
After four years of operation, the four pilot landfill cells were visually inspected and demolished
using a hydraulic excavator (van Zomeren et al., 2007). Bulk samples were taken at various spots
within the stabilized waste and cores were drilled to sample detailed waste profiles. The three
exposed cells (Cells A, B and D) were heavily weathered to a depth of 20-30 cm such that material
could be easily removed with a spade. Cracking and swelling of the material was visible on the
exposed surfaces. The outer first centimeter was light grey in color and then the material was dark
grey to black to a depth of 20-30 cm. The material became much more solid below 40 cm depth.
Plant roots grew in the stabilized waste to a depth from a few centimeters (Cell B) to 10-15 cm (Cell
D). The material from Cell D (mixed waste) crumbled easily when removed while the material from
Cell B below 50 cm was removed as blocks of about 20-50 cm in diameter that also crumbled
readily under the bucket of the hydraulic excavator. The unexposed cell (Cell C) was visually
unchanged in comparison with the initial condition after placement. The material was solid, grey in
color and had no cracks or swelling. The unexposed material came out as large blocks (up to 0.5
m3) which did not break when they were dropped (on the sand) from 3-4 meter height. These
blocks did break after (repeated) hitting with the bucket of the hydraulic crane. These observations
clearly showed a significant difference in material properties (i.e., hardness, weathering, color,
cracking) between the exposed and unexposed stabilized waste.
4.9.2 Results and Discussion
A complete set of figures showing the results from the laboratory pH-dependent leaching tests and
column tests along with results from the pilot-scale test cells and the landfill are provided in
Appendix H. Results are presented in the form of concentration as a function of pH (left graphs)
including pH-dependent test results on freshly stabilized waste following a 28-day cure interval
(connected orange dots), composited core samples obtained after four years from test Cell B
(connected blue diamonds) and test Cell C (connected green triangles), leachates from the test cells
(individual filled blue, green and fuchsia symbols), leachate from the full-scale landfill (open red
circles), single point extractions on test cell cores (open blue diamonds, green triangles and fuchsia
squares) and single point extractions on landfill core samples (gold dots). Results are also
presented in the form of concentration as a function of L/S (right) including column test results on
freshly stabilized waste following a 28-day cure interval (connected orange dots), test cell leachates
(open blue diamonds, green triangles and fuchsia squares) and the first fraction at L/S of 0.1 of a
column test on two core samples from the landfill (gold dots).
156
-------
The pH of the fresh material (one week old) in demineralized water was between 12 and 12.5,
whereas the pH of the older samples (four months) increased with depth from 10.9 to 11.9 (van der
Sloot et al., 2007). After six months, the pH of the stabilized waste at 15-25 cm below the surface
had decreased to about 11.7. After four months, Cl was depleted from at least the first 10 cm of the
stabilized waste, indicating substantial washout of this mobile element.
The depletion of mobile constituents and, possibly, enhanced carbonation of the outer layer was
determined to be due to increased porosity and were the main processes responsible for the
observed material properties (van Zomeren et al., 2007). Related research on intermittent wetting
and carbonation of solidified/stabilized waste by Garrabrants et al (2002, 2003) and Sanchez et al
(2002) indicated that relaxation of internal constituent gradients during non-wetting periods and
solubility constrained leaching (i.e., local equilibrium at the surface in the presence of small
volumes of contacting water) has a significant impact on leaching under these circumstances. A
conceptual model of the processes that occurred during the pilot field experiment is illustrated in
Figure 4-75.
Cratk
formation/
repair?
Pore
wralinc?
repair.' (
Ll /
I n fi It ra t ion/eva pora lio n
Carbonation zone
r^ }
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Liner'
pH Buffi-ring
Soil&
ground water
impact
Lcachatc (pH neutral)
Metal binding;
Figure 4-75. Conceptual model of processes occurring during the field pilot study of monolithic waste
disposal (from van der Sloot et al., 2007).
The following are notable relationships between leaching test and field results:
Leachate and runoff from the field pilot and landfill was 6 < pH < 9 while laboratory column
tests indicated 12 < pH < 13 (Figure 4-76). This difference was most likely due to
carbonation on the surface for runoff and a combination of carbonation and neutralization
by the underlying soil/buffer material for leachate in the field. Leachate pH values from the
full-scale disposal cell were consistent with the values observed from the pilot cells.
157
-------
1
A ~. n
i
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o
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Sb o
0.000001 0.0001 0.01 1 10
-- Fresh Stabilized Waste
: Monofill individual Cores (lOyr)
-*Coll 6 - Core Composite (1 yr)
O Cell 6 Lcachate
A Cell C Leachate
Cell DLeochate
L/S (L/kg)
Figure 4-76. Comparison of pH for laboratory testing of waste materials and landfill cores
to landfill leachate pH for stabilized waste.
Reaction of the field material with atmosphere carbon dioxide (i.e., carbonation) is
demonstrated by the decreased concentrations of barium, calcium and strontium at 6 < pH <
10 for the field cores as compared to the initially prepared samples (see calcium and
strontium in Figure 4-77). The decrease in concentration for these analytes in this pH range
is a typical result of the formation of carbonates of barium, calcium and strontium.
158
-------
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-- Fresh Stabilized Waste -*-Cell B - Core Composite (4 yr)
O Monofill - Individual Cores (10 yr) * Cell B - Individual Cores (L/S 10; 4 yr)
O Monofill Leachate O Cell B Leachate
-A-Cell C - Core Compos te (covered; 4 yr) D Cell D - Individual Cores (L/S 10; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr) D Cell D Leachate
A Cell C Leachate
Figure 4-77. Calcium and strontium leaching from laboratory and field materials showing
decrease in concentrations in the pH range 6 < pH < 10 consistent with carbonate formation.
Similarly lower concentrations are indicated by pH-dependent leaching testing for lead from
aged core samples compared to freshly stabilized material resulting from carbonation to
form lead carbonate (see Figure 4-78).
159
-------
2 i -
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100
9- Fresh Stabilized Waste
O Monofill - Individual Cores (10 yr)
O Monofill Leachate
A-Cell C - Core Composite (covered; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr)
A Cell C Leachate
*-Cell B - Core Composite (4 yr)
O Cell B - Individual Cores (L/S 10; 4 yr)
O Cell B Leachate
D Cell D - Individual Cores (L/S 10; 4 yr)
D Cell D Leachate
Figure 4-78. Lead leaching from laboratory and field materials showing decrease in
concentrations in the pH range 6 < pH < 10 consistent with carbonate formation.
Lower concentrations in pH-dependent solubility curves for core samples from field test
after four years indicate effects of washout of highly soluble constituents like chloride,
potassium and sodium (see Figure 4-79). However, several other elements are essentially
unchanged (i.e., Al, Cu, Mg, S). Similarly, comparison of eluate concentrations from column
testing with pH-dependence test results for highly soluble species (e.g., Cl, K, Na) indicates
rapid washout as a nearly vertical response at the eluate pH, although initial eluate
concentrations from the column test are greater than the concentration indicated by the pH-
dependence test results. The initial eluate concentrations from laboratory column tests at
L/S<0.5 mL/g are consistent with the peak concentrations in field leachate and runoff from
the pilot and full-scale cases. For column tests, concentrations decline by greater than an
order of magnitude by L/S=2 mL/g. Scatter in field leachate and runoff concentrations is
attributable to diffusion-controlled release during larger precipitation/infiltration events,
dilution and depletion. Although peak concentrations are similar for pilot-scale and full-
scale leachate samples, the rate of release of highly soluble salts is substantially slower than
observed in laboratory column studies. Peak concentrations reflect pore water
equilibration, while extended infiltration events result in a concentration gradient within
the monolith, slowing release which is controlled by diffusion within the monolithic
material. Dilution is caused by preferential flow paths channeling around the material.
160
-------
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-- Fresh Stabilized Waste -*-Cell B - Core Composite (4 yr)
O Monofill - Individual Cores (10 yr) * Cell B - Individual Cores (L/S 10; 4 yr)
O Monofill Leachate O Cell B Leachate
-A-Cell C - Core Compos te (covered; 4 yr) D Cell D - Individual Cores (L/S 10; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr) D Cell D Leachate
A Cell C Leachate
Figure 4-79. Chloride and potassium leaching from laboratory and field materials showing
washout of highly soluble species.
For several anionic species such as sulfate and oxyanions of arsenic, molybdenum, selenium,
appreciably higher concentrations, by up to a factor of 20, are observed for field leachate
and runoff samples than would be expected by direct comparison to laboratory pH-
dependence test results and laboratory column test results due to two factors: (i) speciation
is pH-dependent, and (ii) the species present at the field pH is highly soluble. As a result,
the observed peak concentrations are indicative of pore-water (L/S ~0.2-0.5 mL/g, based on
porosity of ca. 0.2-0.5) and are best approximated as 20 times the concentration observed at
corresponding pH in the pH-dependence test (L/S=10 mL/g).
Laboratory column test results on freshly stabilized waste (near pH 12) are equal to or less
than indicated by pH-dependence test results on laboratory samples for several elements,
indicating depletion of the soluble species of the element at the eluate pH conditions (e.g.,
As, Cr, Mo, Se, V); this behavior is typical for oxyanion species. Vanadium and selenium
(Figure 4-80) are examples where the more soluble speciation as an oxyanion (e.g., V20s)
appears to have been washed out as indicated by the decrease in the near neutral pH range
161
-------
(e.g., pH 6-8 for vanadium and pH 7-10 for selenium) based on pH-dependent leaching test
results on core samples taken after four years compared to freshly stabilized waste.
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O Monofill - Individual Cores (10 yr) O Cell B - Individual Cores (L/S 10; 4 yr)
O Monofill Leachate o Cell B Leachate
-A-Cell C - Core Composite (covered; 4 yr) D Cell D - Individual Cores (L/S 10; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr) D Cell D Leachate
A Cell C Leachate
Figure 4-80. Vanadium and selenium leaching from laboratory and field materials showing
washout of more soluble oxyanions.
For many elements, where solubility is highly pH-dependent, the distinctions between
laboratory column test results and field leachate and runoff can readily be understood
based on the difference between eluate pH under laboratory column test conditions
(12
-------
Field leachate and runoff results were consistent with the pH-dependence test results for
solubility-controlled species but a distinction must be made for elements that are not
affected by carbonation and elements significantly affected by carbonation (e.g., Ba, Ca;
compare with pH-dependence results of field cores).
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-- Fresh Stabilized Waste -*-Cell B - Core Composite (4 yr)
O Monofill - Individual Cores (10 yr) O Cell B - Individual Cores (L/S 10; 4 yr)
O Monofill Leachate O Cell B Leachate
-A-Cell C - Core Composite (covered; 4 yr) D Cell D - Individual Cores (L/S 10; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr) D Cell D Leachate
A Cell C Leachate
^_
1 1C
Figure 4-81. Copper, chromium and manganese leaching from laboratory and field samples of
stabilized waste.
163
-------
Field leachate and runoff results for highly soluble species, oxyanions of arsenic, chromium
and molybdenum (Figure 4-82), selenium and vanadium as well as highly soluble species
such as chloride, potassium, and sodium, exhibited consistent behavior with column test
results although when plotted with pH-dependence results display nearly vertical scatter
shifted to correspond with the field pH (e.g., 6 < pH < 9).
O
I 1-
c
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, 0.1
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<
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a Cell B - Core Composite (4 yr)
ores (10 yr) O Cell B - Individual Cores (L/S 10; 4 yr)
O Cell B Leachate
te (covered; 4 yr) D Cell D - Individual Cores (L/S 10; 4 yr)
es (L/S 10; 4yr) D Cell D Leachate
Figure 4-82. Molybdenum leaching from laboratory and field samples of stabilized waste.
Laboratory leaching of the core samples obtained at depths from 1 to 12 m from the full-
scale disposal site after eight years of operation indicated that no significant leaching of any
constituents had occurred at a depth of 1 m (minimum sample depth) or greater, including
highly soluble salts, and that carbonation had not occurred at that depth (van Zomeren,
2011).
For several elements (i.e., Al, Ba, Ca, Cu, Fe, Mg, Pb, and Zn), laboratory monolith test results
(green squares) fall either on or close to the pH-dependent solubility curve (red lines),
indicating chemical saturation in aqueous solution rather than diffusion-controlled
constituent release under the test conditions for the monolith test.
For several elements (i.e., Cd, Cr, Mo, Na, S and Se), the laboratory monolith test results
(green squares) are significantly less than the pH-dependent solubility curve (red lines),
indicating that either the dissolution rate or diffusion-controlled constituent release
dominates leaching of at the test conditions of the monolith test.
4.9.3 Chemical Speciation Insights - Stabilized Waste
Figure 4-83 through Figure 4-85 present chemical speciation modeling results at L/S=10 and 0.3
mL/g for Cu, Pb and S04 in comparison to (i) laboratory pH dependent leaching test data from fresh
164
-------
stabilized waste (ca. 28 days cure) and core samples taken after 4 years from the field test site (i.e.,
Cell B, Cell C and Cell D) and after 10 years from the full-scale mono fill (i.e., Monofill), (ii) leachate
from the field test site, and from the full-scale mono fill, and (iii) laboratory column percolation data
from testing the fresh stabilized waste after curing and crushing. Figure 4-83, providing results for
Cu, also compares chemical speciation modeling when the assume copper precipitate is either
copper hydroxide [Cu(OH)2] or tenorite [CuO] which are very similar with tenorite being a more
stable mineral form. Leaching test results from fresh and aged stabilized waste suggests
transformation from copper hydroxide to tenorite as the material ages but this has not been
independently confirmed. Comparison of leaching test results for lead from fresh and aged samples
also suggests that more stable states as represented by the chemical speciation are formed as the
material ages.
Stabilized Waste (the Netherlands)
Partitioning of Cu at L/S=10
2>
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l.E+02
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l.E-01
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l.E-04
Stabilized Waste Characterization
Partitioning of Cu at L/S=10; Tenorite
9 10 11 12 13 14
--Fresh Stabilized Waste -ป-Cell B - Core Composite (4 yr)
Monofill - Individual Cores (10 yr) O Cell B - Individual Cores (L/S 10; 4 yr)
Monofill Leachate O Cell B Leachate
-A-Cell C - Core Composite (covered; 4 yr) D Cell D - Individual Cores (L/S 10; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr) D Cell D Leachate
A Cell C Leachate
Figure 4-83. Chemical speciation modeling at L/S=10 and 0.3 mL/g for copper from stabilized waste
(the Netherlands) compared to field leachate data, laboratory pH dependence test data (CEN/TS
14429) on fresh stabilized waste (ca. 28 day cure) and field core samples after 4 years, and percolation
165
-------
column data on fresh stabilized waste (CEN/TS 14405). Also included is a comparison of assuming Cu
precipitation as Cu(OH)2 and as tenorite [CuO].
Stabilized Waste (the Netherlands)
l.E+04
l.E+01 -
l.E+00 -
l.E-01 -
l.E-02 -
l.E-03 -
l.E-04 -
l.E-05
A
pH-dependence
Percolation Column
[Pb+2] L/S=0.3
I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I
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Stabilized Waste Characterization
10000
9 10 11 12 13 14
l.E+04
l.E+03
Partitioning liquid-solid, Pb
1 2
--Fresh Stabilized Waste
Monofill - Individual Cores (10 yr)
Monofill Leachate
-A-Cell C - Core Composite (covered; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr)
A Cell C Leachate
--Cell B - Core Composite (4 yr)
Cell B - Individual Cores (L/S 10; 4 yr)
O Cell B Leachate
D Cell D - Individual Cores (L/S 10; 4 yr)
D Cell D Leachate
Figure 4-84. Chemical speciation modeling at L/S=10 and 0.3 mL/g for lead from stabilized waste (the
Netherlands) compared to field leachate data, laboratory pH dependence test data (CEN/TS 14429) on
fresh stabilized waste (ca. 28 day cure) and field core samples after 4 years, and percolation column
data on fresh stabilized waste (CEN/TS 14405).
166
-------
l.E+05
Stabilized Waste (the Netherlands)
3 l.E+04 -;
Ul
l.E+03 -
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Partitioning of S04 as S at L/S=10
3
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l.E+04 -
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9 10 11 12 13 14
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Stabilized Waste Characterization
10000
10
2 3
10 11 12 13 14
--Fresh Stabilized Waste
Monofill - Individual Cores (10 yr)
Monofill Leachate
-A-Cell C - Core Composite (covered; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr)
A Cell C Leachate
-Cell B - Core Composite (4 yr)
Cell B - Individual Cores (L/S 10; 4 yr)
O Cell B Leachate
D Cell D - Individual Cores (L/S 10; 4 yr)
D Cell D Leachate
Figure 4-85. Chemical speciation modeling at L/S=10 and 0.3 mL/g for sulfate from stabilized waste
(the Netherlands) compared to field leachate data, laboratory pH dependence test data (CEN/TS
14429) on fresh stabilized waste (ca. 28 day cure) and field core samples after 4 years, and percolation
column data on fresh stabilized waste (CEN/TS 14405).
167
-------
Figure 4-86 through Figure 4-90 compare the impact of carbonation from reaction of atmospheric
carbon dioxide with the alkaline stabilized waste for Ca, Cu, Cr, Mg and Zn. Most notable is the
impact of the loss of ettringite and the formation of calcite reducing the solubility of Ca at alkaline
pH with an analogous but less pronounced effect on Mg speciation and solubility. In case of Mg, a
significant transformation of the solubility-controlling phases occurs upon carbonation, as brucite
effectively disappears and is replaced by C03-hydrotalcite. The main effect of carbonation is
expected for Group II elements of the periodic table (e.g., Mg, Ca, Sr, Ba). Carbonation has minimal
impact on Cu and results in increased Zn leaching over the pH domain from 8 to 11. However, a
substantial impact is observed for Cr, where initial oxyanion substitution for sulfate in ettringite is
lost with progressing carbonation.
l.E+OO
l.E-01
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
L/S=10 at Different Carbonate Levels
I
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Ca+2] 10 wt%
Ca+2] 12 wt%
Ca+2] 14 wt%
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Partitioning of Ca at L/S=10; 3 wt% C03
l.E-01 -
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l.E-06 -
1 F-H7 .
D Free
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POM-bound
Fe Oxide
a Ettringite
AA_Portlandite
OAA Jennite
DAA Gypsum
DM Calcite
DAA_3CaO_AI203_6H20 [s]
~^ ^
\
\
\
2 3 4 5 6
7 8
PH
9 10 11 12 13 14
L/S=0.3 at Different Carbonate Levels
o
ID
u
l.E+OO -
l.E-01 -
1 F-IT3 -
l.E-04 -
l.E-05 -
1 F-nfi -
F
I
r__[
i 1
K
^-
H-de
erco
Ca+2
Ca+2
Ca+2
Ca+2
i
v (
\
'>
1
\
sendence
ation Column
] 3 wt% COS
] 10 wt% COS
] 12 wt% COS
] 14 wt% COS
i li 1
V
\
\
-
\
.%
\
~\
\
*i
\
\
\
\
L
\
V
^
_ *ป
\
^~-
-
1234567
9 10 11 12 13 14
PH
Partitioning of Ca at L/S=10; 14 wt% C03
l.E+OO
ID
U
l.E-07
2 3
10 11 12 13 14
Figure 4-86. Chemical speciation modeling for calcium from stabilized waste (the Netherlands) at
different carbonate levels compared to pH-dependence data (CEN/TS 14429) and percolation column
data (CEN/TS 14405) for cement stabilized fly ash (the Netherlands).
168
-------
l.E-01
l.E-02
l.E-03
L/S=10 at Different Carbonate Levels
l.E-09
pH-dependence
A Percolation Column
[Cu+2] 3wt% COS
[Cu+2] 10wt%C03
[Cu+2] 12wt%C03
O
O
u
l.E-01
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Partitioning of Cu at L/S=10; 3 wt% C03
DFree
FeOxide
DDOC-bound
DTenorite
IPOM-bound
I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I
234567
9 10 11 12 13 14
01
a.
a.
o
u
l.E-01
l.E-02
l.E-03
l.E-04
l.E-05
l.E-06
l.E-07
l.E-08
l.E-09
L/S=0.3 at Different Carbonate Levels
1
[
<
1
r~
! P
A P
! [
; [
[
H-dependence
ercolation Column
:u+2] 3 wt% COS
:u+2] 10 wt% COS
Zu+2] 12 wt% COS
:u+2] 14 wt% COS
\
*
\
\
V
/
/
y
1 2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Partitioning of Cu at L/S=0.3; 14 wt% C03
PH
^^
_1
~o
E
^>
i_
01
a.
a.
o
u
i.c-ui -
l.E-02
l.E-03
l.E-04
l.E-05 -
l.E-06
l.E-07
l.E-08
1c no
.b-uy -
DFree DDOC-bound BPOM-bound
FeOxide DTenorite
;
V /
V-^ /
[ V^-^y
f V /
x-^ /
V- 7
f ^^
1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1 ' 1
L 2 3 4 5 6 7 8 9 10 11 12 13 1
PH
Figure 4-87. Chemical speciation modeling for copper from stabilized waste (the Netherlands) at
different carbonate levels compared to pH-dependence data (CEN/TS 14429) and percolation column
data (CEN/TS 14405).
169
-------
L/S=10 at Different Carbonate Levels
L/S=0.3 at Different Carbonate Levels
I
u
l.E-07 -
l.E-08
1 F-nQ .
1
r
*x^
A
.
x
jH-de
Derco
Cr04
Cr04
Cr04
Cr04
X.
*
I
Vฃ
1
&
,^^s
pendence
ation Column
+2] 3 wt% COS
+2] 10 wt% COS
+2] 12 wt% COS
+21 14 wt% COS
7
-j
'~F*
m
^
Vฅ
x
L A
A
A
r
t
ium (mol/L)
t
u
1
l.E-05
l.E-06
1 F-07
l.E-08
2 3 4 5 6 7 8 9 10 11 12 13
PH
Partitioning of Cr; L/S=10, 3 wt% C03
;\=^w
! OFree
: DDOC-bound
'. m POM-bound
! DEttringite
; DCr[OH]3[C]
L 2 3 4 5 6 7 8 9 10 11 12 13 1
pH
'-.
l.E-04 - ,
\
E
.5 : 1
ง 1-tu/ !
f
0 l.E-08 - ,
pH-de
V j
^* Z'S*^~^l
v-^.
oendence
A Perco ation Co umn
[Cr04
[Cr04
+2] 3 wt% COS
+2] 10 wt% COS
+2] 12 wt% COS
+2] 14 wt% COS
123456789
PH
rf-^J
**
A A
A
A
10 11 12 13 1
Partitioning of Cr; L/S=10; 14 wt% C03
1 F-f14 -
^> l.E-05 -
_i
"5
,ฃ l.E-06 -
E
| l.E-07 -
0 l.E-08 -
r
^1 /"
^^y
N f
D Free
r ODOC-bound
POM-bound
DCr[OH]3[C]
l.E-09 i i i
123
i i i i i i
456789
S
1 1 ' 1 ' 1 ' 1 ' 1
10 11 12 13 14
pH
Figure 4-88. Chemical speciation modeling for chromium from stabilized waste (the Netherlands) at
different carbonate levels compared to pH-dependence data (CEN/TS 14429) and percolation column
data (CEN/TS 14405).
170
-------
L/S=10 at Different Carbonate Levels
l.E-02
O
| l.E-06 -
Ul
ฃ l.E-07
l.E-08
1 F-riQ .
|
'
'
A
\
pH-dependence
Percolation Column
[Mg+2] 3 wt% COS
[Mg+2] 10 wt% COS
[Mg+2] 12 wt% COS
[Mg+2] 14 wt% COS
\
s
\
V
\
9
-\
v \
\
*k
^^
1
O
E
_3
'ซ
01
c
Z
L/S=0.3 at Different Carbonate Levels
2 3 4 5 6
7 8 9 10 11 12 13 14
PH
Partitioning of Mg at L/S=10; 3 wt% C03
Ul
a
10 11 12 13 14
Partitioning of Mg at L/S=10; 12 wt% C03
o
Ul
i
1 2
1 E+00 -|
l.E-01
1 E-02
l.E-04
l.E-05
l.E-06
l.E-07 -
l.E-08
f
|
!
I
!
r
r
r
o
A
pH-d
'erco
[Mg+
;Mg+
;Mg+
[Mg+
\<
|
v
spendence
ation Column
2] 3 wt% COS
2] 10 wt% COS
2] 12 wt% COS
2] 14 wt% COS
""^s
**
*
\
k
\\
x
N
^
^
ซ
\
;VN
"H
-------
l.E-01
l.E-02
L/S=10 at Different Carbonate Levels
L/S=0.3 at Different Carbonate Levels
^ l.
o
N
.E-03
ฃ-04
ฃ-05
ฃ-06
ฃ-07
pH-dependence
A Percolation Column
[Ca+2] 3wt% COS
[Ca+2] 10wt%C03
[Ca+2] 12wt%C03
[Ca+2] 14wt%C03
23456
l.E-01 -
5 l.E-02 -
"3
u
.= l.E-04 -
N
l.E-05 -
l.E-06 -
1 F-H7 .
P
A r
[
r
0
H -dependence
ercolation Colun
Zn+2] 3 wt% C
Zn+2] 10 wt% (
Zn+2] 12 wt% (
Zn+2] 14 wt% (
\
D3
:os
:os
:os
\
L ^
\
\
\
L
V
^
V
/
/.'
y
/I/
'/
l.E-01
l.E-02 - <
3 l.E-03 -,
Partitioning of Zn; L/S=10, 3 wt% C03
l.E-01
2 3 4 5 6 7 8 9 10 11 12 13 14
PH
Partitioning of Zn; L/S=10, 14 wt% CO
o
l.E-02 - -
l.E-03 -,
l.E-04 -
N l.E-05 -,
N
l.E-06 -,
l.E-07
12
10 11 12 13 14
123
10 11 12 13 14
Figure 4-90. Chemical speciation modeling for zinc from stabilized waste (the Netherlands) at
different carbonate levels compared to pH-dependence data (CEN/TS 14429) and percolation column
data (CEN/TS 14405).
4.9.4 Case Summary
Case 9 focused on a pilot-scale field demonstration of near surface disposal of MSWI fly ash
stabilized with a mixture of pozzolonic binders (i.e., multiple ash types). Initial samples of the
stabilized material were subjected to laboratory leaching tests. Leachate and runoff was collected
during that evaluation period of approximately 4 years, after which cores were taken of the
stabilized material for laboratory leaching testing. Comparative results were also available from a
full-scale mono fill receiving the same stabilized waste. The applicable pH domain was between pH
12.5 for freshly stabilized material to pH 6 for field runoff. For several anionic species such as
sulfate and oxyanions of arsenic, molybdenum, selenium, appreciably higher concentrations, by up
to a factor of 20, are observed for field leachate and runoff samples than would be expected by
direct comparison to laboratory pH-dependence test results and laboratory column test results due
to two factors: (i) speciation is pH-dependent, and (ii) the species present at the field pH is highly
soluble. As a result, the observed peak concentrations are indicative of pore-water (L/S ~0.2-0.5
mL/g, based on porosity of ca. 0.2-0.5) and are best approximated as 20 times the concentration
observed at corresponding pH in the pH-dependence test (L/S=10 mL/g). Peak monofill leachate
172
-------
concentrations of highly soluble species (i.e., chloride, potassium) were approximately a factor of 10
greater than measured using pH dependent testing on freshly prepared material and approximately
half of peak values from percolation column tests, likely because of diffusion controlled release and
preferential flow. Carbonation at the surface of the stabilized material from reaction with
atmospheric carbon dioxide resulted in lower pH (6-9) for runoff and leachate samples and
characteristic reductions in leaching of calcium, barium and strontium. Field leachate
concentrations indicate solubility controlled (local equilibrium with the surface) for several
constituents (e.g., copper, chromium, manganese). Laboratory leaching of cores obtained from field
testing after 10 years from the full-scale facility indicated that no significant leaching had occurred
at a depth of 1 m. Chemical speciation modeling was used to illustrate the impact of carbonation on
leaching of several constituents.
4.10 Portland Cement Mortars and Concrete
4.10.1 Case Description
One high-volume end use for secondary materials (e.g., coal fly ash, granulated blast furnace slag) is
as substitutes for portland cement or admixtures in cement and concrete construction products. In
addition, some secondary materials may be used by being included in cement-based materials as
fine or coarse aggregate. For example, more than 11 million tons of coal fly ash were used as a
cement replacement in concrete in 2010 in the U.S. (ACAA, 2012).
A review of LEAF-analogous laboratory leach testing for portland cement-based mortars and
concretes made with and without fly ash indicated that pH-dependent leaching and monolith
leaching of COPCs is systematic and fairly consistent between non-amended and fly-ash amended
materials with up to approximately 30 wt% of fly ash substituted for cement (van der Slootetal.,
2012). Laboratory testing of commercial formulations of blended concretes and microconcretes
(i.e., those where a portion of portland cement is replaced with coal fly ash) using EPA Method 1313
for pH-dependent leaching and EPA Method 1315 for monolithic mass transfer rate leaching
demonstrated the following (Kosson et al., 2014 and Garrabrants et al., 2014):
The pH-dependent leaching of COPCs in amended materials, with up to 45 wt% substitution
of fly ash for portland cement and three-month cures, was controlled by the cement
chemistry and was significantly different from the LSP measured for the component fly ash
material incorporated into the blended sample,
Eluate concentrations for COPCs in monolithic mass transfer leaching decrease when
amended cement-based materials with substitution rates up to 45 wt% fly ash are allowed
to cure beyond the typical 28-days used for physical testing of cement-based materials,
The combination of concrete chemistry and physical retention (e.g., observed diffusivity and
tortuosity) provided by the portland cement paste in the blended material controlled the
monolithic mass release of COPCs from concrete materials, and
173
-------
Most COPCs (e.g., Al, As, B, Ba, Cd, Cr, Mo, Pb, Sb, Se, Tl and V) are well-retained in fly ash-
amended concrete materials, resulting in observable monolith leaching from concretes
containing 45 wt% fly ash substitution for only a few analytes (e.g., Al, Ba, Cr, Sb and V).
Unanswered questions in the studies described above are the impact of sample aging processes (i.e.,
carbonation and decalcification) that have the potential to alter the chemistry and physical
retention of the concrete.
The laboratory-to-field comparisons for concretes and mortars are based on pH-dependence testing
of laboratory prepared concretes and mortars to pH-dependence testing of field samples that have
been "in service" for extended time intervals:
1. Two sets of core samples of concrete in place for 40 years obtained from a test site in
Stuttgart, Germany (Schieftl, 2003)
a. Core samples from a surface that has been exposed to rain and other weather
variations,
b. Core samples from a surface that was permanently immersed in fresh water.
2. Core samples from a Roman aqueduct, aged for approximately 2,000 years (van der Sloot et
al., 2011),
3. Recycled concrete aggregate (RCA) that was used as roadbase in a test road in Norway
(Engelsenetal., 2009; 2010)
a. Fresh recycled concrete sampled from material used in the road base during the
field test site preparation,
b. Field samples of the recycled concrete aggregate from the roadbase after four years
of roadway use, < 10 mm sieved from the field material (therefore more
carbonated),
c. Field samples of the recycled concrete aggregate from the roadbase after four years
of roadway use, 20-120 mm sieved from field material (and then size-reduced for
laboratory testing).
Testing results from these field samples are compared to two laboratory-prepared reference
mortars from Germany (sample: Cement mortar CEM I DE) and Norway (sample: Cement mortar
CEM I NO).
4.10.2 Results and Discussion
A complete set of figures illustrating available pH-dependent leaching behavior for the comparison
materials is provided in Appendix H. In general, LSP was consistent between materials cured for
short times (i.e., 28 days) and materials exposed to field conditions for extended time periods
(Figure 4-91).
174
-------
Cement mortar CEM 1 (DE) - Cement mortar CEM 1 (NO)
ป- Roman Aqueduct - Core (2,000 yr) RCA (fresh; NO)
A Concrete - Core (40 yr exposed to rain, DE) D RCA- Roadbase (4 yrs; <10 mm, NO)
A Concrete - Core (40 yr imersed, DE) RCA - Roadbase (4 yrs; 20-120 mm; NO)
Figure 4-91. Aluminum, antimony, copper and zinc as example results from pH-dependent
leaching tests on field core samples of concrete of different ages and exposure conditions in
comparison with reference mortars. LSP was consistent between reference materials cured for
short times (i.e., 28 days) and materials exposed to field conditions for extended time periods.
The following are notable observed effects of field aging:
Arsenic and chromium leaching are shown in Figure 4-92. For arsenic, elevated and more
erratic leaching was observed for the Roman cement (entire pH domain), possibly the result
of combined carbonation and decalcification, and the German reference mortar. Chromium
leaching was greatest at neutral to alkaline pH for the Norwegian reference mortar. The
German reference sample contained a reducing agent to decrease chromate content to meet
EU regulations on occupational exposure.
The effect of carbonation (Figure 4-93) to decrease leaching of barium, calcium and
strontium at neutral to alkaline pH is evident, with assumed increasing extent of
carbonation from short cure time reference samples (minimal carbonation), four-year-old
Norwegian recycled concrete, and 2,000-year-old Roman cement (complete carbonation).
175
-------
10 12 14
Cement mortar CEM 1 (DE)
O Roman Aqueduct - Core (2,000 yr)
A Concrete - Core (40 yr exposed to rain, DE)
A Concrete - Core (40 yr imersed, DE)
Cement mortar CEM 1 (NO)
RCA (fresh; NO)
RCA- Roadbase (4 yrs; <10 mm, NO)
RCA - Roadbase (4 yrs; 20-120 mm; NO)
Figure 4-92. Arsenic and chromium results from pH-dependent leaching tests on field core
samples of concrete of different ages and exposure conditions in comparison with reference
mortars.
100000
10000
1 1000
10
1
100
10 12 14
PH
3
1
s
10 -
0.1 -:
0.01
ฃS
PH
ป "-
*-Iซ-*^A
o
10 12
14
-Cement mortar CEM I (DE)
O Roman Aqueduct - Core (2,000 yr)
A Concrete - Core (40 yr exposed to rain, DE)
A Concrete - Core (40 yr imersed, DE)
Cement mortar CEM I (NO)
RCA (fresh; NO)
RCA- Roadbase (4 yrs; <10mm, NO)
RCA - Roadbase (4 yrs; 20-120 mm; NO)
Figure 4-93. Calcium and strontium results from pH-dependent leaching tests on field core
samples of concrete of different ages and exposure conditions in comparison with reference
mortars. The effect of carbonation to decrease leaching at neutral to alkaline pH is evident.
176
-------
Chemical Speciation Insights - Cement and Concrete
l.E-01 -
^^ 1 E-02
"5 l.E-03 -
E
"T" l.E-04
| l.E-05 -
0 l.E-06 -
l.E-07
'' -* J*.
\*x:r^r "^^
x*X< ~^\xx^
f Increasing degree Njr \ \ V
of carbonation \ \ \ Nปx
\ \
pH-dependence (CEM I) , \ ^
f -[Ca+2] lwt% COS . . - * "
[Ca+2] 2 wt% COS N
[Ca+2] 2.85 wt% COS
[Ca+2] 6 wt% COS
0 2 4 6 8 10 12 1
PH
Partitioning of Ca; L/S=10, 2.85 wt% C03
1 E 1 00 -r
l.E-01
5 l.E-02 -
ฃ l.E-03
| l.E-04
"a l.E-05 -
U
l.E-06
:
! \
!
f
l.E+00
l.E-01
J l.E-02
1 l.E-03
E l.E-04
5 l.E-05
U
l.E-06
l.E-07
4
l.E-01 -r
2* l-E-02 -
i 1-E'03'!
'g' l.E-04 -',
ฐ l.E-06 -
l.E-07 1 i i i ' i ' i i i i i i ' i ' i ' i J..L.-U/ T
1 2 3 4 5 6 7 8 9 10 11 12 13 14 l
PH
DFree DDOC-bound
FeOxide DEttringite
DAA_2CaO_Fe203_Si02_8H20[s] D AA_3CaO_AI2O3_6H2O[s]
DAA_Calcite DAA_Gypsum
AA_Portlandite AA_Tobermorite-l
Partitioning of Ca; L/S=10, 1 wt% C03
I
r
r
1 2 3 4 5 6 7 8 9 10 11 12 13 1
PH
Partitioning of Ca; L/S=10, 6 wt% C03
2 3 4 5 6 7 8 9 10 11 12 13 1
PH
ROM-bound
D AA_2CaO_AI2O3_SiO2_8H2O[s]
AA_3CaO_Fe203_6H20[s]
AA_Jennite
OCa2Cd[P04]2
Figure 4-94 presents the impact of progressive extent of carbonation on the observed solubility of
Ca (upper left graph) and the change in solid and liquid phase speciation at different extents of
carbonation (i.e., 1, 2.85 and 6 percent by mass total carbonate in the initial solid phase). As the
extent of carbonation progresses as a result of the alkaline cement material reacting with carbon
dioxide (most frequently from either atmospheric or biological sources), the solubility of Ca
decreases over the pH domain from 6 to 14. Progressive extent of carbonation results in the
conversion of ettringite [Ca6Al2(S04)3(OH)i2-26(H20)], portlandite [Ca(OH)2] and calcium oxide-
aluminates and other alkaline cement phases to calcite [CaC03].
177
-------
l.E-01
2< l.E-02
^ l.E-03
"T" l.E-04
3 l.E-05
ซ l.E-06
l.E-07 -
_, .
[ ^t- - -~*jr -7]*
^ri^
-------
0.1
o.oi
0.001
0.0001
0 0.00001
0.000001
0.0000001
1
f D
[
[
^
\
\
\
n
*^ซ
- A- -CEM I Mortar (56 days)
r D Recyled Concrete Aggregate (4 yrs)
> Roman Cement (2,000 yrs)
_^
Ax
n n
n
^
0
10
12
14
PH
1 E-02
l.E-03 -
l.E-04 -
l.E-05 -
l.E-06 -
l.E-07 -
r
f
r
f
r
In
creasin>
of car
pH-depe
-[Ca+2]
[Ca+2]
[Ca+2]
[Ca+2]
[Ca+2]
[Ca+2]
**fe
3 degree
Donatior
v
*^"" "
i \
\
ndence(CEMI)
1 wt% COS
2 wt% COS
2.7 wt% COS
2.85 wt% COS
3 wt% COS
5 wt% COS
^
;==*^
\
\
\
\
X
\'X
\
ซ
\
V
\.^
0 2 4 6 8 10 12 1
PH
Figure 4-95 compares the laboratory testing and chemical speciation results (from
l.E-01
2< l.E-02
^ l.E-03
^ l.E-04
| l.E-05
ซ l.E-06
l.E-07 -
\xv^>\xx\
f Increasing degree \ie N \ \
of carbonation N \ \ %ปx
\ \ ~""x
pH-dependence (CEM Y> , \ ..
[ -[Ca+2] lwt% COS x . , ~
[Ca+2] 2 wt% COS ^
^ -[Ca+2] 2.85 wt% COS
[Ca+2] 6 wt% COS
0 2 4 6 8 10 12 1
PH
Partitioning of Ca; L/S=10, 2.85 wt% C03
1 C i 00 r
l.E-01 -
5 l.E-02
"3
E l.E-03 -
| l.E-04 -
To l.E-05
U
l.E-06 -
!
! \
! N. Y
r %^ =^,
f
!
l.E+00
l.E-01
5 l.E-02
E l.E-03
| l.E-04
l.E-06
l.E-07
4
l.E-01 -
2" l.E-02 -
| l.E-03 -
*ฃ l.E-04 -
3
!S l.E-05 -
ID
ฐ l.E-06 -
1 c n-? .
1 2 3 4 5 6 7 8 9 10 11 12 13 14 *
PH
Partitioning of Ca; L/S=10, 1 wt% C03
' ^
: ^
1 2 3 4 5 6 7 8 9 10 11 12 13 1
PH
Partitioning of Ca; L/S=10, 6 wt% C03
2 3 4 5 6 7 8 9 10 11 12 13 1
PH
DFree DDOC-bound ROM-bound
FeOxide DEttringite DAA_2CaO_AI2O3_SiO2_8H2O[s]
AA_2CaO_Fe2O3_SiO2_8H2O[s] AA_3CaO_AI2O3_6H2O[s] AA_3CaO_Fe2O3_6H2O[s]
DAA_Calcite DAA_Gypsum BAA_Jennite
AA_Portlandite AA_Tobermorite-l DCa2Cd[PO4]2
Figure 4-94) for Ca with pH dependence leaching test data from samples of cementitious materials
with a range of extent of aging. Older materials are expected to have greater extents of carbonation
179
-------
1
0.1
o.oi
0.001
0.0001
0 0.00001
0.000001
0.0000001
because of prolonged exposure. Included in
l.E-01 -
2> l.E-02
^ l.E-03 -
"ฑ l.E-04
| l.E-05 -
0 l.E-06 -
l.E-07
- <-
[ Increasin
: of car
r
pH-depe
r [Ca+2]
[Ca+2]
[ [Ca+2]
-[Ca+2]
F [Ca+2]
[Ca+2]
V-
ป*t;
* /*
3 degree ปjr
Donation \
\
ndence (CEM I) ,
1 wt% COS
2 wt% COS
2.7 wt% COS
2.85 wt% COS
_ ฃ
7^
\
\
\
\
\
N
*,
~1Tป
ซ
\\
\
*
.
\
V
v\
*x
6 wt% COS
0 2 4 6 8 10 12 1
PH
1
f D
[
[
[
^
\
\
*"-ป
-A- -CEM I Mortar (56 days)
r D Recyled Concrete Aggregate (4 yrs)
> Roman Cement (2,000 yrs)
.^
N
c
"^
1
0
10
12
14
PH
Figure 4-95 are a CEM I standard mortar after 56 days of curing (least extent of carbonation and
similar to the CEM I standard mortar in Figure I], a recycled concrete aggregate (0-32 mm
diameter) after field exposure through use in a roadbed for 4 years with Ca leaching behavior
similar to 2.7% carbonate content, and Roman cement that had been in service for approximately
2,000 years with Ca leaching behavior similar to between 3 and 6% carbonate content.
i
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-A- -CEM I Mortar (56 days)
r D Recyled Concrete Aggregate (4 yrs)
ซ Roman Cement (2,000 yrs)
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--
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l.E-03 -
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l.E-07 -
l.E-08 -1
r
r
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creasin>
of car
\*~-~
3 degree \if
Donation \
1 \
pH-dependence(CEM I)
- [Ca+2] 1 wt% COS
[Ca+2] 2 wt% COS
--- [Ca+2] 2.7 wt% COS
[Ca+2] 2.85 wt% COS
[Ca+2] 3 wt% COS
[Ca+2] 6 wt% COS
<
i
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x' \
\
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\
k >
-T*
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1 ' I ' I ' I ' ' I ' ' I
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12
14
PH
Figure 4-95. Leaching of CEM I mortar (56-day cure) with recycled concrete aggregate (field aged 4
years) and Roman cement (field aged 2,000 years) indicative of different extents of carbonation
180
-------
compared to chemical speciation modeling of the impacts of carbonation on solubility of Ca and pH-
dependence leaching test data on portland cement CEM I standard mortar after 28-day cure.
a
U
O
l.E+00
l.E-01
l.E-02
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[ \
pH-dependence (
f -[Ca+2] 1 wt% CC
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F [Ca+2] 2.7wt%(
-[Ca+2] 2.85 wt%
r [Ca+2] 3 wt% CC
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:EMI)
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[Mo04-2] 1 wt% COS
_ _ [Mo04-2] 2 wt% COS
[Mo04-2] 2.7 wt% COS
[Mo04-2] 2.85 wt% COS
[Mo04-2] 3 wt% COS
_ _ [Mo04-21 6 wt% COS
--ป-
gree /
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of carbonation \\ /
\^ /
pH-dependence(CEM I)
-[S04-2] lwt%C03
_ _ [S04-2] 2 wt% COS
___ [S04-2] 2.7 wt% COS
-[S04-2] 2.85 wtฐ/
3C03
[S04-2] 3 wt% COS
[S04-2]
6 wt% COS
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\'J
10
12
14
PH
l.E-04
"5 l.E-05 -
E
O l.E-06
U
l.E-07
'**"
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Increasing degree / *
or carbonation 11 (
pH-dependence(CEM I)
. ^ -[Cr04-2] 1 wt% COS
_ _ [Cr04-2] 2 wt% COS
[Cr04-2] 2.7 wt% COS
. -[Cr04-2] 2.85 wt% COS
. [Cr04-2] 3 wt% COS
_ _ [Cr04-2] 6 wt% C
03
\ป
\
19
i
I/
10
12
14
PH
Figure 4-96 presents the impact of progressive extent of carbonation on the observed solubility of
Ca, sulfate, Mo and Cr in comparison to pH dependence leaching test data from a standard mortar
(ref) prepared from a CEM I portland cement and cured for 28 days prior to testing. Species that
are either part of ettringite (i.e., sulfate) or co-precipitated with ettringite (i.e., as part of a solid
solution), have relatively low solubility over the pH domain from 10 to 13 where ettringite is
sparingly soluble, but have increased solubility when ettringite reacts to form calcite. Thus,
progressively increasing solubility of sulfate, Mo and Cr are observed between pH 10 to 13 with
increasing extent of carbonation.
181
-------
l.E-01
2< l.E-02
^ l.E-03
"T" l.E-04
3 l.E-05
ซ l.E-06
l.E-07 -
- +-
f
f Increasim
of car
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\
1 degree
jonatior
-
rs**>
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\
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i
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W l.E-05
r
r
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F~"^
- "
Increa;
of c
pH-dependence (
-[S04-2] 1 wt% C
[S04-2] 2 wt% C
[S04-2] 2.7 wt%
-[S04-2]2.85wtฐ/
[S04-2] 3 wt% C
_ _ [S04-2] 6 wt% C
^r
ing dec
arbona
:EM i)
DS
D3
cos
cos
DS
D3
ree s
:ion
v"\
IT
1
'/
0 2 4 6 8 10 12 14 0 2 4 6 8 10 12 1
pH pH
l.E-05
O
O
^~>
E l.E-06 -;
l.E-07
=->
1
V
Incre
of
ฎ
asing d
carbon
pH-dependence(CEM I)
. [Mo04-2] 1 wt% COS
_ _ [Mo04-2] 2 wt% COS
_-- [Mo04-2] 2.7 wt% COS
. - [Mo04-2] 2.85 wt% COS
_ _ [Mo04-2] 3 wt% COS
[Mo04-2] 6 wt% COS
--ป-
;gree /
~
-v*. -
\y
A
i*
\\
\
c
7
i
)
ป
f-^
_l
ฃ l.E-05
SMI*
E
_3
u
^m ^
-*r>
Incre
0
pH-dependence (
-[Cr04-2] lwt%C
[Cr04-2] 2 wt% C
___ [CrO4-2] 2.7 wW
^ -[CrO4-2] 2.85 wt
[Cr04-2] 3 wt% C
[Cr04-2] 6 wt% C
asing c
: carBor
CEM I)
03
03
COS
/o COS
03
03
*
egree /
lation
~\^ 1
I
V
.i
i
/
10
12
14
10
12
14
PH
PH
Figure 4-96. Chemical speciation modeling of the impacts of carbonation on solubility of Ca, SO4, Mo
and Cr compared to pH dependence leaching test data on portland cement CEM I standard mortar
after 28-day cure.
4.10.3 Case Summary/
Case 10 compared the leaching of cement and concrete samples with different aging periods,
including 28 days (standard mortar), 4 years (recycled concrete aggregate), 40 years (field test site)
and 2,000 years (Roman cement). As the concrete ages, the extent of carbonation from reaction
with atmospheric carbon dioxide increases and reduces the natural pH of the material from an
initial pH of 12-13 to a pH of approximately 9. Environmental leaching can result in further
reduction to pH 7 through decalcification. Increasing extent of carbonation results in the loss of
ettringite and the formation of calcite and barium and strontium carbonates, also resulting in
decreasing solubility of calcium, barium and strontium atpH greater than 7 with increasing extent
of carbonation. Increasing extent of carbonation also results in increases in sulfate solubility and
leaching of oxyanions coprecipitated with ettringite (i.e., molybdate and chromate).
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5 RECOMMENDATIONS FOR USE OF THE LEAF TEST METHODS FOR BENEFICIAL
USE AND DISPOSAL DECISIONS
LEAF test results can be used to provide a reasonably conservative (upper-bound) source-term for a
wide range of materials in use and disposal scenarios. The resulting source term should be used in
conjunction with additional assessment steps that include consideration of dilution and attenuation
from the source to receptor, and relevant receptor thresholds. Information presented in this report
supports grouping individual sources of similar materials based on process origin and leaching
behavior into material grouping or classes (i.e., coal fly ash from combustion of bituminous coal,
coal combustion flue gas desulfurization gypsum, blastfurnace slags, MSWI bottom ash, etc.).
Accumulation of LEAF testing data for a range of materials and over time can provide useful
estimates of uncertainty and variability associated with leaching from specific materials and
material classes. Creation of one or more databases containing leaching data used in regulatory
decision making and monitoring can facilitate efficient use of leaching data in future assessments,
including by reducing testing and evaluation costs for well-studied classes of materials.
5.1 Evaluating New Management Scenarios - Material Combinations and Pilot Studies
Leaching assessment can present two forms of challenges:
1. Evaluating a new use or disposal scenario for a previously evaluated material or material
class; and,
2. Evaluating a new material class or specific material without prior characterization of
materials within the same material class.
Careful consideration should be given to the extent of prior knowledge about both the material or
class of material, and the anticipated use or disposal scenario before proceeding. Consideration
should be given to the potential range and changes that may occur with respect to water contact,
physical integrity of the material, blending or interfaces with other materials, chemistry within the
material and of contacting solutions, and evolution of pH and redox (e.g., from atmospheric
exchange, carbonation, sulfide oxidation, organic matter degradation, etc.). Insufficient prior
leaching characterization data or experience with sufficiently similar materials under analogous
management scenarios should trigger use of a field pilot demonstration project when warranted
based on a screening assessment that includes laboratory characterization, to insure that a priori
unforeseen conditions do not result in a significant shift in the phenomena controlling leaching for
the material and scenario under consideration.
The case studies presented in this report provide the basis for recommending specific components
and considerations for initial material characterization and field demonstration projects:
1. Materials being considered should first be characterized using pH dependent leaching
(Method 1313) and either percolation column leaching (Method 1314) or as a minimum,
leaching at low liquid-to-solid ratio (Method 1316). Monolith leaching (Method 1315)
should also be carried out for scenarios where monolith mass transport is anticipated as a
significant factor controlling leaching. A sufficient number of samples based on data quality
objectives should be characterized to reflect the inherent variability of the material being
evaluated.
183
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2. Field demonstration projects should include careful collection and analysis of runoff, pore
water, leachate and other contacting water during the demonstration period. All sampling
should be carried out using techniques that avoid atmospheric exchange and oxygenation,
carbon dioxide uptake, and/or biogenic acidification during sampling. Within the material
and for collected fluids, pH, redox and conductivity should be analyzed to the extent
practical. Analysis of collected leachates and other aqueous samples should include analysis
of major and trace constituents, as well as DOC, DIG and anions.
3. Core samples from the field demonstration project should be obtained at the end of the
demonstration period and be considered to be obtained at intermediate time intervals.
Laboratory leaching analysis of the cores can provide useful insights into the chemical
speciation and physical-chemical status of the material during field aging processes. The
comparison of the leaching behavior as function of pH for different ages of the material in
combination with leachate data and batch or percolation test data at the appropriate pH
provides valuable insight in the leaching behavior over time.
4. An efficient sampling plan consists of preparing a composite of samples taken from different
locations from the pilot, lysimeter or field site for pH dependence and percolation and/or
monolith leach tests and testing individual samples at L/S=10 and the natural pH to see the
variability based on the location of the sampling.
5. Chemical speciation-based LSP and mass-transport modeling should be used to provide
insights into leaching conditions that may evolve in the field and are beyond laboratory test
conditions.
5.2 Estimating Leaching Source Terms
In Kosson et al. (2002), leaching assessment using a performance or "impact-based approach" was
proposed, that subsequently has been referred to as LEAF:
This approach focuses on the release flux of potentially toxic constituents over a
defined time interval. Thus, the management scenario is evaluated based on a source
term that incorporates consideration of system design, net infiltration and the
leaching characteristics of the material. Basing assessment and decisions on
estimated release allows consideration of the waste as containing a finite amount of
the constituent of interest, the time course of release, and the ability to adapt testing
results to a range of management scenarios. The measure of release would be the
mass of constituent released per affected area over time (i.e., release flux).
Knowledge of the release flux would allow more accurate assessment of impact to
water resources (e.g., groundwater or surface water) by defining the mass input of
constituent to the receiving body over time. Results of this impact-based approach
can provide direct input into subsequent risk assessment for decision making, either
based on site-specific analysis or using a generalized set of default assumptions.
The LEAF testing methodology allows for both empirical use of testing data for specific scenarios as
part of a screening assessment, and use of the leaching test data in conjunction with chemical
speciation and mass transport models to provide more realistic and refined, scenario-specific
184
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estimate of constituent leaching that can be used as a source-term for risk assessment. While the
result is a bounding estimate of leaching potential, consideration of waste and scenario-specific
information allows many conservative assumptions to be replaced with data. A tiered-approach
was proposed for developing the leaching source term, considering the type of evaluation being
carried out, the level of information available, and the extent of conservatism embedded in the
estimate (Figure 5-1). Subsequently, the EPA published its Methodology for Evaluating Encapsulated
Beneficial Uses of Coal Combustion Residuals (2013b; also EPA, 2014) which provides for a tiered
approach specifically applied to a more limited set of uses of two secondary materials (i.e., coal fly
ash use as a cement replacement in concrete and FGD gypsum use in gypsum board). The
observations and information gathered in this report provides a basis for the more detailed
recommendations provided below on the use of LEAF test methods, consistent with the initially
proposed methodology (2002) and the EPA methodology (2013). Additional relevant details
regarding assessment approaches can be found in Kosson et al (2002), Sanchez etal (2002) and
Kosson et al (1996), EN 12920 (1996), Verschoor et al (2008), Carter et al (2009), Postma et al
(2009), van der Slootand van Zomeren (2012), and Hjelmar etal (2013). These methodologies
also recognize that decision making typically is based on a water concentration-based comparison
to human health or ecologically based standards, or an exposure assessment at a point of
compliance. It must be emphasized that these recommendations for use of leach testing data only
provide the approach for estimating the leaching source term (i.e., concentrations and amounts of a
constituents leaching from the material under a specific scenario). Additional determinations are
needed to define or account for (i) the location that serves as the basis for exposure assessment
following constituent leaching release from a source scenario (e.g., point of compliance), (ii)
dilution and attenuation in the vadose zone and groundwater or surface water from the point of
release to the point of compliance, and (iii) appropriate exposure scenarios or reference thresholds
(e.g., human health or ecological thresholds). These evaluations are typically incorporated into a
model of constituent fate and transport leading to possible receptor exposure (e.g., groundwater
transport to a drinking water well, with water ingestion as the exposure pathway).
185
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MATERIAL
WASTE, SOIL OR PRODUCT
MANAGEMENT SCENARIO
Specific disposal or
utilization scenario
Default cases
Specific or
Default (see text)
Scenario
LEVEL A
LEVELB
Random compliance testing1
LEVELC
Figure 5-1. A tiered framework for evaluating leaching (Kosson et al, 2002)
5.3 Scenario Definition
Defining the material use or disposal scenario is the first step to selecting the appropriate leaching
tests and basis for interpreting the resulting data. The extent of information needed as part of the
scenario definition increases as the evaluation seeks to achieve a more detailed and refined
estimate of constituent leaching. The initial scenario definition should as a minimum answer the
following questions:
I. What is the applicable pH domain? The applicable pH domain will extend at least from the
material's natural pH to neutral pH (pH 7), and may be further extended based (i) material
characteristics that may result in self-acidification through oxidation or biodegradation
processes (e.g., materials containing significant amounts of sulfides, other reactive phases or
biodegradable organic matter), (ii) commingling with either more alkaline or more acidic
materials, (iii) external sources of acid or alkalinity such as from adjacent materials or the
chemistry of contacting water. Case studies in this report provide examples of applicable pH
domains for several materials and scenarios.
2. Is the material oxidized as produced and subject to reducing conditions under the proposed use
or disposal scenario? Causes of reducing conditions to form include commingling with other
reducing materials such as slags or some mining wastes, presence of significant amounts of
biodegradable organic matter and barriers to exchange of atmospheric oxygen.
186
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3. 7s the material chemically reduced and subject to oxidizing conditions? Causes of oxidizing
conditions for initially reduced material include exposure to air and oxygenated water (i.e.,
infiltration).
4. Will the primary mode of water contact be through infiltration and percolation through the
material or through contact and exchange at the exterior surface of a large mass or monolith
(e.g., as would occur for materials compacted to low hydraulic conductivity)?
5.4 Screening Assessment (Tier 1)
Recommendations for use of LEAF testing in screening assessment (Tier 1) and equilibrium-based
assessment (Tier 2) are provided in Table 5-1. Leaching assessment for screening purposes (Tier 1)
can be based on the estimated maximum leaching concentration anticipated for each COPC. At this
tier, maximum LSP is estimated based on the maximum concentration for each COPC measured over
the applicable pH domain as defined by the scenario using the pH dependent leaching test (i.e.,
Method 1313) and then adjusted for the anticipated pore water L/S, unless it can be demonstrated
that the specific COPC is solubility controlled throughout the applicable pH domain. The adjusted
(conservative) concentration at the applicable pore water LS can be achieved by
Ci.adjusted = Q,LS=10 * CF
Where CiiadjUSted is the adjusted concentration of constituent /, Q LS=10 is the maximum
concentration over the relevant pH domain at L/S=10 mL/g (as from Method 1313), and CF is the
correction factor which is equal to 10 divided by the pore water L/S (which can be approximated as
the material porosity.
Cases 5 and 8 demonstrated that an effective pore water L/S of 0.5 L/kg is appropriate for coarse
landfilled materials subject to percolation and preferential flow, resulting in a multiplier of 20 to
adjust the eluate concentrations measured using Method 1313. This screening approach does not
account for the amount of material being evaluated that would be present under the scenario (i.e., it
implies an "infinite source" of material or COPCs).
5.5 Equilibrium-based Assessment (Tier 2)
An equilibrium-based leaching evaluation would consider LSP over the applicable pH and redox
domains and the maximum amountof each COPC available for leaching. Method 1313 results in
conjunction with Method 1316 at L/S of 2 mL/g would be used to assess whether LSP for each
COPC was constrained by aqueous solubility or availability. If the COPC exhibits significantly
greater concentration at L/S of 2 mL/g (Method 1316) then measured from Method 1313 at the pH
corresponding with the pH measured at L/S of 2 mL/g, then the Method 1313 results are
considered to be availability constrained and the maximum concentration from Method 1313 over
the applicable pH domain that is adjusted to the pore water L/S is used as the peak source
concentration. If the COPC at L/S of 2 mL/g is the same as (within uncertainty) the concentration
measured at the corresponding pH from Method 1313, then the COPC is considered solubility
constrained and the maximum concentration over the applicable pH domain from Method 1313 is
used as the peak source concentration.
187
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Table 5-1. Tier 1 Screening Assessment and Tier 2 Equilibrium-Based Assessment - Summary of recommended test methods and analyses.
Assessment Type
Tier 1 -
Screening
Assessment1
Leaching
Methods
Method 1313
(applicable pH
range only2)
Eluate Analyses
pH, EC, CO PCs, DOC
Tier 2 - Equilibrium-based Assessment
Tier 2A
Compliance
Tier 2B
Characterization
Tier 2C
Quality Control
Method 1313
(applicable pH
range + pH=2,
7, 9 if not
included)
Method 1316
(L/S=2 mL/g
or lowest L/S
eluate)
Method 1313
(full set of
eluates)
Method 1316
(full set of
eluates)
Method 1313
atnaturalpH,
andpH=2, 7
and/or 9
pH, EC (natural pH
only), COPCs, DOC
pH, EC & pe (natural pH
only)6, COPCs, DOC,
DIG, major and minor
constituents (including
P and S)
pH, EC, relevant COPCs8
(natural pH and for
availability) to meet
environmental
requirements and
additional constituents
to meet beneficial use
requirements
Assessment Basis
Maximum leachate cone.3 estimated as 2Ox or lOx maximum eluate cone, for
highly soluble constituents in granular materials4'5 and the measured maximum
eluate cone, for monolithic materials and solubility controlled constituents (all
materials).
^H
Availability estimated as maximum release at measured pH intervals including
pH=2 and 9; provides basis for finite source by assuming that availability is
maximum cumulative release under field conditions. EC used to estimate ionic
strength. Acid/base neutralization capacity to pH=7. Maximum leachate cone.
estimated as determined from Tier 2B based on Method 1313 results over
applicable pH domain. Method 1316 allows identification of solubility
controlled vs highly soluble constituents.
Availability as indicated in Tier 2A.
Liquid-solid partitioning as a function of pH used for speciation assessment.7
Provides baseline understanding of material leaching behavior. Supports
chemical speciation simulations to understand effects of changes in L/S, pH,
redox, and reactive constituents (e.g., DOC, carbon dioxide, etc.). Maximum
leaching concentration as indicated for Tier 1 or based on simulation results at
L/S of the material pore solution. Method 1316 provides basis for
determination of solubility control and verification of chemical speciation
modeling at low L/S.
Used to verify leaching over "applicable" pH range, acid/base neutralization
capacity to pH=7, and availability of relevant COPCs and other (if applicable)
constituents central to beneficial use application (e.g., Ca, sulfate, etc.). Assumes
definition after completion of Tier 2B and/or analogous prior information.9
Chemical analysis only for determination of leaching at natural pH and
availability (2 or 3 extracts). Further simplification may be possible based on
additional available information.
188
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Notes for Table 5-1:
regulatory frameworks based on a source term concentration, the maximum estimated leaching concentration is recommended for
use in screening assessment. For regulatory frameworks based on the total mass of constituent potentially leached, availability is
recommended for use in screening assessment.
2The applicable pH range is determined considering the material's natural pH, changes in pH due to material aging processes, infiltration
conditions, and interfaces or comingling with other materials.
3"conc." is used as an abbreviation for concentration or concentrations.
4Twenty times the maximum eluate concentration is recommended for highly soluble species when the material is homogeneous (e.g., coal
fly ash) and ten times the maximum eluate concentration is recommended for heterogeneous materials (e.g., MSW incinerator bottom
ash) where significant preferential flow is anticipated. Both multipliers are to account for the increased concentrations expected when
estimating pore water concentrations (L/S=0.2 to 0.5 L/kg) from test conditions of L/S=10 mL/g).
5Highly soluble species are Group IA elements (i.e., Na, K), anions (i.e., bromide, chloride, fluoride, nitrate), and oxyanions (i.e., As, B, Cr, Se,
Mo, V.).
determination of EC and pe is recommended for natural pH eluate only. The sensitivity and uncertainty of pe measurements are
recognized but pe measurement will provide a useful indication of whether or not the material is inherently reducing under abiotic and
anoxic conditions.
7Speciation assessment refers to consideration of the effects of changes in pH, redox conditions, extent of carbonation, complexation with
dissolved organic carbon, etc. which may be accomplished heuristically or in combination with geochemical speciation modeling.
8Relevant COPCs are those constituents that are present in the material and have been found through Tier 2B characterization and/or
prior information to leach at concentrations or release values that approach or challenge regulatory or quality control thresholds.
9Prior information, such as characterization information from similar materials, may reduce or supplant the need for or extent of Tier 2B
characterization.
189
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The maximum amount of a COPC that is available to leach per unit mass of material (i.e., "finite
source") is based on the maximum constituent release (i.e., mg/kg) over the entire pH domain of
Method 1313 (typically pH 2 for cations andpH 9 for oxyanions). The amount of each COPC that
leaches should be estimated based on the amount of contacting water per unit time (i.e., L/S per
year) times the estimated peak concentration.
Initial characterization testing (Tier 2B) should include analysis of both major and trace
constituents in all leaching test eluates because knowledge of the major constituents that control
release of the trace constituents provides insights into the factors that may result in changes in
leaching and allow for calibration of chemical speciation models. However, prior knowledge from
testing of analogous materials may reduce the need for or extent of characterization testing.
For periodic demonstration of compliance with regulatory thresholds, the extent of Method 1313
testing can be reduced to the applicable pH domain and regulatory COPCs, pH and conductivity23.
For quality control purposes, the extent of Method 1313 testing can be further reduced to only the
natural pH value and along with the pH 2 and/or 9 as needed to measure availability for the
relevant COPCs (those that are present and leach at concentrations that approach thresholds) and
conductivity.
Knowledge of the chemical behavior of the COPCs and the scenario should be used to evaluate if
higher leaching concentrations are anticipated because of changes in redox conditions. Anticipated
changes in leaching because of changes in L/S, redox or chemical conditions can also be evaluated
using chemical speciation modeling as demonstrated for the evaluation cases in this report.
5.6 Mass Transport-based Assessment (Tier 3)
Mass transport-based assessment can be divided into two distinct regimes: (i) percolation through
the material as the predominant leaching mechanism, and (ii) mass transport from monolithic
materials where diffusion to the exterior surface of the bulk material and surface dissolution
control constituent leaching. Intermediate conditions between the percolation and monolith
regimes, such as for large aggregates and cracked monolithic materials also exist, but are beyond
the scope of this discussion. Summaries of recommended LEAF testing and evaluation are provided
for percolation mass transport-based assessment and monolithic mass transport-based assessment
in Table 5-2 and Table 5-3, respectively.
Percolation based regimes can be evaluated through use of the pH dependent test (i.e., Method
1313) in conjunction with the percolation column test (i.e., Method 1314) or batch testing (Method
1316) for initial leachate concentrations. Considering the results of Cases 2, 5 and 8 (Sections 4.2,
4.5 and 4.8) initial eluates from Method 1314 or low L/S results from Method 1316 are good
indicators of the anticipated COPC concentrations in initial field leachates and Method 1314
provides the evolution of the leachate concentrations over prolonged periods based on the
progression of the L/S based on the field material geometry and annual infiltration rates.
23 Measurement of conductivity is recommended as an indicator of total ionic strength and therefore can also provide an
indication if there is a significant change in leaching of total salts over the monitoring interval.
190
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Table 5-2. Tier 3 Percolation Mass Transport-Based Assessment - Summary of recommended test methods and analyses.
Assessment Type Leaching Eluate Analyses
Methods
Tier 3 - Percolation Mass Transfer Rate-based Assessment
Tier 3A
Compliance
Method 1313
(pH=2, 9,
applicable pH
domain)
Method 1314
(to L/S=2
mL/g)
Tier 3B
Characterization
Tier 3C
Quality Control
Method 1313
(full set of
eluates)
Method 1314
(full set of
eluates)
Method 1316
(L/S=2)
Method 1313
atpH=2, 7
and/or 9 and
Method 1316
at L/S = 2
pH, EC (natural pH
only), COPCs, DOC
pH, EC (natural pH
only), COPCs, DOC, DIG,
major and minor
constituents
pH, EC, COPCs (1313
for availability and
1314 at L/S of peak
release) to meet
environmental
requirements,
additional constituents
to meet beneficial use
requirements
Assessment Basis
Allows verification of liquid-solid partitioning at natural pH and availability
(from Method 1313). Maximum leachate cone, estimated as established by Tier
3B as greater of either i) maximum cone, from Method 1314 up to L/S =2 mL/g,
or ii) maximum cone, from Method 1316, or iii) maximum cone, from Method
1313 over applicable pH domain.
Availability and leaching as a function of pH and evaluation of potential changes
in conditions as indicated for Tier 2 B.
Method 1314 provides leachate evolution as a function of L/S for source term
based on test elution curve. Supports reactive transport simulations to consider
sensitivity to field conditions such as infiltration chemistry, preferential flow
and material aging. Provides basis for verification of chemical speciation
modeling at low L/S.
Method 1313 extractions used to verify acid/base neutralization capacity to
pH=7, and availability of selected COPCs and other (if applicable) constituents
central to beneficial use application (e.g., Ca, sulfate, etc.). Method 1314 extract
at L/S of prior peak concentration to verify maximum leaching cone. Assumes
definition after completion of Tier 3B Characterization. Chemical analysis only
for determination of leaching at peak release cone, and availability (2 or 3
extracts). Further simplification may be possible based on additional available
information.
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Table 5-3. Tier 3 Monolith Mass Transport-Based Assessment - Summary of recommended test methods and analyses1.
Assessment Type Leaching Eluate Analyses
Methods
Tier 3 - Monolith Mass Transport-based Assessment
Tier 3A
Compliance
Tier 3B
Characterization
Tier 3C
Quality Control
Method 1313
(pH=2, 9,
applicable pH
domain)
Method 1315
(to 7 days)
Method 1313
(full set of
eluates)
Method 1314
(full set of
eluates)
Method 1315
(to 64 days)
Method 1313
atpH=2, 7
and/or 9 and
Method 1315
(to 7 days)
pH, EC (natural pH for
Method 1313 and all
Method 1315 eluates),
COPCs, DOC
pH, EC (natural pH only
for Method 1313 and
all Method 1314, and
1315 eluates),
COPCs, DOC, DIG, major
and minor constituents
Assessment Basis
Allows verification of liquid-solid partitioning at natural pH and availability
(from Method 1313). Maximum leachate cone, estimated as established by Tier
3B as greater of either i) maximum cone, from Method 1314 up to L/S =2 mL/g,
or ii) maximum cone, from Method 1316, or iii) maximum cone, from Method
1313 over applicable pH domain.
pH, EC, COPCs (1313
for availability and
1314 at L/S of peak
release) to meet
environmental
requirements,
additional constituents
to meet beneficial use
requirements
Availability and leaching as a function of pH as indicated for Tier 2B.
Method 1314 (crushed material) up to L/S=2 provides estimate of initial pore
water composition.
Method 1315 provides cumulative release as a function of leaching time for
saturated and intermittent wetting conditions. Also provides basis for
estimating reactive transport parameters (e.g., tortuosity) for simulation of
evolving conditions (e.g., low liquid to surface area, external solution chemistry,
carbonation, oxidation, intermittent wetting, etc.). Provides basis for Tier 3C
quality control.
Method 1313 extractions used to verify acid/base neutralization capacity to
pH=7, and availability of selected COPCs and other (if applicable) constituents
central to beneficial use application (e.g., Ca, sulfate, etc.). Method 1315
cumulative release to 7 days to verify consistency with characterization results
(Tier 2B). Assumes definition after completion of Tier 3B Characterization.
Further simplification may be possible based on additional available
information.
xThe cure time prior to testing of monolithic materials is an important consideration because for many cementitious materials, hydration and
microstructure development continues for more than a one year, with initial cure times of 90 days recommended prior to Method 1315 testing.
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Initial percolation characterization testing should include analysis of both major and trace
constituents in all leaching test eluates (Methods 1313 and 1314 or 1316) because knowledge of
the major constituents (such as Ca, Fe, DOC or SCU) that control release of the trace constituents
provides insights into the factors that may result in changes in leaching and allow for calibration of
chemical speciation models. For compliance testing, Method 1313 can be used as described above
(Equilibrium Based Assessment) and Method 1314 analysis can be simplified to analysis of eluates
as prescribed as Option E in Table 1 of the method (i.e. at L/S=0.2 and along with two composite
samples) for COPCs, pH and conductivity, thus providing peak eluate concentrations and cumulative
release. For quality control purposes, either Method 1313 reduced to only the pH values that result
in peak concentrations over the applicable pH domain and the relevant COPCs or Method 1314
testing as described for compliance testing can be used.
Monolith regimes can be evaluated based on use of Method 1315 in conjunction with Method 1313
(Table 5-3). A detailed example of use of this information for evaluation of use of coal combustion
fly ash as a substitute for Portland cement in concrete considering intermittent water contact via
precipitation is available (EPA, 2013a). An example approach for use of empirical data from Method
1313 (i.e., for availability) and Method 1315 (i.e., for estimated effective diffusivity) is provided for
MSWI bottom ash scenarios in Kosson et al (1996). These approaches can also be used in
conjunction with chemical speciation based mass transfer models (see Section 3) to provide
insights into potential changes in leaching that may occur in response to changing conditions within
or on the external surface of the material being evaluated.
Initial monolith characterization testing should include analysis of both major and trace
constituents in all leaching test eluates (Methods 1313 and 1315) because knowledge of the major
constituents that control release of the trace constituents provides insights into the factors that may
result in changes in leaching and allow for calibration of chemical speciation models. For
compliance testing, Method 1313 should be used to assess availability and solubility at the natural
pH of the material (i.e., no acid or base addition) and Method 1315 analysis can be simplified to
analysis of eluates at exchange up to 7 days for COPCs, pH and conductivity. For quality control
purposes, Method 1315 can be reduced to only analysis of pH and conductivity and composited
eluates up to 7 days for COPCs to determine cumulative release.
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6 CONCLUSIONS
This report evaluated the relationships between laboratory leaching tests as defined by the
Leaching Environmental Assessment Framework (LEAF) or analogous EU/international test
methods and leaching of constituents of potential concern (COPCs) from a broad range of materials
during field disposal and beneficial use conditions. This evaluation was achieved by defining a
framework for interpretation of laboratory testing results, comparison of laboratory testing on "as
produced" material, laboratory testing of "field aged" material, and results from field leaching
studies, and illustrating the use of chemical speciation modeling as a tool to facilitate evaluation of
scenarios beyond the conditions of laboratory testing.
Ten field evaluation cases for disposal or beneficial use that have a combination of laboratory
testing and field analysis were considered that included the following materials: (i) coal fly ash
(CFA), (ii) fixated scrubber sludge typically produced by combining coal fly ash with acid gas
scrubber residue and lime at some coal fired power plants (FSSL), (iii) municipal solid waste
incinerator bottom ash (MSWI-BA), (iv) a predominantly inorganic waste mixture comprised of
residues from soil cleanup residues, contaminated soil, sediments, C&D waste and small industry
waste(IND), (v) municipal solid waste (MSW), (vi) cement-stabilized municipal solid waste
incinerator fly ash (S-MSWI-FA), and (vii) Portland cement mortars and concrete. The field data
presented in this report include (i) leachate from field lysimeters, (ii) porewater from landfill or use
applications, (iii) eluate from leaching tests on sample cores taken from field sites, and (iv) leachate
collected from landfills. Principal uncertainties for field data in many cases include (i) the extent of
preferential flow or dilution that may have occurred during water contact within the material and in
sampling of landfill leachate, and (ii) the exact exposure and aging conditions that contribute to the
field data.
Primary aging processes and reactions that can impact leaching are (i) establishment of reducing
conditions from biogenic processes (i.e., degradation of organic matter), (ii) oxidation from
atmospheric exchange, and (iii) carbonation from either atmospheric exchange, dissolved carbon
dioxide (or carbonates) in contacting water, or reaction with biogenic carbon dioxide. Other slow
mineral formation processes, such as with stabilized waste, may result in small changes in leaching
relative to freshly prepared material after initial curing periods (i.e., 90 days). Constituents in
infiltrating or contacting water, either from natural processes (e.g., DOC in the form of humic
substances from leaf decay) or from anthropogenic origin (e.g., leaching from up gradient disposed
materials) may have a substantial effect on leaching.
Based on the above comparisons and observations along with results discussed in earlier sections,
the following conclusions and recommendations are drawn:
1. The combination of results from pH-dependent leaching tests (i.e., EPA Method 1313 or
CEN/TS 14429 or CEN/TS 14997) and percolation column tests (i.e., EPA Method 1314 or
CEN/TS 14405) can be used to provide accurate estimates within defined uncertainty
bounds of maximum field leachate concentrations, extent of leaching and expected leaching
responses over time and to changes in environmental conditions under both disposal and
use scenarios. Leaching test results should be evaluated with consideration of the potential
for changes in leaching conditions that are beyond the domain of laboratory test conditions,
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such as oxidation of reduced materials, reduction of oxidized material, carbonation and
introduction of DOC from external sources. When field conditions beyond the domain of
laboratory test conditions are plausible, chemical speciation modeling can be used to
consider the magnitude of effects from the postulated changing conditions. Peak leaching
concentrations and availability of COPCs estimated from laboratory testing can be used to
provide a conservative estimate (i.e., reasonable upper bound) of anticipated field leaching.
Results from batch testing at low L/S ratios (i.e., EPA Method 1316 or EN 12457) can also be
used in place of column test results when column testing is impractical. Thus, the LEAF
laboratory leaching tests can be used effectively to estimate the field leaching behavior of a
wide range of materials under both disposal and use conditions. Interpretation of the
leaching test results should be in the context of the controlling physical and chemical
mechanisms of the field scenario.
a. For elements and species that are highly soluble, solubility is not a function of pH
and a saturated solution is not expected to occur (e.g., Cl, K, Na). The initial eluates
from a column leaching test (i.e., Method 1314) are a reasonable estimate of the
expected peak concentration from field leaching and are representative of
porewater solutions. Constituent concentrations obtained from the pH-dependent
leaching test (i.e., Method 1313) at the material natural pH at L/S=10 mL/g can be
multiplied by the ratio of L/S at batch testing conditions to the L/S at porewater
conditions based on field porosity (i.e., L/S=0.2-0.5 mL/g with resulting factors of
20-50) to estimate anticipated concentrations under porewater conditions.
Similarly, results from an L/S dependence leaching test (i.e., Method 1316) at
L/S=0.5 mL/g can provide a reasonable estimate of the expected peak concentration
from field leaching. However, for many conditions, because of either solubility
constraints or preferential flow, the estimated value under pore water conditions
may be overly conservative and not realized in field leachate. Considering these
factors, an adjustment factor of 20 has been shown to be a reasonable basis for
estimating peak concentrations from LSP data obtained at L/S=10 mL/g. For
monolithic materials, peak concentrations are indicative of a "first flush"
phenomenon occurring during initial surface wetting after a period without
leaching, whereby internal concentration gradients have relaxed. Peak
concentrations will decline rapidly during a prolonged wetting event because of
diffusion and dissolution limitations on leaching at the external surface. Higher
concentrations will return after a non-flow period because of relaxation of internal
concentration gradients and re-equilibration of porewater.
b. For elements and species where solubility is pH-dependent and a saturated solution
is found to occur based on pH-dependence and column or batch L/S leaching tests,
the pH-dependent leaching test (i.e., Method 1313) provides a reasonable estimate
of the expected field leachate concentrations over the anticipated pH domain with
solubility control, which in turn may be diluted by flow channeling that bypasses
contact with the solid material (such as often happens with collection systems or
large spatial integration). For monolithic materials, local equilibrium between the
porewater and monolith surface can be anticipated as a result of intermittent
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infiltration and wetting, followed by diffusion controlled leaching and gradient
relaxation.
c. For field percolation scenarios and for elements and species that are highly soluble
over a limited portion of the anticipated pH domain (e.g., oxyanions of Cr, As, V),
laboratory column test results may be indicative of leaching under initial conditions
and as long as oxidized field conditions are anticipated. Peak barium concentrations
under oxidized field conditions may be much lower than indicated by laboratory
testing because of precipitation with sulfate present at higher concentrations in pore
water and leachate. Under field reducing conditions, several oxyanions (e.g., As, Cr,
Mo, Se) along with phosphorus and barium exhibit leaching behavior as highly
soluble species, a result, in part, of loss of iron oxide sorptive surfaces during iron
reduction and mobilization, and therefore high concentrations of iron in leachate
should be considered as indicative of reducing conditions. The resulting peak field
leachate concentrations are greater than measured during laboratory column testing
because the laboratory column test methods typically do not achieve the strongly
reduced conditions. As a result, the peak leachate concentration for these
constituents under reducing conditions (if anticipated] is best conservatively
estimated based on the mass of the constituent available for leaching based on the
pH-dependent leaching test multiplied by the correction factor from L/S=10 L/kg to
the L/S based on field porosity.
d. Highly alkaline materials (e.g., cement stabilized wastes, alkaline fly ashes, etc.) are
likely to exhibit highly alkaline natural pH during laboratory testing (ll 7.0) conditions. Carbonation will result in
lower solubility of Group II elements of the periodic table (i.e., calcium, strontium,
etc.) due to formation of carbonate minerals, and loss of ettringite can result in
increased leaching of co-precipitated oxyanions (e.g., chromate, molybdate,
arsenate). Leaching of solubility controlled constituents will reflect the liquid-solid
partitioning as indicated by the pH-dependent test results at the resultant pH. Thus,
leaching for these constituents should be evaluated based on the pH domain from
the initial natural pH of the material to a near neutral pH or the anticipated pH
domain anticipated for mixed materials.
e. Dissolved organic carbon (DOC), often in the form of substances analogous to humic
substances or volatile fatty acids, can result in complexation of several elements
(e.g., copper, chromium), and thereby increase measured aqueous phase
concentrations of these elements during laboratory testing and under field
conditions. Reducing conditions in the field along with high organic matter content
in materials being managed can result in elevated concentrations of DOC in the
leachate not observed in results from laboratory test methods.
Field testing of new use or disposal scenarios or new classes of materials to be used or
disposed in new ways is highly beneficial to understanding the factors that control leaching
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for the specific scenario. Thereafter, materials within a given class can be anticipated to
behave similarly under the established use or disposal scenario and the LEAF testing
approach can be used to distinguish "acceptable" versus "unacceptable" materials and use
conditions within the general class of materials and scenario. The EPA guidance on
beneficial use of coal fly ash in concrete (EPA, 2014) provides an example of the use of LEAF
test results in such decisions.
3. Establishment of a national database of LEAF laboratory leaching test results for materials
and leaching observed under field conditions would provide useful insights for evaluation of
new cases and material use and disposal decisions.
4. Field testing should include (i) sampling and leaching characterization of the initial
material, including pH-dependent, column and monolithic mass transfer rate (where
applicable) testing; (ii) field leachate collection and monitoring over extended time frames
(i.e., several years); and (iii) collection and characterization of test materials after prolonged
field exposure (i.e., core samples from field test sites). Sample collection systems and
subsequent handling need to be designed to avoid sample changes prior to analysis that
degrade the representativeness of the samples and can result in misleading results (e.g.,
sample oxidation or carbonation during collection or handling resulting in changes in pH
and constituent speciation). Furthermore, sample analysis should include a full suite of
major and trace constituents that influence and provide a context for understanding COPC
leaching.
5. Chemical speciation modeling of liquid-solid partitioning can be used for understanding the
mechanisms (e.g., mineral phases, sorption and aqueous phase complexation phenomena)
controlling leaching of the full range of constituents in the laboratory and the field, and
understanding material leaching under conditions that are not readily subject to testing.
Although the general behavior of many of the major and trace constituents are reasonably
represented in relevant scenarios, application of chemical speciation modeling to waste
management currently is constrained by the availability of test data for identifying
important solid phases and the range of available thermodynamic data available for model
parameters. Application of chemical speciation modeling as a tool for understanding waste
management should be expanded, along with underlying research to fill data gaps.
6. Single point leaching tests and other common leaching assessment approaches cannot
provide needed insights into the expected leaching performance of materials under the
range of expected field conditions. The LEAF integrated evaluation of multiple types of
leaching test data (i.e., pH dependent LSP along with percolation and/or monolithic mass
transport behavior) and field data within the context of understanding fundamental
leaching behavior (i.e., processes controlling liquid-solid partitioning and mass transport
rates), along with use of chemical speciation based modeling provides extensive insights
into the expected leaching behavior over a range of field conditions that cannot be obtained
otherwise. The resulting estimates of COPC release reduce the use of conservative
assumptions in favor of more complete data and refined speciation models, and
consequently expands alternatives and provides a sound scientific basis for making
decisions about appropriate disposal or use of secondary materials on the ground.
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208
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APPENDIX A. CHEMICAL SPECIATIOIM MODELS FOR EXAMPLE CASES
TABLE OF CONTENTS
Coal Fly Ash A-2
MSWI Bottom Ash A-6
Inorganic Industrial Waste (Nauerna Landfill) A-ll
MSW A-16
Stabilized Waste A-21
Concrete A-26
A-l
-------
Table A-l. Chemical Speciation Fingerprint for Coal Combustion Fly Ash
Chemical Speciation Fingerprint - Municipal Solid Waste Landfill
LeachXS
2012
Prediction case
Speciation session
Material
Solved fraction DOC
Sum of pH and pe
L/S
Clay
HFO
SHA
Percolation material
Avg L/S first perc. f ractii
LtoF MSW
Landgraaf mix
Mixed organicwaste DS
0.2
13.00
10.0000
l.OOOE-01
l.OOOE-02
4.000E-02
Mixed organicwaste DS
0.1240
NL(P,1,1)
I/kg
kg/kg
kg/kg
kg/kg
NL(C,1,D
I/kg
DOC/DHAdata
pH
1.00
2.75
3.69
6.37
6.81
7.48
8.78
10.32
11.66
14.00
Polynomial coeficients
[DOC] (kg/I)
4.539E-04
2.810E-04
1.790E-04
1.470E-04
1.730E-04
1.740E-04
3.330E-04
6.195E-04
8.380E-04
9.574E-04
DMA fraction
0.55
0.40
0.30
0.25
0.20
0.20
0.25
0.35
0.55
0.90
[DMA] (kg/I)
2.496E-04
1.124E-04
5.370E-05
3.675E-05
3.460E-05
3.480E-05
8.325E-05
2.168E-04
4.609E-04
8.617E-04
CO
Cl
C2
C3
C4
C5
-3.446E+00
-8.161E-02
-7.705E-02
1.349E-02
-5.311E-04
O.OOOE+00
Reactant concentrations
Reactant
Ag+
AI+3
H3As04
H3B03
Ba+2
Br-
Ca+2
Cd+2
Cl-
Selected Minerals
AI[OH]3[a]
alpha-TCP
Analbite
Anglesite
Anhydrite
Ba[SCr]04[96%S04]
BaSrS04[50%Ba]
mg/kg
not measured
3.076E+03
6.116E-01
7.289E+01
1.567E+01
9.010E+00
2.272E+04
1.695E+01
2.330E+03
Birnessite
Brucite
Ca2Zn[P04]2
CaCu2[P04]2
Calcite
CaMo04[c]
Cerrusite
Reactant
Cr04-2
Cu+2
F-
Fe+3
H2C03
Hg+2
1-
K+
Li+
CuC03[s]
Diopside
Dolomite
Fe_Vanadate
Fe2[OH]4Se03
Ferrihydrite
Fluorite
mg/kg
5.273E+01
2.342E+02
1.680E+02
1.341E+04
3.010E+04
not measured
not measured
1.584E+03
2.670E+00
Huntite
hydrozincite
Magnesite
Manganite
NiC03[s]
Nsutite
OCP
Reactant
Mg+2
Mn+2
Mo04-2
Na+
NH4+
Ni+2
N03-
P04-3
Pb+2
Otavite
Pb2V207
Pb3[V04]2
PbMo04[c]
Rhodochrosite
Strontianite
Talc
mg/kg
1.632E+03
3.392E+02
7.673E+00
2.079E+03
not measured
8.473E+01
not measured
7.881E+01
5.878E+02
Wairakite
Witherite
Zn[OH]2[B]
ZnC03:H20
Reactant
S04-2
Sb[OH]6-
Se04-2
H4Si04
Sr+2
Th+4
U02+
V02+
Zn+2
mg/kg
2.769E+03
1.813E+00
5.495E-01
1.973E+03
6.760E+01
not measured
not measured
4.727E+00
2.110E+03
A-2
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3 b b b c
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Concentration (mol/l)
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bob
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pH dependent test data
Model description for L/S=10 in L/kg
Percolation column data
Model prediction for L/S=0.3 in L/kg
^
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PH
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l.OE-04
l.OE-05
l.OE-06
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Figure A-2. Chemical speciation model for constituents in coal combustion fly ash.
A-4
-------
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3
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a
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o
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bob
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Concentration (mol/l)
3 b b b c
3 0 0 0 C
1 1
/ ^J
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1 1
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Concentration (mol/l)
3 b b b c
3 0 0 0 C
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-------
Table A-2. Chemical Speciation Fingerprint for MSWI Bottom Ash
Chemical Speciation Fingerprint - Municipal Solid Waste Incinerator Bottom Ash
LeachXS
2012
Prediction case
Speciation session
Material
Solved fraction DOC
Sum of pH and pe
L/S
Clay
HFO
SHA
Percolation material
Avg L/S first perc. fractions
Reactant concentrations
Reactant
Ag+
AI+3
H3As04
H3B03
Ba+2
Br-
Ca+2
Cd+2
Cl-
Selected Minerals
AA_3CaO_AI203_6H20[s]
AA_3CaO_Fe203_6H20[s]
AA_AI[OH]3[am]
AA_Brucite
AA_Calcite
AA_Fe[OH]3[microcr]
LtoFMSWI BAAust + kol
MSWI BA Austria + kolom AA
MSWI Bottom ash Austria (P,l,l)
0.2
13.00
10.0000
O.OOOE+00
7.000E-04
2.000E-03
MSWIBA-AA(C,1,D
0.2195
mg/kg
not measured
3.614E+03
1.837E-01
2.180E+01
1.463E+01
not measured
5.178E+04
4.110E+00
2.000E+04
I/kg
kg/kg
kg/kg
kg/kg
I/kg
Reactant
Cr04-2
Cu+2
F-
Fe+3
H2C03
Hg+2
1-
K+
Li+
AA_Gypsum
AA_Magnesite
AA_Portlandite
BaSrS04[50%Ba]
Ca2Cd[P04]2
Ca4Cd[P04]30H
DOC/DHA data
pH
1.00
3.46
4.01
5.70
7.26
8.79
9.62
10.68
11.86
14.00
mg/kg
9.543E+00
1.674E+02
5.000E+01
2.079E+03
3.800E+04
not measured
not measured
1.373E+03
2.760E+00
Cd[OH]2[A]
Cr[OH]3[C]
Cu[OH]2[s]
Manganite
Ni[OH]2[s]
OCP
[DOC] (kg/I)
6.711E-05
4.320E-05
4.070E-05
4.700E-05
4.880E-05
4.820E-05
4.010E-05
4.900E-05
5.880E-05
8.026E-05
Reactant
Mg+2
Mn+2
Mo 04- 2
Na+
NH4+
Ni+2
N03-
P04-3
Pb+2
Pb[OH]2[C]
Pb2V207
Pb3[V04]2
PbCr04
PbMo04[c]
P-Wollstanite
DMA fraction
0.35
0.18
0.15
0.10
0.18
0.24
0.35
0.45
0.55
0.70
mg/kg
5.026E+03
1.139E+02
6.727E-01
3.669E+03
l.OOOE+01
5.628E+00
2.000E+02
5.717E+02
1.408E+02
Wairakite
Willemite
ZnSi03
[DMA] (kg/I)
2.349E-05
7.776E-06
6.105E-06
4.700E-06
8.784E-06
1.157E-05
1.404E-05
2.205E-05
3.234E-05
5.618E-05
Reactant
S04-2
Sb[OH]6-
Se04-2
H4Si04
Sr+2
Th+4
U02+
V02+
Zn+2
Polynomial coeficients
CO -4.230E+00
Cl
C2
C3
C4
C5
mg/kg
4.649E+03
1.472E+00
9.660E-02
7.279E+03
7.071E+01
not measured
not measured
3.257E+00
6.088E+02
-4.461E-01
5.797E-02
-1.872E-03
O.OOOE+00
O.OOOE+00
A-7
-------
a
3
Concentration (mol/l)
Concentration (mol/l)
a>
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Q.
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8
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N) -
U) -
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cn -
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-------
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C h-* N) UJ _fc un a
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Concentration (mol/l)
a
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ft
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DMA (kg/I)
Concentration (mol/l)
D O O O O C
. (n rn rn rn rn r..
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31
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Concentration (mol/l)
o o o
rn rn rn
o o o
CO VI Ol
M
uj S
on ^
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CO /
/
10
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ANC/BNC (mol/kg)
Concentration (mol/l)
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n
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-------
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s
Concentration (mol/l)
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Concentration (mol/l)
It
o'
0)
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s
o
3
del
const
Q.
0)
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5'
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Q.
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1
o
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5'
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Q.
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3
&
si
Concentration (mol/l)
Concentration (mol/l)
Concentration (mol/l)
Ot
SL
s
ft
ID
5'
o
3'
It
3
o
3
m
N) -
U) -
on -
o> -
Concentration (mol/l)
Concentration (mol/l)
Concentration (mol/l)
u b b c
i 1 g i
0
f'
.' .1 ,
0 S.\
b b c
!0 0 C
U1 -& ^
1 /
/ s'
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/
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I
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U) -
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on -
Oi -
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^
N) "
U) '
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DOOOOOOC
O^IOiO1-^U)N)h-
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1 1
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h
t \ N
V\ 3
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^^"^"^W
^
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N) -
U) -
-& -
on -
Oi -
^1 -
CO -
^D -
O "
N) "
U) "
1 1
1
1
Ik
^
/
/
^s
* /
1 S
1 s
1 ''
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f ป. O
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-------
a
3
ฃ
a>
Concentration (mol/l)
8
I
//
X
( x/
s
s
/
0
Q.
ฃL
a
o
31
C
n
p
UJ
5'
Q.
0)
I
o
5'
Q.
n>
Q.
0)
3
&
sr
Concentration (mol/l)
a
OJ
ft
o
o
o-
I
o
3
OJ
o
r-a
Concentration (mol/l)
N) -
U) -
(A
CT
-------
Table A-3. Chemical Speciation Fingerprint for Inorganic Waste Landfill at Nauerna (The Netherlands).
Chemical Speciation Fingerprint - Predominantly Inorganic Waste Landfill
LeachXS
2012
Prediction case
Speciation session
Material
Solved fraction DOC
Sum of pH and pe
L/S
Clay
HFO
SHA
Percolation material
Avg L/S first perc. fracti
EPA LtoF Predominantly Inorganic Waste Landfill DOC/DHA data
LtoF Nauerna_pilot
Pred Inorg Wastemix NL(P,1,1)
0.2
10.00
10.0000
O.OOOE+00
1.500E-03
1.900E-02
I/kg
kg/kg
kg/kg
kg/kg
Pred Inorg Wastemix NL(C,2,1)
0.2791
I/kg
PH
1.00
3.02
4.00
5.27
6.36
7.23
8.18
9.51
10.70
12.01
13.17
14.00
[DOC] (kg/I)
2.914E-05
1.500E-05
1.840E-06
3.800E-06
2.580E-06
2.700E-06
3.560E-06
7.800E-06
1.756E-05
2.960E-05
9.860E-05
1.408E-04
DMA fraction
0.20
0.15
0.12
0.10
0.15
0.18
0.25
0.35
0.50
0.70
0.90
0.95
[DMA] (kg/I)
5.828E-06
2.250E-06
2.208E-07
3.800E-07
3.870E-07
4.860E-07
8.900E-07
2.730E-06
8.780E-06
2.072E-05
8.874E-05
1.338E-04
Polynomial coeficients
CO
Cl
C2
C3
C4
C5
-4.684E+00
-5.010E-01
5.562E-04
7.768E-03
-3.543E-04
O.OOOE+00
Reactant concentrations
Reactant
Ag+
AI+3
H3As04
H3B03
Ba+2
Br-
Ca+2
Cd+2
Cl-
Selected Minerals
Albite[low]
AIOHS04
alpha-TCP
Anhydrite
Ba[SCr]04[96%S04]
BaSrS04[50%Ba]
Boehmite
Brucite
mg/kg
not measured
2.276E+03
2.570E+00
1.865E+01
1.536E+00
3.452E+01
5.015E+04
2.760E+00
5.268E+03
Bunsenite
Ca2Cd[P04]2
Ca4Cd[P04]30H
Calcite
CaZincate
Cd[OH]2[C]
Cr[OH]3[A]
Cu[OH]2[s]
Reactant
H2C03
Cr04-2
Cu+2
F-
Fe+3
Hg+2
1-
K+
Li+
Ferrihydrite
Fluorite
Gypsum
Hausmannite
Hinsdalite[2]
Hydromagnesite
Leu cite
Manganite
mg/kg
5.600E+04
1.919E+01
3.977E+01
5.000E+01
1.636E+04
not measured
not measured
1.059E+03
2.623E+00
Ni[OH]2[s]
NiC03[s]
OCP
Otavite
Pb[OH]2[C]
Pb2V207
PbCr04
PbMo04[c]
Reactant
Mg+2
Mn+2
Mo04-2
Na+
NH4+
Ni+2
N03-
P04-3
Pb+2
Portlandite
Rhodochrosite
Sb[OH]3[s]
Strengite
Strontianite
Struvite
Willemite
Zincite
mg/kg
3.002E+03
5.737E+02
2.872E+00
2.360E+03
6.096E+02
2.323E+01
not measured
8.157E+01
2.500E+02
ZnSi03
Reactant
S04-2
Sb[OH]6-
Se04-2
H4Si04
Sr+2
Th+4
U02+
V02+
Zn+2
mg/kg
1.272E+04
3.863E-01
3.191E-01
3.015E+03
1.761E+02
not measured
not measured
5.225E+00
2.401E+03
A-12
-------
a
s
OD
ID
o'
0)
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3
Q.
ID
8
ft
Concentration (mol/l)
Concentration (mol/l)
N) -
U) -
Concentration (mol/l)
b b b b
m rn rn rn
oooo
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Concentration (mol/l)
I
L
o
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Q.
n>
a
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31
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II
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5'
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Concentration (mol/l)
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Concentration (mol/l)
Concentration (mol/l)
Concentration (mol/l)
1 /
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U) -
-t> -
on -
CT> -
^1 -
V
I
CO -
^D -
0 '
ฃ -
^
ro '
U) "
h-t
u w ^ ui un -i
1 1
1 1
! !
1 1
1 1
| ^->-^-/
- '^'1'^"
r" $
i
i
X B
\
\ i 09
\ 1 "*
V r*
^ w
N) -
U) -
-^ -
on -
a> -
^1 -
^
X
CO -
^D -
O "
ฃ '
1_k
N) "
U) "
I-1 .
1 J
| ^
1^^
^^ ^
/ ^X
/ /
//
t u
\ \ w
^^ ~'
-^^
^^^^
1^
^ "Nx
1 i
-------
TO"
3
p
n "
3-
fD
3
O on
0)
V)
8
ป' *
o'
3
Q.
ID
31 ~
8
3 C
ft
Z*'
Conductivity (mS/cm)
D O O O O O C
X"
/ Q.
X C
1
I <
X^
f
\
^
""
Concentration (mol/l)
N) -
U) -
on -
CO -
O "
N) "
w
^
*!* )
' '.) /
/ '
/ /
*---. /X
/ ~"~'^
0
Q.
QL
-o
ฃ
a
o
h
\
to
II
p
U)
5'
C
iS7
-a
n>
8
aj
o'
8
C
Q_
ft
QJ
0
Q.
Q.
K
n
"S'
0
3
31
^
to
II
o
5'
C
iS7
n:
Q.
(D
ป
1
3
I
Q.
1
DMA (kg/I)
Concentration (mol/l)
Concentration (mol/l)
O
2
ft
OJ
3
a.
ป
(T>
.Sx
Concentration (mol/l)
^
3.
3
ANC/BNC (mol/kg)
Concentration (mol/l)
O CO 01 -fc M
o
09
O
I
I
y
I
I*
I
t
)
N) -
U) -
on -
Oi
CO -
O "
N) "
1 1
1 /
Q) 0 '
1
1
1
* *""
/
. 1
1
I /
-------
a
3
a>
o'
3
Q.
ID
8
Concentration (mol/l)
Concentration (mol/l)
O
1
o'
ft
ID
5T
Q.
n
5i'
Concentration (mol/l)
N) -
U) -
-tป -
on
Oi -
^1 -
CO -
^D -
0 '
N) "
U) "
/
(/
! \Nx
\ V
-t^-''"
x-'^-*ft
^(x
^lv ป
*N^N
1 ป
Concentration (mol/l)
b b b b
rn rn rn rn
oooo
^i en on -^
Concentration (mol/l)
Concentration (mol/l)
b b b b b b
on -
Oi -
^i -
co -
^D -
T
I I
N
Sbbbbbbbo
^IOiU1-&U)N)l-.0
o
Q.
fD
a
a
to
II
p
U)
5'
ง
Q.
sr
o
Q.
o
31
o
5'
Q.
n>
I
I
Concentration (mol/l)
V
( ^x
IT-
i
i
i
.!
j
0
Q.
Concentration (mol/l)
N) -
U) -
-^ -
on -
Oi -
^1 -
CO -
^D -
O "
N) "
U) "
,_k
/ /
/ \
J \
/ \
f i
. /
. ' . . /
tv '
v \
\?X ซ
\ ^0 ^
^^v^
i ^^.
-------
pH dependent test data
description for L/S=10 in L/kg
Model
Percolation column data
l.OE-03
l.OE-04
f l.OE-05
"^ l.OE-06
'5
2 l.OE-07
e
e l.OE-08
o
o
l.OE-09
l.OE-09
- Model prediction for L/S=0.3 in L/kg I-OE-IO
Mo
\ r< V-"
\'li -^*~
1 2 3 4 5 6 7 8 9 10 11 12 13 14
pH
O
5
s
l.OE-06
l.OE-07
l.OE-08
Qh
k. X
: .
2 3 4 5 6 7 8 9 10 11 12 13 1
PH
l.OE-03
l.OE-04
^.
I l.OE-05 -
e
| l.OE-06
ซ l.OE-07
ฐ l.OE-08
S\
\\
\\
\ *
\ \
\
l.OE-09 1 r-
12345
6 7
pH
8 9 10 11
12 13 14
Figure A-12. Chemical speciation model for constituents in inorganic waste landfill material.
A-16
-------
Table A-4. Chemical Speciation Fingerprint for Municipal Solid Waste (The Netherlands).
Chemical Speciation Fingerprint- Municipal Solid Waste Landfill
LeachXS
2012
Prediction case
Speciation session
Material
Solved fraction DOC
Sum of pH and pe
L/S
Clay
HFO
SHA
Percolation material
AvgL/Sfirstperc.fractii
LtoF MSW
Landgraaf mix
Mixed organic waste DS
0.2
13.00
10.0000
l.OOOE-01
l.OOOE-02
4.000E-02
Mixed organic waste DS
0.1240
NL(P,1,1)
I/kg
kg/kg
kg/kg
kg/kg
NL(C,1,D
I/kg
DOC/DHAdata
pH
1.00
2.75
3.69
6.37
6.81
7.48
8.78
10.32
11.66
14.00
Polynomial coeficients
[DOC] (kg/I)
4.539E-04
2.810E-04
1.790E-04
1.470E-04
1.730E-04
1.740E-04
3.330E-04
6.195E-04
8.380E-04
9.574E-04
DMA fraction
0.55
0.40
0.30
0.25
0.20
0.20
0.25
0.35
0.55
0.90
[DMA] (kg/I)
2.496E-04
1.124E-04
5.370E-05
3.675E-05
3.460E-05
3.480E-05
8.325E-05
2.168E-04
4.609E-04
8.617E-04
CO
Cl
C2
C3
C4
C5
-3.446E+00
-8.161E-02
-7.705E-02
1.349E-02
-5.311E-04
O.OOOE+00
Reactant concentrations
Reactant
Ag+
AI+3
H3As04
H3B03
Ba+2
Br-
Ca+2
Cd+2
Cl-
Selected Minerals
AI[OH]3[a]
alpha-TCP
Analbite
Anglesite
Anhydrite
Ba[SCr]04[96%S04]
BaSrS04[50%Ba]
mg/kg
not measured
3.076E+03
6.116E-01
7.289E+01
1.567E+01
9.010E+00
2.272E+04
1.695E+01
2.330E+03
Birnessite
Brucite
Ca2Zn[P04]2
CaCu2[P04]2
Calcite
CaMo04[c]
Cerrusite
Reactant
Cr04-2
Cu+2
F-
Fe+3
H2C03
Hg+2
1-
K+
Li+
CuC03[s]
Diopside
Dolomite
Fe_Vanadate
Fe2[OH]4Se03
Ferrihydrite
Fluorite
mg/kg
5.273E+01
2.342E+02
1.680E+02
1.341E+04
3.010E+04
not measured
not measured
1.584E+03
2.670E+00
Huntite
hydrozincite
Magnesite
Manganite
NiC03[s]
Nsutite
OCP
Reactant
Mg+2
Mn+2
Mo04-2
Na+
NH4+
Ni+2
N03-
P04-3
Pb+2
Otavite
Pb2V207
Pb3[V04]2
PbMo04[c]
Rhodochrosite
Strontianite
Talc
mg/kg
1.632E+03
3.392E+02
7.673E+00
2.079E+03
not measured
8.473E+01
not measured
7.881E+01
5.878E+02
Wairakite
Withe rite
Zn[OH]2[B]
ZnC03:H20
Reactant
S04-2
Sb[OH]6-
Se04-2
H4Si04
Sr+2
Th+4
U02+
V02+
Zn+2
mg/kg
2.769E+03
1.813E+00
5.495E-01
1.973E+03
6.760E+01
not measured
not measured
4.727E+00
2.110E+03
A-17
-------
a'
3 E
i c
i-> c
UJ i-1 -
n M
IB
i.
m *
en "i
0 <" '
Jj. ^, .
0' I
=
3 ID -
Q. ^
IB ฐ '
? -
8 s"
3 "-1
ft
c
IB
3
r*
VI
5' i
ง *
-2
3 w -
o'
tf U) -
ft
t/1 -
5T
Q.
^^
= V
T
3 I co-
Si
fl)
s; s
N) "
U) "
4i
h
c
r
c
f.
N) -
U) -
on -
0,-
V
X
CO -
^D
0 ~
I--.
N) "
U) "
Concentration (mol/l)
3 b b b b b ฃ
3 O O O O O C
n on -ti w ro !- c
i i
1 1
* 1
j 1
1 I
1 /
I /
i y
* /
** / %k
s /
*s^ '
\ s
\ ;
\l
. ;i 2
x/i o
.x1 X*
Concentration (mol/l)
3 b b b c
n rn rn rn r
3 0 0 0 C
ri on -^ w r-
i i
1 1
fr 1
t !
1 /
1 /
' xX
9 / .
^ 0 ^k ^
^ /
X /
/ /
\ / w
V "^
*.\
j)
Concentration (mol/l)
n b b b b p
n b b b b c
Ti .& w ro !-. c
1 /
(A /
i [
a> L
0) #
VI (1
J
,[ป
* ^\fc
*' \
i ^x
1 \
1 ^
1
J 1
1 1
1 1
1 1
3 C
n r
3 i
3 c
ro -
U) -
-^ -
on -
CTi -
^1 -
I
CO -
^D -
^
O "
ro "
UJ
-^
c
^ c
3 ^
ro -
w -
-^ -
on -
d -
^l -
I
CO -
^D -
0 '
^
ro '
U) '
4i
^ ri
i i
ro -
U) -
4i -
on -
d -
^1 -
^
I
CO -
^D -
O "
,_L
^
ro
U) '
Concentration (mol/l)
DbbbbbSS
n m rn rn rn rn '^' '+
Dbbbbboc
. i . .
i i
I ^-^^
^^
s^
/
#
.
1 * *^*
L *
0
V-
,\
\{
Concentration (mol/l)
D
i b
\ 1 2 ฐ ~ ฃ
1 1
i I
ai 1
t !
1 X
1 X
1 '
' /
^ '
ttr
. ป
^ 1
y 1
/; '
\/
\
\
],
Concentration (mol/l)
D b b b b c
D b b b b c
D ^i CTI on -t> u
OB ;
1
'
.' ^ ^ ^ "*
XX/ซ
^ *JL
/ %**
^ ปi
N N
^x V
v \
^^
\\
N
ro -
U) -
2
0
Q.
ฃL
T3
ni
s
O
31
J^
n
p
UJ
5'
ฃ
-rj
R
o
01
o'
8
c
1
Q.
2
o
Q.
ฃL
Q.
ffi
a
T3
Cฑ
O
6"
C
II
O
5'
ง
T3
I
Q.
0)
"o>
^
Q.
0)
I
Q_
$
Concentration (mol/l)
^
j^^
Concentration (mol/l)
)/
00
-------
a
3 5
h->
J^
n " -
n>
3.
ฃ
VI
8.
Q) "O
o'
3
Q.
It
6* ~"
T
8
3 C -
ft
Z*'
ANC/BNC (mol/kg)
/
z '*
o fr
n 1
" .'
1
1
f
^
1
t
1
I
1
i
'
^
Concentration (mol/l)
Conductivity (mS/cm)
i-i ro w ^ on
00000
3'
O
1
o'
ft
It
5T
ฐ- o ^
=: i
1
ft
S]
U) "
X"
r
r
i
i
*/
i
i
; s
i 1
v -
V,-
CO -
^D
O "
N) "
UJ '
|__.
1 /
1 t
4 \
~ 1 '
\ \
\ \
1 \
4 \
2 \
j l
i
t
i
i
i
i
2
0
Q.
ฃL
T3
ni
s
O
31
C
n
p
UJ
5'
E
-rj
R
o
01
o'
8
c
1
Q.
Concentratit
2
o
Q.
ฃL
Q.
ffi
a
T3
Cฑ
O
6"
C
II
O
5'
ง
on (mol/l)
T3
I
Q.
0)
"ฐ
^
Q.
0)
I
Q_
ff
N) -
U) -
-^ -
on -
CT> -
^1 -
CO -
^D -
O "
N) "
U) "
/ X"
^^\ *
' ^\
| \
I /^
\ ^
&*
^
"%*
\^
1
1
0
a>
in
o
^^
1
DMA (kg/I)
Concentration (mol/l)
Concentration (mol/l)
U) -
on -
^l -
^D -
ฃ '
U) "
/
/
/
/
/. i
^
\-
\
X
X
>^
^
^^
^^^
X
\
;
N) -
U) -
J>. -
on -
^
Z
CO -
o "
ฃ -
N) "
U) "
,_..
1
|
4 1
1
^- ^
if"+'
\
\
V
1
I X
\
1 \
| \
1 \
1-1 '
N) -
U) -
-^
on
0> -
^1 -
V
I
CO -
^D -
O "
ฃ -
N) "
U) "
,_..
1 1
1 /
= 4 1
Q) , |
r i
i /
i /
i *
u /
I" /
1 ป/
i /
/
1 '
\ s
1 X
1 /
1 1
-------
a
Concentration (mol/l)
Concentration (mol/l)
It I
1 t
^
n NJ -
1 -
O' 4^ -
0)
(/) "1 -
ฐo
8.
Jj. ^ .
5' I
= CO -
Q.
fD l~'
? ~"
8 G-
ft
c *
It
3
r*
V)
5' i
1' ฃ
2
3 ro -
o'
^ U) -
ft
">
01
3 Ol -
Q.
=: vi -
3 ^co-
Si
It ">
SL s-
-
N) "
U) "
Dobbbbbp
D O O O O O O C
i i
N I '
3 4 I
i 1
I )
, f
\ /
* tr'
%ix
* f/
'\
\
Concentration (mol/l)
D b b b c
D b b b c
n -^ w ro i-
i
I
09 k
\
\
\
\
** ซT*
1 \
\ \
' ^
. 1 1
| 1
1 1
1 1
n F
D C
D C
N) -
U) -
on
Oi -
xj -
X
CO -
o
ro '
4i
n 'f
= S
N) -
U) -
*-
on -
Oi -
XI -
I
CO -
^D
O ~
^ -
N) ~
UJ ~
,_k
sbbbbbbc
uooooooc
/ /
/ XX
ft'
I /
I.
CL
. T*
* \I
\
\ป
\ ซ
V;
Concentration (mol/l)
D b b b b b c
D b b b b b c
j 01 on -^ w ro i-
i i
I I
t /
J '
/ /
/ /
/ /
J y
/ /
* /'
/ /
y
*l
V Z
\x ~"
1 ^x
! \
2
0
Q.
ฃL
T3
ni
5
o
31
J^
n
p
UJ
5'
-g
R
o
01
o'
8
c
1
Q.
2
o
Q.
QL
Q.
ffi
a
T3
Cฑ
O
6"
C
II
O
5'
T3
I
Q.
0)
"o>
^
Q.
0)
I
Q_
ff
Concentration (mol/l)
N) -
U) -
-^ -
OI -
Oi -
xj -
CO -
^D -
O "
N) "
t_L
U) "
^
1 1
1 1
4 1
1 !
1 s
I ,'
' /
* / /
7/
IS
* /'
/T 2
/ ' 3
^ /
X X
Concentration (mol/l)
N) -
U) -
on -
Oi -
tSJ
O
/\
x
I /
^
-
-^.
Concentration (mol/l)
00000000
Concentration (mol/l)
b b b b b b b
So b b b b b
co xj en on -ti w
-------
pH dependent test data
-- Model description for L/S=10 in L/kg
Percolation column data
-- Model prediction for L/S=0.3 in L/kg
l.OE-03
1 l.OE-04
e
S l.OE-05
1
ซ l.OE-06
ฐ l.OE-07
l.OE-08
l.OE-03
l.OE-04
f l.OE-05
"^ l.OE-06 -
'5
2 l.OE-07
e l.OE-08
3
l.OE-09
1 2 3 4 5 6 7 8 9 10 11 12 13 14
pH
l.OE-10
\. :*/--'
k \ ^/
Mo
1 2 3 4 5 6 7 8 9 10 11 12 13 14
pH
l.OE-04
= l.OE-05
"o
^ l.OE-06 -
'5
g l.OE-07
S
S l.OE-08
l.OE-09
^-" \
ซ. .. .
Se
l.OE-03
1 2 3 4 5 6 7 8 9 10 11 12 13 14
pH
l.OE-04
^.
1 l.OE-05
e
B l.OE-06
1
ซ l.OE-07
ฐ l.OE-08
l.OE-09
A 1
'
1 2 3 4 5 6 7 8 9 10 11 12 13 14
pH
Figure A-16. Chemical speciation model for constituents in inorganic waste landfill material.
A-21
-------
Table A-5. Chemical Speciation Fingerprint for Stabilized Waste Landfill Material (The Netherlands).
Chemical Speciation Fingerprint-Stabilised Waste
LeachXS
2012
Prediction case
Speciation session
Material
Solved fraction DOC
Sum of pH and pe
L/S
Clay
HFO
SHA
Percolation material
Avg L/S first perc. fractions
LtoF Stabised waste
Stabilised waste
Stabilised waste NL (P,6,1)
0.2
13.00
10.0000
O.OOOE+00 kg/kg
1.000E-05 kg/kg
5.000E-04 kg/kg
Stabilised waste NL (C,15,1)
0.2222 I/kg
DOC/DHA data
PH
1.00
3.60
4.78
6.06
7.28
7.80
9.50
10.30
11.69
14.00
[DOC] (kg/I)
4.000E-06
3.200E-06
3.100E-06
1.900E-06
2.400E-06
2.200E-06
3.100E-06
2.300E-06
3.000E-06
4.000E-06
DMA fraction
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
[DMA] (kg/I) Polynomial coefficients
8.000E-07
6.400E-07
6.200E-07
3.800E-07
4.800E-07
4.400E-07
6.200E-07
4.600E-07
6.000E-07
8.000E-07
CO
C1
C2
C3
C4
C5
-6.006E+00
-7.827E-02
4.355E-03
5.802E-05
O.OOOE+00
O.OOOE+00
Reactant concentrations
Reactant mg/kg Reactant
Ag+ not measured CrO4-2
AI+3 6.056E+03 Cu+2
H3AsO4 1.450E-01 F-
H3BO3 5.947E+01 Fe+3
Ba+2 1.933E+01 H2CO3
Br- 8.338E+02 Hg+2
Ca+2 8.362E+04 I-
Cd+2 1.782E+02 K+
Cl- 5.350E+04 Li+
Selected Minerals
AA_2CaO_AI2O3_8H2O[s]
AA_2CaO_AI2O3_SiO2_8H2O[s]
AA_2CaO_Fe2O3_SiO2_8H2O[s]
AA_3CaO_AI2O3[Ca[OH]2]0_5_[CaCO3]0_5_11_5H2O[s]
AA_3CaO_AI2O3_CaCO3_11 H2O[s]
AA_3CaO_AI2O3_CaSO4_12H2O[s]
AA_3CaO_Fe2O3_CaCO3_11 H2O[s]
AA_4CaO_AI2O3_13H2O[s]
AA_AI[OH]3[am]
AA_Brucite
AA Calcite
mg/kg
9.690E+00
3.650E+02
1.904E+03
7.393E+01
1.500E+04
not measured
not measured
3.381 E+04
2.452E+01
Reactant
Mg+2
Mn+2
MoO4-2
Na+
NH4+
Ni+2
NO3-
PO4-3
Pb+2
AA_CaO_AI2O3_1 OH2O[s]
AA_CO3-hydrotalcite
AA_Fe[OH]3[microcr]
AA_Gibbsite
AA_Gypsum
AA_Jennite
AA_Magnesite
AA_Portlandite
AA_Syngenite
AA_Tricarboaluminate
Analbite
mg/kg
3.903E+03
1.750E+02
7.700E+00
2.563E+04
not measured
9.290E+00
not measured
4.740E+00
9.551 E+02
BaSrSO4[50%Ba]
Cd[OH]2[A]
Corkite
Cr[OH]3[C]
CSH_ECN
Cu[OH]2[s]
Fe_Vanadate
Fluorite
Laumontite
Manganite
Ni[OH]2[s]
Reactant
SO4-2
Sb[OH]6-
SeO4-2
H4SIO4
Sr+2
Th+4
UO2+
VO2+
Zn+2
mg/kg
1.066E+04
4.920E+00
4.600E-01
3.556E+03
2.060E+02
not measured
not measured
5.800E-01
8.015E+03
Pb[OH]2[C]
Pb2V2O7
Pb3[VO4]2
PbCrO4
PbMoO4[c]
Plgummite[1]
Rhodochrosite
Strontianite
Wairakite
Willemite
A-22
-------
a
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CO -
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Concentration (mol/l)
DOOOOOOOO
DOOOOOOOO
DCO^ICTiO1-^U)N)i-'
1
1
i j
^
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sj
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Concentration (mol/l)
D O O O O O O
D 0 0 0 0 0 0
0 ^l d on -t> w ro
1
1
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1
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Concentration (mol/l)
N) -
U) -
Concentration (mol/l)
B
I
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0
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Concentration (mol/l)
ooooooooooornrn
K^K^OOOOOOOOOOO
i-^o^Dcoxiaim-^u)N)i-^oi-^
Concentration (mol/l)
Concentration (mol/l)
Concentration (mol/l)
H11 +
2 g
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a
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DMA (kg/I)
Concentration (mol/l)
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Concentration (mol/l)
Concentration (mol/l)
Concentration (mol/l)
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O^DCO^ICTiO1-^U)N)l-'
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1
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Concentration (mol/l)
N) -
U) -
-^ -
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^1 -
CO -
^D -
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U) "
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1
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1
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I
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v
Conductivity (mS/cm)
* g s
Concentration (mol/l)
s
-------
a
3
Concentration (mol/l)
Concentration (mol/l)
ID
n
0)
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8
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Concentration (mol/l)
Concentration (mol/l)
Concentration (mol/l)
3 c
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N N) -
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Concentration (mol/l)
Concentration (mol/l)
Concentration (mol/l)
So o
co ^i
>
Ul
N) -
U) -
4i -
on -
CO -
o
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U) "
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1
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1
1
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1
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X
I
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-------
pH dependent test data
- Model description for L/S=10 in L/kg
Percolation column data
- Model prediction for L/S=0.3 in L/kg
l.OE-04
E l.OE-05
ซ l.OE-06
I
l.OE-07
Se
1 2 3 4 5 6 7 8 9 10 11 12 13 14
^
^
e
ncentratio
Q
i.uc-ut
l.OE-05
l.OE-06
l.OE-07
l.OE-08
l.OE-09
l.OE-10
^ S
^v /
ซ /
^ *. XX -
^ / \ \ s
\\ ./ s-
N> v.^ /
V \ /
\ /
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pH
1 2 3 4 5 6 7 8 9 10 11 12 13 14
pH
Figure A-20. Chemical speciation model for constituents in stabilized waste landfill material.
A-26
-------
Table A-6. Chemical Speciation Fingerprint for Concrete.
Chemical Speciation Fingerprint - Cement Mortar
LeachXS
2012
Prediction case LTF Cement Mortar CEM 1
Speciation session Cement Mortar CEM 1
Material Cement Mortar CEM I_SCCC (P,l,l)
Solved fraction DOC
Sum of pH and pe
L/S
Clay
HFO
SHA
0.2
17.00
10.0000
O.OOOE+00
2.000E-04
2.000E-05
I/kg
kg/kg
kg/kg
kg/kg
Percolation material Cement Mortar CEM I_SCCC (C,l,l)
Avg L/S first perc. fractions
Reactant concentrations
Reactant
0.1455
mg/kg
I/kg
Reactant
DOC/DHA data
pH [DOC] (kg/I)
1.00 2.000E-07
2.10
5.10
7.10
9.20
11.60
11.95
12.10
12.90
14.00
mg/kg
2.000E-07
2.000E-07
2.000E-07
2.000E-07
2.000E-07
2.000E-07
2.000E-07
2.000E-07
2.000E-07
Reactant
DMA fraction
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
mg/kg
[DMA] (kg/I)
4.000E-08
4.000E-08
4.000E-08
4.000E-08
4.000E-08
4.000E-08
4.000E-08
4.000E-08
4.000E-08
4.000E-08
Reactant
Polynomial coeficients
CO -7.398E+00
Cl
C2
C3
C4
C5
mg/kg
O.OOOE+00
O.OOOE+00
O.OOOE+00
O.OOOE+00
O.OOOE+00
Ag+ not measured
AI+3
H3As04
H3B03
Ba+2
Br-
Ca+2
Cd+2
Cl-
Cr04-2
Selected Minerals
AA_2CaO_AI203_Si02_8H20[s]
AA_2CaO_Fe203_8H20[s]
AA_2CaO_Fe203_Si02_8H20[s]
AA_3CaO_AI203_6H20[s]
AA_3CaO_Fe203_6H20[s]
AA_AI[OH]3[am]
AA_Brucite
5.104E+03
2.509E+00
2.005E+01
1.906E+01
5.000E+01
9.840E+04
2.262E-01
1.445E+03
1.830E+01
Cu+2
H2C03
Fe+3
Hg+2
1-
K+
Li+
Mg+2
Mn+2
AA_Calcite
AA_C03-hydrotalcite
AA_Fe[OH]3[microcr]
AA_Gypsum
AA_Jennite
AA_Magnesite
AA_Portlandite
3.035E+01
5.000E+03
3.187E+03
not measured
not measured
1.896E+03
2.748E+00
1.959E+03
6.325E+01
Mo04-2
Na+
NH4+
Ni+2
N03-
Pb+2
P04-3
Sb[OH]6-
Se04-2
4.382E+00
4.418E+02
not measured
6.133E+00
not measured
4.936E+00
1.051E+02
1.892E-01
2.345E-01
AA_Tobermorite-l
Analbite
Ca2Cd[P04]2
Ca4Cd[P04]30H
Cd[OH]2[C]
Cr[OH]3[A]
Fe_Vanadate
H4S104
S04-2
Sr+2
Th+4
U02+
V02+
Zn+2
Magnesite
Manganite
Ni[OH]2[s]
Pb[OH]2[C]
Pb2V207
Pb3[V04]2
PbCr04
2.640E+03
6.423E+03
6.665E+01
2.000E+00
2.000E+00
3.805E+00
3.314E+01
PbMo04[c]
Tenorite
Willemite
A-27
-------
a
s
ID
o
3
Q.
ID
8
i
O
O
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a
n>
Concentration (mol/l)
Concentration (mol/l)
c
r
c
y
NJ -
U) -
* -
01 -
en -
^1 -
CO -
5-
U) "
4i
c
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1
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Concentration (mol/l)
3 b b b b c
\ i a 2 s \
i
4
(A
T
1
*
. t^'"'
^^"*
N) -
U) -
Concentration (mol/l)
1
J
1
1
1
1
1
|
|
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U1 -
u\ -
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D.
ffi.
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5'
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D
D.
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Concentration (mol/l)
( I
<* (.
\
Concentration (mol/l)
Concentration (mol/l)
Concentration (mol/l)
tSJ
00
(A
O
*>
fi)
(n
(A
r ^
I/
Jk
N) -
U) -
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CO -
^D -
g1
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N) -
U) -
rri rri rri
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w M I-*
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tSJ
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3
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1_k
-*
C
1-
N) -
U) -
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^
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CO -
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N) "
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Conductivity (mS/cm)
!- ro w -^ ui c
D O O O O O C
^
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1
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1
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/ 9
13
Q.
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Concentration (mol/l)
DOOOOOOOOOOOC
iuiNji-o.Dcovimui.&uir.
1
^'
s'
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s
s^
s
s
/
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Concentration (mol/l)
Dbbbbbbbbc
j^SSSSSSo!
1 1 1 1
1
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N) "
U) "
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^
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D
U) -
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Concentration (mol/l)
D O O O O p
D O O O O C
n -^ U) N) h-k C
1
i
* 1
1
1
J
1
1
1
i
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1
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1
Concentration (mol/l)
D
= b
52-o
D O O -
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1
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1
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ANC/BNC (mol/kg)
J H* H* 1
1 1 1
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D
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Concentration (mol/l)
D O O O O O C
0 "xj CTi U1 -^ U) N
' ' ' 1 " r
/ i
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i i
i i
i i
i j
J.-""
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V
Concentration (mol/l)
^bbbbbbbbbbm
nmmmmmmmmmm.
^K^OOOOOOOOOC
*
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Concentration (mol/l)
Concentration (mol/l)
n NJ
3"
n>
Lr w
3
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0)
VI "i
D
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0- I
3 CO
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5' i
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1 1
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f/
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t+sT^-^-. "
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Concentration (mol/l)
D CD CD CD CD C
D CD CD CD CD C
J d on -^ U) ^
N) -
U) -
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a. -
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CO -
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DOOOCDCDCDC
Dcbcbcbcbcbcbc::
DCO^IOiOI-^WN
N) -
U) -
-^ -
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Oi -
^1 -
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D.
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5cription f
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Concentration (mol/l)
Concentration (mol/l)
Concentration (mol/l)
Concentration (mol/l)
s i
20
w
oo
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N) -
U) -
4i -
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Oi -
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^D -
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v'lcC~, ฐ
1
-------
pH dependent test data
- Model description for L/S=10 in L/kg
Percolation column data
- Model prediction for L/S=0.3 in L/kg
eป
e
5
3
l.OE-06
l.OE-07
l.OE-08
l.OE-09
l.OE-10
Sb
\ &D
\
\
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\7
1234567
9 10 11 12 13 14
^
e
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s
8
l.OE-04
1 OE-05
l.OE-06
l.OE-07
l.OE-08
l.OE-09
l.OE-10
' '"* V '
^ 1
~~~ l""N'~ /"^
\ y
I \ /
N \ /
\ +*
V
1234567
9 10 11 12 13 14
PH
pH
Figure A-24. Chemical speciation model for constituents in concrete.
A-31
-------
APPENDIX B. COAL COMBUSTION FLY ASH LANDFILL LEACHATE (U.S.)
B-l
-------
0.1
PH
ป EPRI-CFA-Core-38575 EPRI-CFA-Leachate-38575
A EPRI-CFA-Lysimeter-38575 A EPRI-CFA-Lysimeter-50207
-- EPA-14093-012-Leachate Well ป-- EPA-14093-013-Leachate Well
I EPA-23214-010-Leachate Collection System ฉ-- EPA-27413-090-Leachate Well
--ป-- EPA-27413-092-Leachate Well
-A--EPA-50213-002-Lysimeter
-*--EPA-SX-BAG#10-Porewater D EPA-SX-BAG #ll-Porewater
-A--EPA-SX-BAG #8-Porewater EPA-Lab-Fly Ash-5th &95th %
10 12 14
D EPRI-CFA-Leachate-49003B
EPRI-CFA-Well-50207
A EPA-14093-014-Leachate Well
X EPA-27413-091-Leachate Well
-- EPA-50211-102-Leachate Collection System -*--EPA-50212-097-Leachate Collection System
--l--EPA-50213-003-Lysimeter -O--EPA-SX-BAG #l-Porewater
-0--EPA-SX-BAG #5-Porewater
EPA-Lab-Fly Ash-Median
Figure B-l. Comparison of laboratory and field concentration results for coal combustion fly ash
landfill (United States).
B-2
-------
10000
^ 1000 -r
Ol
^
3
1000
100 T
10
1 -
f 0.1 -r
a. 0.01
&
o
u
0.001
0.0001
12 14
\
N
~\
^
\x-
\
%
x_
- -
ป *
DD4k
^
[
A<
ป\<
V M
:
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>
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CB
X
f^
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10
12
PH
14
Ol
^~>
*;
a
ja
o
u
m -
m -
m -
^
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i i i i i
N
^-111
s
\
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! i i i 1
\
^
^ \
o
i i i i i
n
x
+ '
A
! i i i 1
]
^
n
X
*
10 12
PH
14
5
* EPRI-CFA-Core-38575 EPRI-CFA-Leachate-38575
A EPRI-CFA-Lysimeter-38575 A EPRI-CFA-Lysimeter-50207
-- EPA-14093-012-Leachate Well ~ EPA-14093-013-Leachate Well
I EPA-23214-010-Leachate Collection System ฉ-- EPA-27413-090-Leachate Well
D EPRI-CFA-Leachate-49003B
EPRI-CFA-Well-50207
--A EPA-14093-014-Leachate Well
-X EPA-27413-091-Leachate Well
--ป-- EPA-27413-092-Leachate Well
-A--EPA-50213-002-Lysimeter
-XS--EPA-SX-BAG #10-Porewater
- A- EPA-SX-BAG #8-Porewater
--EPA-50211-102-Leachate Collection System -*--EPA-50212-097-Leachate Collection System
--l--EPA-50213-003-Lysimeter -O-- EPA-SX-BAG #l-Porewater
-- EPA-SX-BAG #ll-Porewater -O- EPA-SX-BAG #5-Porewater
EPA-Lab-Fly Ash-5th & 95th % EPA-Lab-Fly Ash-Median
Figure B-2. Comparison of laboratory and field concentration results for coal combustion fly ash
landfill (United States).
B-3
-------
10
ci
^>
01
o
0.1 -:
0.01
PH
ฐ4
10 12 14
0.1 -r
0.01 -r
0.001
0.0001 -:
0.00001
1
\
\\
\
\
^
*
1 ,
^
<
ป
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ป Ai
>
^
9ป .
y +
'
^
_i
1
Ol
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^ n 1
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Jti
J n m -
n nm -
i i_i i I
o
1 1 1 1 1
A A
* \
c
A
X +
X
O
10
12
14
PH
PH
ป EPRI-CFA-Core-38575 EPRI-CFA-Leachate-38575
A EPRI-CFA-Lysimeter-38575 A EPRI-CFA-Lysimeter-50207
-- EPA-14093-012-Leachate Well -~ป--- EPA-14093-013-Leachate Well
I EPA-23214-010-Leachate Collection System ฉ~- EPA-27413-090-Leachate Well
--ป-- EPA-27413-092-Leachate Well
-A--EPA-50213-002-Lysimeter
-*- EPA-SX-BAG #10-Porewater D EPA-SX-BAG #ll-Porewater
- A- EPA-SX-BAG #8-Porewater EPA-Lab-Fly Ash-5th &95th %
D EPRI-CFA-Leachate-49003B
EPRI-CFA-Well-50207
A EPA-14093-014-Leachate Well
*~ EPA-27413-091-Leachate Well
--EPA-50211-102-Leachate Collection System -*--EPA-50212-097-Leachate Collection System
--l--EPA-50213-003-Lysimeter -O--EPA-SX-BAG #l-Porewater
-0--EPA-SX-BAG #5-Porewater
EPA-Lab-Fly Ash-Median
Figure B-3. Comparison of laboratory and field concentration results for coal combustion fly ash
landfill (United States).
B-4
-------
0.1
ป EPRI-CFA-Core-38575
A EPRI-CFA-Lysimeter-38575
--EPA-14093-012-Leachate Well
-H EPA-23214-010-Leachate Collection System
--- EPA-27413-092-Leachate Well
-A--EPA-50213-002-Lysimeter
-3K--EPA-SX-BAG #10-Porewater
- A- EPA-SX-BAG #8-Porewater
EPRI-CFA-Leachate-38575
A EPRI-CFA-Lysimeter-50207
~ป EPA-14093-013-Leachate Well
-ฉ-- EPA-27413-090-Leachate Well
--EPA-50211-102-Leachate Collection System
--l--EPA-50213-003-Lysimeter
-- EPA-SX-BAG #ll-Porewater
EPA-Lab-Fly Ash-5th & 95th %
PH
D EPRI-CFA-Leachate-49003B
EPRI-CFA-Well-50207
--A EPA-14093-014-Leachate Well
-*- EPA-27413-091-Leachate Well
-*--EPA-50212-097-Leachate Collection System
-O-- EPA-SX-BAG #l-Porewater
-0--EPA-SX-BAG #5-Porewater
EPA-Lab-Fly Ash-Median
Figure B-4. Comparison of laboratory and field concentration results for coal combustion fly ash
landfill (United States).
B-5
-------
Ol
"(5
n nnnm .
r
^ .ป.
ป* ^
^
x
"X
V.
_ ^
X
n
J1
_ ^
\
y.
10 12 14
PH
10 12 14
* EPRI-CFA-Core-38575 EPRI-CFA-Leachate-38575 C
A EPRI-CFA-Lysimeter-38575 A EPRI-CFA-Lysimeter-50207 I
-- EPA-14093-012-Leachate Well *- EPA-14093-013-Leachate Well t
I EPA-23214-010-Leachate Collection System ฉ-- EPA-27413-090-Leachate Well
EPA-27413-092-Leachate Well -- EPA-50211-102-Leachate Collection System -4
EPRI-CFA-Leachate-49003B
EPRI-CFA-Well-50207
. EPA-14093-014-Leachate Well
EPA-27413-091-Leachate Well
-EPA-50212-097-Leachate Collection System
-A--EPA-50213-002-Lysimeter
-XS--EPA-SX-BAG #10-Porewater
-A--EPA-SX-BAG #8-Porewater
--l--EPA-50213-003-Lysimeter
--EPA-SX-BAG #ll-Porewater
EPA-Lab-Fly Ash-5th & 95th %
-O--EPA-SX-BAG #l-Porewater
-0--EPA-SX-BAG #5-Porewater
EPA-Lab-Fly Ash-Median
Figure B-5. Comparison of laboratory and field concentration results for coal combustion fly ash
landfill (United States).
B-6
-------
APPENDIX C. LANDFILL OF COAL COMBUSTION FIXATED SCRUBBER SLUDGE
WITH LIME (UNITED STATES)
Table C-l. Data Sources for Laboratory-to-Field Comparisons for Coal Combustion Fixated Scrubber
Sludge with Lime.
Legend ID
FSSL - "as produced"
(MAD)
FSSL - Field Core
(FCM)
Landfill Porewater
Source
Pub Mill (fresh 4
hr composite)
FSSL Landfill
FSSL Landfill
Material Type
Fixated Scrubber
Sludge with Lime
Core at depth (3-
5m)
Leachate
Data Type
pH-dependence
(SR002)
pH-dependence
(SR002)
"
Citation
Sanchez etal., 2008
EPRI.2012 (draft)
EPRI.2012 (draft)
C-l
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n nni -
A
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: A
A
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A
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of
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0 1
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5 n nm
n nnm
4
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n m -
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)
A
A
(
A
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00 C
k
c
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(
^
^A ฐ
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1
A
cq
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PH
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J
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^
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8 1
i
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v
D
3 AC
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0 1
0%
AA
A
A
i
Q
2 1
0 2 4 6 8 10 12 14
PH
0 2 4 6 8 10 12 14
PH
^ 10 "
1
^J 1
s
o
CO
0.1 -
0.01 -
C
*
Q&c
kA^tf
ซซ$
0^>C
<
) 2 4 6 i
PH
O FSSL - "as produced" (MAD)
A FSSL -Field Core (FCM)
^ Landfill Porewater
' oo
'A0^
AA
3
8
A*,
^
O
3 10 12 1
2" o.i -
Ol
E 0.01 -
3
E
o
o 0.001 -
0.0001 -
4 C
A
A^
A
ni O ฎ^s>
W A
) 2 4 6 ฃ
PH
10 12 14
Figure C-l. Comparison of laboratory and field concentration results for a coal combustion fixated
scrubber sludge with lime (FSSL) landfill (United States).
C-2
-------
^ 1000 -
1
Dl
ju
O in .
Chromium (mg/L)
0
8 b p 0
D 0 0 0 P I-* h
1-'1-'1-'1-'1-'0 oH
j
S.
a.
5 0.01-
A
cod
*A*P4
^
^
SDCO
(A ฐ Oo
^^j^W^
O
inn . .
/A
o
'C 1 - -
I !
o
A A1
*
V
03
A"
A
O
2 4 6 8 10 12 14 0 2 4 6 8 10 12 1
pH pH
A
^.
.
A
k
Cfc
OD O
ฃ*ป
<3%5
ซx><
ปQp^
.".-
>
^
3 00
D c
0
oi ni -^ ฐ cc^
COrO
| al | CfeO A^0
Ja u.ui
O :
O
%
0ฐ
0 2 4 6 8 10 12 14 0 2 4 6 8 10 12 1
pH pH
1 AA
A
4k
0
cPc
A^
W
*4|
0246
PH
O FSSL - "as produced" (MAD)
A FSSL -Field Core (FCM)
^ Landfill Porewater
o ^^
AA
A A
O
J.WW |
1 10 - L
(0 A Q\ p
O O2^C^AA
w ^
ฃ> n 1 -
|^ "-1
5
&&&
o
'A
0
3 10 12 14 0 2 4 6 8 10 12 1
PH
Figure C-2. Comparison of laboratory and field concentration results for a coal combustion fixated
scrubber sludge with lime (FSSL) landfill (United States).
C-3
-------
1
w
^ !
0) 1
^
0
IL. n 1 -
n m -
0
10
1
s-^
_l
"Si 0.1
E
^>
"S o.oi
3
0.001
0.0001
mnnn -
mnn
Magnesium (mg/L)
h
-, I-* C
J I-* O C
l-> 0 0 C
A
V
A
2
A
\A A^A^A^AA
&
*
4 6
A*
A
\
A
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.cp.Q . . .(
3
*
H
%
o
100 -
^
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E
^>
c 1 .
S :
n m .
A
;
:
G*
o
~i
J
^
.
*ป<
^F
(
)
5 80
1
0
8 10 12 14 0 2 4 6 8 10 12 1
pH pH
+ซ*
>\fn]TTV
Lฐฐ,
A
3 *
0
0 2 4 6 8 10 12 1
PH
A
0
A
Q^C
2
^
S%
o^^
4 6
ฃ
PH
O FSSL - "as produced" (MAD)
A FSSL -Field Core (FCM)
^ Landfill Porewater
AA
C
)
; 8cฃ
AA
o
! 10 12 1
Lithium (mg/L)
3
I-" C
, I ,
4 0
100
^. 10
01
1 1
01
S
ฃ o.i
Ol
c
ID
2 0.01
0.001
4
A
4ซ
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4ฐ
A
oo
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A
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_
2 4 6 8 10 12 1
PH
1
A A^
&AA
QD o
ซ*
/\"0
J(
>
>
t
A
O ^
5
0 2 4 6 8 10 12 1
PH
Figure C-3. Comparison of laboratory and field concentration results for a coal combustion fixated
scrubber sludge with lime (FSSL) landfill (United States).
C-4
-------
W
I ,
Molybdeni
3
* I-
J
i
e0o
o
o
^
'*"cP
r
^o c
A
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1
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z o.oi -
A
A
CX)
)
1
4
4
^9Cf
54ป
0
0 2 4 6 8 10 12 14 0 2 4 6 8 10 12 1
pH pH
tnnn -tn
Potassium (mg/L)
h
!- C
I-* O C
* o o c
(
1000
100
1> 10
8 i
M
0.1
0.01
: A
AA
rtiO
A A
4
coot*
ฃDCฃ
Qf^
A
o
Selenium (mg/L)
I g ฐ
* I-1 I-1 I-1 C
A
A
4A 0
J
O
^
^V
0
) 2 4 6 8 10 12 14 0 2 4 6 8 10 12 1
pH pH
1 AAAA
A
- i
A
A
^
0246
PH
O FSSL - "as produced" (MAD)
A FSSL -Field Core (FCM)
^ Landfill Porewater
V
A
'1L
o
E
_3
O
W -in .
A
cifq
^A^/
fs^^fx
AA
> OcP
D
3 10 12 14 0 2 4 6 8 10 12 1
PH
Figure C-4. Comparison of laboratory and field concentration results for a coal combustion fixated
scrubber sludge with lime (FSSL) landfill (United States).
C-5
-------
f-^
-1
1
^>
C in
Strontiur
i-
-i c
Vanadium (mg/L) Thallium (mg/L)
1 b P ^5 | g o >
* *A
)
1
.1
01
01
01
n
u
0 -
1 -
i
1 -
r
^CD
0
2 4 6 8 10 12 1
PH
A V
^0^
ftป
'j*
J
0
ป
ฐ0
)
0
0 2 4 6 8 10 12 1
PH
AA
A *
A
A^
\\\ 1
ซ
0246
PH
FSSL - "as produced" (MAD)
A FSSL -Field Core (FCM)
^ Landfill Porewater
A
^
A
O
oc
'o
8 10 12 1
^ 1UUU
_l
1
^ mn
4J
"5
w m -
A
3
kA*4
M
^
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C
ฃb^
^
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L AAA
ปB
>&
(
3
ป
o
2 4 6 8 10 12 1
PH
Figure C-5. Comparison of laboratory and field concentration results for a coal combustion fixated
scrubber sludge with lime (FSSL) landfill (United States).
C-6
-------
APPENDIX D. MUNICPAL SOLID WASTE INCINERATOR BOTTOM ASH
LANDFILL (DENMARK)
Table D-l. Data Sources for Laboratory-to-Field Comparisons for MSWI Bottom Ash Landfill
Legend ID
MSWI BA (AT)
MSWI BA (DE)
Landfill Leachate
(DK)
Landfill Core (DK)
MSWI BA (ML)
MSWI BA (IT)
MSWI BA (UK)
Source
Austria, MSW
Incinerator
Germany, MSW
Incinerator 1
Denmark
Denmark
The Netherlands
Italy
UK, MSW
Incinerator
Material Type
MSWI Bottom
Ash
MSWI Bottom
Ash
Field Leachate
Landfill Core
MSWI Bottom
Ash
MSWI Bottom
Ash
MSWI Bottom
Ash
pH-dependence
Percolation
pH-dependence
Percolation
-
Batch L/S
pH-dependence
Percolation
pH-dependence
Percolation
pH-dependence
Percolation
Citation
van der Sloot et al.,
2000b
Bergeretal., 2005
Hjelmar et al., 1991
Meima, 1997
ECN ongoing studies on
MSWI BA
ECN ongoing studies on
MSWI BA (Italian client)
ECN studies on UK
MSWI BA
D-l
-------
0.01
0.1 1
L/S (L/kg)
O Landfill Leachate (DK)
* Landfill Cores (DK)
--- MSWI BA (AT)
-MSWI BA(DE)
--- MSWI BA(IT)
-4--MSWI BA(NL)
A MSWI BA (UK)
Figure D-1. Eluate pH from leachates from the Vestkoven monofill (red circles) compared to the
percolation column pH for comparable bottom ash samples (solid symbols).
D-2
-------
Aluminum (mg
0.001
10 12 14
^>
1000
100
10
0.1
0.01
0.001
1
I 1
Q
0 ฐrt
^ *
rC--J
-"
o
GDDG2QDQOI
""--1
-'^*ปr H
ป
0.01
0.1 1
L/S (L/kg)
10
o
s
0.1 -:
0.01 -:
0.001
1 -F
01
01
E
0.01 -
0.001 - :
0.0001
PH
10 12 14
O Landfill Leachate (DK)
-- MSWI BA (AT)
-- MSWI BA(IT)
A MSWI BA (UK)
Landfill Cores (DK)
0--MSWI BA(DE)
4--MSWI BA(NL)
Ul
^>
>.
o
s
<
0.1 -:
0.001
0.01
01
01
ฃ
<
0.001 -
0.0001
0.01
4-
4-
0.1 1
L/S (L/kg)
0.1 1
L/S (L/kg)
10
Figure D-2. Comparison of laboratory and field concentration results for a MSWI bottom ash landfill
(Denmark).
D-3
-------
^ 1
Ol
E
E
ID
ffl 0.01
0.001
100
10
1 '
c
ฃ 0.1
o
CO
0.01
0.001
mnn -=
100 -
E^* m -
^
01
o
E 1 "
S
CO
.
^
<
0
^i*
8M:
Q
?A' N
^^
W^
"
^-
0 2 4 6 8 10 12 1
PH
"*-. A '
^-A-
>
<ง
-"2*-^
0
^0
A^S*
juuua
ป0^
o
ฑ
'"
L
0 2 4 6 8 10 12 1
PH
ฃ
> {
4
^00.
ปป
^^ i
1
Ol
E
3
c
ID
ffl 0.01
0.001
4 0
100
10
c
ฃ 0.1
o
CO
0.01
0.001
4 0
mnn -=
100 -
E^* m -
^
01
o
E 1 "
S
CO
0.1 -
r" *^
\
'" ""^
"-
I ซ...
~T?~~ A *
i
l^^^^^w
~~l
01 0.1 1 1
L/S (L/kg)
[
006
0 000
,-.-.-| -ป__
X1
A^ A A xi
01 0.1 1 1
L/S (L/kg)
V
^
\
*v
^-i-
0 2 4 6 8 10 12 14 0.01 0.1 1 1
pH L/S (L/kg)
-MSWI Bottom Ash (Germany)
--- MSWI Bottom Ash (Italy)
MSWI Bottom Ash (Austria)
4- - MSWI Bottom ash (the Netherlands)
A MSWI Bottom Ash (UK)
O MSWI Monofill Leachate (Denmark)
4 MSWI Monofill Cores (L/S 2)
Figure D-3. Comparison of laboratory and field concentration results for a MSWI bottom ash landfill
(Denmark).
D-4
-------
^ 0.1
Dl
.ง ฐ-ฐ]
E
| o.ooi
O
ID
ฐ 0.0001
0.00001
Calcium (mg/L]
i-
!- C
* o c
3 0 C
1 1 1
0
100000
10000
1
ฃ 1000
01
o
'i 10ฐ
u
10
1
Hv*
"~"^lv^ n*
\N"t$>*
m
*<-ซ
,
&
0 2 4 6 8 10 12 1
PH
T^rt?*"*-*,
r>ps
O ^s^P
*$
ฐ
"
2 4 6 8 10 12 1
PH
'' %KriS
4n
3
r ja o
^>- roB$ซ - :^^^^^
n^
-9
3"~B
k-*
0 2 4 6 8 10 12 1
PH
O Landfill Leachate (DK) Landfill Cores (DK)
-- MSWI BA (AT) -MSWI BA(DE)
--- MSWI BA(IT) 4--MSWI BA(NL)
A MSWI BA (UK)
^ 0.1
Dl
.ง ฐ-ฐ]
E
| o.ooi
D
ID
ฐ 0.0001
0.00001
4
Calcium (mg/L]
i-
l-^ C
* o c
3 0 C
1 1 1
4 O.C
100000
10000
1
ฃ 1000
01
D
'i 10ฐ
u
10
1
4 0
O
o CEO oaP'oroS^OT' '"'
Wป-^^^A) Cisฐ-0a--J
^<
0.01 0.1 1 1
L/S (L/kg)
n *-
v%S:-l
tt
1 0.1 1 1
L/S (L/kg)
^ ฐ^1?5|>
^^
HN^
1
01 0.1 1 1
L/S (L/kg)
Figure D-4. Comparison of laboratory and field concentration results for a MSWI bottom ash landfill
(Denmark).
D-5
-------
^ 1 .
1
Ol
E n 1 -
E
3
'z n m -
n nnm -
0
1
0.1
"|> 0.01
J 0.001
o
u
0.0001
0.00001
10 -
J* <
Ol
s.
g- n m -
U
H
^
> i
ง1
?*ป
%
2 4 6 8 10 12 1
PH
A
A
6--.
\k
\1
1%
ป^
$"^
-
&ฃ
\
*-*
^
!ป
0 2 4 6 8 10 12 1
PH
x.
4
^g1-^
^
o
\
1
9
3
ฃ
S
5 o.ooi -
n nnm -
4 O.C
1
0.1
"|> 0.01
J 0.001
O
u
0.0001
0.00001
4 0
10 -
j" ,
Ol
S.
ง o.oi -
u
0ฐฐ:
G 0 ฎ
'x.
Jv
1? X QD Q)
x\>v
x
' o*"^?"*"'
VT,
)1 0.1 1 1
L/S (L/kg)
l,^
\ ^*NI ,
v\
^ B~ - - -^- ^
/ 4 4
**]//' ^s
*-'
.01 0.1 1 1
L/S (L/kg)
1
0 0
o
c
^ X ! "*" *]
'"^^v V<^5
^j
^ฐ *'
't^_
0 2 4 6 8 10 12 14 0.01 0.1 1 1
pH L/S (L/kg)
O Landfill Leachate (DK) Landfill Cores (DK)
MSWI BA (AT) -MSWI BA(DE)
--- MSWI BA(IT) 4--MSWI BA(NL)
A MSWI BA (UK)
Figure D-5. Comparison of laboratory and field concentration results for a MSWI bottom ash landfill
(Denmark).
-------
Ived Organic Carbon
(mg/L)
h-
!- C
h-^ 0 C
* o o c
(A
(A
5
<
[
v^
\
\
\
<
"--
> <
ซv
o
;^:
o$*
'o*
OBDO
S-^ซ
j
D
0 2 4 6 8 10 12 1
pH
mnn -
100 -
^ 10
w
c
HH
n m -
r
k
^
*\
N,
s'
^ s
^, \
\ \
A
>
A
A
i 'f *
^
>
fe*1
f^e?
3"
*V
S5*
*
Ived Organic Carbon
(mg/L)
h-
l-^ C
h-^ 0 C
l-^ O O C
o o o c
" 1
in 1
'5
0.1
4 0
mnn -
?-^
^ 10 -
2 1 -
^-s 1
C
HH
n m -
J
: O ODO OO5
-2J
i
t
^Skoo^
r vซ--'
5^
01 0.1 1 1C
L/S (L/kg)
0
U O w
o O(*- . m. -r*ซ-Q^-ซ- o no
0 ^
f-^c* ^=
"**%?^aงL
AN-A "^^"^
" 4- -B-H
0 2 4 6 8 10 12 14 0.01 0.1 1 1C
pH L/S (L/kg)
1
Ol
.E 0.1
o
8 n m -
B:
ฃxm
xป7 i
"Tt
Ki
V-
v<
\ ^N i
-i 1 -
1
*E o.i -
o
5 o.oi -
0.001 -
o
1
0 ฐ00 0^
1 :^
/
%ซ'^c|
\o ^^^i
> "->_
iA A i
0 2 4 6 8 10 12 14 0.01 0.1 1 1C
pH L/S (L/kg)
O Landfill Leachate (DK) Landfill Cores (DK)
MSWI BA (AT) ป--MSWI BA(DE)
-HB- MSWI BA(IT) 4--MSWI BA(NL)
A MSWI BA (UK)
Figure D-6. Comparison of laboratory and field concentration results for a MSWI bottom ash landfill
(Denmark).
D-7
-------
0.1
^^
_l
| 0.01
^>
E
.S 0.001
1
0.0001
0.00001
100
I1 10
E
Magnesiu
1 g P
i l-i l-i h
Manganese (mg/L)
0 C
0 P o C
0 0 P ,-, C
O O O . ,-, h-i 1-
0 0 0 0 P l-i 0
"<
0
p
p
m.
^
2
^3
V*
0 A
*:^
***
t,
H.HV
k/-cP^-i
V*
,
]
-*
0.1 -
*>ซ>
_l
1
fn m -
+->>
E
|
0.0001 -
L^^l
;;;m;*^f%^^
""V1
\
\
I
4
4 6 8 10 12 14 0.01 0.1 1 1C
PH L/S (L/kg)
i- ป.
^6 o
**Q<>
*
'+
to|f
ฐc
o o
F
^
%
0
t
O
ฃ 10 -f
3 ^ i
8
ง, o.i -f
i
0.01 -r
0 o oQ
'-^^ฃ^
^ *- *-i
0 ^'"x'*-^
ll"\*^t~~f
-w-i-U
o o o
?
k
^m->.
K. .P**4
) 2 4 6 8 10 12 14 0.01 0.1 1 1C
PH L/S (L/kg)
-
!
<
'
0
?
2
6ฃ
If
VA *
^
f
ฃฃ
Binmi
'f
?
f^L
(JV-"1
r~*"
i
*
10 -
J1
w
0)
(A
V
(0
= 0.001 -
z
0.0001 -
I
0
^m ป-!
ป** *!?" ^ -^ซ r ^
O 6-QO ,T|
4 6 8 10 12 14 0.01 0.1 1 1C
PH L/S (L/kg)
O Landfill Leachate (DK) Landfill Cores (DK)
MSWI BA (AT) ซ--MSWI BA(DE)
--- MSWI BA(IT) O--MSWI BA(NL)
A MSWI BA (UK)
Figure D-7. Comparison of laboratory and field concentration results for a MSWI bottom ash landfill
(Denmark).
D-8
-------
1
0.1
^ 0.001
3
5 o.oooi
z
0.00001
0.000001
1 1 " :
1
E
E
3
C
oi n m -
"5
|
f
' [
ซ-<
0
ฐ(
tr**
00
)ODQ
>
n~
10
A
0 2 4 6 8 10 12 1
PH
A
<
ซi
k ...,-^AT
T^ir'Vj >
\\
ป*
0.1
^i 0'01
ฃ
^ 0.001
ซ 0.0001
z
0.00001
0.000001
4 0
1 1 " :
1
E
E ' !
3
C
o \
"o
I
f
8
- - --ฎQ-ซ
o o (9 o
1
O OO OOa CDOD ffiffl
>--'*ป
ป
0)
.01 0.1 1 1
L/S (L/kg)
"^"^>
1
iW
0 2 4 6 8 10 12 14 0.01 0.1 1 1
PH L/S (L/kg)
1 -
5 o.i -
Ol
^ 0.01 -
01
n nnm -
A
\:
^
ซ '
JH
(g
J ^
5 o.i -
Ol
^ 0.01 -
01
n nnm -
^ C
s: ~ ^&
^!^ฅhr3?
oo^o^ ^
D
)
t A- A '
ง^%-"W""1
*^
i
0 2 4 6 8 10 12 14 0.01 0.1 1 1
PH L/S (L/kg)
O Landfill Leachate (DK) Landfill Cores (DK)
-- MSWI BA (AT) -MSWI BA(DE)
--- MSWI BA(IT) 4--MSWI BA(NL)
A MSWI BA (UK)
Figure D-8. Comparison of laboratory and field concentration results for a MSWI bottom ash landfill
(Denmark).
D-9
-------
1000
1000
1
0
I-1
0.1 1
L/S (L/kg)
10
O Landfill Leachate (DK)
MSWI BA (AT)
-- MSWI BA(IT)
A MSWI BA(UK)
ป Landfill Cores (DK)
-MSWI BA(DE)
4--MSWI BA(NL)
Figure D-9. Comparison of laboratory and field concentration results for a MSWI bottom ash landfill
(Denmark).
D-10
-------
100000
100000
Ol
0.1
0.01
0.001
0.0001
0.00001
0.1
L/S (L/kg)
10
t
^ *""
N^>*>Jf
\A / t
6 8 10 12 14
PH
0.01
0.1
10
L/S (L/kg)
O Landfill Leachate (DK)
MSWI BA (AT)
-- MSWI BA(IT)
A MSWI BA(UK)
ป Landfill Cores (DK)
-MSWI BA(DE)
4--MSWI BA(NL)
Figure D-10. Comparison of laboratory and field concentration results for a MSWI bottom ash landfill
(Denmark).
D-ll
-------
100
5 10
I
E 1
_3
'S
s
8 o-1
0.01
100 -:
10 -r
IA^
10 12 14
PH
v-
\
ป
I ' I ' ' I ' I
I ' I
10 12 14
PH
O Landfill Leachate (DK)
- MSWI BA (AT)
-- MSWI BA(IT)
A MSWI BA (UK)
Landfill Cores (DK)
-MSWI BA(DE)
4--MSWI BA(NL)
01
100
10 -;
1 -
S.
8 o.i
0.01
0.01
10000
1000
Ol
3
w
0.01
10000
1000
01
100 -:
10 T
0.01
4-
4-
0.1 1
L/S (L/kg)
0.1 1
L/S (L/kg)
0.1 1
L/S (L/kg)
10
Figure D-11. Comparison of laboratory and field concentration results for a MSWI bottom ash landfill
(Denmark).
D-12
-------
O Landfill Leachate (DK)
MSWI BA (AT)
-- MSWI BA(IT)
A MSWI BA (UK)
ป Landfill Cores (DK)
ป--MSWI BA(DE)
4--MSWI BA(NL)
0.1 1
L/S (L/kg)
10
Figure D-12. Comparison of laboratory and field concentration results for a MSWI bottom ash landfill
(Denmark).
D-13
-------
APPENDIX E. MUNICPAL SOLID WASTE INCINERATOR BOTTOM ASH USE IN
ROADBASE (SWEDEN)
Table E-l. Data Sources for Laboratory-to-Field Comparisons for MSWI Bottom Ash used in Roadbase
(Sweden).
Legend ID
Vandora - Core 1
Vandora - Core 2
Vandora - Core 3
Vandora - Core 4
Vandora - Individual
Cores(L/S1016yrs)
MSWI BA (ML)
MSWI BA 2 (ML)
MSWI BA (DE)
MSWI BA (AT)
MSWI BA (UK)
MSWI BA (DE)
Source
Sweden
Sweden
Sweden
Sweden
Sweden
The Netherlands
The Netherlands
SIWAP, Germany
Austria, MSW
Incinerator
UK, MSW
Incinerator
Germany, MSW
Incinerator 1
Material Type
Core composite
from roadbase
based on level of
carbonation
Core composite
from roadbase
based on level of
carbonation
Core composite
from roadbase
based on level of
carbonation
Core composite
from roadbase
based on level of
carbonation
Cores from
roadbase
MSWI Bottom Ash
MSWI Bottom Ash
MSWI Bottom Ash
MSWI Bottom Ash
MSWI Bottom Ash
MSWI Bottom Ash
Data Type
pH-dependence
Percolation
pH-dependence
Percolation
pH-dependence
Percolation
pH-dependence
Percolation
Batch L/S
(EN 12457-2)
pH-dependence
Percolation
pH-dependence
Percolation
pH-dependence
Percolation
pH-dependence
Percolation
pH-dependence
Percolation
pH-dependence
Percolation
Citation
ECN ongoing
studies on MSWI
BA
ECN ongoing
studies on MSWI
BA
Bergeretal., 2005
van der Sloot et al.,
2000b
ECN studies on UK
MSWI BA
Bergeretal., 2005
E-l
-------
Vandora - Core Composite 1 (Sweden)
Vandora - Core Composite 2 (Sweden)
Vandora - Core Composite 3 (Sweden)
Vandora - Core Composite 4 (Sweden)
O Vandora - Individual Cores (L/S 10)
A- - MSWI Bottom Ash (The Netherlands)
- - MSWI Bottom Ash 2 (The Netherlands)
- MSWI Bottom Ash (Germany)
m MSWI Bottom Ash (Austria)
A MSWI Bottom Ash (UK)
Figure E-l. pH from laboratory testing of Vandora cores and composites from roadbasel (Sweden).
E-2
-------
0.0001
10 12 14
10000
1000
100
10
0.01
0.01
> o.i -
o
a
< o.oi
0.001
0.01
0.1 v
0.01
0.001 -:
0.0001
0.01
A . A
^'T-
4-
4-
0.1 1
L/S (L/kg)
0.1 1
L/S (L/kg)
10
0.1 1
L/S (L/kg)
ป Vandbra - Core Composite 1 (Sweden)
-A Vandora - Core Composite 2 (Sweden)
- Vandbra - Core Composite 3 (Sweden)
- Vandbra - Core Composite 4 (Sweden)
O Vandbra-Individual Cores (L/S 10)
A- - MSWI Bottom Ash (The Netherlands)
- MSWI Bottom Ash 2 (The Netherlands)
- MSWI Bottom Ash (Germany)
MSWI Bottom Ash (Austria)
A MSWI Bottom Ash (UK)
Figure E-2. Comparison of laboratory and field concentration results for MSWI bottom ash used in
roadbase (Sweden).
E-3
-------
CD
0.01
o
I
10
1 -f
0.1 -r
0.01 -r
0.001
0.01
Ul
f
"
0.01
0.001
0.01
oi
S
CD
0.01
0.01
4-
4-
0.1 1
L/S (L/kg)
10
0.1 1
L/S (L/kg)
0.1 1
L/S (L/kg)
ป Vandbra - Core Composite 1 (Sweden)
A Vandbra - Core Composite 2 (Sweden)
Vandbra - Core Composite 3 (Sweden)
Vandbra - Core Composite 4 (Sweden)
O Vandbra- Individual Cores (L/S 10)
A- - MSWI Bottom Ash (The Netherlands)
- MSWI Bottom Ash 2 (The Netherlands)
O MSWI Bottom Ash (Germany)
-- MSWI Bottom Ash (Austria)
A MSWI Bottom Ash (UK)
Figure E-3. Comparison of laboratory and field concentration results for MSWI bottom ash used in
roadbase (Sweden).
E-4
-------
10000
o 1000 -
5
100000
o
U
^-s
I
o
0.00001
0.01
1000
100000
10000
t-^
_l
--*
I* 1000
^>
v
1 100
o
ฃ
10
0.1 1
L/S (L/kg)
0.1 1
L/S (L/kg)
\ \
^
4-
4-
0.01
0.1 1
L/S (L/kg)
10
ป Vandbra - Core Composite 1 (Sweden)
-A Vandbra - Core Composite 2 (Sweden)
- Vandbra - Core Composite 3 (Sweden)
- Vandbra - Core Composite 4 (Sweden)
O Vandbra-Individual Cores (L/S 10)
A- - MSWI Bottom Ash (The Netherlands)
- MSWI Bottom Ash 2 (The Netherlands)
- MSWI Bottom Ash (Germany)
MSWI Bottom Ash (Austria)
A MSWI Bottom Ash (UK)
Figure E-4. Comparison of laboratory and field concentration results for MSWI bottom ash used in
roadbase (Sweden).
E-5
-------
10 12 14
0.0001
0.01
1000
100
0 0.01
0.001
0.0001
0.01
0.1 1
L/S (L/kg)
r 1
L
^2^^
v,-'-V
0.1 1
L/S (L/kg)
10
0.01
0.1 1
L/S (L/kg)
ป Vandbra - Core Composite 1 (Sweden)
-A Va'ndora - Core Composite 2 (Sweden)
- Vandbra - Core Composite 3 (Sweden)
- Vandbra - Core Composite 4 (Sweden)
O Vandbra-Individual Cores (L/S 10)
A- - MSWI Bottom Ash (The Netherlands)
- MSWI Bottom Ash 2 (The Netherlands)
- MSWI Bottom Ash (Germany)
MSWI Bottom Ash (Austria)
A MSWI Bottom Ash (UK)
Figure E-5. Comparison of laboratory and field concentration results for MSWI bottom ash used in
roadbase (Sweden).
E-6
-------
0.001
12
14
10000
1000
100
10
1
0.1
0.01
0.001
0.0001
0.01
100
10
1 [
0.1 -f
0.01 -r
0.001
0.0001
0.01
ฃ
0.01 -:
0.001
0.01
ooo
0.1 1
L/S (L/kg)
4-
4-
0.1 1
L/S (L/kg)
0.1 1
L/S (L/kg)
ป Vandbra - Core Composite 1 (Sweden)
-A Va'ndora - Core Composite 2 (Sweden)
- Vandbra - Core Composite 3 (Sweden)
- Vandbra - Core Composite 4 (Sweden)
O Vandbra-Individual Cores (L/S 10)
A- - MSWI Bottom Ash (The Netherlands)
- MSWI Bottom Ash 2 (The Netherlands)
- MSWI Bottom Ash (Germany)
MSWI Bottom Ash (Austria)
A MSWI Bottom Ash (UK)
Figure E-6. Comparison of laboratory and field concentration results for MSWI bottom ash used in
roadbase (Sweden).
E-7
-------
Magnesium (mg/L)
B b P ^ S E
j. l_i l_i l_i O O C
r~
!
!
t^-^^
^
10
1 1-
B
0 2 4 6 8 10 12 1
PH
Magnesium (mg/L)
; p o - <
> O . I-* O C
1 h-i h-i h-i O O C
U.UUI H
4 0.
100C
IOC
5 1C
Ol
I 1
(U
8 o.i
| o.oi
ฃ 0.001
0.0001
0.00001
4
1
0.1
5
| 0.01
+->>
t
3 o.ooi
V
0.0001
0.00001
4
i
r
p
p
I
r
01
-
1
[
[
[
A
i r
< r
*^
=3
X
\ v -^ A->
ป**,
^
''' "**t
0.1 1 1
L/S (L/kg)
<
I
[
0.01
p="*s^!3
i
v^
fc^^
--^
tj.^A"*"l
o ooc^
0.1 1 1
L/S (L/kg)
f
<
0.01
ป Vandbra - Core Composite 1 (Sweden) A- - MSWI Bottom Ash (The Netherlands)
A Vandbra - Core Composite 2 (Sweden) - MSWI Bottom Ash 2 (The Netherlands)
Vandbra - Core Composite 3 (Sweden) O MSWI Bottom Ash (Germany)
Vandbra - Core Composite 4 (Sweden) -- MSWI Bottom Ash (Austria)
O Vandbra- Individual Cores (L/S 10) A MSWI Bottom Ash (UK)
-
r^^
^
0.1 1 1
L/S (L/kg)
Figure E-7. Comparison of laboratory and field concentration results for MSWI bottom ash used in
roadbase (Sweden).
E-8
-------
5 01
oi ฐ'1
^>
3n m -
TT n nm .
z
n nnm .
^N
\ ]
^\
A
^
o.Ol
> 10
0.0001
0.01
0.1 1
L/S (L/kg)
0.1 1
L/S (L/kg)
10
o.Ol
0.1 1
L/S (L/kg)
ป Vandbra - Core Composite 1 (Sweden)
A Vandbra - Core Composite 2 (Sweden)
Vandbra - Core Composite 3 (Sweden)
Vandbra - Core Composite 4 (Sweden)
O Vandbra- Individual Cores (L/S 10)
A- - MSWI Bottom Ash (The Netherlands)
- MSWI Bottom Ash 2 (The Netherlands)
O MSWI Bottom Ash (Germany)
-- MSWI Bottom Ash (Austria)
A MSWI Bottom Ash (UK)
Figure E-8. Comparison of laboratory and field concentration results for MSWI bottom ash used in
roadbase (Sweden).
E-9
-------
tassium (mg/L
5 c
DOC
ฃ
,
: '
!*?
^1|P
)
-o -o
0 2 4 6 8 10 12 1
pH
2> 0.1
1!
_ n m .
3
1
$ 0.001
n nnm -
"*)f
-W
\ Ty
\ /
-
"^
^
N
_^
,'*.
\ i
0 2 4 6 8 10 12 1
pH
1 10ฐ"
IT 10
8
55 1
0.1 -
001
1.
'
i
U
Mk
l^v,
FT/'
V
L
otassium (mg/L
i-
1-* C
^ O C
DOC
ft. 1U
1 -1
4 0.
1
2" o.i
1
a
ฃ 0.01
3
1
& o.ooi
0.0001
4
mnnn -,
I
- 10-
8
10
-M
t
Dl
A
!><^'^\C
-. \
\ ^. /
v/ '^
n a -.....,
/ L
0.1 1 1C
L/S (L/kg)
C
t-"*^.-.
L*"ฐฐฐ
A - ^t--Y ป--'
0 2 4 6 8 10 12 14 0.01
PH
ป Vandbra - Core Composite 1 (Sweden) A- - MSWI Bottom Ash (The Netherlands)
A Vandbra - Core Composite 2 (Sweden) - MSWI Bottom Ash 2 (The Netherlands)
Vandbra - Core Composite 3 (Sweden) O MSWI Bottom Ash (Germany)
Vandbra - Core Composite 4 (Sweden) -- MSWI Bottom Ash (Austria)
O Vandbra- Individual Cores (L/S 10) A MSWI Bottom Ash (UK)
* -*:<
w
0.1 1 1C
L/S (L/kg)
Figure E-9. Comparison of laboratory and field concentration results for MSWI bottom ash used in
roadbase (Sweden).
E-10
-------
10000
o 1000 -
I
'o
&
10 -
10000
o 1000 -
01
a
100 -:
10 -:
10000
1000 -:
.5
5
8 10 12 14
PH
10 12 14
10000
^ 1000 -:
um (mg
100 -r
o.Ol
01
a
.s
in
0.01
10000
0.1 1
L/S (L/kg)
nn -
in .
ป
__^
"X
V
S
\
S
-*~ L
0.1 1
L/S (L/kg)
0.1 1
L/S (L/kg)
10
ป Vandbra - Core Composite 1 (Sweden)
A Vandbra - Core Composite 2 (Sweden)
Vandbra - Core Composite 3 (Sweden)
Vandbra - Core Composite 4 (Sweden)
O Vandbra- Individual Cores (L/S 10)
A- - MSWI Bottom Ash (The Netherlands)
- MSWI Bottom Ash 2 (The Netherlands)
O MSWI Bottom Ash (Germany)
-- MSWI Bottom Ash (Austria)
A MSWI Bottom Ash (UK)
Figure E-10. Comparison of laboratory and field concentration results for MSWI bottom ash used in
roadbase (Sweden).
E-ll
-------
I
0.001
ium
Stro
0.01
0.001
0.01
0.1 1
L/S (L/kg)
T 0.1 -
01
0.01 -:
0.001 -r
0.0001
\
^A
I I'A^ I
4 6 8 10 12 14
PH
0.1
0.01
0.001 T
0.0001
0.01
4-
4-
0.1 1
L/S (L/kg)
0.1 1
L/S (L/kg)
10
ป Vandbra - Core Composite 1 (Sweden)
A Vandbra - Core Composite 2 (Sweden)
Vandbra - Core Composite 3 (Sweden)
Vandbra - Core Composite 4 (Sweden)
O Vandbra- Individual Cores (L/S 10)
A- - MSWI Bottom Ash (The Netherlands)
- MSWI Bottom Ash 2 (The Netherlands)
O MSWI Bottom Ash (Germany)
-- MSWI Bottom Ash (Austria)
A MSWI Bottom Ash (UK)
Figure E-ll. Comparison of laboratory and field concentration results for MSWI bottom ash used in
roadbase (Sweden).
E-12
-------
100 -
f-^
J 10
E 1-
^-s ฑ
N 0-1 -
0.01
0.001
[ ^^"S*0
^*
f
I
f
f
!
1
u
1
0
If*"
^^-<
$
^
^ 10
E '
^>
_C
0 2 4 6 8 10 12 14 o.Ol
PH
Dissolved Organic Carbon
(mg/L)
5 i
-L O O C
\
\
\
\
, ,L
V-
0 0
/fo
"* T
|
inn -
||
O ฃ
| 10 -
5
1- , ^
^* A!
feV^T
^%" 0^^
0.1 1 1
L/S (L/kg)
*'
0 2 4 6 8 10 12 14 0.01
PH
ป Vandbra - Core Composite 1 (Sweden) A- - MSWI Bottom Ash (The Netherlands)
A Vandbra - Core Composite 2 (Sweden) - MSWI Bottom Ash 2 (The Netherlands)
Vandbra - Core Composite 3 (Sweden) - MSWI Bottom Ash (Germany)
Vandbra - Core Composite 4 (Sweden) MSWI Bottom Ash (Austria)
O Vandbra- Individual Cores (L/S 10) A MSWI Bottom Ash (UK)
xฐ *--.
\\
\x
"'V ]
0.1 1 1
L/S (L/kg)
Figure E-12. Comparison of laboratory and field concentration results for MSWI bottom ash used in
roadbase (Sweden).
E-13
-------
APPENDIX F. INORGANIC INDUSTRIAL WASTE LANDFILL (THE
NETHERLANDS)
Table F-l. Data Sources for Laboratory-to-Field Comparisons for Inorganic Waste Landfill.
Legend ID
^^^l^^^^M
Inorganic Waste Mix
NAU-Lysimeter
13AA
NAU-Lysimeter 1
Source
^^^^^M
Nauerna Landfill,
the Netherlands
Nauerna Landfill,
the Netherlands
Nauerna Landfill,
the Netherlands
Material Type
m^^^^m^m
Mixed Waste
(predominantly
inorganic - input
to landfill]
Leachate
Leachate
ES^Siu
^^gg^H^j
pH-dependence
(CEN/TS 14429)
Percolation
CCEN/TS 14405)
Citation
^^^^^^^^H
van der Sloot et al.,
2003
van Zomeren and van
der Sloot, 2006b
van der Sloot et al.,
2003
van Zomeren and van
der Sloot, 2006b
van der Sloot et al.,
2003
van Zomeren and van
der Sloot, 2006b
F-l
-------
6.
4 -
-) .
C
AD
LmmjiL^B
F*-ป
0.000001
0.0001
0.01
L/S (L/kg)
100
-Inorganic Waste Mix
A NAU-Lysimeter 13AA
D NAU-Lysimeter 1
Figure F-l. Comparison of laboratory and field pH results for an inorganic industrial waste landfill
(The Netherlands).
F-2
-------
G;
SMI*
E1
3
_C
En 1 -
3
<
n m -
n nm .
\
^
\
\
A.
%
n !
y
In
r^
r
/
5
SMI*
E1
3
_n
En 1 -
3
<
n m -
n nni .
r g
A
nn
A
,AฃJP
omzERHHrn
w
ZL
PH
10 12 14 0.000001 0.0001 0.01
L/S (L/kg)
01
2
0.01
0.001 -
0.0001
SMI*
E
ID
CO
0.1 -:
0.01
10
12
14
0.000001
PH
0.0001 0.01
L/S (L/kg)
-Inorganic Waste Mix
A NAU-Lysi meter 13AA
D NAU-Lysimeter 1
100
100
Figure F-2. Comparison of laboratory and field concentration results for an inorganic industrial
waste landfill (The Netherlands).
F-3
-------
0.000001 0.0001 0.01
L/S (L/kg)
0.0001 0.01
L/S (L/kg)
-Inorganic Waste Mix
A NAU-Lysi meter 13AA
D NAU-Lysimeter 1
100
Figure F-3. Comparison of laboratory and field concentration results for an inorganic industrial
waste landfill (The Netherlands).
F-4
-------
0.0001 0.01
L/S (L/kg)
Inorganic Waste Mix
A NAU-Lysi meter 13AA
D NAU-Lysimeter 1
Figure F-4. Comparison of laboratory and field concentration results for an inorganic industrial
waste landfill (The Netherlands).
F-5
-------
0.0001 0.01
L/S (L/kg)
Inorganic Waste Mix
A NAU-Lysi meter 13AA
D NAU-Lysimeter 1
100
Figure F-5. Comparison of laboratory and field concentration results for an inorganic industrial
waste landfill (The Netherlands).
F-6
-------
Molybdenum (mg/L) Mercury (mg/L)
1 b P 0 1 b P 0
D OOO. O O O . c
l_i l_i l_i l_i l_i OOOO.~
O O O O C
1 .
s-^
_l
w
**- * n 1 -
"3
je
.ซ
0 01 -
n nm -
2
A
1 A
1
1 A
DCE
i i ii in
A .
HD
2 4 6 8 10 12 1
PH
r -^
nfflfe^
^
i
x^-4
/ป
f
2 4 6 8 10 12 1
PH
*.
^1
^
-fc'
^T''ni
la
k*'
r
4
A^
^
U.U1
2> o.ooi
Ol
^ 0.0001
1
01
2 0.00001
0.000001
4 O.C
1
2" o.i
Ol
E 0.01
3
c
01
o
ฃ, o.ooi
0
0.0001
4 0.00
10 -r
^^
_1
Ol
P n 1
5 ฐ-1 '
"3
je
o
Z'~ n m -
A
A
i
D
100001 0.0001 0.01 1 10
L/S (L/kg)
: ง
4n
^aB|%
A ^ 1
*ซ
ฑi
A i
1
]
ซ-
0001 0.0001 0.01 1 10
L/S (L/kg)
E
DDE
A
*
A^l
^^^
Ajปซ
ii >W
n I
N
5
4 6 8 10 12 14 0.000001 0.0001 0.01 1 10
pH L/S (L/kg)
Inorganic Waste Mix
A NAU-Lysimeter 13AA
D NAU-Lysimeter 1
Figure F-6. Comparison of laboratory and field concentration results for an inorganic industrial
waste landfill (The Netherlands).
F-7
-------
Inorganic Waste Mix
A NAU-Lysimeter 13AA
D NAU-Lysimeter 1
0)
^>
in
3
0
0.01
0.000001
0.0001 0.01
L/S (L/kg)
1000
Ul
8
ID
100 -
10 -
0.000001 0.0001 0.01
L/S (L/kg)
10000
1000
E 100 -
dium
S
Ainn
I
"4-
0.000001 0.0001 0.01
L/S (L/kg)
100
Figure F-7. Comparison of laboratory and field concentration results for an inorganic industrial
waste landfill (The Netherlands).
F-i
-------
0.1 -r
ฃ 0.01 -
0.001 -
0.0001
10000
1000
. 100
I
' 10
1
0.1
0.01
1000
' 100 -
i
'
10 -
0.0001 0.01
L/S (L/kg)
PH
PH
-Inorganic Waste Mix
A NAU-Lysi meter 13AA
D NAU-Lysimeter 1
10 12
10 12 14
14
10000
1000
T 100
10
1
0.1
0.01
ui
^>
01
I
3
W
0.000001 0.0001 0.01
L/S (L/kg)
1000
100 -
0.000001 0.0001 0.01
L/S (L/kg)
100
100
Figure F-8. Comparison of laboratory and field concentration results for an inorganic industrial
waste landfill (The Netherlands).
F-9
-------
-Inorganic Waste Mix
A NAU-Lysi meter 13AA
D NAU-Lysimeter 1
12
14
2> o.i -
1
Ol
^~>
_s
'o
ID
C
o.ooc
1000
100
10
^
"Si i
tr o.i
ฃ
N 0.01
0.001
0.0001
o.oc
E
E
ID
ffl
t&
] a Sf
V"
001 0.0001 0.01 1 10
L/S (L/kg)
[
r.
"' i
"[
[
]
A11-
%tf
i A A An
T^SM Jl
1
AA
A
I
ซ(
k!s_
0001 0.0001 0.01 1 10
L/S (L/kg)
Figure F-9. Comparison of laboratory and field concentration results for an inorganic industrial
waste landfill (The Netherlands).
F-10
-------
APPENDIX G. MUNICIPAL SOLID WASTE LANDFILL (THE NETHERLANDS)
Table G-l. Data Sources for Laboratory-to-Field Comparisons for MSW Landfill
Legend ID
MSW Organic Waste
(initial)
MSW Landfill - Core
Composite (8 yr)
MSW Landfill -
Individual Cores
(L/S 10; 8 yr)
MSW Landfill -
Leachate
(recirculation)
Source
Landgraaf, The
Netherlands
Pilot-scale
landfill,
Landgraaf, The
Netherlands
Pilot-scale
landfill,
Landgraaf, The
Netherlands
Pilot-scale
landfill,
Landgraaf, The
Netherlands
Material Type
Mixture of MSW
organic waste
Composite of
landfill cores
after 8 years in
landfill
Cored material
after 8 years in
landfill
Landfill Leachate
Data Type
pH-dependence
(CEN/TS 14429)
Percolation
CCEN/TS 14405)
pH-dependence
(CEN/TS 14429)
Percolation
(CEN/TS 14405)
Batch L/S
(EN 12457-2)
Citation
Luningetal., 2006
van der Sloot et al.,
2008a
Luningetal., 2006
van der Sloot et al.,
2008a
Luningetal., 2006
van der Sloot et al.,
2008a
Luningetal., 2006
van der Sloot et al.,
2008a
G-l
-------
I I I I ? I I I
0.01
12 14
-A MSW Organic Waste (initial)
-MSW Landfill - Core Composite (8 yr)
O MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
O)
E
^
<
10
1 -L-
0.1 -:
0.01
-M*
4-
4-
0.001 0.01
0.1 1
L/S (L/kg)
10
u
'c
01
0.01 -:
0.001 - r
0.0001
0.01
0.001 0.01
0.1 1
L/S (L/kg)
100
0.001 0.01 0.1 1 10 100
L/S (L/kg)
Figure G-l. Comparison of laboratory and field concentration results for a municipal solid waste
landfill (The Netherlands).
G-2
-------
10000
10000
2> 1000 -
I
Hi 100
o
10
-+-
-4-
6 8
pH
10
12
A MSW Organic Waste (initial)
MSW Landfill - Core Composite (8 yr)
ป MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
14
10000
^ 1000 -
Calcium (mg
100 -
0.001
0.01
0.1 1
L/S (L/kg)
_
I
3
10
1
0.1
0.01
0.001
0.0001
0.00001
00
4-
4-
4-
0.001 0.01
0.1 1
L/S (L/kg)
10000
10
0.001
0.01
0.1 1
L/S (L/kg)
100
100
100
Figure G-2. Comparison of laboratory and field concentration results for a municipal solid waste
landfill (The Netherlands).
G-3
-------
0.1 1
L/S (L/kg)
10
A MSW Organic Waste (initial)
MSW Landfill - Core Composite (8 yr)
MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
100
100
100
Figure G-3. Comparison of laboratory and field concentration results for a municipal solid waste
landfill (The Netherlands).
G-4
-------
1000 -
_ 100 -
w 10 -
SMI*
_ 1 .
s
l"H n 1
n m -
(
100
10
5 1
01
,ง, 0.1
o
3 0.01
0.001
0.0001
mnn
2> 100 -r
1
.c. m _ .
Magnesium I
i P
* I-1 l-L C
1 1
0
I
f
1
[
*>^
*T
M
_i
"fl?
^-
VA^
^
) 2 4 6 8 10 12 1
PH
0
2
^
.
^
?
i3T
csW
T
4&^
2 4 6 8 10 12 1
PH
=ฑ1
n
*H
1^
3t
\t>
0
A,-A
V-1
_l
NUT*
S
" 01-
4 O.C
100
10
5 1
Ol
ฃ 0.1
o
% 0.01
0.001
0.0001
4 0
1 i
O)
t i n -
E
3
S'~ i
1 i
C
Ol
IS
S 0.1 -:
!
1
*-ฃ&
***!
%'
"A
i
k
i
01 0.01 0.1 1 10 10
L/S (L/kg)
C
) A
0
iV^J
^^^w
P^I
r_2ง_
^7?
l!i
i
001 0.01 0.1 1 10 10
L/S (L/kg)
0
-Xtป
1
<
*b
L m^
V*
i
4 6 8 10 12 14 0.001 0.01 0.1 1 10 10
pH L/S (L/kg)
A MSW Organic Waste (initial)
MSW Landfill - Core Composite (8 yr)
MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
Figure G-4. Comparison of laboratory and field concentration results for a municipal solid waste
landfill (The Netherlands).
G-5
-------
0.1
f-^
_l
1 o.oi
^>
ฃ
g o.ooi
01
0.0001
0.00001
s-^
1 1-
^>
1 01-
c
01
o
ja
>.
'
O
O
0
1
ta^
O
3
)
0 2 4 6 8 10 12 1
PH
:
0
1 -
5
Ol
01
je
u
r
4
~
\
\\,
^
2
0
z
fe
4
*s
2
J
4
''^
Jj
f "**
b
o
*-A
^
0.1
f-^
_l
1 o.oi
^>
ฃ
g o.ooi
01
0.0001
0.00001
4
S^
^ 1 -
1
^>
.
s
'
0
U Of
o
0
u
6~
D.001 0.01 0.1 1 10 10
L/S (L/kg)
0
4
_*-
*-ฃ
eft
1
V
ft
1
6 8 10 12 14 0.001 0.01 0.1 1 10 10
pH L/S (L/kg)
^
O
4
^
1
0
t^^*
*-*
^
^^
_i
Ol
^ 0.1
01
*e
o
0.01
:
o
4
^
cn^bu
6 8 10 12 14 0.001 0.01 0.1 1 10 10
PH L/S (L/kg)
A MSW Organic Waste (initial)
MSW Landfill - Core Composite (8 yr)
MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
Figure G-5. Comparison of laboratory and field concentration results for a municipal solid waste
landfill (The Netherlands).
G-6
-------
10
0.01
0
O
o
0
l-^
O
o
0
Potassium (mg
Selenium (mg
,-,
o
h-i
0.001 -
0
U.
2
g
0.1 1
L/S (L/kg)
A MSW Organic Waste (initial)
MSW Landfill - Core Composite (8 yr)
MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
10
100
Figure G-6. Comparison of laboratory and field concentration results for a municipal solid waste
landfill (The Netherlands).
G-7
-------
E
3
'5
v> in -
0
J1
1
*S
M
*=*
2
0
=ป
o
1
?
y
^
^
0 2 4 6 8 10 12 1
pH
A MSW Organic Waste (initial)
B MSW Landfill - Core Composite (8 yr)
MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
-t
Vanadium (mg/L)
0
ง b P o
S S S b P
/
\
t
C
o
%o
wl
O^\rj ป 1
&\
\
1
k
0.01 0.1 1 10 10
L/S (L/kg)
d
0
0
* >
*- MM
^
0
tf
j, V
k
0.001 0.01 0.1 1 10 10
L/S (L/kg)
Figure G-7. Comparison of laboratory and field concentration results for a municipal solid waste
landfill (The Netherlands).
GO
-O
-------
Ol
u
c
N 0.1 -
0.01 -
tx
x
\
\
1
1
o
r
-(^i
Jm
i^^
_i
1
Ol
E n 1 -
U
C
N
o
i
TPy^
1
ฐ0
^
h
ฐ^L\
o" Y
\
1
1
0 2 4 6 8 10 12 14 0.001 0.01 0.1 1 10 10
pH L/S (L/kg)
A MSW Organic Waste (initial)
MSW Landfill - Core Composite (8 yr)
MSW Landfill - Individual Cores (L/S 10; 8 yr)
O MSW Landfill Leachate (recirculation)
Figure G-8. Comparison of laboratory and field concentration results for a municipal solid waste
landfill (The Netherlands).
G-9
-------
APPENDIX H. STABILIZED MUNICIPAL SOLID WASTE INCINERATOR FLY ASH
DISPOSAL (THE NETHERLANDS)
Table H-l. Data Sources for Laboratory-to-Field Comparisons for Stabilized Waste (The Netherlands).
Legend ID
Fresh Stabilized
Waste
Monofill - Individual
Cores (lOyr]
Monofill Leachate
Cell B - Core
Composite (4 yr]
Cell B - Individual
Cores (L/S 10; 4 yr]
Cell B Leachate
Cell C - Composite
(covered; 4 yr]
Cell C - Individual
Cores (L/S 10; 4 yr]
Cell C Leachate
Cell D - Individual
Cores (4 yr]
Cell D Leachate
Source
Full-scale
monofill,
Full-scale
monofill,
Pilot Cell B
(MSWI FA,
5x8x2. 4m]
Pilot Cell B
Pilot Cell B
Pilot Cell C
(MSWI FA,
5x8x2. 4m]
Pilot Cell C
Pilot Cell C
Pilot Cell D
(MSWI FA,
5x8x2. 4m]
Pilot Cell D
Material Type
S/S MSWI FA
Individual cores
at depth > 12 m
Field Leachate
(bottom of drain]
Composite - top
layer uncovered
cell
Individual cores
at depth
Field Leachate
(bottom of drain]
Composite - top
layer covered cell
Individual cores
at depth
Field Leachate
(bottom of drain]
Composite - top
layer uncovered
cell
Field Leachate
(bottom of drain]
Data Type
pH-dependence
(CEN/TS 14429]
Percolation
(CEN/TS 14405]
Batch L/S
(EN 12457-2]
Percolation
(CEN/TS 14405]
pH-dependence
(CEN/TS 14429]
Batch L/S
(EN 12457-2]
pH-dependence
(CEN/TS 14429]
Batch L/S
(EN 12457-2]
pH-dependence
(CEN/TS 14429]
Citation
van Zomeren and van
derSloot, 2006b
Keulen,2010
van Zomeren and van
derSloot, 2006b
Keulen,2010
van Zomeren and van
derSloot, 2006b
Keulen,2010
van Zomeren and van
derSloot, 2006b
Keulen,2010
van Zomeren and van
derSloot, 2006b
Keulen,2010
van Zomeren and van
derSloot, 2006b
Keulen,2010
van Zomeren and van
derSloot, 2006b
Keulen,2010
van Zomeren and van
derSloot, 2006b
Keulen,2010
van Zomeren and van
derSloot, 2006b
Keulen,2010
van Zomeren and van
derSloot, 2006b
Keulen,2010
van Zomeren and van
derSloot, 2006b
Keulen,2010
H-l
-------
14
12 -
10 --
a
ฐ
>oฐ%ฐ8
0.000001 0.0001 0.01
L/S (L/kg)
100
o.oi
o.ooi i
o.oi
o.ooi -
0.000001
0.0001
0.01
L/S (L/kg)
0.01
6 8
PH
10
D
O
M
D
0.01
o.oooooi
0
*
0.0001
0.01
L/S (L/kg)
100
-Fresh Stabilized Waste * Cell B- Core Composite (4yr)
O Monofill - Individual Cores (10 yr) * Cell B- Individual Cores (L/S 10; 4 yr)
O Monofill Leachate O Cell B Leachate
A Cell C-Core Composite (covered; 4 yr) D Cell D- Individual Cores (L/S 10;4yr)
A Cell C - Individual Cores (L/S 10; 4yr) D Cell D Leachate
A Cell C Leachate
Figure H-l. Comparison of laboratory and field pH for stabilized MSWI fly ash disposal (The
Netherlands).
H-9
-------
Aluminum (mg/L)
I b P ^ 5 8 1
-'h-'l-'l-'OOOC
1 j 4 j j j 4 4
4
^
s_
^s
\j.
)
\
y&
j|
ซงฃ
V&
IDly
&
^0.
a&
TO
5
p
D
Aluminum (mg/L)
I b P ^ S 8 1
J.|_L|_L|_LOOOC
I
r
r
f
r
r
[
&/
rV
&o n
/vtf*,
vnj
ป
* \^
V W\
i
M
"ft
V
0 2 4 6 8 10 12 14 0.000001 0.0001 0.01 1 10
pH L/S (L/kg)
10000 -
^^
_l
1
g1 1000 -
^>
E
3 100 -
3
10 -
1 _
c
1000000
100000
^^
_l
1
f 10000
^>
01
= 1000
^
u
100
10
t
*=**
^
hsp
^^
-
n.
*ซf*i
r^
^
W
*-
f
2 4 6 8 10 12 1
PH
|
O
-
<>-
4P
^
i. X [
1
> * "
^
^v
0 ฐ
T A -A
s*^^
t
^
0 2 4 6 8 10 12 1
pH
_l
'
9
_3
|w
3 in -
4 O.OOC
1000000
100000
f-^
^ 10000
V 1000
^
| 100
u
10
1
4 0.(
n
A o
n O n A
AQ0 D
1001
-
r
r
[E
p
CCQ
$
A ? ป<
vC
>ฐ0o
s*-*
0.0001 0.01 1 10
L/S (L/kg)
ฐ0
^ ฐ
'DO ,
tSQ><*
5
n
^u*
;7^
1
i
^
)00001 0.0001 0.01 1 10
L/S (L/kg)
Fresh Stabilized Waste Cell B - Core Composite (4 yr)
Monofill - Individual Cores (10 yr) O Cell B- Individual Cores (L/S 10; 4 yr)
O Monofill Leachate O Cell B Leachate
A Cell C - Core Composite (covered; 4 yr) D Cell D - Individual Cores (L/S 10; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr) D Cell D Leachate
A Cell C Leachate
Figure H-2. Comparison of laboratory and field concentration results for stabilized MSWI fly ash
disposal (The Netherlands).
H-9
-------
10
0.1
12
14
Chromium
P
0
l_i
0.001 -
0.0001
AA
o
A
D
O
2fe
"V
0.000001 0.0001 0.01
L/S (L/kg)
100
mg
Coppe
0.0001
0.000001
0.0001 0.01
L/S (L/kg)
0.000001
0.0001 0.01 1
L/S (L/kg)
Fresh Stabilized Waste Cell B - Core Composite (4 yr)
Monofill - Individual Cores (10 yr) O Cell B- Individual Cores (L/S 10; 4 yr)
O Monofill Leachate O Cell B Leachate
A Cell C - Core Composite (covered; 4 yr) D Cell D - Individual Cores (L/S 10; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr)
A Cell C Leachate
D Cell D Leachate
Figure H-3. Comparison of laboratory and field concentration results for stabilized MSWI fly ash
disposal (The Netherlands).
H-9
-------
-1 1
Ul
c
^ 0.01
0.001 -
n nnm -
<
1000
100
10
5 1
Ol
.E 0.1
g 0.01
0.001
0.0001
0.00001
mnn
Magnesium (mg/L)
I b P ~ E
j. l_i l_i l_i O C
j I i i i
\
NS
N
\
\
i
&H
o
|^
^
t|
ฃ_
*
3 2 4 6 8 10 12 1
PH
!
"
irv
\s
\
J]A C
O^ฐ
L
O
V
V
?***
0 2 4 6 8 10 12 14 0.000001 0.0001 0.01 1 10
pH L/S (L/kg)
Fresh Stabilized Waste Cell B - Core Composite (4 yr)
Monofill - Individual Cores (10 yr) O Cell B- Individual Cores (L/S 10; 4 yr)
O Monofill Leachate O Cell B Leachate
A Cell C - Core Composite (covered; 4 yr) D Cell D - Individual Cores (L/S 10; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr) D Cell D Leachate
A Cell C Leachate
Figure H-4. Comparison of laboratory and field concentration results for stabilized MSWI fly ash
disposal (The Netherlands).
H-9
-------
10 -
E
^ 0 1
M
= 0.01
ID
Dl
E, 0.001
z
0.0001
0.00001
o.c
^. o.oc
1
Dl
^ o.ooc
01
2 o.oooc
o.ooooc
inn
3 O i-< T-
3 ^ c
(l/6ui) uinua
I 0.01
0
1
1
1
1
1
i
ซ
A
^ *^
i
. '1K>
N|?
AซrJ\V-
_
^* A
.nฐ..
10 -r
E :
^^ ' 01-
Oj
1 ฐ-01-:
DI :
0.001 -r
Z
0.0001 -r
n nnnm _ .
g
O
A
ฐn<
rPg
o 2
to
L
a*.
.A
^
2 4 6 8 10 12 14 0.000001 0.0001 0.01 1 1C
pH L/S (L/kg)
0
:
<
ฐ8
Cttf
A
0
O
)O
ฎ
0
ซ
o
p
1
Dl
01
2 0.00001 -
n nnnnm _
0 DA<
/s
: ./
.
V
7
2 4 6 8 10 12 14 0.000001 0.0001 0.01 1 1C
pH L/S (L/kg)
1AA
t
N?
^
/
/
^
M
T
n
zy
R
M>
^
S^
n
_^_^
3 O i-l i-
3 ^ c
(l/6ui) uinua
o <^
^ n A
f A DO
D
o V
X
5
0 2 4 6 8 10 12 14 0.000001 0.0001 0.01 1 1C
pH L/S (L/kg)
Fresh Stabilized Waste Cell B - Core Composite (4 yr)
Monofill - Individual Cores (10 yr) O Cell B- Individual Cores (L/S 10; 4 yr)
O Monofill Leachate O Cell B Leachate
A Cell C - Core Composite (covered; 4 yr) D Cell D - Individual Cores (L/S 10; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr) D Cell D Leachate
A Cell C Leachate
Figure H-5. Comparison of laboratory and field concentration results for stabilized MSWI fly ash
disposal (The Netherlands).
H-9
-------
1
5 O-1
at
^ 0.01
01
~ 0.001
0.0001
0.00001
Potassium (mg/L)
h-
!- C
I-1 O C
!- O O C
h-^ 0 0 0 C
-L O O O O C
-
'
L
t
^1
Wo
\
jNqjjtf
IN
\
>
N/
V
A
rtestgo
0 2 4 6 8 10 12 1
pH
p
p
r
r
0
1
j"
Selenium (mg
1 g F
* h-i 1-
*.
^
2
i
0
m
>L
^^
<
4
^J
>
>v
X
^ArA
Qa5fiTTปJ
fij
^%4P
:*ฃ>
1
"Si o.i
^ 0.01
u
Z
0.001
0.0001
4 O.OC
^ 10000 -
Ol
,ง 1000 -
E
1 10ฐ "
1 .
rjtfT^
:A ฐฐ
U
mn c
^0*
o
00 0(
V.
0001 0.0001 0.01 1 10
L/S (L/kg)
. A
A D
O C
[Ai ^ n
n
tlQ^!?'
n
O
o
U
L
s
4 6 8 10 12 14 0.000001 0.0001 0.01 1 10
pH L/S (L/kg)
^
^
2
r*^ซ
.^/i
E::s^
0
o
n
a?
^
rf
*^
sgl ^p
V1 y^"
J1
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E
3
'E
o> n m -
01
w
O
<^
n
al ฃ
^o nn A.
A
&
.M
(
^
4 6 8 10 12 14 0.000001 0.0001 0.01 1 10
pH L/S (L/kg)
Fresh Stabilized Waste Cell B - Core Composite (4 yr)
Monofill - Individual Cores (10 yr) O Cell B- Individual Cores (L/S 10; 4 yr)
O Monofill Leachate O Cell B Leachate
A Cell C - Core Composite (covered; 4 yr) D Cell D - Individual Cores (L/S 10; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr) D Cell D Leachate
A Cell C Leachate
Figure H-6. Comparison of laboratory and field concentration results for stabilized MSWI fly ash
disposal (The Netherlands).
H-9
-------
10000
I1 1000
ฅ
.= 100
o
o
w
10
1
100000
10000
I1 1000
2 100
w
10
1
innnn T
3
W
in .
0
1
> <
^^
5
^
ฃq
a
^
> n
f
'
^
ซo>
ป/
>
n
10000
I1 1000
ฅ
.= 100
o
o
w
10
1
n ^
O D
:B 0 <
n n
^
^> *^
1
0 2 4 6 8 10 12 14 0.000001 0.0001 0.01
pH L/S (L/kg)
: *
\
> -<
fc=!
JS
|Bป
4
0246
PH
4
> t,
eป=-<
if
^
$
*%<
r
10000
I1 1000
2 100
w
10
1
o
1 <> -
0<^
%
^ ft
o
v
\
L 10
>
k
3 10 12 14 0.000001 0.0001 0.01 1 10
L/S (L/kg)
1 AAAA
^
ซ
*
0
A
D
01
3
W
in .
O
Aa
-------
12
14
100
10 -:
on
S
OPD
,Dl
.^
n
0.1
0.000001
oV
0.0001
0.01
L/S (L/kg)
10
01
^>
E
3
0.01 -
0.001
0.0001
nrf
O
\
.o.
"V
0.000001 0.0001 0.01 1
L/S (L/kg)
Zinc
0.000001
0.0001 0.01
L/S (L/kg)
< Fresh Stabilized Waste Cell B - Core Composite (4 yr)
O Monofill - Individual Cores (10 yr) O Cell B-Individual Cores (L/S 10; 4yr)
Monofill Leachate O Cell B Leachate
Cell C - Core Composite (covered; 4 yr) D Cell D - Individual Cores (L/S 10; 4 yr)
A Cell C - Individual Cores (L/S 10; 4yr)
A Cell C Leachate
D Cell D Leachate
100
100
mnn -
m -
n 1 -
n m -
[
^JL n
A ^ ฐ D
ID <
[
o n
o ^
L
?
**
o
v_
-
100
Figure H-8. Comparison of laboratory and field concentration results for stabilized MSWI fly ash
disposal (The Netherlands).
H-9
-------
APPENDIX I: PORTLAND CEMENT MORTARS AND CONCRETE
Table 1-1. Data Sources for Laboratory-to-Field Comparisons for Portland Cement Mortars and
Concrete
Legend ID
Cement Mortar GEM
I(DE)
Concrete - Core (40
yr, rain exposed, DE)
Concrete - Core (40
yr, immersed, DE)
Roman Aqueduct -
Core (2,000 yr; DE)
Cement Mortar GEM
I (NO)
RCA (fresh, NO)
RCA - Roadbase (4
yr, <10 mm, NO)
RCA - Roadbase (4
yr, 2 0-12 Omm, NO)
Source
Germany
Germany
Germany
Norway
Norway
Norway
Norway
Material Type
GEM I type cement
mortar
Core from Roman
Aqueduct
GEM I type cement
mortar
Recycled Concrete
Aggregate
Recycled Concrete
Aggregate, recovered
from roadbase
(depth < 10 mm
Recycled Concrete
Aggregate, recovered
from roadbase
Data Type
^^^^^^^^m
pH-dependence
pH-dependence
pH-dependence
pH-dependence
pH-dependence
pH-dependence
pH-dependence
pH-dependence
Citation
^^^^^^^^^^
SchiefSl,2003
SchiefSl,2003
SchiefSl,2003
van der Sloot et al.,
2011
Engelsen et al., 2009;
2010
Engelsen etal., 2009;
2010
Engelsen etal., 2009;
2010
Engelsen etal., 2009;
2010
-------
100 -
"Si 10 -
I *
En 1 -
3
0.01 -
0
1
0.1
1* o.oi
o
1 o.ooi
2
0.0001
0.00001
10
1
01
^ 0.01
ฃ
o o.OOl
0.0001
0.00001
M
\
L
\
\ \
\ 1
?
/
t
_-.
v-^s
0.01 -
5 n nm -
D
il
"ฐ.
V **
K'
I "
^
i ,1
^
_O^-k
r
D
2 4 6 8 10 12 14 0 2 4 6 8 10 12 1
pH pH
N
K
i,,__
o
=4-
B Oi
A
1.4
n
n
A
0 2 4 6 8 10 12 1
PH
! ~i
[Sffib iQj) E
i \
\
^
'^^
> ^
2
St.
)
^
k
0 2 4 6 8 10 12 1
PH
10 -
j~
I M
E
i
0.01 -
4 0
1
^ 0.1
01
.ง ฐ-01
ฅ
| o.ooi
o
ฐ 0.0001
0.00001
4
1
:?
M
>
^
^ i
\
3
**$
* n
,!-"
D [D
'A. yv
/ ~
>
"
2 4 6 8 10 12 1
PH
C
ฐSX
c
D
/-
^Vi
p
024
Cement mortar CEM 1 (DE) - Cement mortar CEM 1 (NO)
O Roman Aqueduct - Core (2,000 yr) RCA (fresh; NO)
A Concrete - Core (40 yr exposed to rain, DE) D RCA - Roadbase (4 yrs; <10 mm, NO)
A Concrete - Core (40 yr imersed, DE) RCA - Roadbase (4 yrs; 20-120 mm; NO)
-A
/
-------
era
n
o
3
a
o
o
*!
O
s
a
3
O
o o
, m
i' x "3
n> "a fj,TJ}
S 8 o
D
m
I D
I 70 70 O
Iron (mg/L)
Copper (mg/L)
Calcium (mg/L)
S S
I I
I I
'
/
>o
/
0 -1
f
*
1
[
1
I
&
S
on
W
*
Lead (mg/L)
Dissolved Organic Carbon
(mg/L)
Chromium (mg/L)
on
-------
Cement mortar CEM 1 (DE)
O Roman Aqueduct - Core (2,000 yr)
A Concrete - Core (40 yr exposed to rain, DE)
A Concrete - Core (40 yr imersed, DE)
- Cement mortar CEM 1 (NO)
RCA (fresh; NO)
D RCA - Roadbase (4 yrs; <10 mm, NO)
RCA - Roadbase (4 yrs; 20-120 mm; NO)
Figure 1-3. Comparison of portland cement mortars, concretes and recycled aggregates.
-------
issium (mg/L)
h-
!- C
* o c
DOC
1 1 1
S.
0
10000
1000
1> 100
c
8 10
55
1
0.1
inn
trontium (mg/L)
E
-ป !-ป 0 C
W "
C
DD
>
\
<
n oC
r-"~v,
n E
L
-
^$B C
1 A">
r~ ^i_r
l^
A
A
2 4 6 8 10 12 1
PH
r
^V
t^-..
^ฃ3
0
,'
\
>
0 2 4 6 8 10 12 1
PH
<
: *1
^---g^^. A - A
tPiffl:
H
^j^"T^
\ 1
\
\
*\
4
^B D
4
"
B
% ^,
A
V
1
*"7* 0.
I
ฃ 0.0]
_3
W 0.00]
0.000]
4
10000
^ 1000
'c' 100
3
'o
ซ 10
1
4
mnn
llfate as S (mg/L)
h
h-^ C
I-' O C
* o o c
I I I I
(fi
-
-
^n
; s
O
v
f-v-
\
^
"
^n
/
/
o
^
4ฐ
0 2 4 6 8 10 12 1
PH
r
<
0
>
q
2
DD
0
0 2 4 6 8 10 12 14 0
PH
c
2
3iqf
n
JH
^^^ rrcrr
c
-I ฃh
*
>
fi-n
ป
ซ-
f
4 6 8 10 12 1
PH
&
O
~ m
X
4 6
o
o
x>
fl
rg-^
D^
5
n
^
8 10 12 1
PH
Cement mortar CEM 1 (DE) - Cement mortar CEM 1 (NO)
O Roman Aqueduct - Core (2,000 yr) RCA (fresh; NO)
A Concrete - Core (40 yr exposed to rain, DE) D RCA - Roadbase (4 yrs; <10 mm, NO)
A Concrete - Core (40 yr imersed, DE) RCA - Roadbase (4 yrs; 20-120 mm; NO)
Figure 1-4. Comparison of portland cement mortars, concretes and recycled aggregates.
-------
01
0.0001
0.00001
0 2 4 6 8 10 12 14
PH
0.0001
0 2 4 6 8 10 12 14
PH
10 -
:? i
1
a
,ง 0.1 -
u
c
n nni -
D
r -
'
D
I
bdtS
T\\ ]
'>
'
i
:
\f
K-\!
<
^d
. .D
*T5tf
A
0 2 4 6 8 10 12 14
PH
Cement mortar CEM 1 (DE) - Cement mortar CEM 1 (NO)
O Roman Aqueduct - Core (2,000 yr) RCA (fresh; NO)
A Concrete - Core (40 yr exposed to rain, DE) D RCA - Roadbase (4 yrs; <10 mm, NO)
A Concrete - Core (40 yr imersed, DE) RCA - Roadbase (4 yrs; 20-120 mm; NO)
Figure 1-5. Comparison of portland cement mortars, concretes and recycled aggregates.
------- |