EPA 600/R-18/011 | July 2019 | www.epa.gov/research
United States
Environmental Protection
Agency
v>EPA
Vulnerability of Waste Infrastructure to Climate
Induced Impacts in Coastal Communities
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Vulnerability of Waste Infrastructure to Climate-
Induced Impacts in Coastal Communities
U.S. Environmental Protection Agency
Office of Research and Development
National Risk Management Research Laboratory
Research Triangle Park, NC
National Center for Environmental Assessment
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
DISCLAIMER
This document has been reviewed in accordance with U.S. Environmental Protection Agency
policy and approved for publication. Mention of trade names or commercial products does not
constitute endorsement or recommendation for use.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
AUTHORS, CONTRIBUTORS, AND REVIEWERS
This study was conducted under the Air, Climate, and Energy (ACE) research program of EPA's Office of
Research and Development. The initial draft of the report was prepared by RTI International in Research
Triangle Park, NC under U.S. EPA Contract Number EP-D-11-084, Work Assignment 4-04, Task 5. Ozge
Kaplan served as the Technical Lead and Alternative Work Assignment Manager, providing overall
direction and technical assistance, and was a contributing author.
MAIN AUTHORS:
Ozge Kaplan, U.S. EPA, Office of Research and Development
Britta Bierwagen, U.S. EPA, Office of Research and Development
Susan Julius, U.S. EPA, Office of Research and Development
Marissa Liang, U.S. EPA, Office of Research and Development
Susan Thorneloe, U.S. EPA, Office of Research and Development
Keith Weitz, RTI International
PROJECT TEAM:
Kibri Everett, RTI International
INTERNAL REVIEWERS:
Paul Lemieux, U.S. EPA, Office of Research and Development
Mario lerardi, U.S. EPA, Office of Land and Emergency Management
Chris Carusiello, U.S. EPA, Office of Land and Emergency Management
William H. Yelverton, U.S. EPA, Office of Research and Development
C. Andy Miller, U.S. EPA, Office of Research and Development
EXTERNAL REVIEWERS:
Morton A. Barlaz, North Carolina State University
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Tabie of Contents
DISCLAIMER II
AUTHORS, CONTRIBUTORS, AND REVIEWERS Ill
EXECUTIVE SUMMARY 1
1. INTRODUCTION 5
1.1. Project Goal 5
1.2. Coastal Community Case Study Site 5
1.3. Climate Resiliency Studies in The Norfolk Area 6
2. MODELS 7
2.1. Incident Waste Decision SupportTool(I-WASTE) 7
2.2. Municipal Solid Waste Decision SupportTool(MSW DST) 8
3. DATA AVAILABILITY AND LIMITATIONS 9
3.1. Waste Infrastructure 9
3.2. Transportation and Utilities Infrastructure 12
3.3. Natural Weather Events 12
3.4. Sea Level Rise 13
3.5. Identified Gaps in the Existing Data and Information 13
3.5.1. Waste Infrastructure 14
3.5.2. Climate-Related Impacts 14
4. CLIMATE-INDUCED RISKS: PRECIPITATION 14
4.1. Frequency of Tropical Storms 15
4.2. Intensity of Tropical Cyclones 19
4.3. Summary of Frequency and Intensity Data for Norfolk, VA 20
4.4. Hurricane Intensity versus Flooding Probability 22
4.5. Key Findings and Observations 22
5. CLIMATE-INDUCED RISKS: SEA LEVEL RISE 23
5.1. Geological Characteristics of the Virginia Coastal Plain 24
5.2. Approaches for Analyzing the Effects of Sea Level Rise on Groundwater 28
5.2.1 Use of MODFLOW to Simulate Current and Future Groundwater Levels 28
5.2.2 Use of the Pee Dee River and Atlantic Intracoastal Waterway Salinity Model-Decision Support System
(PRISM2-DSS) 29
6. UNDERSTANDING IMPACTS ON LANDFILLS 29
6.1. Precipitation related 29
6.2. Sea Level Rise 30
7. UNDERSTANDING IMPACTS ON TRANSPORTATION INFRASTRUCTURE 32
7.1. Transportation Infrastructure Supporting Waste Management 33
7.2. Disruptions-Duration, RecoveryTimes, and Alternative Options 36
7.3. Sea Level Rise and Groundwater 38
8. UNDERSTANDING IMPACTS ON UTILITIES AND OTHER SUPPORTING INFRASTRUCTURE 38
8.1. Water Supply 38
8.2. Electric Utilities 38
9. ASSESSING COST AND ENVIRONMENTAL IMPACTS OF ALTERNATIVE WASTE MANAGEMENT SCENARIOS.. 38
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
9.1. Scenarios Analyzed Usingthe MSW DST 39
9.2. Scenario Results 44
9.2.1. Cost 44
9.2.2. Energy Consumption 45
9.2.3. Carbon Emissions 46
9.3. Sensitivity Analyses 47
10. CONCLUDING REMARKS 48
11. REFERENCES 50
APPENDIX A: DETAILED SCENARIO MODELING RESULTS 56
GLOSSARY 72
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
List of Tables
Number Page
Table ES-1. Base Case and Alternative MSW Flow and Management Facilities 3
Table 1. List of Waste Facilities in the Norfolk Region from l-WASTE 11
Table 2. List of Transportation Data Sources 12
Table 3. List of Weather-Related Data Sources 13
Table 4. List of Data Sources for Sea Level Rise Analysis 13
Table 5. Summary of Annual Probabilities for Hurricanes at Norfolk, VA 19
Table 6. Frequency of Occurrence for Category 1 to 5 Landfalling Hurricanes 19
Table 7. Cumulative Probability of Different Hurricane Intensities at Norfolk, VA 21
Table 8. Hurricane Scenarios for Norfolk, VA 22
Table 9. Flooding Probabilities at Norfolk Waste Sites, for Various Hurricane Categories 23
Table 10. Major Roads, Bridges, and Tunnels Supporting Waste Management in and around Norfolk 34
Table 11. Mass Flows of MSW for Simulation Scenarios including Base Case 39
Table 12. Facilities and Tonnages Used for Base Case and Alternative MSW Management Scenarios 40
Table 13. Key Assumptions Used in the Scenario Analysis 42
Table 14. Assumed Waste Composition Based on U.S. Average 43
Table 15. Regional Average Electricity Grid Mix of Fuels Used in the Scenario Analysis 43
Table 16. Summary Level Scenario Results (NetTotals) 49
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
List of Figures
Number Page
Figure ES-1. Norfolk Waste Facilities with Hurricane Storm Surge Categories 3
Figure 1. Map of Waste Facilities Available from l-WASTE 10
Note: Thetriangle represents Norfolk, VA; Source: NOAA, 2014a 17
Figure 3. Probability (%) per year of a hurricane coming within 60 miles of any point in the North Atlantic 17
Note: Thetriangle represents Norfolk, VA; Source: NOAA, 2014a 18
Figure 4. Probability (%) per year of a major hurricane coming within 30 miles of any point in the North Atlantic.... 18
Figure 5. Sea LevelTrend atSewell's Point, VA 24
Figure 6. Generalized Hydrogeologic Section and Direction of Groundwater Flow in the Virginia Coastal Plain
Groundwater Changes Resulting from Sea Level Rise 25
Figure 7. USGS Groundwater Wells (depth to water, feet below land surface) 26
Figure 8. Areas Currently Subjectto Shallow Coastal Flooding 27
Figure 9. Coastal Flood Frequency at Sewells PointTide Gauge (Source: NOAA) 28
Figure 10. Overview of OLEM 3MRA Modules to Model Releases, Fate and Transport, Exposures, and Risks from
Waste Management Units 32
Figure 11. Annual Average DailyTraffic Counts for Major Roads in Norfolk 35
Figure 12. Norfolk Waste Management Facilities with Hurricane Storm Surge Categories 36
Figure 13. Location of Base Case and Assumed Alternative MSW Management Facilities 41
Figure 14. NetTotalCost Results for Scenarios Modeled 45
Figure 15. NetTotal Energy Consumption Results for Scenarios Modeled in Million BTUs 46
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Executive Summary
A recent report by the U.S. Global Change Research Program (USGCRP) states that "Global average sea
levels are expected to continue to rise, by at least several inches in the next 15 years and by 1-4 feet by
2100" (USGCRP, 2017). These levels are even higher than the projected ranges estimated by an earlier
report by the Intergovernmental Panel on Climate Change (IPCC) (IPCC, 2001). USGCRP (2017) states
expected sea-level rise (SLR) would be higher than the global average on the East and Gulf Coast of the
United States (U.S.). This projected SLR coupled with other climate-induced impacts such as more
frequent and intense heavy precipitation events, hurricanes and resulting storm surges, and increase in
number of tidal floods (nuisance floods) may increase recurring damage to municipal infrastructure,
including waste management facilities. The potential for climate-induced impacts thus creates an
immediate concern for the security and resiliency of communities, specifically coastal communities.
The goal for this project was to devise a methodology for communities to utilize in understanding the
effects of climate-induced extreme weather events and their impacts (e.g., SLR, storm surge, flooding,
tidal flooding) on waste management facilities and their operation. The methodology included (1)
mapping and other analytic/statistical methods to identify community characteristics at multiple spatial
scales and evaluate locations and site-specific characteristics, (2) U.S. Environmental Protection Agency's
(EPA's) Incident Waste Decision Support Tool (l-WASTE) tool to identify the locations of waste
management facilities, and (3) U.S. EPA's Municipal Solid Waste Decision Support Tool (MSW DST) to
understand life-cycle impacts of waste management operations and demonstrate how plans can be
modified to robustly incorporate resilience to climate change. These tools further advanced the
understanding of future uncertainty of the extent and impact of these events into long term waste
management planning. The methodology is illustrated for City of Norfolk, Virginia and surrounding area;
however, the methods and the data sources can be utilized in other communities.
Climate-induced impacts on communities could be categorized into three components: 1) temperature,
2) precipitation, and 3) sea level rise (SLR) (Zimmerman, 2010) related impacts. Temperature impacts
include long-term changes in mean annual temperatures as well as changes in frequency, duration, and
intensity of heat waves. Precipitation impacts include long-term changes in mean annual precipitation as
well as intensity and frequency of these events. SLR impacts include inundation and extent of storm
surge. The report focuses on impacts of precipitation (Chapter 4) and SLR (Chapter 5). Chapter 4
presents the data available for historic precipitation events and approaches to project the risk
associated with precipitation events. Chapter 5 presents the literature characterizing the effects of SLR
on tidal flooding, groundwater levels and salinity. The study evaluates each of these climate-induced
risks for landfills (Chapter 6), transportation infrastructure (Chapter 7) and other supporting
infrastructure (Chapter 8). For instance, Chapter 6 outlines a risk assessment procedure for contaminant
release in the event of a climate-induced impact. It will be important to estimate potential contaminant
releases from landfills and other waste facilities that are impacted by extreme weather events and
estimate the transport of such pollutants in the groundwater to nearby populations. A tiered approach
has been adopted or used by numerous state and federal agencies to evaluate risks associated with
exposures to pollutants in the environment. As described in Chapter 6, the approach begins with a Tier 1
screening level assessment that includes a simplified conceptual model of the environmental releases
and exposure. If unacceptable risks are identified (predicted exposure is greater than the threshold
screening value), then a Tier 2 assessment is implemented by refining the release-exposure scenario to
include more realism to reflect key sensitive scenario and site-specific conditions. If unacceptable risks
persist, then a detailed site-specific conceptual model is developed and evaluated under a Tier 3
analysis.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
The City of Norfolk, Virginia was selected as the project site based on its coastal location, availability of
data, and proximity to a varied set of waste facilities. The coastal region of Virginia is the second most
vulnerable area to impacts of climate change such as SLR, tidal flooding and extreme precipitation in the
U.S., behind New Orleans, and is currently being impacted by SLR (City of Virginia Beach, 2009).
Intensified by land subsidence in the region, SLR is happening at a fast rate in Norfolk. Sea levels have
increased approximately 18 inches since 1900 and 8.79 inches in the past 45 years (Connolly, 2015) in
Norfolk, primarily due to subsidence. Old Dominion University scientists predict a 2- to 5-foot rise in
Norfolk's sea level by 2100 (Center for Sea Level Rise, 2015).
The City of Norfolk's waste collection programs include the collection of more than 95,000 tons of waste
per year for households and businesses in the city (City of Norfolk Division of Waste Management,
2016). Once collected, waste is hauled to the city's transfer station or directly to one of the regional
management facilities such as the Tidewater Fibre Corporation (TFC) recycling facility, Wheelabrator
waste-to-energy (WTE) plant, or Southeastern Public Service Authority of Virginia (SPSA) landfill
Figure ES-1 shows the location of the City of Norfolk's waste management facilities mapped to hurricane
storm surge boundaries. As shown on the map, all but the SPSA landfill appear to be vulnerable to
inundation. Identifying the alternative MSW management facilities that would be used should the city's
current facilities be inundated is not straightforward. The city does not have a formal plan to identify
alternative sites in case of emergencies. Rather, the approach is to determine which facilities have the
capability/capacity to handle waste at the time of the emergency. Therefore, reasonable and likely
alternative facilities were identified using l-WASTE, SPSA plans, and proximity to the city.
Legend
© Bridges Norfolk Waste Sites
3> Tunnels
Hazmat Routes m
QNorfolk City Limit
Hurricane Evacuation m
Routes
^ Evacuation Direction
Virginia Hurricane Storm Surge
¦I Category 1 I I Category 3
I I Category 2 H Category 4
Souto*' Vrgna Humcan* Storm Surge Tool
Closed Landfill
Wheelabrator MSW Combustion
SPSA Regional Landfill
TFC Recycling
Transfer Station
Figure ES-1. Norfolk Waste Facilities with Hurricane Storm Surge Categories
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Based on available data and information about current and alternative facilities, the alternative facilities
are assumed to be identical in terms of design and operating parameters. The differences between
alternative scenario results and the base case results are primarily caused by the differences in
collection and transportation distances. Key findings from the modeling results (presented in Chapter 5)
are as follows:
¦ For the non-optimized scenarios, the cost, energy consumption, and emissions generally follow
an increasing trend from the base case to Alternative 3 (high impact), primarily due to the
increase in transportation distance from the point of waste collection to the alternative
management facilities. The cost and environmental performance for the city's current base case
was found to fall generally between the results of the cost- and GHG-optimized cases.
¦ Least-cost (i.e., cheapest) scenario (optimized) results pointed to MSW collection and landfill
disposal as being least costly. Sensitivity analysis was performed on the recycling rate for the
cost-optimized scenarios, and it was found that a 5 percent change in the recycling rate
corresponds to an approximately 5 percent change in cost.
¦ GHG-optimized scenarios showed that significant reductions in GHG emissions (and energy
consumption) could be achieved by greater levels of materials and energy recovery, but the cost
of such a scenario increased significantly as well.
¦ For scenarios in which WTE was excluded (Alternative 4), cost generally decreased but
environmental impacts increased due to the subsequent removal of energy and materials
recovery benefits associated with WTE.
A thorough discussion of the cost and environmental tradeoffs of moving to alternative waste facilities
should existing facilities be inundated and closed is presented in Chapter 9. A scenario-based approach
was taken to understand and incorporate future uncertainty of the extent and impact of these events
into the long- term waste management planning. There are some caveats to this analysis. For example,
the storm surge and SLR scenarios looked at individual facility flooding however, other factors might
influence the availability of the waste management facility such as inundation of access roads, or worker
availability in the event of a storm. These aspects of waste management could be covered under
emergency management planning process. The study is not intended for emergency management or
analysis of options during an event.
The results from this project can help communities in gaining a better understanding of the nature of
climate-induced impacts, and how those impacts can affect waste management infrastructure and long-
term planning needs. The methodology evaluates environmental impacts and cost implications of
alternative waste management options available for municipalities. The insights gathered from
illustrative scenario analysis for Norfolk, VA revealed that there can be opportunities to be leveraged if
intensity and frequency of precipitation events continue to increase for the region. Solid waste
management planners could utilize these opportunities to better design the system to be more resilient
and responsive at cheaper costs, and in some cases resulting in better environmental outcomes (e.g.,
reduced air emissions).
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
1. Introduction
Climate change creates an immense challenge to the security and resilience of coastal communities (U.S.
Global Change Research Program (USGCRP), 2014). More frequent and intense disruptive events
including hurricanes and storm surges may increase the frequency and extent of damage to municipal
infrastructure, including waste sector facilities. Impacts to supporting infrastructure such as
transportation routes, energy supplies, and water supply and treatment can also significantly affect
waste facility operations. Potentially large amounts of debris and the release of pollutants and
contaminants to the environment can have cascading effects such as the failure of additional facilities
triggered by the failure of the initial one. The impacts of changing climate on waste facilities and their
operations is an immediate concern for coastal communities. Extreme events may result in exposure to
contaminants from treatment, storage and disposal facilities, non-hazardous and hazardous waste sites,
municipal recycling facilities, or other relevant facilities or sites.
1.1. Project Goal
The overall goal for this project was to develop an approach to evaluate vulnerability of solid waste
management infrastructure and adaptation strategies to increase its resilience to climate change.
Vulnerability of waste management infrastructure to acute and extreme weather events needs to be
analyzed to identify those for which siting, treatment and disposal of hazardous, municipal wastes and
mixed wastes will be affected. The study utilized (1) mapping and other analytic/statistical methods to
identify community characteristics at multiple spatial scales and evaluate locations and site-specific
characteristics, (2) U.S. Environmental Protection Agency's (EPA's) Incident Waste Decision Support Tool
(l-WASTE) tool to identify the locations of waste management facilities, and (3) U.S. EPA's Municipal
Solid Waste Decision Support Tool (MSW DST) to understand life-cycle impacts of waste management
plans and demonstrate how plans can be modified to robustly incorporate resilience to climate change.
The resulting information is intended for use in better understanding the nature of climate-related
impacts on coastal communities and how those impacts can affect waste management facilities and
plans, options available for minimizing environmental impacts, and cost implications for municipalities.
This report will enable U.S. EPA's Office of Land and Emergency Management (OLEM) to provide support
in the form of guidance, training, and technical assistance to communities in need.
Climate-induced impacts on communities could be categorized into three components: 1) temperature,
2) precipitation, and 3) sea level rise (SLR) (Zimmerman, 2010) related impacts. Temperature impacts
include long-term changes in mean annual temperatures as well as changes in frequency, duration, and
intensity of heat waves. Precipitation impacts include long-term changes in mean annual precipitation as
well as intensity and frequency of these events. SLR impacts include inundation and extent of storm
surge. In this report, our focus is on precipitation and SLR impacts. In the following chapters, we will
discuss impacts of these changes on the waste infrastructure.
1.2. Coastal Community Case Study Site
The City of Norfolk was selected as the project site based on its coastal location, availability of data, and
proximity to a varied set of waste facilities. The City of Norfolk's population was 242,803 in 2010. Since
2000, the population has grown 3.6 percent, whereas the region (i.e., Hampton Roads region) has grown
7.8 percent (City of Norfolk, 2014). The Intergovernmental Panel on Climate Change (IPCC) estimated
that by 2100, global warming will cause sea levels to rise approximately 0.5 to 3 feet (IPCC, 2001). The
IPCC estimates have since been updated, and the 2100 predictions now range from 0.66 to 6.6 feet
(USGCRP, 2014). Virginia's coastal region is the second most climate-vulnerable area in the U. S., behind
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
New Orleans, and is currently being impacted by SLR (City of Virginia Beach, 2009). Intensified by land
subsidence in the region, the sea level is rising quickly in Norfolk and the surrounding Hampton Roads
area. Sea levels have risen approximately 18 inches since 1900 and 8.79 inches in the past 45 years in
Norfolk (Connolly, 2015), primarily due to subsidence. Old Dominion University scientists project a 2- to
5-foot SLR at Norfolk by 2100 (Center for Sea Level Rise, 2015). The city is responsible for waste
management, and thus our primary spatial boundary is the city proper. Waste management facilities in
the surrounding region are also captured, since the potential impacts and solutions are regional in
nature.
13. Climate Resiliency Studies in The Norfolk Area
Numerous climate resiliency analyses and reports have been prepared for Norfolk and the surrounding
region. In this section, studies identified to date that contain potentially relevant information are
identified and briefly summarized. In general, while these studies provide good information about the
context for potential climate impacts and mitigation/adaptation strategies, most point to the same
government data sources already identified. Few studies present additional or detailed datasets that
contain useful supplemental data for this project.
The Hampton Roads Sea Level Rise Preparedness and Resilience Intergovernmental Planning Pilot
Project
Old Dominion University's Center for Sea Level Rise in Norfolk conducted a two-year pilot study called
The Hampton Roads Sea Level Rise Preparedness and Resilience Intergovernmental Planning Pilot
Project. The project combined the efforts being conducted at all levels of government with researchers
and businesses to achieve a "whole of government, whole of community" approach. The aim of this
collaboration was to reduce the negative impacts from climate change and SLR. (Steinhilber, E. et al., 2015)
Vulnerability of Hampton Roads, Virginia, to Storm-Surge Flooding and Sea-Level Rise
This study mapped the locations of vulnerable sub-populations and compared them to flood-risk
exposure zones. For this project, overlays with Geographical Information Systems (GIS) could be
performed to evaluate where the locations of the waste facilities lie in relation to these flood-risk
exposure zones. (Kleinosky, L.R., et al., 2007)
Sea Level Rise and Flooding Risk in Virginia
This study found that SLR in the Hampton Roads region occurs twice as fast (2 inches every 10 years) as
it does globally because of the ocean circulation and subsidence in the area. The U.S. National Oceanic
and Atmospheric Administration's (NOAA's) tide gauge data were used to determine the number of
hours per year that streets within neighborhoods were flooded. (Atkinson, L. P. et al., 2012)
The Potential Economic Impact of Hurricanes on Hampton Roads
The study by the Hampton Roads Planning District Commission (2006) provides the dollar amount of
damage to residential, commercial, and industrial sectors in the Hampton Roads area that resulted from
hurricanes.
Recurrent Flooding Study for Tidewater Virginia
For various coastal localities in Virginia, this project calculated the number of road miles and the total
area with potential flooding using GIS. The elevation generated from this study has the highest
resolution of any available as of 2014. (Mitchell, M. et al., 2013)
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Coastal Resiliency: Adapting to Climate Change in Hampton Roads
GIS tools were used to evaluate potential vulnerability of the Hampton Roads region to one meter of SLR
through identification of the impacts for population, housing, property, roads, businesses, and natural
resources. Maps were created that showed the inundation of areas under various scenarios at Mean
Higher High Water by 2100. Mean Higher High Water is defined as the average of the Higher High Water
height of each tidal day observed over the National Tidal Datum Epoch. (McFarlane, B., 2013J
Street-Level Inundation Modeling
Dr. Harry Wang of the Virginia Institute of Marine Sciences (VIMS) has led research that involves street-
level inundation modeling. The model uses Light Detection and Ranging (LiDAR) data, which allows for
the Chesapeake Bay's shoreline to be simulated more accurately, thereby allowing for modeling at the
street level. The researchers validated the model with a pilot study that predicted flood levels within a
few centimeters of the actual levels observed in the Potomac River during Hurricane Isabel. (Virginia
Institute of Marine Science, 2008)
2. Models
This study utilized (1) mapping and other analytic/statistical methods to identify community
characteristics at multiple spatial scales and evaluate locations and site-specific characteristics; (2) U.S.
EPA's l-WASTE tool to identify the locations of waste management facilities, and (3) U.S. EPA's MSW DST
to understand life-cycle impacts of waste management plans and demonstrate how plans can be
modified to robustly incorporate resilience to climate change.
In addition, we characterized infrastructure related to waste management systems including
transportation and utilities infrastructure, as well as historic climate driven events such as precipitation,
temperature, and SLR.
2.1. Incident Waste Decision Support Tool (l-WASTE)
U.S. EPA's l-WASTE tool provides a framework for planning and response decision-making
and consists of calculators to generate waste quantity estimates; databases of treatment and
disposal facilities; and a quick reference to technical information, regulations, and
guidance to work through the complicated series of decisions needed to assure safe and efficient
removal, transport, and management of waste materials (U.S. EPA, 2017). The objective of l-WASTE is to
help reduce restoration time and expense by providing quick access to information that will inform the
decision-making process for incident waste management. l-WASTE includes:
1. Information on characteristics of waste, debris, and potential contaminants, as well as
characteristics of decontamination agents that could be used and may be present as residuals in
the waste;
2. Databases of treatment, disposal, and recycling facilities (e.g., hazardous waste incinerators,
landfills, medical waste autoclaves), including locations, contact information, permits, and
capacities for the different types of waste;
3. A waste quantity estimator that allows end-users to generate order-of-magnitude estimates of
volumes and masses of waste and debris from events involving a variety of types of single
buildings or several structures over a wide area;
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
4. A water systems module with information from different geographical areas to support the
unique considerations involved in the management of waste (e.g., filter media, piping)
generated because of decontaminating water treatment and distribution systems;
5. Agricultural biomass disposal guidelines including training modules developed by the U.S.
Department of Agriculture;
6. Natural disaster debris disposal guidelines including case studies organized by disaster type (e.g.,
hurricanes, tornadoes, earthquakes, floods);
7. Debris transportation, packaging, and staging information;
8. Radiological waste management information and guidelines; and
9. Worker protection information.
2.2. Municipal Solid Waste Decision Support Tool (MSW DST)
The MSW DST was developed through a competed cooperative agreement between U.S. EPA's Office of
Research and Development (ORD) and Research Triangle Institute (RTI) International to provide a
credible and quantitative framework to identify sustainable solutions for managing municipal solid
waste (MSW), while considering carbon emissions, energy, air criteria pollutants, waterborne pollutants,
and cost. Across the U.S., strategies are being implemented to reduce waste and encourage recycling
and composting without the benefit of understanding the environmental tradeoffs. Optimal strategies
can differ depending on population density, infrastructure, energy grid mix, waste composition, and
transportation distances for hauling waste to and from facilities for processing, recovery, or disposal.
The MSW DST considers all waste management activities and the inherent differences among materials
(e.g., food waste, glass, metals, paper, plastics, yard debris) that can affect energy recovery and life-
cycle environmental tradeoffs. Options can be interrelated, and it can be unclear how best to manage
MSW considering total emissions over time. For example, what may be more environmentally
advantageous in a rural region may be different from urban or suburban communities. Another factor to
consider is that most carbon inventories consider annual emissions and not total emissions over the life-
cycle. For most unit processes, emissions are instantaneous. However, if waste is buried in a landfill,
then total emissions can occur over many decades and depending upon the time horizon, carbon
storage may occur. The MSW-DST provides a systematic approach to evaluating total life-cycle emissions
for hauling, processing, and disposal of MSW, while factoring in offsets for materials and energy
recovery.
In addition to the U.S. EPA and RTI, the research team also included North Carolina State University,
which had a major role in the development of the life-cycle inventory databases for process and cost
models as well as the prototype MSW DST. The MSW DST includes many process models that represent
the operation of each waste management unit including options for collection, sorting, processing,
transport, and disposal of waste. In addition, there are process models to account for the emissions
associated with the production and consumption of fuels, electricity, and conversion of recyclables into
new products. An offset analysis is used to calculate the environmental benefits or added burdens from
the conversion of recycled materials to new products and from the generation of electricity from landfill
gas and waste-to-energy (WTE). All unit processes are integrated, and the mass balance is represented
by a series of waste flow equations that may be solved for the minimum value of cost, net energy
consumption, or emissions of selected pollutants. The functional unit in each process model is 1 ton of
waste item set out for collection. Each process model can track and report 32 life-cycle parameters,
including energy consumption, carbon dioxide (C02), carbon monoxide (CO), nitrogen oxides (NOx),
sulfur oxides (SOx), carbon dioxide equivalents (C02e), particulate matter (PM), methane (CH4), water
pollutants, and solid wastes. The MSW DST reports out emission factors per ton of waste item handled
in that process along with cost.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
The MSW DST is available through https://mswdst.rti.org/index.htm (last accessed 5/16/2018). The
website includes tutorials and downloadable resources to provide background life-cycle assessments
and process model documentation.
3. Data Availability and Limitations
This section summarizes the data available for characterizing waste management systems and climate-
induced risks for the Norfolk region along with key gaps in the data reviewed to date. Available data are
presented for (1) waste infrastructure, (2) transportation and utilities infrastructure, (3) historic
precipitation events, and (4) SLR.
3.1. Waste Infrastructure
The primary source for waste infrastructure data was l-WASTE, which is a tool used to help decision
makers in managing waste materials that result from accidents, natural disasters, and terrorist attacks. A
list of waste facilities in the Norfolk, VA, study area was obtained from l-WASTE and mapped using a GIS.
These sites are listed in Table 1 and displayed in Figure 1.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
HRSD - Army Base STP
Portsmouth Cit$ v' A
- Craney Island HRSD - Virginia
Landfill Initiative, STP
Wheelabrator " J-
Petrochem
Recovery
Services Inc.
Marpol A Area
"^Container
Serviceslnc
Wheelabrator
Portsmouth ^Portsmouth
County
Suffolk
County
BFI / A
Chesapeake
Transcyclery
Safety-KleenA
Chesapeake County
SPSA /
Chesapeake
Transfer
Station
Chesapeake
County
Legend
l-WASTE Facility Type
Combustion/MSW Combustion Facilities
Compost Facility
A Decontaminated Wastewater/CWT Facilities
Decontaminated Wastewater/POTW
Government/Govemment-Owned Land/Facilities
Government-Owned Land/Facilities
Landfills/Inert or C and D Landfills
Landfills/MSW Landfills
Other/Electric Arc Furnaces
~
~
A Transfer Station
v—V"
HRSD -
York River
Sewage Plant
~
York County
J^es Transfer
„Clty, Station
bounty (compost Facility)
HRSD -
V\, James River
yj Seyvage Treatment
A Newport
News
County
Poquoso
County
York
County
USA Waste of VA j
Landfills-Bethel »
Hampton-NASA VPPSA - Kifig
WMl / Recycle steam Plant William County
America Hampton Hampton ^Transfer Station
County
\ Roads a
A^
Huntington Ingalls Newport News
Incorporated-NN^ Materials
Shipbldg Div Recovery Facility
Isle of
Wight
County
AVDOT 1-64 Goochland Rest Area
Norfolk
County
Virginia
Beach
County
Virginia Landfill
.No.2
SPSA ^
Landstown
Transfer Station
Figure 1. Map of Waste Facilities Available from l-WASTE
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table 1. List of Waste Facilities in the Norfolk Region from l-WASTE
Name
Hampton- NASA Steam Plant
Wheelabrator Portsmouth, Inc.
Type
Combustion/MSW Combustion Facilities
Combustion/MSW Combustion Facilities
York County Transfer Station
Compost Facility
Marpol
Decontaminated Wastewater/Centralized
Waste Treatment
Petrochem Recovery Services Inc.
Decontaminated Wastewater/Centralized
Waste Treatment
Hampton Roads Sanitation District-Army Base
Sewage T reatment
Decontaminated Wastewater/ POTW
HRSD - Boat Harbor Sewage Treatment
Decontaminated Wastewater/POTW
HRSD - Nansemond Sewage Treatment Plant
Decontaminated Wastewater/POTW
HRSD - Virginia Initiative Sewage Treatment Plant
Decontaminated Wastewater/POTW
HRSD - York River Sewage Treatment
Decontaminated Wastewater/POTW
Virginia Department of Transportation (VDOT)
Interstate 64 Goochland Rest Area
Decontaminated Wastewater/POTW
\laval Base Norfolk
Government-Owned Land/Facilities
Portsmouth City - Craney Island Landfill
Landfills/Inert or Construction and Demolition
(C and D) Landfills
Virginia Beach Landfill No. 2
Landfills/Inert or Construction and Demolition
(C and D) Landfills
USA Waste of Virginia Landfills - Bethel Landfill
Landfills/ MSW Landfills
Virginia Beach Landfill No. 2
Landfills/MSW Landfills
Huntington Ingalls Incorporated - NN Shipbldg. Div.
Other/Electric Arc Furnaces
HRSD - James River Sewage Treatment
POTW; Other/Electric Arc Furnaces
Area Container Services Inc.
Transfer Station
Waste Management, Inc./Recycle America Hampton
Rds.
Transfer Station
Browning-Ferris Industries/Chesapeake Transcyclery
Transfer Station
Craney Island Materials Recovery Facility
Transfer Station
Newport News Materials Recovery Facility
Transfer Station
Safety-Kleen/Chesapeake County
Transfer Station
Southeastern Public Service Authority of Virginia
(SPSA)/Chesapeake Transfer Station
Transfer Station
SPSA/Landstown Transfer Station
Transfer Station
Virginia Peninsula Public Service Authority - King
William County Transfer Station
Transfer Station
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
3.2. Transportation and Utilities Infrastructure
The transportation infrastructure in an area is particularly vulnerable to the impacts from SLR. GIS can
be used to identify infrastructure that may be vulnerable to storm surge and SLR and was used in this
study of the Norfolk area. Spatial analyses can be performed with the infrastructure and weather data to
assess the duration of flooding on roads and bridges in the study area. Mitchell et al. (2013) concluded
that in 2012, Norfolk had 119 road miles that are vulnerable to flooding.
Table 2 shows the data sources that were used to assess the potential impacts on transportation for the
study. Several datasets, including primary and secondary roads, bridges, railroads, and hazardous
material routes were obtained from the U.S. Department of Transportation (DOT) National
Transportation Atlas Database. Annual average daily traffic data were obtained from the VDOT. This
dataset was used to evaluate heavily traveled roads and help identify places where traffic problems
could occur in severe flooding events.
Table 2. List of Transportation Data Sources
i Dataset s Source : Year
Primary & Secondary Roads
| U.S. DOT National Transportation Atlas Database
2013
National Bridge Inventory
| U.S. DOT National Transportation Atlas Database
2012
Railroad Bridges
I U.S. DOT National Transportation Atlas Database
2012
Railway Crossings
| U.S. DOT National Transportation Atlas Database
2012
Railway Network
[ U.S. DOT National Transportation Atlas Database
2012
Hazardous Material Routes
I U.S. DOT National Transportation Atlas Database
2012
VDOT Annual Average Daily Traffic
VDOT
2015
Detailed data and information about potential street-level inundation within the city was not found.
However, VIMS has conducted research that involves street-level inundation modeling (VIMS, 2008).
The modeling uses LiDAR data, which allow for the Chesapeake Bay shoreline to be simulated more
accurately, thereby allowing for modeling at the street level. This, or a similar model, may provide a
means for Norfolk to analyze street-level inundation.
The U.S. Department of Energy (DOE) Transportation Routing Analysis Geographic Information System
(TRAGIS) model was also reviewed to the extent possible as it requires a sponsor to get full access. While
DOT sources provide adequate data for identifying transportation routes and infrastructure, the TRAGIS
model may be useful for determining options for alternative routing scenarios.
Spatial data for locating utility infrastructure (namely, electricity and water) were not found from online
sources for the City of Norfolk, possibly due to homeland security concerns.
3.3. Natural Weather Events
Climate change will have an impact on the frequency and intensity of storms in the Norfolk region. Table
3 lists the identified and reviewed weather-related data sources. An analysis of historic storm and
hurricane data was performed using publicly available meteorological data. Geospatial data
representing past Atlantic storm tracks were downloaded from the National Weather Service (NWS).
Tabular data containing information about storm events are provided by NOAA going back to 1951. In
addition to the locations, the duration of the event, number of injuries, and dollar amount of damage
are also included.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
The City of Norfolk has published maps showing approximate tidal flooding at 2, 4, 6, and 8 feet. The
tidally influenced flood-prone areas are shown on maps with streets within the city that get flooded at
each of those four levels. The extent of the flooding could be combined with other variables (i.e., areas
where utility service outages occur) to show areas at the census block group level that would have the
highest likelihood for being affected by storm surge and SLR. The locations of the city and regional waste
facilities could be part of this analysis, and those that fall within these high-risk block groups could be
identified.
Table 3. List of Weather-Related Data Sources
Dataset \ Source Year
Storm Events
NOAA
2000-2015
Past Atlantic Storm Tracks
NWS
2015
Flood Frequency
NOAA
2015
Tidally-influenced Flood Prone Areas
City of Norfolk
2012
3.4. Sea Level Rise
Table 4 lists data sources available for analyzing SLR in the Norfolk region. The City of Norfolk provides
flood zone data that is updated regularly. NOAA's SLR web mapping application allows users to
download the data used in the program. From the NOAA website, geospatial datasets were obtained
that represent SLR inundation for various feet above mean high water (0, 1, 2, 3, 4, 5, and 6). A digital
elevation model (DEM) was also obtained, as well as flood frequency data for the study area.
NOAA also has four tide gauge stations in the Norfolk area at Sewell's Point, Money Point, Chesapeake
Bay Bridge Tunnel, and at the U.S. Coast Guard (USCG) Training Center. Water levels are available on an
hourly basis. Sea level trends and tide prediction data are also available hourly at some of these sites.
Table 4. List of Data Sources for Sea Level Rise Analysis
Dataset
Source
Year
Flood Zone
Norfolk
2015
SLR inundation above mean higher high water for 0-6 feet of SLR
NOAA
2015
Hydrologically unconnected inundation areas for 0-6 feet of SLR
NOAA
2015
DEM
NOAA
2015
Flood Frequency
NOAA
2015
Water Levels
NOAA
2015
NOAA Tide Predictions
NOAA
2015
Sea Level Trends
NOAA
2015
3.5. Identified Gaps in the Existing Data and Information
In this section, available data and key data gaps that will need to be addressed to complete an
assessment of waste infrastructure vulnerability to climate-induced events are summarized.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
3.5.1.Waste Infrastructure
For the purposes of this study, we rely on l-WASTE to identify waste management infrastructure within
the study area. The facilities represented in l-WASTE are based mostly on facilities listed in the
EnviroFacts database (U.S. EPA, 2017) and primarily focus on waste transfer stations, combustion units,
and landfill disposal units for hazardous and nonhazardous solid wastes. l-WASTE (and EnviroFacts) is
more limited in its representation of recycling, composting, and other small-scale waste facilities. This is
a consequence of recycling and composting facility information being contained in proprietary
databases.
l-WASTE captures both public and private facilities. The tool does include some information about the
types of materials accepted at each facility and the current facility capacity. Key gaps in the waste
infrastructure data available from l-WASTE includes the following:
• Closed facilities (e.g., old disposal units); note that EnviroFacts does provide information about
facilities that have been closed,
• Recycling and composting facilities, and
• Composting and chip/grind facilities.
To help fill gaps in facilities information available from l-WASTE, city officials and waste facility managers
were contacted.
3.5.2.Climate-Related Impacts
Many tools, models, and applications on the web map SLR, storm surge, and flooding in the Norfolk area
under various scenarios. These tools were evaluated to make sure the most recent, highest resolution
data were being used and that analyses that have already been carried out were not being repeated as
part of this project. With respect to key data gaps, our review of the weather-related information that is
publicly available did not yield much data related to duration of inundation. Detailed climate models
with a variety of data inputs are required to estimate this variable.
4. Climate-Induced Risks: Precipitation
Precipitation impacts include long-term changes in mean annual precipitation as well as intensity,
frequency of these events. USGCRP's Climate Science Special Report (2017), part of the 4th National
Climate Assessment, focused on climate change science and related physical impacts in the U.S.
According to the report, heavy rainfall is increasing in intensity and frequency across the U.S. and
globally and is expected to continue to increase. The largest changes have been observed in the
Northeast. Still, translating this summary to actual quantitative projections of future hurricane
frequencies and strengths in the North Atlantic basin (where Norfolk is located) will be difficult.
Landfalling major hurricanes are a relatively rare event in the U.S., happening on average once every
three years. Up until August 2017, it had been more than 12 years since a major hurricane (Category 3
or higher) has made landfall in the U.S., exceeding the major hurricane draught record of eight years set
from 1861 through 1868 (NOAA National Centers for Environmental Information, 2016). However, the
2017 Atlantic hurricane season ended up being a hyperactive active season with six major hurricanes,
including Hurricanes Harvey, Irma, and Jose. These hurricanes resulted in major infrastructure damage
and serious health outcomes in the impacted communities.
The purpose of this section is to detail the data available and approach used for projecting risk
associated with the potential future frequency, intensity, and tracks for precipitation events and
hurricanes that may impact waste management infrastructure in the Norfolk region. We gathered the
following data specific to the Norfolk area:
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
¦ Frequency of tropical storms,
¦ Intensity of tropical storms,
¦ Storm surge levels caused by storms of different intensities,
¦ Locations of the waste handling units (especially elevation above sea level), and
¦ Projected future SLR.
4.1. Frequency of Tropical Storms
Historical data regarding tropical storm landfalls in the United States have been used to generate Figure
2, which shows the annual percentage probability of a hurricane making landfall along each 50 miles of
the U.S. Gulf Coast and East Coast (Locke, 2005).1 Figure 2 contains two sets of probability values. The
set of values closest to the coastline is the probability of any hurricane (i.e., wind speed greater than 33
m/s or 74 mph) making landfall on each 50-mile segment of U.S. coast. The other set of probability
values is for "great" hurricanes with wind speeds greater than 54 m/s (125 mph), approximately a high
Category 3 hurricane or greater.
Figure 2 indicates that for Norfolk, VA (segment number 44, located at approximately 37N, 77W on the
map) the probability of a hurricane landfall is two percent per year, and the probability of a "great"
hurricane is one percent per year. Note that these probability estimates are based on 1900-1996
historical data and do not consider potential changes in hurricane frequency or intensity due to climate
change.
Figure 2 provides the possible landfall location frequency for hurricanes. However, a hurricane might
make landfall in North Carolina or another East Coast state and travel up the coast to Norfolk. This
situation would generate a storm surge in Norfolk, even if the hurricane did not make landfall at Norfolk.
For example, Hurricane Isabel in 2003 made landfall in Pamlico Sound, NC, and crossed the North
Carolina-Virginia border approximately 75 miles west-southwest of Norfolk (NOAA, 2015), but this storm
produced the largest storm surge of any hurricane at the Sewell's Point storm surge measuring station
near Norfolk at 7.9 feet (Weather Underground, 2018).
1 Figure 2 appears to be originally to be from the National Oceanic and Atmospheric Administration (NOAA)
National Hurricane Center (NHC), but the NOAA/NHC website cited by Locke, 2005 no longer contains that figure.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
(80 km) coastline
All hurriearws
Great hurricanes
Percent per year probability (histori
Hurricane >33 m/s (74 mph)
Great Hurricane >54 m/s
(125 mph)
Note: The triangle and #44 represents Norfolk, VA; Source: Locke, 2005
Figure 2. Hurricane landfall probabilities for U.S. Gulf and East Coast, based on historical data
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Figure 3 shows the probability of a hurricane or named storm coming within approximately 60
miles of any location in any year, from June to November, based on data from 1944 to 1999. It
is difficult to discern the exact value for Norfolk, VA from Figure 3 (located at approximately
37N, 77W on the grid), but it appears that the probability of a hurricane or named storm
coming within approximately 60 miles of Norfolk, VA, in a year appears to be between 4 and 6
percent, so this analysis uses a value of 5 percent.
9QW BOW 7Q'XI BOW SOW 40W 3QW 2QW
14 16 18 20 22 24 26
Note: The triangle represents Norfolk, VA; Source: NOAA, 2014a
Figure 3. Probability [%) per year of a hurricane coming within 60 miles of any point in the North
Atlantic
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
4
130-156 mph
18
0.09
5
157 mph or higher
3
0.02
Total, all categories
74 mph or higher
192
1.00
It is possible to use annual probabilities of occurrence to calculate the cumulative probability of a
hurricane in the future. For example, if the annual chance of a hurricane making landfall at Norfolk, VA is
2 percent, the chance that a hurricane will not make landfall at Norfolk, VA is 98 percent (i.e., a
fractional value of 0.98), and the chance that a hurricane will not make landfall over 10 years is 82
percent (i.e., 0.98 raised to the 10th power). Therefore, the probability that a hurricane will make landfall
at Norfolk, VA in 10 years is 18 percent. The formula for calculating the cumulative probability based on
annual probability is:
CP = 1 - (1 - AP)n
where:
CP = fractional cumulative probability over n years
AP = fractional annual probability of occurrence
n = number of years into the future.
For example, if the annual probability of occurrence of a hurricane landfall at Norfolk, VA, is 2 percent
(fractional value of 0.02), the cumulative fractional probability of a hurricane making landfall in the 35
years from 2015 to 2050 is approximately 0.51, or 51 percent (i.e., 1 - (1 - 0.02)35).
43.Summary of Frequency and Intensity Data for Norfolk, VA
The previous frequency and intensity discussions are combined and summarized in Table 7. The first two
columns in Table 7 contain the cumulative probabilities for landfalling hurricanes at Norfolk, based on
Figure 2. The next two columns contain the cumulative probabilities for hurricanes passing within
approximately 60 miles of Norfolk, based on Figures 3 and 4. Table 7 then has five columns with the
cumulative probability of landfalling hurricanes of Saffir-Simpson categories 1 through 5, based on
Figure 2 and the hurricane intensity data in Table 6. The final five columns in Table 7 show the expected
probability of hurricanes with different intensities passing within approximately 60 miles of Norfolk,
based on data from Figure 3 and Table 6.
It is instructive to examine cumulative probabilities to the year 2050 (i.e., the next 35 years from 2015).
For example, the Wheelabrator WTE plant commenced operations in 1988, so 2050 would represent a
conservative 62-year lifetime for the facility. From Table 3, there is a cumulative fractional probability of
0.21 (i.e., 21 percent) for a Category 1 hurricane making landfall at Norfolk by 2050, but only a 0.05 (5
percent) cumulative chance for a Category 4 hurricane making landfall in the same time frame. Similarly,
there is a cumulative fractional probability of 0.34 (34 percent) for a Category 1 hurricane passing within
approximately 60 miles of Norfolk by 2050,
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
but only an 0.08 (8 percent) cumulative probability of a Category 4 hurricane passing within the same
area.
4.4. Hurricane Intensity versus Flooding Probability
The NOAA/ NWS National Hurricane Center (NHC) Storm Surge Unit has calculated storm surge flooding
levels for hurricane categories 1 through 5 for the East Coast and Gulf Coast of the U.S. (NOAA, 2014b).
The calculations are based on the Sea, Lake and Overland Surges from Hurricanes (SLOSH) computer
program, using "Maximum of Maximums (MOM)" values. MOM values choose maximum surge heights
for a given category of hurricane, for a range of storm scenarios, and the surge values are calculated at
high tides. Storm surge predictions from the NOAA/NWS/NHC/Storm Surge Unit website were reviewed
for four waste handling facilities in the Norfolk area.
4.5. Key Findings and Observations
Table 3 presented cumulative probabilities for hurricanes of varying intensity making landfall at Norfolk
or passing near Norfolk, based on average data from the 20th century. The cumulative fractional
probabilities from the years 2015 to 2050 are presented in Table 8.
Table 8. Hurricane Scenarios for Norfolk, VA
Scenario
Cumulative Fractional Probability of Occurrence, 2015-2050
Category 1
Category 2
Category 3
Category 4
Category 5
Landfall in 50 miles
coastal segment for
Norfolk
0.21
0.13
0.11
0.05
0.01
Pass within approximately
60 miles of Norfolk
0.34
0.21
0.19
0.08
0.01
The results of an assessment of the NOAA (2014b) probabilities for flooding are presented for the four
main Norfolk, VA waste facilities in Table 9. It is extremely unlikely (less than 1 percent chance) that any
of the four waste sites would be flooded in a Category 1 hurricane. In contrast, the Portsmouth WTE
plant would be very likely (greater than 90 percent chance) to flood in a Category 4 storm, whereas it
would still be very unlikely (less than 10 percent chance) that the TFC recycling facility would flood, even
in a Category 4 storm. Note that the NOAA/NWS/NHC Storm Surge Unit analysis does not consider
Category 5 storms north of the North Carolina and Virginia border, so there is no analysis for Category 5
storms presented in Table 9.
The results of Table 8 and Table 9 can be combined to get an overall cumulative storm surge flooding
probability for the four waste sites in the Norfolk area for the years 2015-2050. The most likely facility
to flood appears to be the Portsmouth WTE plant; the Portsmouth WTE plant appears very likely to
flood in a Category 4 hurricane. However, from Table 4, there is only about a 5 percent chance that a
Category 4 hurricane will make landfall at Norfolk within the 2015-2050 period, and only an 8 percent
chance that a hurricane will pass within approximately 60 miles of Norfolk in the 2015-2050 period.
Therefore, the overall chance that even the Portsmouth WTE plant will be flooded by a storm surge in
the 2015-2050 period is low (less than 20 percent).
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table 9. Flooding Probabilities at Norfolk Waste Sites, for Various Hurricane Categories
Waste Handling Location
Meters
above Sea
Levela
Probabilityb the Site Will Be Flooded, MOM c
Conditions, High Tide
Category 1
Category 2
Category 3
Category 4
Portsmouth WTE plant
4
0-0.01
0-0.33
0.66-1.00
0.90-1.00
SPSA Regional Landfill
5
0-0.01
0-0.01
0-0.33
0.33-0.66
SPSA Norfolk Transfer Station
7
0-0.01
0-0.10
0.33-0.66
0.66-1.00
TFC Recycling
7
0-0.01
0-0.01
0-0.01
0-0.10
a From Google Earth, using lowest elevation at each location.
b Using NOAA, 2014b.
c MOM = "Maximum of Maximums;" uses the maximum surge values for a range of storm simulations.
The overall chance of storm surge flooding in the 2015-2050 period for the SPSA Regional Landfill -
Suffolk and the SPSA Norfolk Transfer Station is less than 10 percent, and the chance of storm surge
flooding for TFC Recycling is less than 1 percent. However, it is important to note that these flooding
probability estimates do not consider possible changes in the frequency and intensity of hurricanes from
2015 to 2050 as well as flooding of access roads that might impact the availability of the facility.
5. Climate-Induced Risks: Sea Level Rise
This chapter summarizes some of the literature characterizing the effects of SLR on tidal floods,
groundwater levels and salinity and the impact of those changes on landfills located in Virginia's
southern coastal plain and presents historic coastal inundation.
Wuebbles et al. (2017) states with very high confidence that SLR has caused the number of tidal floods
each year -also called "nuisance floods"- to increase 5- to 10- fold since the 1960s in several U.S. coastal
cities. Specifically, the rate has been accelerating in over 25 Atlantic and Gulf Coast cities. In addition,
SLR is one of the contributors to increase in the frequency and extent of extreme flooding associated
with coastal storms (Wuebbles et al., 2017).
In addition to nuisance floods, SLR will impact groundwater levels, specifically aquifers located near the
coast, which could lead to groundwater emergence and shoaling during high precipitation events
(Hoover et al., 2017).
The closest tidal gauge to Norfolk that has sea level data to 2010 is Sewells Point, VA. Figure 5 shows the
results from monitoring at that station from approximately 1928 to 2015. The relative sea level trend is
4.62 millimeters/year with a 95 percent confidence interval of +/- 0.22 mm/yr based on monthly mean
sea level data from 1927 to 2017, which is equivalent to a change of 1.52 feet in 100 years (NOAA,
2018). Assuming the rise rate remains roughly constant, the SLR from 2015 to 2050 would be
approximately 6 inches (0.5 feet). This level would not significantly change the results of the analyses.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
FALL LINE
WEST
PIEDMONT
METERS PHYSIOGRAPHIC
PROVINCE
COASTAL PLAIN PHYSIOGRAPHIC PROVINCE
YORKTOWN-EASTOVER AQUIFER
COLUMBIA AQUIFER
r', 1 v ', , w;', ' v \
, YORKTQWN CONFINING
UNIT
LEVEL
1.500
VERTICAL SCALE GREATLY EXAGGERATED
COLUMBIA AQUIFER
CONFINING UNIT
EXPLANATION
AQUIFER COASTAL PLAIN REGIONAL AQUIFER SYSTEM
~ Shallow (Depths less than 200 feet}
> ' M BEDROCK
hZ-ZH SAPROLITE
^ FRACTURES
DIRECTION OF GROUND-WATER FLOW
n Middle (Depths between 200 and 400 feet)
~ Deep (Depths greater than 400 feet)
Source: USGS, 2003
Figure 6. Generalized Hydrogeologic Section and Direction of Groundwater Flow in the Virginia Coastal
Plain Groundwater Changes Resulting from Sea Level Rise
A Columbia Water Center study suggests that groundwater levels have been on the decline throughout
the U.S. over the last several decades because of over-pumping (Russo et al., 2014). SLR may cause
some of the groundwater levels in the area to rebound because water tables rise with increases in sea
levels, saturating the soil and impacting the ability of surface water to drain (Rotzoll and Fletcher, 2013).
This rise in the water table could potentially inundate infrastructure (including waste management
facilities) in low-lying areas. Groundwater inundation will start sporadically but when it does happen, it
will be most likely to occur at high tide and heavy rainfall (Rotzoll and Fletcher, 2013).
Figure 7 shows the sites where the City of Norfolk sends its waste and includes locations of USGS
groundwater wells in the area. The groundwater depths at the USGS monitoring wells in the Norfolk
area range from roughly 77 to 90 feet below the land surface. The city sends its waste to the SPSA
landfill in Suffolk, which is adjacent to the Great Dismal Swamp National Wildlife Refuge. The bottom of
the waste cells at this landfill are pyramid shaped. At their deepest points, they are 48 feet below
existing grade, or -48 feet mean sea level. The center is at -10 feet mean sea level. Coastal wetlands,
such as the Great Dismal Swamp, will undoubtedly be impacted by climate change and SLR.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
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USGS Groundwater Wells (depth to water, ft below land surface)
Legend
-®- USGS Groundwater Wells (depth to water, ft below land surface)
Norfolk Waste Sites
~ Closed Landfill
¦ Wheelabrator MSW Combustion
¦ SPSA Regional Landfill (-48 ft. M SL)
~ TFC Recycling
C Transfer Station
~ Norfolk City Limit
Miles
B3RTI
IN-IIVkllONAl
Figure 7. USGS Groundwater Wells (depth to water, feet below land surface)
Figure 8 shows shallow coastal flooding areas in red. These are areas where flooding occurs, usually in
the form of ponding, with an average depth ranging from 1 to 3 feet. None of the sites where the City of
Norfolk sends its waste appear to fall within these shallow flooding areas. Two monitoring stations are
shown on the map. The Sewells Point NOAA Tide Gauge station is expected to see approximately 2.5
feet of rise by 2100 (Atkinson et al,, 2012). This increase in mean sea level will also lead to an increase in
saltwater intrusion into freshwater aquifers as the mixing zone between fresh water and saline water
moves farther inland. It should also be noted that there is a closed landfill in the City of Norfolk that is
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
located right at the coast in a flood zone. Although this site has been converted to a golf course, the
wastes buried there are still subject to being released into the environment because of the impacts
associated with flooding and storm surges, and possibly from groundwater rise.
Flood Zone
Norfolk Waste Sites
Subject to inundation by the i% Annual-chance flood event
| Closed La nd i d
¦
Subject to inundation by 1% Annual-chance shallow flooding {usually areas of ponding)
| Wheelabrator MSW Combustion
__
Buildings here subject to a greater hazard
Moderate lood hazard areas
500-^ar too dp lain jCCv
OPEN WATER XjS'
| SPSA Regional Landfill
U TFC Recycling
"1 T ra rtsfer Statio n
AREA NOT INCLUDED
Sewells PointTse Gauge Station
Money Point Station
BRTI
IN-HfAirOMAt
H
Shaltaw CoasSI Flooding Areas ^ ^.5
Norfolk City Limit
Miles
Sources: FEMA and NOAA
Areas Currently Subject to Shallow Coastal Flooding
Figure 8. Areas Currently Subject to Shallow Coastal Flooding
Figure 9 shows the Sewells Point Tide Gauge station current frequency of coastal flood events and
durations, due to coastal storm events, as compared to hypothetical 0.5 m (1.6 ft) and 1 m (3.3 ft) SLR
scenarios (NOAA, 2013). Flooding begins at 4.5 ft mean lower low water (MLLW). With 0.5 m of SLR,
nearly 400 flood events (which could occur twice a day at both high tide and low tide, based on a 3-
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
MODFLOW to do two different simulations of groundwater levels in New Haven, Connecticut. The first
simulation involved an assessment of future groundwater levels from a 3-foot rise in sea level. The
second simulation also included a 3-foot rise in sea level combined with a 12 percent increase in
groundwater recharge. The output from the first simulation yielded a 3-foot rise in groundwater levels
near the coast, which tapered off closer to a discharge area at a non-tidal stream in the study area.
Water levels were affected even where the pre-simulation water table was 17-24 feet above the
current sea level. When combined with a 12 percent recharge, groundwater levels were as much as a
foot higher in some locations.
5.2.2 Use of the Pee Dee River and Atlantic intracoastal Waterway Salinity Model-Decision
Support System (PRISM2-DSS)
A study prepared by Carolinas Integrated Sciences and Assessments (2012) analyzed how climate change
is affecting and will affect the Yadkin-Pee Dee River basin. It particularly focused on investigating the
frequency and duration of saltwater intrusion events due to SLR. The inputs for the saltwater intrusion
model include tidal range, mean water level, and streamflow data inputs, which are used to estimate
specific conductance, and in return, salinity responses of water discharge under various scenarios.
A secondary component of the study included enhancing a decision support system (DSS) that can be
used by resource managers, industry, and water and sewer districts to plan for future coastal climate
change. Scenarios for how SLR may impact the inland penetration and duration of saltwater intrusion
events can be adjusted with this DSS. The DSS can also be used to help stakeholders prepare for severe
events to plan for things like repositioning freshwater intakes and treatment facilities and to help
determine ways to handle increased treatment costs.
6. Understanding Impacts on Landfills
6.1. Precipitation related
Flooding risks should be taken into consideration in the long-term management of landfills, both during
operation, post-closure and monitoring phases. A review paper outlines existing and needed practices
for better management of landfills to minimize the risks posed by precipitation events or other types of
impacts to avoid adverse effects on human health and the environment. The paper reviews practices
and case studies conducted in Europe, U.S., Canada and Japan. Closure management practices
contribute to outcomes on human health and the environment (Laner et al., 2012).
Quantitative methodologies were developed to assess potential of risks posed by landfill flooding using
metrics such as proximity to flood plains, frequency and extent of precipitation events, chemical load in
the landfills etc. Laner et al. (2009) presents a case study to evaluate vulnerability of landfills in Austria
due to flooding. A quantitative methodology is developed to quantify likelihood of flooding and release
of pollutants through leachate. Neuhold et al. (2011) builds on the Laner study to develop a quantitative
approach to assess flood risk associated with flood-prone waste disposal sites determined in the Laner
study.
There are no case studies conducted for Norfolk, VA related to precipitation impacts on landfills,
however the above-mentioned studies and methods can be applied to understand the risks. The SPSA
landfill serving Norfolk, VA is rather inland and far away from the coastal flooding zones (Figure 8).
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
6.2. Sea Level Rise
Even under extreme SLR scenarios, landfills in the Norfolk VA are not projected to inundate. However,
potential changes in water tables could threaten wastes stored in landfills. The risk of contaminants or
pollutants leaching through liners could increase as salt water permeates through clay liners that are
impervious to fresh water (Flynn et al., 1984). The primary landfill, the SPSA landfill in Suffolk, used by
the City of Norfolk, is adjacent to the Great Dismal Swamp National Wildlife Refuge, where the water
table would be very close to the surface. As described earlier, the bottom of the waste cells at the SPSA
landfill are pyramid-shaped with their deepest points at 48 feet below existing grade (or -48 feet mean
sea level) with the center at 10 feet below existing grade (or -10 feet mean sea level).
Although groundwater may be impacted in the region, there is not enough data and information to
ascertain if and how the SPSA landfill would be impacted by groundwater changes. The hydrogeology
beneath the landfill may be multilayered and complex. There are both shallow and deep groundwater
levels in the nearby USGS monitoring wells, as shown in Figure 7, and the USGS 7.5-minute quadrangle
map of Suffolk, VA, shows that the landfill is surrounded by wetland areas. The wetlands are, at least in
part, an extension of the Great Dismal Swamp National Wildlife Refuge located along the border of the
landfill site. The water level of the shallow groundwater (6 feet below ground surface), as shown in
Figure 7, is also evidence that the base of the landfill is likely below the water table. The permit for the
landfill indicates that hydraulic control is required to keep the waste from being buoyant. The elevation
of groundwater beneath the landfill is not known but the depth of sumps used for groundwater control
is between elevation 30 to 18 feet below sea level, and the land surface is approximately 20 feet above
mean sea level; therefore, the water table is lower near the base of the landfill, and the deepest points
of the site base are 48 feet below the land surface.
The areas along streams and wetlands near the SPSA landfill location are also subject to flooding (see
Figure 8). Flooding is currently addressed in the landfill's Emergency Management Plan (SPSA, 2015),
but not in response to anticipated SLR. Any storm event in association with SLR would increase the
flooding potential of the landfill area. Given research into potential SLR-induced impacts to coastal
groundwater (e.g., Bjerklie et al., 2012), it appears that there is a potential for direct impacts on the
SPSA landfill site.
One of the impacts to the SPSA landfill complex could be loss of waste buoyancy control. Current plans
(HDR Engineering, Inc., 2011) in the landfill permit indicate that monitoring of the sumps used for
hydraulic control will not be necessary after adequate ballast is in place. SLR could change the ballast
requirement and result in increased costs for monitoring, maintaining, and potentially expanding the
system. It is also possible that a rise in groundwater levels could complicate hydraulic control if sumps
were flooded above the drainage head, and pumping wells were necessary. Although an unlikely
scenario, there is a possibility that the pumping wells or sump systems would need to be maintained
indefinitely, either to avoid buoyancy issues or to isolate waste types. In addition to complications of
hydraulic control beneath the landfill, there could be indirect impacts to supporting infrastructure and
utilities that affect site operations such as interruption of electricity or sewer service.
As sea levels rise, there is also greater likelihood for standing pools of brackish water, maximized at high
tide, because the ability for groundwater drainage is impacted. Waste infrastructure in low-lying coastal
areas, where withdrawal is not substantial, should plan properly to minimize the impacts of SLR on
groundwater.
It is important to estimate potential contaminant releases from climate-impacted landfills and the
transport of such pollutants in the groundwater to nearby populations. In addition, other climate
impacts such as flooding and washout from extreme precipitation events could transport contaminants
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
to downstream receptor populations. Resources should also be appropriately allocated to evaluate
potential climate-related releases based on anticipated changes in the hydrogeological setting of a
landfill. More resources could and should be assigned to address complicated and significant situations
rather than to address situations considered routine and relatively minor.
A tiered approach has been adopted or used by numerous state and federal agencies to evaluate risks
associated with exposures to pollutants in the environment in a conservative manner. For example, the
Illinois EPA uses a tiered approach to support remediation objectives for cleanup of contaminated soil
and groundwater3. To be successful, tiered approaches need to have clearly defined and measurable
endpoints between tiers. In general, a tiered approach begins with a Tier 1 screening level assessment
that includes a simplified conceptual model of the environmental setting and pollutant release
mechanisms combined with conservative exposure assumptions for humans and habitats. If
unacceptable risks are identified (predicted exposure > threshold screening value), then a Tier 2
assessment is implemented using a more realistic release-exposure scenario to reflect key sensitive
scenario and site-specific conditions. If unacceptable risks persist, then a detailed site-specific
conceptual model is developed and evaluated under a Tier 3 analysis.
A possible Tier 1 scenario for climate-impacted landfills would be to assume direct contact and failure of
the liner system with the water table, resulting in groundwater exposures equal to measurements or
estimates of landfill leachate concentrations, which are then compared to screen levels corresponding
to specific receptors and exposure pathways. Alternatively, if water table elevations are not expected to
rise to that extent, national groundwater dilution-attenuation factors (DAFs) available in U.S. EPA tools
(e.g., U.S. EPA Region 5 Delisting Risk Assessment Software [DRAS]4) can be applied to expected leachate
concentrations for screening comparisons. Tier 2 analyses consisting of deterministic or probabilistic
fate and transport simulations can be conducted using existing U.S. EPA tools (e.g., Industrial Waste
Management Evaluation Model [IWEM]5) that require a minimum of key site- or location-specific data to
predict potential landfill releases subject to changes in water table elevations.
As mentioned above, established open source groundwater flow and transport software (e.g., USGS
MODFLOW6 and SEAWAT7) for detailed Tier 3 site-specific investigations are available. Existing U.S. EPA
OLEM and ORD models specific to sources (land disposal units) and fate and transport pathways
(groundwater, air, surface water) with supporting data can be combined and customized to address
conditions specific to climate-impacted landfills (i.e., no unsaturated zone). For example, existing U.S.
EPA's OLEM and ORD solid/hazardous waste models and data—including the Science Advisory Board-
reviewed Multimedia, Multi-pathway, Multi-receptor Exposure and Risk Assessment technology (3MRA,
U.S. EPA, 2003) modules (Figure 10) and the next generation of these models currently being developed
within the HE2RMES (Human and Ecological Exposure & Risk in Multimedia Systems) (Babendreier et al.,
2012) domain within U.S. EPA's FRAMES v 2 (Framework for Risk Analysis in Multimedia Environmental
Systems, version 2)—can be adopted or adapted to investigate exposures to populations and
ecosystems from flood-impacted landfills (and other land disposal units). To support such modeling
efforts, comprehensive physical and chemical properties, human and ecological benchmarks, and the
3 See http://www.epa.illinois.gov/topics/cleanup-programs/taco/index (Last accessed October 2017)
4 Available at https://www.epa.gov/hw/hazardous-waste-delisting-risk-assessment-software-dras (Last accessed
October 2017)
5 Available at https://www.epa.gov/smm/industrial-waste-management-evaluation-model-version-31 (Last
accessed October 2017)
6 Available at http://water.usgs.gov/ogw/modflow/MODFLOW.html (Last accessed October 2017)
7 Available at http://water.usgs.gov/ogw/seawat/ (Last accessed October 2017)
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
2. Data characterizing the extent that transportation infrastructure may be impacted at varying
levels of SLR and per other climate-induced impacts.
3. Alternative waste collection and transportation route options with consideration given to other
transportation system variables (e.g., traffic patterns, vehicle size and weight restrictions).
4. Geophysical information characterizing areas where waste collection routes and transfer and
processing facilities could potentially be rerouted or relocated.
GIS can be used to quantify and measure the impacts because it provides a platform to compile and
present transportation data that cover the Norfolk area. Roads that are used to support waste
management infrastructure are identified, particularly those that are flooded by tides. Various scenarios
of SLR and storm surge could be run to highlight vulnerable areas within the transportation network.
To complete this task, available data and information for characterizing transportation-related impacts
from storms and hurricanes were reviewed. Hurricane Sandy in 2012 provided the most recent and
relevant information as the storm tracked up the east coast of the U.S. In Norfolk, Hurricane Sandy
resulted in closures of major tunnels to the city including Midtown, Brooklyn-Battery, Holland and
Queens Tunnels as well as more than 100 secondary roads due to flooding (Preston et al, 2012). In New
York City, Hurricane Sandy caused severe traffic gridlock for three days (Kaufman et al., 2012), and
infrastructure systems were damaged by the breach of seawater (U.S. Department of Housing and
Urban Development, 2014). In preparation for flooding and winds, all bridges and tunnels in New York
City were closed before the storm. However, taking this precautionary measure did not prepare
transportation authorities for flooding in the city's tunnels. Coastal flooding and storm surge during
Hurricane Sandy led to dune and beach erosion as well as "inundation of wetland habitats, removal of or
erosion to coastal dunes, destruction of coastal lakes, and new inlet creation" (U.S. Department of
Housing and Urban Development, 2014).
In both Norfolk and New York, waste management departments responded within a day after the storm
to remove storm debris and collect waste (AltDaily, 2012; Discard Studies, 2014). One of the
recommendations made after Hurricane Sandy was to develop and apply infrastructure resilience
guidelines nationally. These guidelines would entail making risk-based decisions that incorporate
potential climate change impacts and development patterns throughout the life cycle of the
infrastructure.
7.1. Transportation Infrastructure Supporting Waste Management
Major roads, bridges, and tunnels near Norfolk that support waste management that have been
identified (Hampton Roads Planning District Commission, 2011) as being vulnerable to hurricanes and
storm surge inundation are listed in Table 10. Figure 11 shows state-maintained roads in the City of
Norfolk that have been categorized by their annual average daily traffic counts. There are 189 existing
arterial miles in Norfolk. There are also 22 miles of freeway, plus a seven-mile reversible high-occupancy
vehicle (HOV) lane on 1-64 (City of Norfolk, 2015). Interstate 64 and U.S. Highways 58 and 60 are the
major routes that go from east to west. U.S. Highway 13 and Highway 460 are the major connectors
between the north and south. The Hampton Roads Beltway includes 1-64, 1-264, 1-464, and 1-664 and
forms a loop around Norfolk and other cities in the region.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table 10. Major Roads, Bridges, and Tunnels Supporting Waste Management in and around Norfolk
Major Roads
Major Bridges
Tunnels
|-64, I-264, I-464, I-664
Berkley Bridge
Hampton Roads Bridge Tunnel
US-13, US-58, US-60, US-460
High Rise Bridge
Downtown Tunnel, Midtown Tunnel
Legend
O Bridges
<3) Tunnels
Norfolk City Limit
Norfolk Waste Sites
| Wheelabrator MSW Combustion
~ Transfer Station
0 12
Miles
Annual Average Dailty Traffic
70 - 10,000
10,001 - 25,000
25,001 - 50,000
50,001 - 100,000
100,001 - 179,000
Source: VA DOT
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Figure 11. Annual Average Daily Traffic Counts for Major Roads in Norfolk
Norfolk's transportation network also includes several bridges and tunnels. Major bridges in the city are
the Berkley Bridge and High-Rise Bridge. Heavily traveled tunnels include the Hampton Roads Bridge
Tunnel and the Downtown and Midtown Tunnels. During severe weather events, these bridges and
tunnels may be closed to restrict their use, becoming a major hindrance to waste collection and
transportation service.
Interstate 64 is the only route that has a reversal plan, which means the eastbound lanes will be
reserved so that additional traffic can travel west towards Richmond (Virginia Department of
Transportation, 2012). This plan will only be enacted during the most extreme weather events.
Figure 12 shows regional arterial roads and the City of Norfolk's waste management facilities along with
inundation areas from a hurricane storm surge. The storm surge elevations displayed, which come from
a tool created by the Virginia Department of Emergency Management that utilizes NOAA's SLOSH model
"presents 'worst-case' combinations of direction, forward speed, landfall point, and astronomical tide
for each Saffir-Simpson scale of hurricane category" (Virginia Department of Emergency Management,
2014). The map also shows evacuation directions that go south and west away from the city's waste
operation sites towards the regional landfill.
As shown in Figure 12, many of the city's roadways, bridges and tunnels appear to fall within Category
1-4 hurricane storm surge levels. According to Mitchell et al. (2013), Norfolk currently has 119 road
miles that are vulnerable to flooding. In addition, the Norfolk Flooding Strategy Overview (City of
Norfolk, 2017) estimated that 17 percent of the city's road miles require drainage and roadway
improvements.
Detailed data and information about potential street-level inundation within the city were not found.
However, VIMS has conducted research that involves street-level inundation modeling (VIMS, 2008).
The modeling uses LiDAR data, which allows for the Chesapeake Bay's shoreline to be simulated more
accurately and modeling at the street level. This or a similar model may provide a means for Norfolk to
analyze street-level inundation. The U.S. DOT's National Transportation Atlas Database is a source of
data for primary and secondary roads and bridges. VDOT also collects average daily traffic data. These
datasets may be useful for evaluating heavily traveled roads and identifying places where traffic
problems could occur during severe flooding events.
Although the SPSA regional landfill is in a location that is free from hurricane storm surge, the WTE
plant, transfer station, and recycling center could be impacted by strong hurricanes. The closed landfill
site included on the map is also in a vulnerable location.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
o Bridges
© Tunnels
Hazmat Routes
PjNorfolk City Limit
Hurricane Evacuation
Routes
^ Evacuation Direction
Legend
Norfolk Waste Sites
~ Closed Landfill
J Wheelabrator MSW Combustion
| SPSA Regional Landfill
| TFC Recycling
I I Transfer Station
Virginia Hurricane Storm Surge
I 1 Category 1 I I Category 3
I I Category 2 Category 4
Source Vrgrtta Hufrican* Stew m Surge Tool
2
V <"ft5
Figure 12. Norfolk Waste Management Facilities with Hurricane Storm Surge Categories
7.2. Disruptions-Duration, Recovery Times, and Alternative Options
Hurricanes and storms can cause disruptions in waste collection and management. When Hurricane Ike
struck Houston in 2008, city services were disrupted for "weeks" (Centers for Disease Control and
Prevention, 2009). To glean information about the duration of disruptions, time until recovery, and
alternative options for handling disruptions, several documents in the public domain were reviewed
including city and regional studies, emergency management and resiliency plans from VIMS, SPSA, and
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
the Hampton Roads Planning District Commission. Electronic communications and phone calls were also
made to the City of Norfolk's GIS and Public Works Department, but responses were not returned.
Transportation infrastructure is a significant target for the city's Norfolk Flooding Strategy Overview (City
of Norfolk, undated), which includes increasing the elevation of buildings and roadways. A "roadway and
intersection improvement" project is under way at Brambleton and Colley Avenue which involves raising
the westbound lanes to reduce the frequency of flooding.
SPSA manages the landfill that serves the greater Hampton Roads region. The SPSA Disaster Response
Plan (2015) describes their implementation and emergency response procedures. The authority empties
its transfer stations prior to the onset of an anticipated weather event because there often is an
increase in disposal of waste from residents before the arrival of a storm. They may elect to suspend
residential disposal if it is negatively impacting their ability to handle municipal and commercial solid
waste (SPSA, 2015). There is no additional capacity to handle large amounts of storm debris, even from
a Category 1 hurricane, and SPSA may contract out this work to private companies that specialize in
disaster debris management.
When winds are greater than 40 mph, hauling operations are likely to be suspended to and from SPSA
facilities. According to SPSA's Disaster Response Plan, normal operations are resumed as soon as
conditions allow. The decision to reopen facilities is based on the time of day, quantities of waste that
are currently at their facilities, duration of the storm, and the ability to continue to receive waste at the
city's transfer station.
According to the city, trash collection is rarely delayed, and when trash collection is delayed, all plans
stipulate that personnel be back on the job as soon as possible to resume the collection of refuse (City of
Norfolk, 2016). Factors that may impact waste collection transportation efficiency for storm debris and
other wastes include:
• Well-defined transportation network,
• Hauling times,
• Debris volume,
• Accumulation of debris at temporary accumulation sites,
• Destination linkage of highways and disposal sites, and
• Number of disposal sites (Solis et al., 1995).
The City of Norfolk uses the Verizon Network fleet electronic system to track and monitor their waste
collection and transportation vehicles. The city is knowledgeable of the roads that are prone to flooding
and will adjust collection routes based on the timing of events. No information was available from the
city at the time of this report about the frequency of collection route adjustment. Traffic congestion is
another significant factor in the challenges associated with the transport of waste, both under normal
conditions and under conditions that could arise during a hurricane or over the years because of SLR. In
addition to the roads used to collect and transfer waste, bridges and tunnels in the area are often
congested and can present significant constraints that impact waste management systems (Hampton
Roads Planning District Commission, 2011).
Concerns raised by stakeholders in the area has hindered the selection of temporary disposal sites and
the modification and configuration of transportation routes. Previous proposals have been considered
that involved using railways and barging in waste from out-of-state. However, these alternative options
were rejected for political reasons (Hampton Roads Planning District Commission, 2011). Norfolk's
complex geography with peninsulas connected by bridges and tunnels creates few alternative routes
(Mitchell et al., 2013).
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
73. Sea Level Rise and Groundwater
Although direct impacts of groundwater level and quality changes are not likely to affect roads, indirect
impacts can occur when the capacity for soil infiltration is reduced or when storm water drainage
systems become impaired, in turn possibly leading to flooding on roads and leading to road closures and
roadway deterioration. Roads may need to be elevated to abate the effects of SLR.
8. Understanding Impacts on Utilities and Other Supporting
Infrastructure
SLR and potential changes to groundwater levels and salinity can impact urban infrastructure and
utilities. In this section, potential impacts of SLR on utilities and roads are summarized.
8.1. Water Supply
In the areas around Norfolk, some homeowners rely on wells for their drinking water. If the salinity in
these wells increases, additional treatment may be necessary to make the water usable. An increase in
the salinity of wells will also likely result in greater stress on surface water sources. Saltwater intrusion
into groundwater wells may also reduce the amount of water that comes from surface water intakes,
which in turn could put pressure on groundwater resources and lead to higher treatment costs that
would be passed on to the public.
8.2. Electric Utilities
Many of Norfolk's utilities are located not too far underground and could easily be impacted by
increased flooding and SLR. According to the City of Norfolk, Department of Utilities Standard Design
Criteria Manual (2005), the water mains are installed 6 feet underground or less. The minimum cover
depth for all sewer lines is 3 feet (36 inches).
The National Electrical Safety Code (IEEE, 1999) requires driven rods to be at least 8 feet deep, unless
rock bottom is encountered. Bare wires and strips of metal are buried only at a minimum of 18 inches
deep. The minimum depth for metal plates is only 5 feet. Supply cables and conductors that are 0-600
Volts (V) can be placed only 24 inches deep. Those that are 601V-50,000V are buried at least 30 inches
and those that are greater than 50,000V must be buried at least 42 inches.
Pipe and electrical equipment are often designed to withstand corrosive subsurface conditions and may
not be affected as much by inundation by saline groundwater. The age of the system would likely be an
important factor in the level of impact that would occur.
9. Assessing Cost and Environmental Impacts of Alternative Waste
Management Scenarios
The purpose of this chapter is to detail the approach, assumptions, and outcomes from the assessment
of alternative MSW waste management scenarios should the City of Norfolk waste management
infrastructure be inundated via climate-related impacts. U.S. EPA's MSW DST was utilized to estimate
the cost and environmental impacts for predefined MSW management scenarios.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
9.1. Scenarios Analyzed Using the MSW DSI
The City of Norfolk's current MSW management system includes collection of MSW, recyclables, and
bulk waste for a 2010 population of approximately 242,803 (SPSA, 2016). Once collected, waste is
hauled to the city's transfer station or directly to one of the regional management facilities including the
TFC recycling facility, Wheelabrator WTE plant, or SPSA landfill. This management system serves as the
baseline for purposes of the scenario analysis exercise.
Specific waste flow data for the City of Norfolk were not found; rather, data are presented at the SPSA-
level (SPSA, 2016). Using data for waste generated and amount sent to the Norfolk transfer station per
SPSA (2016) and the SPSA-regional estimates for the percentage of waste that is sent to recycling, WTE,
and landfill disposal per SPSA (2016), the mass flow of MSW for the City of Norfolk was calculated. The
results are shown in Table 11, and these values are used for the scenario modeling exercise using the
MSW DST.
Table 11. Mass Flows of MSW for Simulation Scenarios including Base Case
Process
Percentage
Tonnage
Source
Collection
100%
95,000 tons
Reported (SPSA, 2016)
Transfer
82% (of collected)
77,874 tons
Reported (SPSA, 2016)
Recycling
33% (of collected)
31,065 tons
Calculated (based on SPSA, 2016)
WTE*
21% (of collected)
20,324 tons
Calculated (based on SPSA, 2016)
Landfill
46% (of collected)
43,611 tons
Calculated (based on SPSA, 2016)
* No waste is sent to WTE in Alternative 4 and the 20,324 tons is instead sent to landfill.
Identifying alternative MSW management scenarios based on probable future climate-induced impacts
in the Norfolk region is not straightforward. Determining which facilities would be impacted and taken
off-line was informed by inundation estimates and maps detailing flood boundaries and facility locations
but should be considered hypothetical. The city does not have a formal plan or set alternative sites in
case of emergencies. Rather, their approach is to determine which facilities have the capability/capacity
to handle waste at the time of the emergency. I-WASTE and SPSA (2016) are then used to identify waste
facilities outside the Norfolk region that might serve as alternative sites should the facilities that service
the City of Norfolk be inundated. Reasonable and likely alternatives for each facility have been identified
and assumed.
Table 12 lists, and Figure 13 illustrates on a map, the current (base case) facilities that service the City of
Norfolk and assumed alternative facilities should any base case facilities be inundated or otherwise
taken off-line. Three degrees of climate-induced impact—low, medium, and high—were used to provide
a range of base case facilities that may be taken off-line, and alternative facilities employed. As shown in
Table 12, moving from the base case to Alternative 1 assumes low impact and only the transfer station
is affected. Alternative 2 assumes medium impact where the transfer station, materials recovery facility
(MRF), and WTE plant are affected. Alternative 3 assumes high impact where all facilities are impacted.
In no case was it projected that the SPSA landfill would be inundated, even at the highest SLR estimate.
However, the SPSA landfill was taken offline in Alternatives 3 and 4 for illustrative purposes. For
Alternative 4, it is assumed that the recycling level remains the same all waste sent to WTE would
instead be sent to the Bethel landfill.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table 12. Facilities and Tonnages Used for Base Case and Alternative MSW Management Scenarios
Scenario
Transfer Station
Recycling
WTE
Landfill
Base Case
(current)
95,000 tons
SPSA-Norfolk
77,874 tons
TFC- Norfolk
31,065 tons
Wheelabrator -
Portsmouth
20,324 tons
SPSA - Norfolk
43,611 tons
Alternative 1
(low impact)
95,000 tons
SPSA - Chesapeake
77,874 tons
TFC - Norfolk
31,065 tons
Wheelabrator -
Portsmouth
20,324 tons
SPSA - Norfolk
43,611 tons
Alternative 2
(med impact)
95,000 tons
SPSA - Chesapeake
77,874 tons
TFC - Chester
31,065 tons
Covanta -
Alexandria
20,324 tons
SPSA - Norfolk
43,611 tons
Alternative 3
(high impact)
95,000 tons
SPSA - Chesapeake
77,874 tons
TFC - Chester
31,065
Covanta -
Alexandria
20,324 tons
USA Waste -
Bethel
43,611 tons
Alternative 4
(high, no WTE)
95,000 tons
SPSA - Chesapeake
77,874 tons
TFC - Chester
31,065 tons
NA
0 tons
USA Waste -
Bethel
63,935 tons
Key information and assumptions employed by waste management activity or process for the scenario
analysis are provided in Table 13. With respect to waste collection and potential climate-induced
impacts to collection service and routing, Norfolk's complex geography with peninsulas connected by
bridges and tunnels creates few alternative routes (Mitchell, 2013). In lieu of having quantitative
estimates of collection routing changes that may result from routes being flooded or otherwise
impacted, an assumption was made that the low, medium, and high levels of impact equated to a 10,
20, and 30 percent increase in collection route distance, respectively.
The distance between collection and the alternative transfer station and landfill are assumed to be the
same as the current facilities. The distance between collection and the alternative MRF is 70 miles, and
WTE is 140 miles, which are significantly different from the distances to current facilities. The current
and alternative MRF, WTE, and landfill facilities assume the same design and performance.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Mfton Village
¦Norte*
Military Cwctej
Poplar Hall
irfolk
Portsm
W*ll UJrflW
Port
«p Creek
Legend
Current Norfolk Waste Facilities
Wheelabrator Combustion
SPSA Regional Landfill
TFC Recycling
Norfolk Transfer Station
| Norfolk City Limit
Qi
BRTI
INTflK 4TIONAI
Alternative Facilities
0 Combustion
0 Landfill
£ Recycling
O Transfer Station
Miles
Newport News
Northampton
Figure 13. Location of Base Case and Assumed Alternative MSW Management Facilities
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table 13. Key Assumptions Used in the Scenario Analysis
Parameter
Current Case
Alternative Cases
General
Waste Generation
95,000 tons
95,000 tons
Waste Composition
U.S. Average (Table 14)
U.S. Average (Table 14)
Waste Collection Frequency
1 time per week
1 time per week
Transportation Distances*
Collection to Transfer Station
10 miles one way
10 miles one way
Collection to MRF
10 miles one way
70 miles one way
Collection to WTE
10 miles one way
140 miles one way
Collection to Landfill
10 miles one way
10 miles one way
Recycling (MRF)
Basic Design
Single-stream; semi-automated
Single-stream; semi-automated
Assumed Offset
Average utility grid mix of fuels
Average utility grid mix of fuels
WTE
Basic Design
Mass-burn
Mass-burn
Plant Efficiency
17,500 Btu/kWh
17,500 Btu/kWh
Metals Recovery
Ferrous only; 95% from ash
Ferrous only; 95% from ash
Assumed Electricity Offset
Regional average (Table 15)
Regional average (Table 15)
Landfill
Basic Design
Conventional, Subtitle DType
Conventional, Subtitle D Type
Landfill Gas Collection Average
Efficiency
75%
75%
Landfill Gas Management
Energy recovery
Energy recovery
Assumed Electricity Offset
Regional average (Table 15)
Regional average (Table 15)
*The distances to the facilities in the current case are in the 10-14 miles range from the centroid of the city. We
assumed 10 miles one way in our analysis. Transportation distances are assumed to increase in 10 percent
increments per the base-low-med-high impact cases. For example, base case collection cost, energy, and emission
results are increased 10 percent in the low impact case to account for an assumed 10 percent increase in
transportation distance due to route flooding and subsequent rerouting.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table 14. Assumed Waste Composition Based on U.S. Average
Waste Item
Percent (by mass)
Leaves
4.0%
Grass
5.4%
Branches
4.0%
Newspaper
4.7%
Corrugated Cardboard
12.4%
Office Paper
5.7%
Phone Books
0.7%
Books
1.1%
Magazines
1.3%
3rd Class Mail
2.5%
High-density polyethylene (HDPE) - Translucent
1.9%
HDPE - Pigmented
1.9%
Polyethylene terephthalate (PET)
8.6%
Ferrous Cans
0.9%
Ferrous Metal
5.9%
Aluminum
1.4%
Glass - Clear
2.7%
Glass - Brown
0.9%
Glass - Green
1.0%
Food Waste
14%
Miscellaneous Combustible
15%
Miscellaneous Non-Combustible
4.0%
Table 15. Regional Average Electricity Grid Mix of Fuels Used in the Scenario Analysis
Fuel
Percent
Coal
46.6%
Oil
5.9%
Natural gas
3.8%
Nuclear
41.7%
Hydro
2.0%
Wood
0.0%
Other
0.0%
Source: Mid-Atlantic Area Council of the National Electric Reliability Council.
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
3.2. Scenario Results
In this section, the results from the modeling exercise using the MSW DST are presented. Summary-level
results representing net totals for the scenarios modeled (see Section 5.1) using the MSW DST are
presented in Table 16. Detailed results by scenario are provided in Attachment A.
Figures 14,15, and 16 display the results for each scenario on a bar chart. The tabular and charted
results are grouped as follows:
1. Non-optimized (simulated mass flow according to Table 11)
2. Cost-optimized (no mass flow constraints and MSW DST set to find minimum cost solution)
3. GHG-optimized (no mass flow constraints and MSW DST set to find minimum GHG solution)
Since the alternative facilities are assumed to be identical in terms of design and operating parameters,
based on the available data and information about the current and alternative facilities, the difference
in alternative scenario results from the base case results are primarily due to the differences in
collection and transportation distances. Some other findings/observations are as follows:
¦ For the non-optimized scenarios, the cost and environmental impacts generally follow an
increasing trend from the base case to Alternative 3 (high impact).
¦ For all cases, the unconstrained cost-optimized (i.e., cheapest) solution was found to be MSW
collection and landfill disposal.
¦ For scenarios in which WTE was excluded, cost generally decreased but environmental impacts
increased due to the subsequent removal of energy and materials recovery benefits associated
with WTE.
¦ Level of diversion varied from one scenario set to another. For example, in the simulation
scenarios, the recycling rate was 32%, in the cost-optimization scenarios, there was no recycling
as disposing MSW to landfill is the cheapest option. However, in the GHG-optimization
scenarios, except for Alt 4, the recycling rate decreased to 27%, with increased utilization of the
WTE facility, these scenarios resulted in utilization of landfill to dispose WTE ash, and broken
glass from the Material Recovery Facility. In the case of Alt 4, the recycling rate increased to
48%, while the rest of the MSW is disposed to landfills as this scenario prohibit the use of WTE
facility.
9.2.1. Cost
Net total cost results (reported in 2017 dollars) for each scenario are charted in Figure 14 and include
capital, labor, and operating and maintenance (O&M) costs. Revenue from the recovery and sale of
energy and recyclable materials is netted out of the cost results. The non-optimized results display an
increase in cost for waste management as the level of climate-induced impact increases from the base
case through the alternative (low-medium-high impact) cases. The net difference in cost between the
base case and the alternative scenarios increases as collection and transportation distances increase,
moving from low to high impact. In the Alternative 4 results, there is a slight decrease in net cost as
compared to the base case due to the exclusion of WTE and instead sending that tonnage of MSW to the
alternative landfill. 100% utilization of landfill leads to least-expensive option.
For the cost-optimized scenarios—where all cases found MSW collection and landfill disposal to be
cheapest—the results as shown in Figure 14 display the significant decrease in cost when recycling and
WTE are not utilized.
For the GHG-optimized scenarios, recycling and energy recovery (via WTE) were maximized and only
residual waste resulting from recycling and WTE was landfilled. As shown in Figure 14, the GHG-
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
to equate to an approximate 6 to 7 percent change in landfill carbon (methane and total carbon
equivalent emission) results. While landfill carbon emissions are significant in cases where significant
amounts of MSW are landfilled, recycling and energy recovery (via WTE) can provide significant carbon
emissions reductions. In the non-optimized base case, for example, recycling and WTE reduce total
landfill carbon emissions by half.
10. Concluding Remarks
This report outlines a methodology to evaluate risks and vulnerabilities on waste management
infrastructure due to climate-induced events. The data sources, methods and tools presented can be
applied to any other coastal community to evaluate their vulnerabilities. This project intended to
provide a guideline for better understanding of risks posed by changing climate (e.g., SLR, storm surge,
flooding, tidal flooding) and possible impacts on waste management infrastructure and its operation.
We utilized U.S. EPA's l-WASTE and MSW DST for data and scenario building. Climate-related impacts
can be categorized into three components, i.e., temperature, precipitation, and SLR. Literature has been
focused on precipitation and SLR impacts rather than temperature related impacts. Therefore, the study
focused on precipitation and SLR impacts.
The City of Norfolk was selected as a case study site through discussions among the project team based
on its coastal location, availability of data, and proximity to a varied set of waste facilities. The coastal
region of Virginia is the second most climate-vulnerable area in the U.S., behind New Orleans, and is
currently being impacted by SLR (City of Virginia Beach, 2009). Historic precipitation and SLR data were
collected and overlaid with the waste management infrastructure (specifically keeping in mind location,
access and engineering design). A scenario-based approach was taken to understand and incorporate
future uncertainty of the extent and impact of these events into the long- term waste management
planning. The results from this project are intended for use in gaining a better understanding of the
nature of climate-induced impacts on coastal communities, and how those impacts can affect waste
management infrastructure and long-term planning needs. The study presented options available for
minimizing impacts and potential cost implications for municipalities. There are some caveats to this
analysis. For example, the storm surge and SLR scenarios looked at individual facility flooding however,
other factors might influence the availability of the waste management facility such as inundation of
access roads, or worker availability in the event of a storm. These aspects of waste management could
be covered under emergency management planning process. The study is not intended for emergency
management or analysis of options during an event.
The insights gathered from scenario analysis revealed that there can be opportunities to be leveraged if
intensity and frequency of precipitation events continue to increase for the region. Planners could utilize
these opportunities to better design the system to be more resilient and responsive at cheaper costs,
and in some cases resulting in better environmental outcomes (e.g., reduced air emissions).
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Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table 16. Summary Level Scenario Results (Net Totals)
Non-Optimized
Cost-Optimized
GHG-Optimized
Parameter
Units
Basecase
Alt 1
Alt 2
Alt 3
Alt 4
Basecase
Alt 1
Alt 2
Alt 3
Alt 4
Basecase
Alt 1
Alt 2
Alt 3
Alt 4
Cost
1$
16,360,200
17,829,200
19,923,240
21,110,240
20,915,000
8,880,000
9,459,000
10,038,000
10,617,000
10,617,000
23,343,180
26,588,680
25,891,180
27,165,180
20,312,686
0
0
0
0
0
0
0
0
0
0
0
0
Energy Consumption
MMBTL
-663,874
-653,224
-646,214
-640,034
-510,620
84,400
87,420
90,440
93,460
93,460
-899,776
-879,016
-886,236
-879,466
-529,350
0
0
0
0
0
0
0
0
0
0
0
0
Air Emissions
0
0
0
0
0
0
0
0
0
0
0
0
Total Particulate Matter
lb
-213,097
-212,146
-211,915
-211,855
-185,752
4,302
4,332
4,362
4,393
4,393
-237,718
-234,877
-237,596
-237,534
-206,152
Nitrogen Oxides
lb
-291,204
-281,074
-276,054
-272,124
-235,500
39,000
40,960
42,920
44,880
44,880
-338,980
-315,700
-331,040
-327,070
-261,410
Hydrocarbons (non CH4)
lb
-290,263
-287,268
-286,303
-285,788
-312,019
8,010
8,535
9,060
9,585
9,585
-677,713
-669,477
-676,681
-676,165
-322,582
Sulfur Oxides
lb
-655,347
-653,085
-652,253
-651,741
-492,523
7,660
7,914
8,168
8,422
8,422
-855,563
-849,577
-854,531
-854,015
-500,762
Carbon Monoxide
lb
-661,977
-654,183
-651,489
-649,805
-627,978
21,180
22,028
22,876
23,724
23,724
-483,076 _
-462,151
-479,306
-477,421
-648,285
Carbon Dioxide Biogenic
lb
106,002,107
106,002,399
106,002,552
106,002,671
93,003,062
71,500,598
71,500,658
71,500,718
71,500,777
71,500,777
153,402,916
153,403,576
153,403,159
153,403,280
89,602,636
Carbon Dioxide Fossil
TC-eq
-52,305,700
-51,410,300
-51,088,900
-50,907,500
-44,132,800
2,470,000
2,597,000
2,724,000
2,851,000
2,851,000
-110,618,990
-108,185,390
-110,251,790
-110,068,190
-47,203,200
Ammonia
lb
-1,639
-1,638
-1,638
-1,638
-1,622
2
2
2
2
2
-123
-120
-123
-123
-1,636
Lead
lb
-15
-15
-15
-15
-14
0
0
0
0
0
5
5
5
5
-14
Methane
lb
3,933,598
3,933,793
3,933,894
3,933,975
5,817,935
8,030,400
8,030,440
8,030,480
8,030,520
8,030,520
-132,366 _
-131,927
-132,204
-132,122
5,429,324
Hydrochloric Acid
lb
-5,741
-5,740
-5,739
-5,738
-2,027
1,893
1,893
1,894
1,894
1,894
-6,755
-6,752
-6,754
-6,753
-1,801
Carbon Equivalents
lb
6,244
6,368
6,412
6,437
13,817
27,674
27,691
27,709
27,726
27,726
-15,565
-15,231
-15,514
-15,489
12,091
0
0
0
0
0
0
0
0
0
0
0
0
Ancillary Solid Waste
lb
-15,280,714
-15,274,234
-15,270,804
-15,268,074
-11,227,550
427,400
428,740
430,080
431,420
431,420
-16,678,860
-16,664,370
-16,673,440
-16,670,730
-11,082,940
0
0
0
0
0
0
0
0
0
0
0
0
Water Releases
0
0
0
0
0
0
0
0
0
0
0
0
Dissolved Solids
lb
-189,413
-187,749
-186,885
-186,201
-154,569
8,040
8,383
8,726
9,069
9,069
-485,379 _
-481,613
-483,987
-483,291
-164,412
Suspended Solids
lb
10,868
10,905
10,925
10,941
14,422
348
356
364
372
372
-23,544
-23,458
-23,512
-23,496
14,172
BOD
lb
109,595
109,601
109,605
109,607
141,367
83,213
83,214
83,215
83,217
83,217
9,548
9,562
9,554
9,556
134,459
COD
lb
97,864
97,906
97,927
97,945
187,173
232,085
232,094
232,102
232,111
232,111
-5,970
-5,876
-5,936
-5,918
177,399
Oil
lb
9,572
9,611
9,631
9,647
13,694
19,179
19,187
19,195
19,203
19,203
-2,600
-2,513
-2,568
-2,552
12,081
Sulfuric Acid
lb
-643
-643
-643
-642
-642
1 | 1 | 1 I 1 I 1
-2,054
-2,054
-2,054
-2,054
-647
Iron
lb
2,871
2,872
2,872
2,873
3,099
23
23
23
23
23
-3,248
-3,246
-3,247
-3,247
3,131
Ammonia
lb
546,868
546,869
546,869
546,869
798,878
127,001
127,002
127,002
127,002
127,002
-835
-833
-834
-834
798,878
Copper
lb
0
0
0
0
0
0
0
0
0
0
-6
-6
-6
-6
0
Cadmium
lb
-7
-7
-7
-7
-6
2
2
2
2
2
-8 | -8 | -8 | -8 | -6
Arsenic
lb
3
3
3
3
5
26
26
26
26
26
-2
-2
-2
-2
5
Mercury
lb
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Phosphate
lb
1,130
1,130
1,130
1,131
1,678
1,700
1,700
1,700
1,700
1,700
-196
-196
-196
-196
1,676
Selenium
lb
2
2
2
2
4
1 | 1 | 1 I 1 I 1
-6
-6
-6
-6
4
Chromium
lb
3
3
3
3
10
23
23
23
23
23
-20
-20
-20
-20
8
Lead
lb
2
2
2
2
3
4
4
4
4
4
-4
-4
-4
-4
3
Zinc
lb
49
49
49
49
51
0
0
0
0
0
-23
-23
-23
-23
51
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
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-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Appendix A: Detailed Scenario Modeling Results
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-l. Base Case Non-optimized MSW DST Results
Rec
MSW
Transfer
Parameter
Units
Collection
Collection
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
6,740,000
5,130,000
224,000
3,450,000
1,630,000
1,420,000
42,200
244,000
-2,520,000
16,360,200
0
Energy Consumption
MBTU
36,000
25,800
1,040
13,000
-123,000
26,500
276
5,510
-649,000
-663,874
0
Air Emissions
0
Total Particulate Matter
lb
311
297
448
5,390
-17,000
2,350
17
1,090
-206,000
-213,097
Nitrogen Oxides
lb
20,100
19,200
5,910
20,900
-30,700
10,600
186
7,600
-345,000
-291,204
Hydrocarbons (non CH4)
lb
0
5,150
736
970
-507
1,280
48
3,060
-301,000
-290,263
Sulfur Oxides
lb
2,620
2,500
701
45,800
-157,000
4,840
32
2,160
-557,000
-655,347
Carbon Monoxide
lb
9,980
6,860
1,480
2,440
2,140
6,570
63
7,490
-699,000
-661,977
Carbon Dioxide Biogenic
lb
612
586
40
654
30,800,000
38,700,000
3
212
36,500,000
106,002,107
Carbon Dioxide Fossil
tons
574,000
1,240,000
169,000
7,020,000
-6,520,000
912,000
13,300
886,000
-56,600,000
-52,305,700
Ammonia (Air)
lb
0
0
0
1
-3
1
0
1
-1,640
-1,639
Lead (Air)
lb
0
0
0
1
-1
0
0
0
-14.2
-15
Methane (CH4)
lb
412
393
30
8,120
-28,600
4,020,000
2
141
-66,900
3,933,598
Hydrochloric Acid
lb
4
3
1
1,760
-3,290
1,130
0
1
-5,350
-5,741
Carbon Eguivalents
lb
80
171
23
984
-987
13,800
2
121
-7,950
6,244
0
Ancillary Solid Waste
lb
14,000
13,300
1,260
972,000
-3,460,000
374,000
96
4,630
-13,200,000
-15,280,714
0
Water Releases
0
Dissolved Solids
lb
3,500
3,340
229
7,120
-23,900
1,070
18
1,210
-182,000
-189,413
Suspended Solids
lb
80
76
5
648
-2,280
110
1
28
12,200
10,868
BOD
lb
13
13
1
16
-52
69,200
0
5
40,400
109,595
COD
lb
87
84
6
29
-66
192,000
94
30
-94,400
97,864
Oil
lb
81
78
5
13
-8
8,770
189
28
416
9,572
Sulfuric Acid
lb
1
1
0
0
1
0
0
0
-646
-643
Iron
lb
2
2
0
64
-223
5
0
1
3,020
2,871
Ammonia
lb
1
1
0
3
-9
548,000
1
0
-1,130
546,868
Copper
lb
0
0
0
0
0
0
0
0
0
0
Cadmium
lb
0
0
0
0
0
1
0
0
-8.29
-7
Arsenic
lb
0
0
0
0
0
3
0
0
0
3
Mercury
lb
0
0
0
0
0
0
0
0
-0.00474
0
Phosphate
lb
0
0
0
0
1
1,210
0
0
-81.2
1,130
Selenium
lb
0
0
0
0
0
2
0
0
0
2
Chromium
lb
0
0
0
0
-1
12
0
0
-8.36
3
Lead
lb
0
0
0
0
0
2
0
0
-0.0368
2
Zinc
lb
0
0
0
0
-2
0
0
0
50
49
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-2. Alternative 1 Non-Optimized MSW DST Results
Parameter
Units
Rec Collection
MSW
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
7,414,000
5,643,000
224,000
3,450,000
1,630,000
1,420,000
42,200
526,000
-2,520,000
17,829,200
0
0
Energy Consumption
MBTU
39,600
28,380
1,040
13,000
-123,000
26,500
276
9,980
-649,000
-653,224
0
0
Air Emissions
0
0
Total Particulate Matter
lb
342
327
448
5,390
-17,000
2,350
17
1,980
-206,000
-212,146
Nitrogen Oxides
lb
22,110
21,120
5,910
20,900
-30,700
10,600
186
13,800
-345,000
-281,074
Hydrocarbons (non CH4)
lb
0
5,665
736
970
-507
1,280
48
5,540
-301,000
-287,268
SulfurOxides
lb
2,882
2,750
701
45,800
-157,000
4,840
32
3,910
-557,000
-653,085
Carbon Monoxide
lb
10,978
7,546
1,480
2,440
2,140
6,570
63
13,600
-699,000
-654,183
Carbon Dioxide Biogenic
lb
673
645
40
654
30,800,000
38,700,000
3
384
36,500,000
106,002,399
Carbon Dioxide Fossil
tons
631,400
1,364,000
169,000
7,020,000
-6,520,000
912,000
13,300
1,600,000
-56,600,000
-51,410,300
Ammonia (Air)
lb
0
0
0
1
-3
1
0
3
-1,640
-1,638
Lead (Air)
lb
0
0
0
1
-1
0
0
0
-14.2
-15
Methane (CH4)
lb
453
432
30
8,120
-28,600
4,020,000
2
255
-66,900
3,933,793
Hydrochloric Acid
lb
4
4
1
1,760
-3,290
1,130
0
2
-5,350
-5,740
Carbon Equivalents
lb
88
188
23
984
-987
13,800
2
220
-7,950
6,368
0
0
Ancillary Solid Waste
lb
15,400
14,630
1,260
972,000
-3,460,000
374,000
96
8,380
-13,200,000
-15,274,234
0
0
Water Releases
0
0
Dissolved Solids
lb
3,850
3,674
229
7,120
-23,900
1,070
18
2,190
-182,000
-187,749
Suspended Solids
lb
88
84
5
648
-2,280
110
1
50
12,200
10,905
BOD
lb
14
14
1
16
-52
69,200
0
8
40,400
109,601
COD
lb
96
92
6
29
-66
192,000
94
55
-94,400
97,906
Oil
lb
89
85
5
13
-8
8,770
189
51
416
9,611
Sulfuric Acid
lb
1
1
0
0
1
0
0
0
-646
-643
Iron
lb
2
2
0
64
-223
5
0
1
3,020
2,872
Ammonia (Water)
lb
2
1
0
3
-9
548,000
1
1
-1,130
546,869
Copper
lb
0
0
0
0
0
0
0
0
0
0
Cadmium
lb
0
0
0
0
0
1
0
0
-8.29
-7
Arsenic
lb
0
0
0
0
0
3
0
0
0
3
Mercury (Water)
lb
0
0
0
0
0
0
0
0
-0.00474
0
Phosphate
lb
0
0
0
0
1
1,210
0
0
-81.2
1,130
Selenium
lb
0
0
0
0
0
2
0
0
0
2
Chromium
lb
0
0
0
0
-1
12
0
0
-8.36
3
Lead (Water)
lb
0
0
0
0
0
2
0
0
-0.0368
2
Zinc
lb
0
0
0
0
-2
0
0
0
50
49
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-3. Alternative 2 Non-Optimized MSW DST Results
Parameter
Units
Rec Collection
MSW
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
8,088,000
6,156,000
224,000
3,450,000
1,630,000
1,420,000
42,200
1,433,040
-2,520,000
19,923,240
Energy Consumption
MBTU
43,200
30,960
1,040
13,000
-123,000
26,500
276
10,810
-649,000
-646,214
Air Emissions
Total Particulate Matter
lb
373
356
448
5,390
-17,000
2,350
17
2,150
-206,000
-211,915
Nitrogen Oxides
lb
24,120
23,040
5,910
20,900
-30,700
10,600
186
14,890
-345,000
-276,054
Hydrocarbons (non CH4)
lb
0
6,180
736
970
-507
1,280
48
5,990
-301,000
-286,303
SulfurOxides
lb
3,144
3,000
701
45,800
-157,000
4,840
32
4,230
-557,000
-652,253
Carbon Monoxide
lb
11,976
8,232
1,480
2,440
2,140
6,570
63
14,610
-699,000
-651,489
Carbon Dioxide Biogenic
lb
734
703
40
654
30,800,000
38,700,000
3
417
36,500,000
106,002,552
Carbon Dioxide Fossil
tons
688,800
1,488,000
169,000
7,020,000
-6,520,000
912,000
13,300
1,740,000
-56,600,000
-51,088,900
Ammonia (Air)
lb
0
0
0
1
-3
1
0
3
-1,640
-1,638
Lead (Air)
lb
0
0
0
1
-1
0
0
0
-14.2
-15
Methane (CH4)
lb
494
472
30
8,120
-28,600
4,020,000
2
276
-66,900
3,933,894
Hydrochloric Acid
lb
4
4
1
1,760
-3,290
1,130
0
2
-5,350
-5,739
Carbon Equivalents
lb
96
205
23
984
-987
13,800
2
239
-7,950
6,412
Ancillary Solid Waste
lb
16,800
15,960
1,260
972,000
-3,460,000
374,000
96
9,080
-13,200,000
-15,270,804
Water Releases
Dissolved Solids
lb
4,200
4,008
229
7,120
-23,900
1,070
18
2,370
-182,000
-186,885
Suspended Solids
lb
96
91
5
648
-2,280
110
1
54
12,200
10,925
BOD
lb
16
15
1
16
-52
69,200
0
9
40,400
109,605
COD
lb
105
100
6
29
-66
192,000
94
60
-94,400
97,927
Oil
lb
98
93
5
13
-8
8,770
189
55
416
9,631
Sulfuric Acid
lb
1
1
0
0
1
0
0
0
-646
-643
Iron
lb
2
2
0
64
-223
5
0
1
3,020
2,872
Ammonia (Water)
lb
2
2
0
3
-9
548,000
1
1
-1,130
546,869
Copper
lb
0
0
0
0
0
0
0
0
0
0
Cadmium
lb
0
0
0
0
0
1
0
0
-8.29
-7
Arsenic
lb
0
0
0
0
0
3
0
0
0
3
Mercury (Water)
lb
0
0
0
0
0
0
0
0
-0.00474
0
Phosphate
lb
0
0
0
0
1
1,210
0
0
-81.2
1,130
Selenium
lb
0
0
0
0
0
2
0
0
0
2
Chromium
lb
0
0
0
0
-1
12
0
0
-8.36
3
Lead (Water)
lb
0
0
0
0
0
2
0
0
-0.0368
2
Zinc
lb
0
0
0
0
-2
0
0
0
50
49
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-4. Alternative 3 Non-Optimized MSW DST Results
Parameter
Units
Rec
Collection
MSW
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
8,762,000
6,669,000
224,000
3,450,000
1,630,000
1,420,000
42,200
1,433,040
-2,520,000
21,110,240
Energy Consumption
MBTU
46,800
33,540
1,040
13,000
-123,000
26,500
276
10,810
-649,000
-640,034
Air Emissions
Total Particulate Matter
lb
404
386
448
5,390
-17,000
2,350
17
2,150
-206,000
-211,855
Nitrogen Oxides
lb
26,130
24,960
5,910
20,900
-30,700
10,600
186
14,890
-345,000
-272,124
Hydrocarbons (non CH4)
lb
0
6,695
736
970
-507
1,280
48
5,990
-301,000
-285,788
Sulfur Oxides
lb
3,406
3,250
701
45,800
-157,000
4,840
32
4,230
-557,000
-651,741
Carbon Monoxide
lb
12,974
8,918
1,480
2,440
2,140
6,570
63
14,610
-699,000
-649,805
Carbon Dioxide Biogenic
lb
796
762
40
654
30,800,000
38,700,000
3
417
36,500,000
106,002,671
Carbon Dioxide Fossil
tons
746,200
1,612,000
169,000
7,020,000
-6,520,000
912,000
13,300
1,740,000
-56,600,000
-50,907,500
Ammonia (Air)
lb
0
0
0
1
-3
1
0
3
-1,640
-1,638
Lead (Air)
lb
0
0
0
1
-1
0
0
0
-14.2
-15
Methane (CH4)
lb
536
511
30
8,120
-28,600
4,020,000
2
276
-66,900
3,933,975
Hydrochloric Acid
lb
5
4
1
1,760
-3,290
1,130
0
2
-5,350
-5,738
Carbon Equivalents
lb
104
222
23
984
-987
13,800
2
239
-7,950
6,437
Ancillary Solid Waste
lb
18,200
17,290
1,260
972,000
-3,460,000
374,000
96
9,080
-13,200,000
-15,268,074
Water Releases
Dissolved Solids
lb
4,550
4,342
229
7,120
-23,900
1,070
18
2,370
-182,000
-186,201
Suspended Solids
lb
104
99
5
648
-2,280
110
1
54
12,200
10,941
BOD
lb
17
16
1
16
-52
69,200
0
9
40,400
109,607
COD
lb
113
109
6
29
-66
192,000
94
60
-94,400
97,945
Oil
lb
106
101
5
13
-8
8,770
189
55
416
9,647
Sulfuric Acid
lb
1
1
0
0
1
0
0
0
-646
-642
Iron
lb
3
2
0
64
-223
5
0
1
3,020
2,873
Ammonia (Water)
lb
2
2
0
3
-9
548,000
1
1
-1,130
546,869
Copper
lb
0
0
0
0
0
0
0
0
0
0
Cadmium
lb
0
0
0
0
0
1
0
0
-8.29
-7
Arsenic
lb
0
0
0
0
0
3
0
0
0
3
Mercury (Water)
lb
0
0
0
0
0
0
0
0
-0.00474
0
Phosphate
lb
0
0
0
0
1
1,210
0
0
-81.2
1,131
Selenium
lb
0
0
0
0
0
2
0
0
0
2
Chromium
lb
0
0
0
0
-1
12
0
0
-8.36
3
Lead (Water)
lb
0
0
0
0
0
2
0
0
-0.0368
2
Zinc
lb
0
0
0
0
-2
0
0
0
50
49
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-5. Alternative 4 Non-Optimized MSW DST Results
Parameter
Units
Rec Collection
MSW
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
8,762,000
6,669,000
224,000
3,450,000
2,080,000
2,070,000
-2,340,000
20,915,000
Energy Consumption
MBTU
46,800
33,540
1,040
13,000
38,900
21,100
-665,000
-510,620
Air Emissions
Total Particulate Matter
lb
404
386
448
5,390
3,440
4,180
-200,000
-185,752
Nitrogen Oxides
lb
26,130
24,960
5,910
20,900
15,500
29,100
-358,000
-235,500
Hydrocarbons (non CH4)
lb
0
6,695
736
970
1,880
11,700
-334,000
-312,019
Sulfur Oxides
lb
3,406
3,250
701
45,800
7,070
8,250
-561,000
-492,523
Carbon Monoxide
lb
12,974
8,918
1,480
2,440
9,610
28,600
-692,000
-627,978
Carbon Dioxide Biogenic
lb
796
762
40
654
56,500,000
811
36,500,000
93,003,062
Carbon Dioxide Fossil
tons
746,200
1,612,000
169,000
7,020,000
1,330,000
3,390,000
-58,400,000
-44,132,800
Ammonia (Air)
lb
0
0
0
1
1
5
-1,630
-1,622
Lead (Air)
lb
0
0
0
1
0
0
-14.5
-14
Methane (CH4)
lb
536
511
30
8,120
5,870,000
539
-61,800
5,817,935
Hydrochloric Acid
lb
5
4
1
1,760
1,650
3
-5,450
-2,027
Carbon Equivalents
lb
104
222
23
984
20,200
464
-8,180
13,817
Ancillary Solid Waste
lb
18,200
17,290
1,260
972,000
546,000
17,700
-12,800,000
-11,227,550
Water Releases
Dissolved Solids
lb
4,550
4,342
229
7,120
1,560
4,630
-177,000
-154,569
Suspended Solids
lb
104
99
5
648
161
105
13,300
14,422
BOD
lb
17
16
1
16
101,000
17
40,300
141,367
COD
lb
113
109
6
29
281,000
116
-94,200
187,173
Oil
lb
106
101
5
13
12,900
108
462
13,694
Sulfuric Acid
lb
1
1
0
0
0
1
-645
-642
Iron
lb
3
2
0
64
8
3
3,020
3,099
Ammonia (Water)
lb
2
2
0
3
800,000
2
-1,130
798,878
Copper
lb
0
0
0
0
0
0
0
0
Cadmium
lb
0
0
0
0
2
0
-8.03
-6
Arsenic
lb
0
0
0
0
5
0
0
5
Mercury (Water)
lb
0
0
0
0
0
0
-0.00472
0
Phosphate
lb
0
0
0
0
1,760
0
-83.3
1,678
Selenium
lb
0
0
0
0
4
0
0
4
Chromium
lb
0
0
0
0
17
0
-8.12
10
Lead (Water)
lb
0
0
0
0
3
0
-0.0366
3
Zinc
lb
0
0
0
0
0
0
50.1
51
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-6. Base Case Cost-Optimized MSW DST Results
Parameter
Units
MSW
Collection
Recyclables
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
5,790,000
0
0
0
0
3,090,000
0
0
0
8,880,000
Energy Consumption
MBTU
30,200
0
0
0
0
54,200
0
0
0
84,400
Air Emissions
Total Particulate Matter
lb
302
0
0
0
0
4,000
0
0
0
4,302
Nitrogen Oxides
lb
19,600
0
0
0
0
19,400
0
0
0
39,000
Hydrocarbons (non CH4)
lb
5,250
0
0
0
0
2,760
0
0
0
8,010
Sulfur Oxides
lb
2,540
0
0
0
0
5,120
0
0
0
7,660
Carbon Monoxide
lb
8,480
0
0
0
0
12,700
0
0
0
21,180
Carbon Dioxide Biogenic
lb
598
0
0
0
0
71,500,000
0
0
0
71,500,598
Carbon Dioxide Fossil
tons
1,270,000
0
0
0
0
1,200,000
0
0
0
2,470,000
Ammonia (Air)
lb
0
0
0
0
0
2
0
0
0
2
Lead (Air)
lb
0
0
0
0
0
0
0
0
0
0
Methane (CH4)
lb
400
0
0
0
0
8,030,000
0
0
0
8,030,400
Hydrochloric Acid
lb
3
0
0
0
0
1,890
0
0
0
1,893
Carbon Equivalents
lb
174
0
0
0
0
27,500
0
0
0
27,674
Ancillary Solid Waste
lb
13,400
0
0
0
0
414,000
0
0
0
427,400
Water Releases
Dissolved Solids
lb
3,430
0
0
0
0
4,610
0
0
0
8,040
Suspended Solids
lb
78
0
0
0
0
270
0
0
0
348
BOD
lb
13
0
0
0
0
83,200
0
0
0
83,213
COD
lb
85
0
0
0
0
232,000
0
0
0
232,085
Oil
lb
79
0
0
0
0
19,100
0
0
0
19,179
Sulfuric Acid
lb
1
0
0
0
0
0
0
0
0
1
Iron
lb
2
0
0
0
0
21
0
0
0
23
Ammonia (Water)
lb
1
0
0
0
0
127,000
0
0
0
127,001
Copper
lb
0
0
0
0
0
0
0
0
0
0
Cadmium
lb
0
0
0
0
0
2
0
0
0
2
Arsenic
lb
0
0
0
0
0
26
0
0
0
26
Mercury (Water)
lb
0
0
0
0
0
0
0
0
0
0
Phosphate
lb
0
0
0
0
0
1,700
0
0
0
1,700
Selenium
lb
0
0
0
0
0
1
0
0
0
1
Chromium
lb
0
0
0
0
0
23
0
0
0
23
Lead (Water)
lb
0
0
0
0
0
4
0
0
0
4
Zinc
lb
0
0
0
0
0
0
0
0
0
0
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-7. Alternative 1 Cost-Optimized MSW DST Results
Parameter
Units
MSW
Collection
Recyclables
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
6,369,000
0
0
0
0
3,090,000
0
0
0
9,459,000
Energy Consumption
MBTU
33,220
0
0
0
0
54,200
0
0
0
87,420
Air Emissions
Total Particulate Matter
lb
332
0
0
0
0
4,000
0
0
0
4,332
Nitrogen Oxides
lb
21,560
0
0
0
0
19,400
0
0
0
40,960
Hydrocarbons (non CH4)
lb
5,775
0
0
0
0
2,760
0
0
0
8,535
Sulfur Oxides
lb
2,794
0
0
0
0
5,120
0
0
0
7,914
Carbon Monoxide
lb
9,328
0
0
0
0
12,700
0
0
0
22,028
Carbon Dioxide Biogenic
lb
658
0
0
0
0
71,500,000
0
0
0
71,500,658
Carbon Dioxide Fossil
tons
1,397,000
0
0
0
0
1,200,000
0
0
0
2,597,000
Ammonia (Air)
lb
0
0
0
0
0
2
0
0
0
2
Lead (Air)
lb
0
0
0
0
0
0
0
0
0
0
Methane (CH4)
lb
440
0
0
0
0
8,030,000
0
0
0
8,030,440
Hydrochloric Acid
lb
3
0
0
0
0
1,890
0
0
0
1,893
Carbon Equivalents
lb
191
0
0
0
0
27,500
0
0
0
27,691
Ancillary Solid Waste
lb
14,740
0
0
0
0
414,000
0
0
0
428,740
Water Releases
Dissolved Solids
lb
3,773
0
0
0
0
4,610
0
0
0
8,383
Suspended Solids
lb
86
0
0
0
0
270
0
0
0
356
BOD
lb
14
0
0
0
0
83,200
0
0
0
83,214
COD
lb
94
0
0
0
0
232,000
0
0
0
232,094
Oil
lb
87
0
0
0
0
19,100
0
0
0
19,187
Sulfuric Acid
lb
1
0
0
0
0
0
0
0
0
1
Iron
lb
2
0
0
0
0
21
0
0
0
23
Ammonia (Water)
lb
2
0
0
0
0
127,000
0
0
0
127,002
Copper
lb
0
0
0
0
0
0
0
0
0
0
Cadmium
lb
0
0
0
0
0
2
0
0
0
2
Arsenic
lb
0
0
0
0
0
26
0
0
0
26
Mercury (Water)
lb
0
0
0
0
0
0
0
0
0
0
Phosphate
lb
0
0
0
0
0
1,700
0
0
0
1,700
Selenium
lb
0
0
0
0
0
1
0
0
0
1
Chromium
lb
0
0
0
0
0
23
0
0
0
23
Lead (Water)
lb
0
0
0
0
0
4
0
0
0
4
Zinc
lb
0
0
0
0
0
0
0
0
0
0
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-8. Alternative 2 Cost-Optimized MSW DST Results
Parameter
Units
MSW
Collection
Recyclables
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
6,948,000
0
0
0
0
3,090,000
0
0
0
10,038,000
Energy Consumption
MBTU
36,240
0
0
0
0
54,200
0
0
0
90,440
Air Emissions
Total Particulate Matter
lb
362
0
0
0
0
4,000
0
0
0
4,362
Nitrogen Oxides
lb
23,520
0
0
0
0
19,400
0
0
0
42,920
Hydrocarbons (non CH4)
lb
6,300
0
0
0
0
2,760
0
0
0
9,060
Sulfur Oxides
lb
3,048
0
0
0
0
5,120
0
0
0
8,168
Carbon Monoxide
lb
10,176
0
0
0
0
12,700
0
0
0
22,876
Carbon Dioxide Biogenic
lb
718
0
0
0
0
71,500,000
0
0
0
71,500,718
Carbon Dioxide Fossil
tons
1,524,000
0
0
0
0
1,200,000
0
0
0
2,724,000
Ammonia (Air)
lb
0
0
0
0
0
2
0
0
0
2
Lead (Air)
lb
0
0
0
0
0
0
0
0
0
0
Methane (CH4)
lb
480
0
0
0
0
8,030,000
0
0
0
8,030,480
Hydrochloric Acid
lb
4
0
0
0
0
1,890
0
0
0
1,894
Carbon Equivalents
lb
209
0
0
0
0
27,500
0
0
0
27,709
Ancillary Solid Waste
lb
16,080
0
0
0
0
414,000
0
0
0
430,080
Water Releases
Dissolved Solids
lb
4,116
0
0
0
0
4,610
0
0
0
8,726
Suspended Solids
lb
94
0
0
0
0
270
0
0
0
364
BOD
lb
15
0
0
0
0
83,200
0
0
0
83,215
COD
lb
102
0
0
0
0
232,000
0
0
0
232,102
Oil
lb
95
0
0
0
0
19,100
0
0
0
19,195
Sulfuric Acid
lb
1
0
0
0
0
0
0
0
0
1
Iron
lb
2
0
0
0
0
21
0
0
0
23
Ammonia (Water)
lb
2
0
0
0
0
127,000
0
0
0
127,002
Copper
lb
0
0
0
0
0
0
0
0
0
0
Cadmium
lb
0
0
0
0
0
2
0
0
0
2
Arsenic
lb
0
0
0
0
0
26
0
0
0
26
Mercury (Water)
lb
0
0
0
0
0
0
0
0
0
0
Phosphate
lb
0
0
0
0
0
1,700
0
0
0
1,700
Selenium
lb
0
0
0
0
0
1
0
0
0
1
Chromium
lb
0
0
0
0
0
23
0
0
0
23
Lead (Water)
lb
0
0
0
0
0
4
0
0
0
4
Zinc
lb
0
0
0
0
0
0
0
0
0
0
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-9. Alternative 3 Cost-Optimized MSW DST Results
Parameter
Units
MSW
Collection
Recyclables
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
7,527,000
0
0
0
0
3,090,000
0
0
0
10,617,000
Energy Consumption
MBTU
39,260
0
0
0
0
54,200
0
0
0
93,460
Air Emissions
Total Particulate Matter
lb
393
0
0
0
0
4,000
0
0
0
4,393
Nitrogen Oxides
lb
25,480
0
0
0
0
19,400
0
0
0
44,880
Hydrocarbons (non CH4)
lb
6,825
0
0
0
0
2,760
0
0
0
9,585
Sulfur Oxides
lb
3,302
0
0
0
0
5,120
0
0
0
8,422
Carbon Monoxide
lb
11,024
0
0
0
0
12,700
0
0
0
23,724
Carbon Dioxide Biogenic
lb
777
0
0
0
0
71,500,000
0
0
0
71,500,777
Carbon Dioxide Fossil
tons
1,651,000
0
0
0
0
1,200,000
0
0
0
2,851,000
Ammonia (Air)
lb
0
0
0
0
0
2
0
0
0
2
Lead (Air)
lb
0
0
0
0
0
0
0
0
0
0
Methane (CH4)
lb
520
0
0
0
0
8,030,000
0
0
0
8,030,520
Hydrochloric Acid
lb
4
0
0
0
0
1,890
0
0
0
1,894
Carbon Equivalents
lb
226
0
0
0
0
27,500
0
0
0
27,726
Ancillary Solid Waste
lb
17,420
0
0
0
0
414,000
0
0
0
431,420
Water Releases
Dissolved Solids
lb
4,459
0
0
0
0
4,610
0
0
0
9,069
Suspended Solids
lb
102
0
0
0
0
270
0
0
0
372
BOD
lb
17
0
0
0
0
83,200
0
0
0
83,217
COD
lb
111
0
0
0
0
232,000
0
0
0
232,111
Oil
lb
103
0
0
0
0
19,100
0
0
0
19,203
Sulfuric Acid
lb
1
0
0
0
0
0
0
0
0
1
Iron
lb
3
0
0
0
0
21
0
0
0
23
Ammonia (Water)
lb
2
0
0
0
0
127,000
0
0
0
127,002
Copper
lb
0
0
0
0
0
0
0
0
0
0
Cadmium
lb
0
0
0
0
0
2
0
0
0
2
Arsenic
lb
0
0
0
0
0
26
0
0
0
26
Mercury (Water)
lb
0
0
0
0
0
0
0
0
0
0
Phosphate
lb
0
0
0
0
0
1,700
0
0
0
1,700
Selenium
lb
0
0
0
0
0
1
0
0
0
1
Chromium
lb
0
0
0
0
0
23
0
0
0
23
Lead (Water)
lb
0
0
0
0
0
4
0
0
0
4
Zinc
lb
0
0
0
0
0
0
0
0
0
0
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-10. Alternative 4 Cost-Optimized MSW DST Results
Parameter
Units
MSW
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
7,527,000
0
0
0
3,090,000
0
0
0
10,617,000
Energy Consumption
MBTU
39,260
0
0
0
54,200
0
0
0
93,460
Air Emissions
Total Particulate Matter
lb
393
0
0
0
4,000
0
0
0
4,393
Nitrogen Oxides
lb
25,480
0
0
0
19,400
0
0
0
44,880
Hydrocarbons (non CH4)
lb
6,825
0
0
0
2,760
0
0
0
9,585
SulfurOxides
lb
3,302
0
0
0
5,120
0
0
0
8,422
Carbon Monoxide
lb
11,024
0
0
0
12,700
0
0
0
23,724
Carbon Dioxide Biogenic
lb
777
0
0
0
71,500,000
0
0
0
71,500,777
Carbon Dioxide Fossil
tons
1,651,000
0
0
0
1,200,000
0
0
0
2,851,000
Ammonia (Air)
lb
0
0
0
0
2
0
0
0
2
Lead (Air)
lb
0
0
0
0
0
0
0
0
0
Methane (CH4)
lb
520
0
0
0
8,030,000
0
0
0
8,030,520
Hydrochloric Acid
lb
4
0
0
0
1,890
0
0
0
1,894
Carbon Equivalents
lb
226
0
0
0
27,500
0
0
0
27,726
Ancillary Solid Waste
lb
17,420
0
0
0
414,000
0
0
0
431,420
Water Releases
Dissolved Solids
lb
4,459
0
0
0
4,610
0
0
0
9,069
Suspended Solids
lb
102
0
0
0
270
0
0
0
372
BOD
lb
17
0
0
0
83,200
0
0
0
83,217
COD
lb
111
0
0
0
232,000
0
0
0
232,111
Oil
lb
103
0
0
0
19,100
0
0
0
19,203
Sulfuric Acid
lb
1
0
0
0
0
0
0
0
1
Iron
lb
3
0
0
0
21
0
0
0
23
Ammonia (Water)
lb
2
0
0
0
127,000
0
0
0
127,002
Copper
lb
0
0
0
0
0
0
0
0
0
Cadmium
lb
0
0
0
0
2
0
0
0
2
Arsenic
lb
0
0
0
0
26
0
0
0
26
Mercury (Water)
lb
0
0
0
0
0
0
0
0
0
Phosphate
lb
0
0
0
0
1,700
0
0
0
1,700
Selenium
lb
0
0
0
0
1
0
0
0
1
Chromium
lb
0
0
0
0
23
0
0
0
23
Lead (Water)
lb
0
0
0
0
4
0
0
0
4
Zinc
lb
0
0
0
0
0
0
0
0
0
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-ll. Base Case GHG-Optimized MSW DST Results
Parameter
Units
Recyclables
Collection
Residuals
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
7,490,000
5,250,000
0
5,580,000
6,110,000
7,680
137,000
28,500
-1,260,000
23,343,180
Energy Consumption
MBTU
41,100
26,600
0
12,700
-355,000
123
891
6,810
-633,000
-899,776
Air Emissions
Total Particulate Matter
lb
317
297
0
3,360
-27,100
2
55
1,350
-216,000
-237,718
Nitrogen Oxides
lb
20,500
19,200
0
12,500
-6,200
28
602
9,390
-395,000
-338,980
Hydrocarbons {non CH4)
lb
0
5,160
0
748
-562
7
154
3,780
-687,000
-677,713
Sulfur Oxides
lb
2,660
2,500
0
27,500
-255,000
5
102
2,670
-636,000
-855,563
Carbon Monoxide
lb
11,700
7,150
0
3,390
-5,790
10
204
9,260
-509,000
-483,076
Carbon Dioxide Biogenic
lb
626
588
0
1,430
137,000,000
0
10
262
16,400,000
153,402,916
Carbon Dioxide Fossil
tons
586,000
1,250,000
0
4,310,000
-33,700,000
2,010
43,000
1,090,000
-84,200,000
-110,618,990
Ammonia (Air)
lb
0
0
0
4
-35
0
0
2
-94
-123
Lead (Air)
lb
0
0
0
0
-1
0
0
0
6
5
Methane (CH4)
lb
419
393
0
5,740
-55,900
0
8
174
-83,200
-132,366
Hydrochloric Acid
lb
3
3
0
916
-938
0
0
1
-6,740
-6,755
Carbon Equivalents
lb
81
171
0
607
-4,780
0
6
150
-11,800
-15,565
Ancillary Solid Waste
lb
14,000
13,100
0
578,000
-5,690,000
11
309
5,720
-11,600,000
-16,678,860
Water Releases
Dissolved Solids
lb
3,590
3,370
0
36,100
-357,000
3
58
1,500
-173,000
-485,379
Suspended Solids
lb
82
77
0
1,790
-17,800
0
2
34
-7,730
-23,544
BOD
lb
13
13
0
77
-761
0
0
6
10,200
9,548
COD
lb
89
84
0
134
-1,250
0
305
37
-5,370
-5,970
Oil
lb
83
78
0
25
-157
47
609
35
-3,320
-2,600
Sulfuric Acid
lb
1
1
0
0
4
0
0
0
-2,060
-2,054
Iron
lb
2
2
0
207
-2,050
0
0
1
-1,410
-3,248
Ammonia (Water)
lb
1
1
0
14
-137
0
4
1
-719
-835
Copper
lb
0
0
0
1
-7
0
0
0
0
-6
Cadmium
lb
0
0
0
0
-1
0
0
0
-8
-8
Arsenic
lb
0
0
0
0
-3
0
0
0
0
-2
Mercury (Water)
lb
0
0
0
0
0
0
0
0
0
0
Phosphate
lb
0
0
0
0
2
0
0
0
-199
-196
Selenium
lb
0
0
0
1
-7
0
0
0
0
-6
Chromium
lb
0
0
0
1
-14
0
0
0
-8
-20
Lead (Water)
lb
0
0
0
0
-5
0
0
0
0
-4
Zinc
lb
0
0
0
2
-21
0
0
0
-4
-23
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-12. Alternative 1 GHG-Optimized MSW DST Results
Parameter
Units
Recydables
Collection
Residuals
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
8,239,000
5,775,000
0
5,580,000
6,110,000
7,680
137,000
2,000,000
-1,260,000
26,588,680
Energy Consumption
MBTU
45,210
29,260
0
12,700
-355,000
123
891
20,800
-633,000
-879,016
Air Emissions
Total Particulate Matter
lb
349
327
0
3,360
-27,100
2
55
4,130
-216,000
-234,877
Nitrogen Oxides
lb
22,550
21,120
0
12,500
-6,200
28
602
28,700
-395,000
-315,700
Hydrocarbons (non CH4)
lb
0
5,676
0
748
-562
7
154
11,500
-687,000
-669,477
Sulfur Oxides
lb
2,926
2,750
0
27,500
-255,000
5
102
8,140
-636,000
-849,577
Carbon Monoxide
lb
12,870
7,865
0
3,390
-5,790
10
204
28,300
-509,000
-462,151
Carbon Dioxide Biogenic
lb
689
647
0
1,430
137,000,000
0
10
801
16,400,000
153,403,576
Carbon Dioxide Fossil
tons
644,600
1,375,000
0
4,310,000
-33,700,000
2,010
43,000
3,340,000
-84,200,000
-108,185,390
Ammonia (Air)
lb
0
0
0
4
-35
0
0
5
-94
-120
Lead (Air)
lb
0
0
0
0
-1
0
0
0
6
5
Methane (CH4)
lb
461
432
0
5,740
-55,900
0
8
532
-83,200
-131,927
Hydrochloric Acid
lb
4
3
0
916
-938
0
0
3
-6,740
-6,752
Carbon Equivalents
lb
89
188
0
607
-4,780
0
6
458
-11,800
-15,231
Ancillary Solid Waste
lb
15,400
14,410
0
578,000
-5,690,000
11
309
17,500
-11,600,000
-16,664,370
Water Releases
Dissolved Solids
lb
3,949
3,707
0
36,100
-357,000
3
58
4,570
-173,000
-481,613
Suspended Solids
lb
90
85
0
1,790
-17,800
0
2
104
-7,730
-23,458
BOD
lb
15
14
0
77
-761
0
0
17
10,200
9,562
COD
lb
98
92
0
134
-1,250
0
305
114
-5,370
-5,876
Oil
lb
91
86
0
25
-157
47
609
106
-3,320
-2,513
Sulfuric Acid
lb
1
1
0
0
4
0
0
1
-2,060
-2,054
Iron
lb
2
2
0
207
-2,050
0
0
2
-1,410
-3,246
Ammonia (Water)
lb
2
1
0
14
-137
0
4
2
-719
-833
Copper
lb
0
0
0
1
-7
0
0
0
0
-6
Cadmium
lb
0
0
0
0
-1
0
0
0
-8
-8
Arsenic
lb
0
0
0
0
-3
0
0
0
0
-2
Mercury (Water)
lb
0
0
0
0
0
0
0
0
0
0
Phosphate
lb
0
0
0
0
2
0
0
0
-199
-196
Selenium
lb
0
0
0
1
-7
0
0
0
0
-6
Chromium
lb
0
0
0
1
-14
0
0
0
-8
-20
Lead (Water)
lb
0
0
0
0
-5
0
0
0
0
-4
Zinc
lb
0
0
0
2
-21
0
0
0
-4
-23
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-13. Alternative 2 GHG-Optimized MSW DST Results
Parameter
Units
Recydables
Collection
Residuals
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
8,988,000
6,300,000
0
5,580,000
6,110,000
7,680
137,000
28,500
-1,260,000
25,891,180
Energy Consumption
MBTU
49,320
31,920
0
12,700
-355,000
123
891
6,810
-633,000
-886,236
Air Emissions
Total Particulate Matter
lb
380
356
0
3,360
-27,100
2
55
1,350
-216,000
-237,596
Nitrogen Oxides
lb
24,600
23,040
0
12,500
-6,200
28
602
9,390
-395,000
-331,040
Hydrocarbons (non CH4)
lb
0
6,192
0
748
-562
7
154
3,780
-687,000
-676,681
Sulfur Oxides
lb
3,192
3,000
0
27,500
-255,000
5
102
2,670
-636,000
-854,531
Carbon Monoxide
lb
14,040
8,580
0
3,390
-5,790
10
204
9,260
-509,000
-479,306
Carbon Dioxide Biogenic
lb
751
706
0
1,430
137,000,000
0
10
262
16,400,000
153,403,159
Carbon Dioxide Fossil
tons
703,200
1,500,000
0
4,310,000
-33,700,000
2,010
43,000
1,090,000
-84,200,000
-110,251,790
Ammonia (Air)
lb
0
0
0
4
-35
0
0
2
-94
-123
Lead (Air)
lb
0
0
0
0
-1
0
0
0
6
5
Methane (CH4)
lb
503
472
0
5,740
-55,900
0
8
174
-83,200
-132,204
Hydrochloric Acid
lb
4
4
0
916
-938
0
0
1
-6,740
-6,754
Carbon Equivalents
lb
98
205
0
607
-4,780
0
6
150
-11,800
-15,514
0
0
Ancillary Solid Waste
lb
16,800
15,720
0
578,000
-5,690,000
11
309
5,720
-11,600,000
-16,673,440
Water Releases
Dissolved Solids
lb
4,308
4,044
0
36,100
-357,000
3
58
1,500
-173,000
-483,987
Suspended Solids
lb
99
93
0
1,790
-17,800
0
2
34
-7,730
-23,512
BOD
lb
16
15
0
77
-761
0
0
6
10,200
9,554
COD
lb
107
101
0
134
-1,250
0
305
37
-5,370
-5,936
Oil
lb
100
94
0
25
-157
47
609
35
-3,320
-2,568
Sulfuric Acid
lb
1
1
0
0
4
0
0
0
-2,060
-2,054
Iron
lb
3
2
0
207
-2,050
0
0
1
-1,410
-3,247
Ammonia (Water)
lb
2
2
0
14
-137
0
4
1
-719
-834
Copper
lb
0
0
0
1
-7
0
0
0
0
-6
Cadmium
lb
0
0
0
0
-1
0
0
0
-8
-8
Arsenic
lb
0
0
0
0
-3
0
0
0
0
-2
Mercury (Water)
lb
0
0
0
0
0
0
0
0
0
0
Phosphate
lb
0
0
0
0
2
0
0
0
-199
-196
Selenium
lb
0
0
0
1
-7
0
0
0
0
-6
Chromium
lb
0
0
0
1
-14
0
0
0
-8
-20
Lead (Water)
lb
0
0
0
0
-5
0
0
0
0
-4
Zinc
lb
0
0
0
2
-21
0
0
0
-4
-23
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-14. Alternative 3 GHG-Optimized MSW DST Results
Parameter
Units
Recyclables
Collection
Residuals
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
9,737,000
6,825,000
0
5,580,000
6,110,000
7,680
137,000
28,500
-1,260,000
27,165,180
Energy Consumption
MBTU
53,430
34,580
0
12,700
-355,000
123
891
6,810
-633,000
-879,466
Air Emissions
Total Particulate Matter
lb
412
386
0
3,360
-27,100
2
55
1,350
-216,000
-237,534
Nitrogen Oxides
lb
26,650
24,960
0
12,500
-6,200
28
602
9,390
-395,000
-327,070
Hydrocarbons (non CH4)
lb
0
6,708
0
748
-562
7
154
3,780
-687,000
-676,165
Sulfur Oxides
lb
3,458
3,250
0
27,500
-255,000
5
102
2,670
-636,000
-854,015
Carbon Monoxide
lb
15,210
9,295
0
3,390
-5,790
10
204
9,260
-509,000
-477,421
Carbon Dioxide Biogenic
lb
814
764
0
1,430
137,000,000
0
10
262
16,400,000
153,403,280
Carbon Dioxide Fossil
tons
761,800
1,625,000
0
4,310,000
-33,700,000
2,010
43,000
1,090,000
-84,200,000
-110,068,190
Ammonia (Air)
lb
0
0
0
4
-35
0
0
2
-94
-123
Lead (Air)
lb
0
0
0
0
-1
0
0
0
6
5
Methane (CH4)
lb
545
511
0
5,740
-55,900
0
8
174
-83,200
-132,122
Hyd rochloric Acid
lb
4
4
0
916
-938
0
0
1
-6,740
-6,753
Carbon Equivalents
lb
106
222
0
607
-4,780
0
6
150
-11,800
-15,489
Ancillary Solid Waste
lb
18,200
17,030
0
578,000
-5,690,000
11
309
5,720
-11,600,000
-16,670,730
Water Releases
Dissolved Solids
lb
4,667
4,381
0
36,100
-357,000
3
58
1,500
-173,000
-483,291
Suspended Solids
lb
107
100
0
1,790
-17,800
0
2
34
-7,730
-23,496
BOD
lb
17
16
0
77
-761
0
0
6
10,200
9,556
COD
lb
116
109
0
134
-1,250
0
305
37
-5,370
-5,918
Oil
lb
108
101
0
25
-157
47
609
35
-3,320
-2,552
Sulfu ric Acid
lb
1
1
0
0
4
0
0
0
-2,060
-2,054
Iron
lb
3
3
0
207
-2,050
0
0
1
-1,410
-3,247
Ammonia (Water)
lb
2
2
0
14
-137
0
4
1
-719
-834
Copper
lb
0
0
0
1
-7
0
0
0
0
-6
Cadmium
lb
0
0
0
0
-1
0
0
0
-8
-8
Arsenic
lb
0
0
0
0
-3
0
0
0
0
-2
Mercury (Water)
lb
0
0
0
0
0
0
0
0
0
0
Phosphate
lb
0
0
0
0
2
0
0
0
-199
-196
Selenium
lb
0
0
0
1
-7
0
0
0
0
-6
Chromium
lb
0
0
0
1
-14
0
0
0
-8
-20
Lead (Water)
lb
0
0
0
0
-5
0
0
0
0
-4
Zinc
lb
0
0
0
2
-21
0
0
0
-4
-23
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Table A-15. Alternative 4 GHG-Optimized MSW DST Results
Parameter
Units
Recyclables
Collection
Residuals
Collection
Transfer
Station
MRF
WTE
Landfill
Ash-landfill
Transport
Remfg
Total
Cost
$
9,737,000
6,825,000
0
4,450,000
0
1,860,000
0
686
-2,560,000
20,312,686
Energy Consumption
MBTU
53,430
34,580
0
15,700
0
35,000
0
6,940
-675,000
-529,350
Air Emissions
Total Particulate Matter
lb
412
386
0
6,510
0
3,160
0
1,380
-218,000
-206,152
Nitrogen Oxides
lb
26,650
24,960
0
25,300
0
14,100
0
9,580
-362,000
-261,410
Hydrocarbons (non CH4)
lb
0
6,708
0
1,180
0
1,680
0
3,850
-336,000
-322,582
Sulfur Oxides
lb
3,458
3,250
0
55,300
0
6,510
0
2,720
-572,000
-500,762
Carbon Monoxide
lb
15,210
9,295
0
2,960
0
8,810
0
9,440
-694,000
-648,285
Carbon Dioxide Biogenic
lb
814
764
0
790
0
52,500,000
0
268
37,100,000
89,602,636
Carbon Dioxide Fossil
tons
761,800
1,625,000
0
8,470,000
0
1,220,000
0
1,120,000
-60,400,000
-47,203,200
Ammonia (Air)
lb
0
0
0
1
0
1
0
2
-1,640
-1,636
Lead (Air)
lb
0
0
0
1
0
0
0
0
-15
-14
Methane (CH4)
lb
545
511
0
9,790
0
5,490,000
0
178
-71,700
5,429,324
Hydrochloric Acid
lb
4
4
0
2,120
0
1,520
0
1
-5,450
-1,801
Carbon Equivalents
lb
106
222
0
1,190
0
18,900
0
153
-8,480
12,091
Ancillary Solid Waste
lb
18,200
17,030
0
1,170,000
0
506,000
0
5,830
-12,800,000
-11,082,940
Water Releases
Dissolved Solids
lb
4,667
4,381
0
8,590
0
1,420
0
1,530
-185,000
-164,412
Suspended Solids
lb
107
100
0
782
0
148
0
35
13,000
14,172
BOD
lb
17
16
0
19
0
93,600
0
6
40,800
134,459
COD
lb
116
109
0
35
0
261,000
0
38
-83,900
177,399
Oil
lb
108
101
0
15
0
11,500
0
36
321
12,081
Sulfuric Acid
lb
1
1
0
0
0
0
0
0
-649
-647
Iron
lb
3
3
0
77
0
7
0
1
3,040
3,131
Ammonia (Water)
lb
2
2
0
3
0
800,000
0
1
-1,130
798,878
Copper
lb
0
0
0
0
0
0
0
0
0
0
Cadmium
lb
0
0
0
0
0
2
0
0
-8
-6
Arsenic
lb
0
0
0
0
0
5
0
0
0
5
Mercury (Water)
lb
0
0
0
0
0
0
0
0
0
0
Phosphate
lb
0
0
0
0
0
1,760
0
0
-85
1,676
Selenium
lb
0
0
0
0
0
4
0
0
0
4
Chromium
lb
0
0
0
0
0
16
0
0
-8
8
Lead (Water)
lb
0
0
0
0
0
3
0
0
0
3
Zinc
lb
0
0
0
1
0
0
0
0
50
51
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
Glossary
ACE
Air, Climate, and Energy
DAF
Dilution-attenuation factor
DEM
Digital elevation model
DOE
U.S. Department of Energy
DOT
U.S. Department of Transportation
DSS
Decision Support System
DRAS
Delisting Risk Assessment Software
EPA
Environmental Protection Agency
FRAMES
Framework for Risk Analysis in Multimedia Environmental Systems
GHG
Greenhouse gas
GIS
Geographic information system
HDPE
High-density polyethylene
HE2RMES
Human and Ecological Exposure & Risk in Multimedia Systems
HOV
High occupancy vehicle
HRSD
Hampton Roads Sanitation District
IPCC
Intergovernmental Panel on Climate Change
1-WASTE
Incident Waste Decision Support Tool
IWEM
Industrial Waste Management Evaluation Model
LiDAR
Light Detection and Ranging
MLLW
Mean lower low water
MOM
Maximum of the maximums
MRF
Materials recovery facility
MSW
Municipal solid waste
MSW DST
Municipal Solid Waste Decision Support Tool
NASA
U.S. National Aeronautics and Space Administration
NHC
National Hurricane Center
NOAA
U.S. National Oceanic and Atmospheric Administration
NWS
National Weather Service
O&M
Operations and maintenance
OLEM
Office of Land and Emergency Management (EPA)
ORD
Office of Research and Development (EPA)
PET
Polyethylene terephthalate
POTW
Publicly owned treatment works
RTI
Research Triangle Institute
SLOSH
Sea, Lake and Overland Surges from Hurricanes
SLR
Sea level rise
SPSA
Southeastern Public Service Authority of Virginia
TFC
Tidewater Fibre Corporation
TRAGIS
Transportation Routing Analysis Geographic Information System
U.S.
United States
USCG
U.S. Coast Guard
-------
Vulnerability of Waste Infrastructure to Climate-Induced Impacts
USGCRP United States Global Change Research Program
USGS United States Geological Survey
VDOT Virginia Department of Transportation
VIMS Virginia Institute of Marine Science
WTE Waste-to-energy
------- |