The Climate-Air Quality Scale Continuum and
the Global Emission Inventory Activity
Paulette Middleton
RAND Corporation
2385 Panorama Avenue
Boulder, CO 80304
paulette@rand. org
William G. Benjey*
Atmospheric Sciences Modeling Division
Air Resources Laboratory
National Oceanic and Atmospheric Administration
Research Triangle Park, NC 27711
beni ev. william@epa. gov
ABSTRACT
The Global Emissions Inventory Activity (GEIA), a core program activity of the International
Global Atmospheric Chemistry (IGAC) Project of the International Geosphere-Biosphere Program,
develops data and other related information on key chemical emissions to the atmosphere and
communicates through its virtual center at www.geiacenter.org. GEIA inventories are developed by
international teams and are quality assured through peer review publications. GEIA inventories are
traditionally provided on a one degree latitude by one degree longitude grid, as annual and/or seasonal
averages, and are aggregated over emission category sectors for individual chemical inventories. As
researchers and decision makers world wide become more concerned about the relationship of global
climate change and regional air quality, additional flexibility in tools, more highly resolved spatial scales
of inventory development, and enhanced coordination among inventory developers will be needed. To
address these growing needs, GEIA plans to distribute other important and quality assured emission
information through its web site. New information will include underlying data sets from which the
emission data were derived (e.g., activity data), global and regional emission inventory data at finer
spatial resolutions and/or more refined temporal resolutions and expanded time periods, algorithms for
modeling processes selected natural emissions, references to promising new approaches to emission
estimates, such as satellite imagery and inverse modeling, and brief summaries of the state of knowledge
regarding emissions of individual chemicals and source categories. Through planning and discussions
with its network of over 500 emission data developers and collaborators, GEIA will seek to increase the
awareness, development, and exchange of versatile data management systems and plans. With sincere
and coordinated global community effort that facilitates modifications and quality assurance of
databases, inventories that are more useful for examining the relationship between global climate change
and regional air quality can be developed.
INTRODUCTION
The Global Emission Inventory Activity (GEIA), a program of the International Global
Atmospheric Chemistry (IGAC) Project was established in 1990 as a result of the need of the
international global climate and air quality community for methodologically uniform and reasonably
current spatially-gridded emission inventories for modeling purposes.1 GEIA is a consortium of
volunteers, relying on the contribution of peer-reviewed global emission inventories by cooperating
*0n assignment to the National Exposure Modeling Laboratory, U. S. Environmental Protection Agency

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scientists. IGAC does not fund development and distribution of data. Inventory development is
sponsored by a variety of organizations throughout the world, and depends on collaborating groups to
develop the databases. The GEIA data management and coordination activity is funded by the United
States National Science Foundation and National Aeronautics and Space Administration. Although
regional and national emission inventories (principally of criteria pollutants) were and are available, they
vary substantially in terms of contents, spatial and temporal representation, and emission estimation
methodology. GEIA approached the problem of producing emission inventories for global modeling by
means of extensive volunteer efforts following agreed formats and documentation procedures under five-
year plans. It was agreed at the beginning of the process that the new inventories would be in a one
degree by one degree longitude and latitude form, would be made available freely on the Internet, and
would be documented by means of peer-reviewed journal articles.
GEIA is nearing the end of the current five year plan for 1998-2003, which has science and data
objectives that began to address data needs related to broader assessments of regional air quality.
GEIA's key scientific objectives during this five year period have included the following: enhanced
uncertainty estimates, completion of biomass burning emission inventories, methane and carbon
monoxide inventories, addition of natural emissions for key chemical compounds, source sector
breakdowns, seasonal/monthly emission variations, updating inventories from 1990 to 1995, addition of
finer grid resolutions and country emission totals, and references to predictive models where possible.
There has been a recognition that the spatial and temporal resolution of current GEIA inventories does
not meet increasing needs for fine resolution in climate and air quality modeling. In addition, the current
GEIA data base is missing inventories for some of the chemical compounds that are key to climate and
air quality modeling, including primary aerosols. Consequently, during the last GEIA international
workshop, held in Paris in June 2001, new plans aimed at enhancing GEIA's role in helping to address
regional-global spatial modeling continuum needs were initiated.
MODELING SPATIAL CONTINUUM, DATA NEEDS AND NEW TECHNIQUES
Historically, air quality modeling and climate modeling developed separately. Air quality
modeling was treated as a relatively local short-term phenomena, and climate modeling was addressed
globally or hemispherically on longer time scales. Increased understanding of the chemical and physical
components of atmospheric circulation and chemistry, and increased computational capacity, made it
clear that atmospheric dynamics and chemistry could not realistically be compartmentalized by spatial
scale and chemical constituents if modeling accuracy was to improve. This problem is recognized in
regional climate modeling by the need to post-process global climate model data to obtain realistic
"down-scaled" data to drive regional climate models.2 Improvement of the performance of global scale
models is focusing on the need to include the chemistry of shorter-lived chemical species such as
nitrogen oxides.3 Recognition of the need for more detailed data has driven the establishment of
improved emission data bases, such as GEIA, and efforts to improve the chemical completeness and
spatial resolution of both climate and air quality models. There is now a partial convergence in research
since, as a part of examining the effects of climate change, there are renewed efforts toward linking
climate change with effects on air quality. For example, the U.S. Environmental Protection Agency's
Office of Air and Radiation and Office of Research and Development have begun work to link the
outputs of climate change models to the input conditions of the regional Community Multiscale Air
Quality (CMAQ) model. The CMAQ and documentation is available on the Internet at
http://www.epa.gov/asmdner/models3/.
For regulatory purposes, air quality is normally evaluated relative to ambient concentration
standards, violations of which are usually triggered by a combination of emitted pollutants and relatively
extreme episodic meteorological events. The pollutants and meteorology are applied to three-

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dimensional gridded chemical transport models (CTMs) that use input emission data and meteorology
data at spatial and temporal scales finer than for global climate models (e.g., 4 km to 50 km horizontal
resolution with equations solved every few minutes vs. approximately 2 to 6 degree grid cell size
horizontal resolution with half hourly equation solutions).4 Within the U.S. Environmental Protection
Agency, regional air quality modeling and the implementation of a unified "one-atmosphere" approach
has led to regional high-resolution multi-pollutant air quality modeling as manifested in the Community
Multiscale Air Quality (CMAQ) model.5 Climate change research has demonstrated that data and
processes needed for global modeling require relatively high resolution (sub-grid scale to a global
climate model) in order resolve important processes such as urban pollution and biomass burning.
Consequently, it is important to bridge between the global spatial and temporal scales of climate
modeling to regional climate, and related regional and local air quality episodes.
Regional climate modelers are working to increase the spatial and temporal resolution of their
models. Three general approaches have been used to date.2 First, atmosphere-ocean general circulation
models (AOGCMs) are used in conjunction with higher resolution atmospheric general circulation
models run at 50 km to 100 km horizontal resolution for periods of interest. Second, regional climate
models are nested from AOGCMs by using the meteorological, surface boundary and initial conditions
from the global climate model to initialize the regional climate model. Regional climate models are run
in horizontal resolutions of approximately 20 km to 125 km.3 Third, statistical downscaling
relationships may be derived between AOGCM variables and local variables reflecting physiographic
features, land-sea distribution and land use. Continental to regional scale chemical transport air quality
models are increasingly sophisticated, and now operate at spatial resolutions which range at the upper
bound from the finer resolutions of regional climate models (approximately 50 to 100 km) down to 4 km
resolution or less, such as CMAQ. The increased role of these chemical transport models is recognized
in the Global Integration and Modeling (GIM) work, which, like GEIA, is a cross-cutting activity of
IGAC, and seeks to improve coordination and inter-comparison of chemical transport models.6
Data Needs
Emission inventories are an increasingly crucial component in the modeling efforts.
Examination of climate change effects on air quality at regional or local scales requires knowledge of a
wider range of chemical emissions (e.g., traditional criteria chemical pollutants, toxic emissions,
naturally occurring emissions) and related atmospheric chemistry than do traditional global climate
change studies. In addition, there is a need for multi-pollutant emission data synonymous in time,
current (e.g., year 2000) inventories, better identification of point sources (emission from stacks), and
more highly resolved data either in terms of finer spatial resolution and/or by political unit and by
emission source sector. It is also important to specify source-category-specific temporal patterns and
species profiles of emissions, location information, surrogate data where necessary to allow spatial
allocation of emission sources, emission modeling/estimation methods, and related activity data such as
population, biomass burning, and land cover. To the extent possible, it is important to retain and report
the greatest resolution of available information, to allow inventory developers and modelers to take
advantage of resolution where it exits. Increased spatial and temporal resolution places greater demands
on the accuracy of emission inventory data. Where coarse resolution might to some degree average or
blur uncertainties in the emission data, finer resolution demands better information.
Finally, it is important to develop information on temporal emission trends and projections at a
level useful for meeting the needs of both air quality and climate modeling. More spatially and
temporally resolved data for the present will improve baseline accuracy for both higher resolution air
quality and climate models, and could provide a common detailed "starting point". Air quality modeling
is generally projected approximately 5 to 20 years into the future based on local and regional annual

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economic projection scenarios,7 while climate modeling scenarios may be projected hundreds of years or
more, based on a range of more generalized economic and physical possibilities (scenarios) for the
world, such as those used by the Intergovernmental Panel on Climate Change.8 Trend and projection
scenarios of emission and activity data need to be developed on common spatial scales, and with
compatible (not identical) methodologies for the 20 to 50 year range in order to be useful for examining
the relationships between air quality and climate change in that time frame. Beyond 50 years,
uncertainties are likely to mask any differences in air quality and climate modeling scenarios.
To better accommodate the examination of the effects of climate change on air quality, the
products required from GEIA and other sources must become much more specific and accurate than the
currently available information. Of course, this is a challenge because of the limitations of available data
in general, and in some areas of the world in particular. The problem can approached by applying a
combination of more highly resolved traditional emission inventories and new observational and
modeling techniques.
Supplemental Emission Estimation Techniques
Establishment of a current high resolution emission inventory remains a significant problem in
many areas of the world. Even where the data are relatively good, many uncertainties remain with
respect to sources and some compounds, for example ammonia. Improving inventories by traditional
reporting methods is constrained by cost and time limitations. Consequently, there is a definite need for
supplemental inventory methods. The application of satellite sensors and inverse modeling of emissions
are two techniques that may help improve accuracy as well as spatial and temporal allocation of
emission inventory data sets.
The application of higher-resolution satellite sensors to near-surface tropospheric chemical constituents
holds promise for significant improvement in verification of chemical transport models and emission
inventories in the next ten years. The limited spatial resolution of satellite sensors, the interference of
water vapor and carbon dioxide spectral bands, and the inability to penetrate the troposphere and
distinguish the near-surface chemical constituents are long-standing problems with satellite-based
techniques. New satellite sensors, such as the Tropospheric Emission Spectrometer (TES) (proposed for
launch in 2004) should provide substantially increased chemical, spatial and temporal resolution in the
longer term.9 For example, TES proposes to use both nadir and limb (horizon) spectral sounding to
detect ozone, water vapor, carbon monoxide, methane, nitric acid, nitrogen dioxide, nitric acid, nitrous
oxide, and perhaps other chemical compounds, with a horizontal resolution of 5 km. The chemical
concentration fields may then be compared with model simulated concentration fields, with differences
having implication for improvements in emission input data.
Inverse modeling is not conceptually new to emission budgets and inventories, particularly at a
global scale.10'11'12 This technique is also being applied at regional modeling scales.13 Basically, a
chemical transport model is used to simulate the concentrations of chemical compounds using emission
inventory input data; and the results are compared to measured concentrations. Using a statistical
reverse modeling technique, emission adjustments are estimated that would normalize (e.g.; minimum
least squares error) the difference between the observations and the model results. This generally
provides information on the "closeness" of emission concentrations between monitored and modeled
results and clues to where the inventory might most benefit from increased attention to sources and
spatial and temporal allocation information. Inverse modeling has traditionally used data from surface
air quality monitoring stations for comparison. As data from satellite sensors improve, inverse modeling
capabilities will be advanced because more spatially representative chemical concentration data can be
considered.

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Inventory Uncertainty
Although compilation of detailed, consistent, regional and global emission inventories is
difficult, it is crucial and often more difficult, to document their uncertainty. For this reason, GEIA has
emphasized peer reviewed documentation of its emission data sets. Although any inventory has
limitations, at least the user is alerted to the strengths and weaknesses. However, it has generally been
infeasible to quantify uncertainty, especially after compilation of an inventory, because of loss of
information about assumptions, and the need for more detailed information to describe uncertainty. An
understanding of the uncertainty of emission inventories at any scale of resolution becomes increasingly
important since emissions drive much of the change depicted by climate and air quality models.
Improvements in quantifying uncertainty are consequently an essential goal. Quantification of
emission inventory uncertainty have been attempted, but are not widely applied in practice. The EPA
has devised a semi-quantitative descriptor, the Data Attribute Rating Systems (DARS), that assigns a
relative weight to each component of an emission estimate.14 The weights are then aggregated to an
overall score. There has also been some research on quantifying uncertainty of specific emission
components (as opposed to the overall inventory).15'16'17 The challenges are to further develop
quantifying techniques, and most importantly, to routinely apply them to emission inventories as the
inventories are developed.
GEIA DIRECTIONS
To respond to the growing needs associated with the climate-air quality continuum analysis,
GEIA plans to build on its existing data and emission information bases and principals, and provide the
highest quality information possible for application to the spatial continuum of global-regional air
quality modeling. This effort relies on the established infrastructure and network of involved
researchers.
GEIA Foundations
The GEIA inventories provide a scientific foundation for policy initiatives designed to address
urgent environmental issues such as global warming, stratospheric ozone depletion, acid precipitation
and biological damage.18 As these issues continue to become more pressing, GEIA has entered a new
phase of revitalization, growth, and enhanced responsiveness to an expanding user community.19
GEIA is composed of a core of dedicated, international participants, many of whom have been
active for over a decade. There are 28 projects, plus the data management and coordination activity
which is responsible for the GEIA communication hub at http://www.geiacenter.org. Since 1990, GEIA
has hosted 12 international planning workshops, and the GEIA e-mail network now includes almost 500
members. Data base quality assurance and protocol updating are ongoing activities.
GEIA collaborators have produced several emission inventories gridded by one degree of latitude
and longitude for the Earth. These inventories, their documentation and GEIA projects are available on
the Internet from the GEIA center. The list below includes more than a dozen available global data
bases. Inventories are available or in progress for many specific chemicals or groups of chemicals and
for several source categories such as biomass burning. Chemical-compound specific data bases are
classified by emissions associated with human activities (A) and by natural processes (N). Additional
emission data bases are organized by emission source, and a beginning has been made on spatial
allocation surrogate data sets with the gridded population and land use data.

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Available Inventories
Inventories in Progress
Ammonia (A and N)20
Black Carbon (A)21'22
Carbon Dioxide (A)23
Carbon Monoxide (A)24
Chlorofluorocarbons (A)25
Nitrous Oxide (A and N)26
Lead
Mercury
Methane (N)27'28
Sulfur and Nitrogen Oxides (A)29
Reactive Chlorine Emissions (A and N)30
Volatile Organic Compounds (A and N)31
Aircraft Emissions
Lightning32
Nitrogen Oxides from Soils (A)33
Sulfur from Volcanos (N)34
Population (activity data)35
Cropland (activity data)36
The GEIA data sets complement other information sources, particularly the Emission Database
for Global Atmospheric Research (EDGAR) inventories compiled by the Netherlands Health and
Environment Agency (RIVM) for greenhouse gases. The latter are available at
http://www.rivm.nl/env/int/coredata/edgar/. In addition, collaborative global emission inventory
compilations are available from the CGEIC on the Internet at http://www.ortech.ca/cgeic/. GEIA and
related web sites also contain maps of emission and support information data bases.
Plans
The 2001 GEIA workshop, held in Paris, was made more successful in that it followed a joint
Precursors of Ozone and their Effects in the Troposphere (POET)/IGAC workshop entitled "Emissions
of Chemical Species and Aerosols into the Atmosphere". The combination of meetings provided
topical reviews on the status of emission inventories, much interaction with the Global Integration and
Modeling (GIM) community, and considerable discussion regarding future directions for GEIA.
Two new GEIA initiatives resulted from the workshop:
to interact more closely with modelers and
to broaden the kinds of emission information provided through GEIA
To encourage interaction with modelers, GIM and GEIA plan to hold workshops focused on
common themes such as "Constraints on emission data based on satellite and in situ observations".
This direction agrees with the need for expanded use of non-traditional methods of composing emission
inventories discussed previously. For example, modelers are increasingly estimating and refining
emissions with the help of field measurements (e.g, the Biomass Burning Experiment), inverse modeling
and, more recently, satellite data. These techniques can be used in conjunction with traditional emission
data, both to expand and verify existing inventories. Therefore, joint modeling and emission workshops
on emission constraints are an appropriate and productive next step for GEIA and the modelers.
Dimethyl sulfide (N)
Organochlorines (A)
Radionucleides (N)
Methane (A)
Primary Particles (A and N)
HCFC (alternative chlorofluorocarbons)
HFC/FPG/SF6
CFC (chlorofluorocarbons)
International Shipping
Biomass Burning

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Model evaluation is another important role for global emission work. GIM studies global
distributions, global budgets and evaluations of trends over time. This is done by development and
implementation of chemical transport models and by intercomparison of modeled concentration fields,
e.g., of ozone, CO, NOx, S02 and precursors; and dynamic aerosol modeling. In particular, inventories
of radon or SF6 are very important because these chemicals can be used as tracers to help evaluate the
transport features of the models.
Some official GEIA inventories are considered "out-of-date" by modelers and other data
developers because they are typically compiled for 1990 or 1995. There is less need for a number of
updates since the more recent peer-reviewed EDGAR data sets are available and widely used, and in
many cases are cited by GEIA as reasonable "non-GEIA" data. Substantial time and resources of the
volunteer community are required to address the publication and the related formal peer review pre-
requisites needed for a data base to become a formal GEIA data base. In view of this resource
constraint, a more feasible and valuable contribution for the GEIA community at this time is to address
the growing need for a determination of which emission information is now available at global and
regional scales, and provide critiques of its quality.
As a first step towards realizing the broadened role for GEIA as an informational data center for
emissions, GEIA is organizing expert groups qualified to provide information for the web site, and to
quality assure information to be placed on the site. The objectives will be to provide references to
alternative emission inventories or (for national sources) scenarios with comments regarding the
strengths or limitations of each; and to incorporate data sets and algorithms (e.g., emission factors) from
which emission data can be derived.
Other steps being considered include allowing different data sets for one source category or
compound, just as there are different models used by GIM, provided that the origins of the differences
are clearly documented. Different versions of an inventory through time (e.g., different years) also ought
to be documented. It is important to highlight emission trends through time. As part of this activity, it
also will be important to periodically prepare review papers inviting the scientific community to
contribute additional or updated information and propose priorities for modifications.
Addition of emission-related data sets contributed by others, e.g., activity data or information on
seasonality, is also being considered for the GEIA web site. GEIA is also considering providing
references to both inventories judged scientifically by the GEIA community, as well as official
government inventories. To capture this valuable information, activities may be initiated to expand the
present GEIA web site to include a web page for each compound with information about the data
available. GIM could be used as an evaluation tool for different emission data sets.
Overall, the GEIA, GIM and other communities recognize the need for dynamic rather than static
inventories, through which variations on all time scales (diurnal to inter-annual to future years) might be
simulated. In order to make GEIA more responsive to informational needs, the contents of the GEIA
site might be broadened further to include, for example, dry deposition information and information on
combinations of feedbacks that might affect future emissions.
In summary, GEIA is embarking on the following new initiatives:
provide web site references to non-GEIA emission data sets with descriptive comments (this
requires collaboration with other (non-GEIA) groups and a review of proposed additions);

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provide, through its web site, underlying data sets and algorithms from which the emission data
were derived ( viz. activity data, calculation algorithms for nationally-provided emission sources,
and seasonal temporal profiles of emissions);
interact more closely with air quality modelers, hold joint meetings with GIM and similar other
modeling efforts, and seek joint modeling/emission activities;
provide clear definitions of the contents of emission data sets and the starting point of modeling
with respect to the data sets (e.g.; primary emissions, extent of (natural) sinks included; and dry
deposition calculated by atmospheric models);
provide long-term historical and future trends of emissions;
provide information on the seasonality of emissions;
provide information on short-term inter-annual changes of emissions in subsequent years;
provide (references to) key scenarios for future emissions available on a gridded basis, e.g., the
IPCC scenarios; and
provide more precise labeling of the reference year of the emission inventories.
CONCLUSIONS
The growing need to better understand the relationships between regional air quality and climate
change is placing new demands on models and emission data bases. Most currently available global data
bases are provided on spatial and temporal scales that are much too coarse for application across the
global-regional modeling continuum. Meeting these data base challenges will require an increased
international and coordinated response since there must be greater consistency and quality for this new
class of emission inventories.
GEIA, as an established and recognized global emission data base coordinating body, is moving
forward to better address these enhanced data needs. The GEIA foundation provides a suite of quality
assured data for many of the key chemicals of concern with respect to climate change and air quality.
However, many of these data need to be updated and expanded, or replaced, by more current
information.
The primary role of GEIA in addressing the now pressing need for new information more
relevant to studies of regional and global issues goes beyond providing the data bases themselves. A
more immediately useful role for GEIA is to be an international coordinating body. In this capacity,
GEIA will provide a formal and internationally accepted organizational structure for identifying the state
of knowledge of available data and progress on development of new techniques and management
systems. GEIA, through its network of experts, will also help provide quality assurance of information
to be distributed.
For development of the necessary new information and data bases needed for regional and global
studies, it will be essential for GEIA and other groups to come together in a collaborative mode for the
greater good of the overall assessment community.

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DISCLAIMER
This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's
peer and administrative review policies and approved for presentation and publication. Mention of trade
names or commercial products does not constitute endorsement or recommendation for use.
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KEY WORDS
emission inventory
global inventory
GEIA
regional
modeling

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REPORT DOCUMENTATION PAGE
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2003
3. REPORT TYPE AND DATES COVERED
4. TITLE AND SUBTITLE: The Climate-Air Quality Scale Continuum
and the Global Emission Inventory Activity
5. FUNDING NUMBERS
None
6. AUTHOR(S)
P. Middleton and W.G. Beniey*
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The Rand Corporation, 2835 Panorama Avenue, Boulder, CO. 80304
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EPA/600/A-03/043
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13. ABSTRACT (Maximum 200 words)
The Global Emissions Inventory Inventory Activity (GEIA), a core program activity of the International Global Atmospheric Chemistry
(IGAC) Project of the International Geosphere-Biosphere Program, develops data and other related information on key chemical
emissions to the atmosphere and communicates through its virtual center at www.geiacenter.org . GEIA inventories are developed by
international teams and are quality assured through peer review publications. GEIA inventories are traditionally provided on a one
degree latitude by one degree longitude grid, as annual and/or seasonal averages, and are aggregated over emission category sectors for
individual chemical inventories. As researchers and decision makers world wide become more concerned about the relationship of
global climate change and regional air quality, additional flexibility in tools, more highly resolved spatial scales of inventory
development, and enhanced coordination among inventory developers will be needed. To address these growing needs, GEIA plans to
distribute other important and qality assured emission through its web site.
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NSN 7540-01-280-5500	Standard Form 298 (Rev. 2-89)
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