Process analysis of a regional air pollution episode over Pearl River Delta Region,China, using the MM5-CMAQ model

This study focuses on the influences of a warm high-pressure meteorological system on aerosol pollutants, employing the simulations by the Models-3/CMAQ system and the observations collected during October 10–12, 2004, over the Pearl River Delta (PRD) region. The results show that the spatial distributions of air pollutants are generally circular near Guangzhou and Foshan, which are cities with high emissions rates. The primary pollutant is particulate matter (PM) over the PRD. MM5 shows reasonable performance for major meteorological variables (i.e., temperature, relative humidity, wind direction) with normalized mean biases (NMB) of 4.5–38.8% and for their time series. CMAQ can capture one peak of all air pollutant concentrations on October 11, but misses other peaks. The CMAQ model systematically underpredicts the mass concentrations of all air pollutants. Compared with chemical observations, SO₂ and O₃ are predicted well with a correlation coefficient of 0.70 and 0.65. PM_2.5 and NO are significantly underpredicted with an NMB of 43% and 90%, respectively. The process analysis results show that the emission, dry deposition, horizontal transport, and vertical transport are four main processes affecting air pollutants. The contributions of each physical process are different for the various pollutants. The most important process for PM₁₀ is dry deposition, and for NO_x it is transport. The contributions of horizontal and vertical transport processes vary during the period, but these two processes mostly contribute to the removal of air pollutants at Guangzhou city, whose emissions are high. For this high-pressure case, the contributions of the various processes show high correlations in cities with the similar geographical attributes. According to the statistical results, cities in the PRD region are divided into four groups with different features. The contributions from local and nonlocal emission sources are discussed in different groups.

Implications: The characteristics of aerosol pollution episodes are intensively studied in this work using the high-resolution modeling system MM5/SMOKE/CMAQ, with special efforts on examining the contributions of different physical and chemical processes to air concentrations for each city over the PRD region by a process analysis method, so as to provide a scientific basis for understanding the formation mechanism of regional aerosol pollution under the high-pressure system over PRD.     

Toward verifying fossil fuel CO2 emissions with the CMAQ model: Motivation,model description and initial simulation

Motivated by the question of whether and how a state-of-the-art regional chemical transport model (CTM) can facilitate characterization of CO₂ spatiotemporal variability and verify CO₂ fossil-fuel emissions, we for the first time applied the Community Multiscale Air Quality (CMAQ) model to simulate CO₂. This paper presents methods, input data, and initial results for CO₂ simulation using CMAQ over the contiguous United States in October 2007. Modeling experiments have been performed to understand the roles of fossil-fuel emissions, biosphere–atmosphere exchange, and meteorology in regulating the spatial distribution of CO₂ near the surface over the contiguous United States. Three sets of net ecosystem exchange (NEE) fluxes were used as input to assess the impact of uncertainty of NEE on CO₂ concentrations simulated by CMAQ. Observational data from six tall tower sites across the country were used to evaluate model performance. In particular, at the Boulder Atmospheric Observatory (BAO), a tall tower site that receives urban emissions from Denver, CO, the CMAQ model using hourly varying, high-resolution CO₂ fossil-fuel emissions from the Vulcan inventory and CarbonTracker optimized NEE reproduced the observed diurnal profile of CO₂ reasonably well but with a low bias in the early morning. The spatial distribution of CO₂ was found to correlate with NOx, SO₂, and CO, because of their similar fossil-fuel emission sources and common transport processes. These initial results from CMAQ demonstrate the potential of using a regional CTM to help interpret CO₂ observations and understand CO₂ variability in space and time. The ability to simulate a full suite of air pollutants in CMAQ will also facilitate investigations of their use as tracers for CO₂ source attribution. This work serves as a proof of concept and the foundation for more comprehensive examinations of CO₂ spatiotemporal variability and various uncertainties in the future.

Implications: Atmospheric CO₂ has long been modeled and studied on continental to global scales to understand the global carbon cycle. This work demonstrates the potential of modeling and studying CO₂ variability at fine spatiotemporal scales with CMAQ, which has been applied extensively, to study traditionally regulated air pollutants. The abundant observational records of these air pollutants and successful experience in studying and reducing their emissions may be useful for verifying CO₂ emissions. Although there remains much more to further investigate, this work opens up a discussion on whether and how to study CO₂ as an air pollutant.     

Reconciling models and measurements to assess trends in atmospheric mercury deposition

Changes in atmospheric mercury deposition are used to evaluate the effectiveness of regulations controlling emissions. This analysis can be complicated by seemingly incongruent data from different model runs, model types, and field measurements. Here we present a case study example that describes how to identify trends in regional scale mercury deposition using best-available information from multiple data sources. To do this, we use data from three atmospheric chemistry models (CMAQ, GEOS-Chem, HYSPLIT) and multiple sediment archives (ombrotrophic bog, headwater lake, coastal salt marsh) from the Bay of Fundy region in Canada. Combined sediment and modeling data indicate that deposition attributable to US and Canadian emissions has declined in recent years, thereby increasing the relative significance of global sources. We estimate that anthropogenic emissions in the US and Canada account for 28-33% of contemporary atmospheric deposition in this region, with the rest from natural (14-32%) and global sources (41-53%).     

Synoptic-scale transport of ozone into Southern Ontario

This study focuses on synoptic-scale transport of ozone as it affects Southern Ontario. This process has been analyzed for the summer in 2001, as an example period of a frequent event that usually occurs during summer in this region. The work was carried out using the mesoscale modeling system generation 5 (MM5)/sparse matrix operator kernel emission modeling system (SMOKE)/community multiscale air quality (CMAQ) regional air quality modeling system, together with observational data from monitoring stations located throughout the modeling domain. Other different analyses have been carried out to supply more information apart from that obtained by the modeling system. A back-trajectory cluster methodology was used to evaluate the magnitude of the effects studied and an analysis of wind direction and cloud cover revealed a significant correlation with ozone concentration (R²=0.5–0.6). Synoptic sea-surface level pressure (SLP) patterns were also analyzed to examine other meteorological aspects. The contribution of natural background ozone to the total amount within the region was compared with that from synoptic-scale transport. The influence of emission of pollutants from selected areas on ozone concentrations in Southern Ontario was also analyzed. As relevant results of these analyses, the model predicts that background ozone is the largest contribution to the ground-level ozone concentration during days in which low values were recorded. However, when smog episodes occurred, the model predicts that around 60% of the ozone formed by anthropogenic emissions of pollutants is due to releases from nearby US states.     

Using a photochemical air quality model to evaluate emissions and simulate concentrations

The air-quality modelling system was conducted to evaluate emissions inventory and simulate air concentration over Thailand. The coupling model of the Regional Atmospheric Modelling System (RAMS) and the models-3 Community Multi-scale Air Quality (CMAQ) was applied to simulate the concentration distributions of gaseous pollutants (i.e., NO_x, SO₂ and CO) over the Central and Eastern regions of Thailand. CMAQ was run for a summertime episode in a sub-grid scale. Simulated air concentrations were then compared with monitoring data. The evaluating results between modelling simulation and monitoring observation show a good agreement within a factor of 2.0 and relevant trend line, representing the acceptable level of emissions and concentration. This coupling model can be applied to support emission control strategies and clean air acts.     

Predictions of U.K. regulated power station contributions to regional air pollution and deposition: a model comparison exercise

Contributions of the emissions from a U.K. regulated fossil-fuel power station to regional air pollution and deposition are estimated using four air quality modeling systems for the year 2003. The modeling systems vary in complexity and emphasis in the way they treat atmospheric and chemical processes, and include the Community Multiscale Air Quality (CMAQ) modeling system in its versions 4.6 and 4.7, a nested modeling system that combines long- and short-range impacts (referred to as TRACK-ADMS [Trajectory Model with Atmospheric Chemical Kinetics-Atmospheric Dispersion Modelling System]), and the Fine Resolution Atmospheric Multi-pollutant Exchange (FRAME) model. An evaluation of the baseline calculations against U.K. monitoring network data is performed. The CMAQ modeling system version 4.6 data set is selected as the reference data set for the model footprint comparison. The annual mean air concentration and total deposition footprints are summarized for each modeling system. The footprints of the power station emissions can account for a significant fraction of the local impacts for some species (e.g., more than 50% for SO2 air concentration and non-sea-salt sulfur deposition close to the source) for 2003. The spatial correlation and the coefficient of variation of the root mean square error (CVRMSE) are calculated between each model footprint and that calculated by the CMAQ modeling system version 4.6. The correlation coefficient quantifies model agreement in terms of spatial patterns, and the CVRMSE measures the magnitude of the difference between model footprints. Possible reasons for the differences between model results are discussed. Finally, implications and recommendations for the regulatory assessment of the impact of major industrial sources using regional air quality modeling systems are discussed in the light of results from this case study.     

A hybrid modeling approach to resolve pollutant concentrations in an urban area

A modeling tool that can resolve contributions from individual sources to the urban environment is critical for air-toxics exposure assessments. Air toxics are often chemically reactive and may have background concentrations originated from distant sources. Grid models are the best-suited tools to handle the regional features of these chemicals. However, these models are not designed to resolve pollutant concentrations on local scales. Moreover, for many species of interest, having reaction time scales that are longer than the travel time across an urban area, chemical reactions can be ignored in describing local dispersion from strong individual sources making Lagrangian and plume-dispersion models practical. In this study, we test the feasibility of developing an urban hybrid simulation system. In this combination, the Community Multi-scale Air Quality model (CMAQ) provides the regional background concentrations and urban-scale photochemistry, and local models such as Hybrid Single Particle Lagrangian Integrated Trajectory model (HYSPLIT) and AMS/EPA Regulatory Model (AERMOD) provide the more spatially resolved concentrations due to local emission sources. In the initial application, the HYSPLIT, AERMOD, and CMAQ models are used in combination to calculate high-resolution benzene concentrations in the Houston area. The study period is from 18 August to 4 September of 2000. The Mesoscale Model 5 (MM5) is used to create meteorological fields with a horizontal resolution of 1×1 km². In another variation to this approach, multiple HYSPLIT simulations are used to create a concentration ensemble to estimate the contribution to the concentration variability from point sources. HYSPLIT simulations are used to model two sources of concentration variability; one due to variability created by different particle trajectory pathways in the turbulent atmosphere and the other due to different flow regimes that might be introduced when using gridded data to represent meteorological data fields. The ensemble mean concentrations determined by HYSPLIT plus the concentrations estimated by AERMOD are added to the CMAQ calculated background to estimate the total mean benzene concentration. These estimated hourly mean concentrations are also compared with available field measurements.     

Uncertainty Analysis of Ozone Formation and Response to Emission Controls Using Higher-Order Sensitivities

Abstract

Understanding ozone response to its precursor emissions is crucial for effective air quality management practices. This nonlinear response is usually simulated using chemical transport models, and the modeling results are affected by uncertainties in emissions inputs. In this study, a high ozone episode in the southeastern United States is simulated using the Community Multiscale Air Quality (CMAQ) model. Uncertainties in ozone formation and response to emissions controls due to uncertainties in emission rates are quantified using the Monte Carlo method. Instead of propagating emissions uncertainties through the original CMAQ, a reduced form of CMAQ is formulated using directly calculated first- and second-order sensitivities that capture the nonlinear ozone concentration-emission responses. This modification greatly reduces the associated computational cost. Quantified uncertainties in modeled ozone concentrations and responses to various emissions controls are much less than the uncertainties in emissions inputs. Average uncertainties in modeled ozone concentrations for the Atlanta area are less than 10% (as measured by the inferred coefficient of variance [ICOV]) even when emissions uncertainties are assumed to vary between a factor of 1.5 and 2. Uncertainties in the ozone responses generally decrease with increased emission controls. Average uncertainties (ICOV) in emission-normalized ozone responses range from 4 to 22%, with the smaller being associated with controlling of the relatively certain point nitrogen oxide (NO_x) emissions and the larger resulting from controlling of the less certain mobile NO_x emissions. These small uncertainties provide confidence in the model applications, such as in performance evaluation, attainment demonstration, and control strategy development.     

Assessment of the emissions and air quality impacts of biomass and biogas use in California

It is estimated that there is sufficient in-state “technically” recoverable biomass to support nearly 4000 MW of bioelectricity generation capacity. This study assesses the emissions of greenhouse gases and air pollutants and resulting air quality impacts of new and existing bioenergy capacity throughout the state of California, focusing on feedstocks and advanced technologies utilizing biomass resources predominant in each region. The options for bioresources include the production of bioelectricity and renewable natural gas (NG). Emissions of criteria pollutants and greenhouse gases are quantified for a set of scenarios that span the emission factors for power generation and the use of renewable natural gas for vehicle fueling. Emissions are input to the Community Multiscale Air Quality (CMAQ) model to predict regional and statewide temporal air quality impacts from the biopower scenarios. With current technology and at the emission levels of current installations, maximum bioelectricity production could increase nitrogen oxide (NO_x) emissions by 10% in 2020, which would cause increases in ozone and particulate matter concentrations in large areas of California. Technology upgrades would achieve the lowest criteria pollutant emissions. Conversion of biomass to compressed NG (CNG) for vehicles would achieve comparable emission reductions of criteria pollutants and minimize emissions of greenhouse gases (GHG). Air quality modeling of biomass scenarios suggest that applying technological changes and emission controls would minimize the air quality impacts of bioelectricity generation. And a shift from bioelectricity production to CNG production for vehicles would reduce air quality impacts further. From a co-benefits standpoint, CNG production for vehicles appears to provide the best benefits in terms of GHG emissions and air quality.

Implications:?This investigation provides a consistent analysis of air quality impacts and greenhouse gas emissions for scenarios examining increased biomass use. Further work involving economic assessment, seasonal or annual emissions and air quality modeling, and potential exposure analysis would help inform policy makers and industry with respect to further development and direction of biomass policy and bioenergy technology alternatives needed to meet energy and environmental goals in California.     

Evaluation of land-use regression models used to predict air quality concentrations in an urban area

Cohort studies designed to estimate human health effects of exposures to urban pollutants require accurate determination of ambient concentrations in order to minimize exposure misclassification errors. However, it is often difficult to collect concentration information at each study subject location. In the absence of complete subject-specific measurements, land-use regression (LUR) models have frequently been used for estimating individual levels of exposures to ambient air pollution. The LUR models, however, have several limitations mainly dealing with extensive monitoring data needs and challenges involved in their broader applicability to other locations. In contrast, air quality models can provide high-resolution source–concentration linkages for multiple pollutants, but require detailed emissions and meteorological information. In this study, first we predicted air quality concentrations of PM_2.5, NO_x, and benzene in New Haven, CT using hybrid modeling techniques based on CMAQ and AERMOD model results. Next, we used these values as pseudo-observations to develop and evaluate the different LUR models built using alternative numbers of (training) sites (ranging from 25 to 285 locations out of the total 318 receptors). We then evaluated the fitted LUR models using various approaches, including: 1) internal “Leave-One-Out-Cross-Validation” (LOOCV) procedure within the “training” sites selected; and 2) “Hold-Out” evaluation procedure, where we set aside 33–293 tests sites as independent datasets for external model evaluation. LUR models appeared to perform well in the training datasets. However, when these LUR models were tested against independent hold out (test) datasets, their performance diminished considerably. Our results confirm the challenges facing the LUR community in attempting to fit empirical response surfaces to spatially- and temporally-varying pollution levels using LUR techniques that are site dependent. These results also illustrate the potential benefits of enhancing basic LUR models by utilizing air quality modeling tools or concepts in order to improve their reliability or transferability.     

Models for gas/particle partitioning,transformation and air/water surface exchange of PCBs and PCDD/Fs in CMAQ

We have added the capability to simulate polychlorinated biphenyls (PCBs) and polychlorinated dibenzo [p] dioxins and polychlorinated dibenzo-furans (PCDD/Fs) to the Community Multiscale Air Quality (CMAQ) modeling system, thus taking advantage of the latter's capability to simulate atmospheric advection, diffusion, gas-phase chemistry, cloud/precipitation, and aerosol processes. The modifications reported here include the addition to the CMAQ system of two gas/particle partitioning models options: the Junge–Pankow adsorption model and the K_OA absorption model, as well as chemical transformations and atmosphere/water surface exchange processes for these semi-volatile organics. Simulations for the purpose of model testing and validation were conducted for the years 2000 and 2002 on a domain covering most of North America. Both partitioning models give reasonable results when compared with available measurements. The model predictions of deposition and air concentrations also agree well with measurements. The modeling results also indicate that the long-range transport is important and anthropogenic emissions of PCBs and PCDD/Fs are dominant although surface exchange of PCBs may be important for some clean locations.     

Modeling assessment of air emission flux of mercury from soils in terrestrial landscape components: model tests and sensitivities

The abilities of a screening-level model to predict variations in elemental mercury (Hg0) air emissions from soils in terrestrial landscapes are examined by comparing simulation results to published observational data and by performing sensitivity analyses. Despite uncertainties and simplifications, the model results obtained offer some degree of confidence in the model's joint ability to relate readily available environmental parameters to airborne emissions of Hg predicted by coupling simple atmospheric and soil parameters with Hg cycling and transport algorithms. The model reasonably predicted the observational data in the considered data sets except for one site for which significant uncertainty was associated with model input data. Predictions are consistent with many trends observed in the field studies; better predictions were obtained for nonvegetated systems (relative errors between 0.4 and 9.7%) than for shaded-soil landscapes (relative errors between 2.3 and 27%). The model reflected field data showing that daily average emission rates of Hg0, formed by the reduction of Hg(II), are primarily controlled by changes in solar radiation, soil moisture, temperature, and, to a lesser extent, wind conditions. The model may have potential use in several preliminary studies to characterize trends of airborne Hg emitted from terrestrial sources to the atmosphere.     

Site Sampling and Treatability Studies for Demonstration of WasteChem’s Asphalt Encapsulation Technology Under EPA’s SITE Program

ABSTRACT

Exposures from indoor environments are a major issue for evaluating total long-term personal exposures to the fine fraction (<2.5μm in aerodynamic diameter) of particulate matter (PM). It is widely accepted in the indoor air quality (IAQ) research community that biocontamination is one of the important indoor air pollutants. Major indoor air biocontaminants include mold, bacteria, dust mites, and other antigens. Once the biocontaminants or their metabolites become airborne, IAQ could be significantly deteriorated. The airborne biocontaminants or their metabolites can induce irritational, allergic, infectious, and chemical responses in exposed individuals.

Biocontaminants, such as some mold spores or pollen grains, because of their size and mass, settle rapidly within the indoor environment. Over time they may become nonviable and fragmented by the process of desiccation. Desiccated nonviable fragments of organisms are common and can be toxic or allergenic, depending upon the specific organism or organism component. Once these smaller and lighter fragments of biological PM become suspended in air, they have a greater tendency to stay suspended. Although some bioaerosols have been identified, few have been quantitatively studied for their prevalence within the total indoor PM with time, or for their affinity to penetrate indoors.

This paper describes a preliminary research effort to develop a methodology for the measurement of nonvi-able biologically based PM, analyzing for mold and ragweed antigens and endotoxins. The research objectives include the development of a set of analytical methods and the comparison of impactor media and sample size, and the quantification of the relationship between outdoor and indoor levels of bioaerosols. Indoor and outdoor air samples were passed through an Andersen nonviable cascade impactor in which particles from 0.2 to 9.0 um were collected and analyzed. The presence of mold, ragweed, and endotoxin was found in all eight size ranges. The presence of respirable particles of mold and pollen found in the fine particle size range from 0.2 to 5.25 um is evidence of fragmentation of larger source particles that are known allergens.     

Lagrangian sampling of 3-D air quality model results for regional transport contributions to sulfate aerosol concentrations at Baltimore,MD, in summer 2004

We use ensemble-mean Lagrangian sampling of a 3-D Eulerian air quality model, CMAQ, together with ground-based ambient monitors data from several air monitoring networks and satellite (MODIS) observations to provide source apportionment and regional transport vs. local contributions to sulfate aerosol and PM_2.5 concentrations at Baltimore, MD, for summer 2004. The Lagrangian method provides estimates of the chemical and physical evolution of air arriving in the daytime boundary layer at Baltimore. Study results indicate a dominant role for regional transport contributions on those days when sulfate air pollution is highest in Baltimore, with a principal transport pathway from the Ohio River Valley (ORV) through southern Pennsylvania and Maryland, consistent with earlier studies. Thus, reductions in sulfur emissions from the ORV under the EPA's Clean Air Interstate Rule may be expected to improve particulate air quality in Baltimore during summer. The Lagrangian sampling of CMAQ offers an inexpensive and complimentary approach to traditional methods of source apportionment based on multivariate observational data analysis, and air quality model emissions separation. This study serves as a prototype for the method applied to Baltimore. EPA is establishing a system to allow air quality planners to readily produce and access equivalent results for locations of their choice.     

Implementation and application of sub-grid-scale plume treatment in the latest version of EPA’s third-generation air quality model,CMAQ 5.01

The Community Multiscale Air Quality (CMAQ) modeling system Version 5.0 (CMAQv5.0) was released by the U.S. Environmental Protection Agency (EPA) in February 2012, with an interim release (v5.01) in July 2012. Because CMAQ is a community model, the EPA encourages the development of proven alternative science treatments by external scientists and developers that can be incorporated as part of an official CMAQ release. This paper describes the implementation, evaluation, and testing of a plume-in-grid (PinG) module in CMAQ 5.01. The PinG module, also referred to as Advanced Plume Treatment (APT), provides the capability of resolving sub-grid-scale processes, such as the transport and chemistry of point-source plumes, in a grid model. The new PinG module in CMAQ 5.01 is applied and evaluated for two 15-day summer and winter periods in 2005 to the eastern United States, and the results are compared with those from the base CMAQ 5.01. Eighteen large point sources of NOx in the eastern United States were selected for explicit plume treatment with APT in the PinG simulation. The results show that overall model performance is negligibly affected when PinG treatment is included. However, the PinG model predicts significantly different contributions of the 18 sources to pollutant concentrations and deposition downwind of the point sources compared to the base model.

Implications: This study describes the incorporation of a plume-in-grid (PinG) capability within the latest version of the EPA grid model, CMAQ. The capability addresses the inherent limitation of the grid model to resolve processes, such as the evolution of point-source plumes, which occur at scales much smaller than the grid resolution. The base grid model and the PinG version predict different source contributions to ozone and PM_2.5 concentrations that need to be considered when source attribution studies are conducted to determine the impacts of large point sources on downwind concentrations and deposition of primary and secondary pollutants.     

Evaluation of air quality models for the simulation of a high ozone episode in the Houston metropolitan area

A high ozone event in the Houston–Galveston–Brazoria area was utilized to study the shortcomings of the current air quality models. To improve the baseline simulations with the Comprehensive Air quality Model with Extensions (CAMx) for developing the state implementation plan, the Texas Commission on Environmental Quality (TCEQ) imputed emissions of highly reactive volatile organic compounds (HRVOCs) by scaling the amount of fugitive emissions of olefins to co-emitted NO_x from selected point sources, effectively multiplying by 3–12 times over the regular inventory values. In this paper, CAMx and the Community Multiscale Air Quality (CMAQ) model were used to determine if the imputed HRVOC emissions were consistent with the observed atmospheric conditions. With the base emissions, CMAQ and CAMx both with the Carbon-Bond 4 (CB-4) mechanism simulated similar ozone concentrations. But with the imputed HRVOC emissions, CMAQ predicted lower ozone peaks than CAMx in the vicinity and downwind of the Ship Channel and other highly HRVOC-rich areas. Based on analyses of sensitivity simulations of CMAQ with different emission inputs and vertical diffusion algorithms in the model, we found that the modeled atmosphere lacked reactivity to produce the observed high ozone event. Although the imputed HRVOC emissions improved ozone prediction at the surface sites, but the ethylene concentrations were not consistent with the measurements at the super sites (La Porte and Clinton) and by NOAA aircraft. Several sensitivity tests designed to provide additional radicals into the system and other research results suggested that the lack of reactivity may need to be corrected by targeted, and probably of episodic, increase of HRVOC emissions, from the sources in the Houston Ship Channel. Additional investigation of the ozone production efficiency for different chemical mechanisms is necessary to pinpoint the emissions uncertainty issues.     

Intercontinental transport of aerosols and photochemical oxidants from Asia and its consequences

The intercontinental transport of aerosols and photochemical oxidants from Asia is a crucial issue for air quality concerns in countries downwind of the significant emissions and concentrations of pollutants occurring in this important region of the world. Since the lifetimes of some important pollutants are long enough to be transported over long distance in the troposphere, regional control strategies for air pollution in downwind countries might be ineffective without considering the effects of long-range transport of pollutants from Asia. Field campaigns provide strong evidence for the intercontinental transport of Asian pollutants. They, together with ground-based observations and model simulations, show that the air quality over parts of North America is being affected by the pollutants transported from Asia. This paper examines the current understanding of the intercontinental transport of gases and aerosols from Asia and resulting effects on air quality, and on the regional and global climate system.     

Modeling the atmospheric transport and deposition of polychlorinated dibenzo-p-dioxins and dibenzofurans in North America

The atmospheric fate of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) was simulated for the year 2000 in North America using a SMOKE/CMAQ-based chemical transport model that was modified for this purpose. The 1999 USEPA emission inventories of PCDD/Fs and criteria pollutants were used. The 1995 Canadian emission inventory of criteria pollutants and the 1995 Canadian area source emissions for PCDD/Fs were used with the 2000 Canadian point source emissions. Modifications to CMAQ involved coupling it with dual organic matter (OM) absorption and black carbon (BC) adsorption models to calculate PCDD/F gas–particle partitioning. The model satisfactorily reproduced the particle bound fractions at all rural sites for which there were measured data and across the whole domain, the modeled vs. measured differences in particle bound fractions were less than 20% for nearly all congeners. The model predicted ambient air PCDD/F concentrations were also consistent with measurements. Simulated deposition fluxes were within 58% of direct measurements. PCDD/F atmospheric depositions to each of the Great Lakes were estimated for the year 2000. The results indicate that approximately 76% of the total deposition of PCDD/Fs to the Great Lakes (in W-TEQ, or toxic equivalent units as defined by the World Health Organization) is attributed to PCDD/Fs absorbed into OM in aerosol. For all of the lakes, more than 92% of all deposition is particle phase wet deposition and only 5–8% is particle phase dry deposition. Wet deposition from the gas phase is negligible. Of the 17 toxic PCDD/F congeners, the Cl_4–5DD/F compounds contribute approximately 70% to the total atmospheric deposition to the Great Lakes. The seasonal changes in the PCDD/F deposition flux track variations in ambient temperature.     

Refining fire emissions for air quality modeling with remotely sensed fire counts: A wildfire case study

This paper examines the use of Moderate Resolution Imaging Spectroradiometer (MODIS) observed active fire data (pixel counts) to refine the National Emissions Inventory (NEI) fire emission estimates for major wildfire events. This study was motivated by the extremely limited information available for many years of the United States Environmental Protection Agency (US EPA) NEI about the specific location and timing of major fire events. The MODIS fire data provide twice-daily snapshots of the locations and breadth of fires, which can be helpful for identifying major wildfires that typically persist for a minimum of several days. A major wildfire in Mallory Swamp, FL, is used here as a case study to test a reallocation approach for temporally and spatially distributing the state-level fire emissions based on the MODIS fire data. Community Multiscale Air Quality (CMAQ) model simulations using these reallocated emissions are then compared with another simulation based on the original NEI fire emissions. We compare total carbon (TC) predictions from these CMAQ simulations against observations from the Inter-agency Monitoring of Protected Visual Environments (IMPROVE) surface network. Comparisons at three IMPROVE sites demonstrate substantial improvements in the temporal variability and overall correlation for TC predictions when the MODIS fire data is used to refine the fire emission estimates. These results suggest that if limited information is available about the spatial and temporal extent of a major wildfire fire, remotely sensed fire data can be a useful surrogate for developing the fire emissions estimates for air quality modeling purposes.     

Preliminary evaluation of the Community Multiscale Air Quality model for 2002 over the Southeastern United States

The Visibility Improvement State and Tribal Association of the Southeast (VISTAS) is one of five Regional Planning Organizations that is charged with the management of haze, visibility, and other regional air quality issues in the United States. The VISTAS Phase I work effort modeled three episodes (January 2002, July 1999, and July 2001) to identify the optimal model configuration(s) to be used for the 2002 annual modeling in Phase II. Using model configurations recommended in the Phase I analysis, 2002 annual meteorological (Mesoscale Meterological Model [MM5]), emissions (Sparse Matrix Operator Kernal Emissions [SMOKE]), and air quality (Community Multiscale Air Quality [CMAQ]) simulations were performed on a 36-km grid covering the continental United States and a 12-km grid covering the Eastern United States. Model estimates were then compared against observations. This paper presents the results of the preliminary CMAQ model performance evaluation for the initial 2002 annual base case simulation. Model performance is presented for the Eastern United States using speciated fine particle concentration and wet deposition measurements from several monitoring networks. Initial results indicate fairly good performance for sulfate with fractional bias values generally within +/-20%. Nitrate is overestimated in the winter by approximately +50% and underestimated in the summer by more than -100%. Organic carbon exhibits a large summer underestimation bias of approximately -100% with much improved performance seen in the winter with a bias near zero. Performance for elemental carbon is reasonable with fractional bias values within +/- 40%. Other fine particulate (soil) and coarse particular matter exhibit large (80-150%) overestimation in the winter but improved performance in the summer. The preliminary 2002 CMAQ runs identified several areas of enhancements to improve model performance, including revised temporal allocation factors for ammonia emissions to improve nitrate performance and addressing missing processes in the secondary organic aerosol module to improve OC performance.