Future year ozone source attribution modeling studies for the eastern and western United States

Three modeling approaches, the U.S. Environmental Protection Agency’s (EPA) Community Multiscale Air Quality (CMAQ) zero-out, the Comprehensive Air quality Model with extensions (CAMx) zero-out, and the CAMx probing tools ozone source apportionment tool (OSAT), were used to project the contributions of various source categories to future year design values for summer 8-hr average ozone concentrations at selected U.S. monitors. The CMAQ and CAMx zero-out or brute-force approaches predicted generally similar contributions for most of the source categories, with some small differences. One of the important findings from this study was that both the CMAQ and CAMx zero-out approaches tended to apportion a larger contribution to the “other” category than the OSAT approach. For the OSAT approach, this category is the difference between the total emissions and the sum of the tracked emissions and consists of non-U.S. emissions. For the zero-out approach, it also includes the effects of nonlinearities in the system because the sum of the sensitivities of all sources is not necessarily equal to the sum of their contributions in a nonperturbed environment. The study illustrates the strengths and weaknesses of source apportionment approaches, such as OSAT, and source sensitivity approaches, such as zero-out. The OSAT approach is suitable for studying source contributions, whereas the zero-out approach is suitable for studying response to emission changes. Future year design values of summer 8-hr average ozone concentrations were projected to decrease at all the selected monitors for all the simulations in each city, except at the downtown Los Angeles monitor. Both the CMAQ and CAMx results showed all modeled locations project attainment in 2018 and 2030 to the current National Ambient Air Quality Standards (NAAQS) level of 75 ppb, except the selected Los Angeles monitor in 2018 and the selected San Bernardino monitor in 2018 and 2030.

Implications:This study illustrates the strengths and weaknesses of three modeling approaches, CMAQ zero-out, CAMx zero-out, and OSAT to project contributions of various source categories to future year design values for summer 8-hr average ozone concentrations at selected U.S. monitors. The OSAT approach is suitable for studying source contributions, whereas the zero-out approach is suitable for studying response to emission changes. Future year design values of summer 8-hr average ozone concentrations were projected to decrease, except at the downtown Los Angeles monitor. Comparing projections with the current NAAQS (75 ppb) show attainment everywhere, except two locations in 2018 and one location in 2030.     

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.     

Results of a Receptor Modeling Feasibility Study

This paper summarizes the results of an Electric Power Research Institute funded research effort to determine the feasibility of using receptor models for the apportionment of power plant contributions to air quality, deposition quality, and light extinction on local and regional scales. Sufficient information currently exists (or was developed during the course of this study) to establish feasibility for the apportionment of power plant contributions to local-scale air quality and to strongly suggest the usefulness of receptor modeling for regional-scale air quality, light extinction, and dry deposition quality apportionment. Insufficient information existed to determine whether or not receptor modeling can be useful for the allocation of wet deposition quality.

A series of seven future research recommendations were prepared for the purpose of advancing receptor modeling from theoretical feasibility to practical utility. Two recommendations address model evaluation: (1) prepare a user-oriented receptor model application and testing package, and (2) perform computer simulation testing of past, current, and proposed receptor model applications. Two recommendations address model development: (1) develop a receptor model requiring minimal information about source profiles, and (2) develop a “hybrid” model (i.e., a model that combines source and receptor oriented methods). Finally, three recommendations address source characterization: (1) develop procedures for individual particle characterization, (2) develop sampling and analysis methods for source profile determination, and (3) measure source profiles of coal- and oil-fired power plants, and other sources that confound identification of emissions from coal- and oilfired power plants.     

Seasonal and spatial variation of organic tracers for biomass burning in PM1 aerosols from highly insolated urban areas

PM₁ aerosol characterization on organic tracers for biomass burning (levoglucosan and its isomers and dehydroabietic acid) was conducted within the AERTRANS project. PM₁ filters (N?=?90) were sampled from 2010 to 2012 in busy streets in the urban centre of Madrid and Barcelona (Spain) at ground-level and at roof sites. In both urban areas, biomass burning was not expected to be an important local emission source, but regional emissions from wildfires, residential heating or biomass removal may influence the air quality in the cities. Although both areas are under influence of high solar radiation, Madrid is situated in the centre of the Iberian Peninsula, while Barcelona is located at the Mediterranean Coast and under influence of marine atmospheres. Two extraction methods were applied, i.e. Soxhlet and ASE, which showed equivalent results after GC-MS analyses. The ambient air concentrations of the organic tracers for biomass burning increased by an order of magnitude at both sites during winter compared to summer. An exception was observed during a PM event in summer 2012, when the atmosphere in Barcelona was directly affected by regional wildfire smoke and levels were four times higher as those observed in winter. Overall, there was little variation between the street and roof sites in both cities, suggesting that regional biomass burning sources influence the urban areas after atmospheric transport. Despite the different atmospheric characteristics in terms of air relative humidity, Madrid and Barcelona exhibit very similar composition and concentrations of biomass burning organic tracers. Nevertheless, levoglucosan and its isomers seem to be more suitable for source apportionment purposes than dehydroabietic acid. In both urban areas, biomass burning contributions to PM were generally low (2 %) in summer, except on the day when wildfire smoke arrive to the urban area. In the colder periods the contribution increase to around 30 %, indicating that regional biomass burning has a substantial influence on the urban air quality.     

Future year ozone source attribution modeling study using CMAQ-ISAM

ABSTRACT

To achieve the current United States National Ambient Air Quality Standards (NAAQS) attainment level for ozone or particulate matter, current photochemical air quality models include tools to determine source apportionment and/or source sensitivity. Previous studies by the authors have used the Ozone and Particulate Matter Source Apportionment Technology and Higher-order Decoupled Direct Method probing tools in CAMx to investigate these source-receptor relationships for ozone. The recently available source apportionment for CMAQ, referred to as the Integrated Source Apportionment Method (ISAM), was used in this study to conduct future year (2030) source attribution modeling. The CMAQ-ISAM ozone source attribution results for selected cities across the U.S. showed boundary conditions were the dominant contributor to the future year highest July maximum daily 8-hour average (MDA8) ozone concentrations. Point sources were generally larger contributors in the eastern U.S. than in the western U.S. The contributions of on-road mobile emissions were around 5 ppb at most of the cities selected for analysis. Off-road mobile source contributions were around 20 ppb or nearly 30%. Since boundary conditions play an important role in future year ozone levels, it is important to characterize future year boundary conditions accurately. The current implementation of ISAM in CMAQ 5.0.2 requires significant computing resources for ozone source attribution, making it difficult to conduct long-term simulations for large domains. The computing requirements for PM source attribution are even more onerous. CMAQ 5.2 was released after this study was completed, and does not include ISAM. If an efficient version of ISAM becomes available, it could be used in long-term ozone and PM2.5 studies. Implications: Ozone source attribution results provide useful information on important emission source contribution categories and provide some initial guidance on future emission reduction strategies. This study explains a new source apportionment technique, CMAQ-ISAM, and compares it to CAMx OSAT. The techniques have similar results: ozone’s highest source contributor is boundary conditions, followed by point sources, then off-road mobile sources. The current version of ISAM in CMAQ 5.0.2 requires significant computing resources for ozone source attribution, while the computing requirements for PM source attribution are even more onerous. CMAQ 5.2 was released after this study was completed, and does not include ISAM.     

Ft. McHenry tunnel study: Source profiles and mercury emissions from diesel and gasoline powered vehicles

During the fall of 1998, the US Environmental Protection Agency and the Florida Department of Environmental Protection sponsored a 7-day study at the Ft. McHenry tunnel in Baltimore, MD with the objective of obtaining PM_2.5 vehicle source profiles for use in atmospheric mercury source apportionment studies. PM_2.5 emission profiles from gasoline and diesel powered vehicles were developed from analysis of trace elements, polycyclic aromatic hydrocarbons (PAH), and condensed aliphatic hydrocarbons. PM_2.5 samples were collected using commercially available sampling systems and were extracted and analyzed using conventional well-established methods. Both inorganic and organic profiles were sufficiently unique to mathematically discriminate the contributions from each source type using a chemical mass balance source apportionment approach. However, only the organic source profiles provided unique PAH tracers (e.g., fluoranthene, pyrene, and chrysene) for diesel combustion that could be used to identify source contributions generated using multivariate statistical receptor modeling approaches. In addition, the study found significant emission of gaseous elemental mercury (Hg⁰), divalent reactive gaseous mercury (RGM), and particulate mercury (Hg(p)) from gasoline but not from diesel powered motor vehicles. Fuel analysis supported the tunnel measurement results showing that total mercury content in all grades of gasoline (284±108 ng L⁻¹) was substantially higher than total mercury content in diesel fuel (62±37 ng L⁻¹) collected contemporaneously at local Baltimore retailers.     

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.     

Source apportionment of particulate matter (PM2.5) in an urban area using dispersion,receptor and inverse modelling

Air pollution emission inventories are the basis for air quality assessment and management strategies. The quality of the inventories is of great importance since these data are essential for air pollution impact assessments using dispersion models. In this study, the quality of the emission inventory for fine particulates (PM_2.5) is assessed: first, using the calculated source contributions from a receptor model; second, using source apportionment from a dispersion model; and third, by applying a simple inverse modelling technique which utilises multiple linear regression of the dispersion model source contributions together with the observed PM_2.5 concentrations. For the receptor modelling the chemical composition of PM_2.5 filter samples from a measurement campaign performed between January 2004 and April 2005 are analysed. Positive matrix factorisation is applied as the receptor model to detect and quantify the various source contributions. For the same observational period and site, dispersion model calculations using the Air Quality Management system, AirQUIS, are performed. The results identify significant differences between the dispersion and receptor model source apportionment, particularly for wood burning and traffic induced suspension. For wood burning the receptor model calculations are lower, by a factor of 0.54, but for the traffic induced suspension they are higher, by a factor of 7.1. Inverse modelling, based on regression of the dispersion model source contributions and the PM_2.5 concentrations, indicates similar discrepancies in the emissions inventory. In order to assess if the differences found at the one site are generally applicable throughout Oslo, the individual source category emissions are rescaled according to the receptor modelling results. These adjusted PM_2.5 concentrations are compared with measurements at four independent stations to evaluate the updated inventory. Statistical analysis shows improvement in the estimated concentrations for PM_2.5 at all sites. Similarly, inverse modelling is applied at these independent sites and this confirms the validity of the receptor model results.     

Modeling air quality during the California Regional PM10/PM2.5 Air Quality Study (CPRAQS) using the UCD/CIT source-oriented air quality model – Part III. Regional source apportionment of secondary and total airborne particulate matter

A comprehensive air quality modeling project was carried out to simulate regional source contributions to secondary and total (=primary + secondary) airborne particle concentrations in California's Central Valley. A three-week stagnation episode lasting from December 15, 2000 to January 7, 2001, was chosen for study using the air quality and meteorological data collected during the California Regional PM₁₀/PM_2.5 Air Quality Study (CRPAQS). The UCD/CIT mechanistic air quality model was used with explicit decomposition of the gas phase reaction chemistry to track source contributions to secondary PM. Inert artificial tracers were used with an internal mixture representation to track source contributions to primary PM. Both primary and secondary source apportionment calculations were performed for 15 size fractions ranging from 0.01 to 10 μm particle diameters. Primary and secondary source contributions were resolved for fugitive dust, road dust, diesel engines, catalyst equipped gasoline engines, non-catalyst equipped gasoline engines, wood burning, food cooking, high sulfur fuel combustion, and other anthropogenic sources.Diesel engines were identified as the largest source of secondary nitrate in central California during the study episode, accounting for approximately 40% of the total PM_2.5 nitrate. Catalyst equipped gasoline engines were also significant, contributing approximately 20% of the total secondary PM_2.5 nitrate. Agricultural sources were the dominant source of secondary ammonium ion. Sharp gradients of PM concentrations were predicted around major urban areas. The relative source contributions to PM_2.5 from each source category in urban areas differ from those in rural areas, due to the dominance of primary OC in urban locations and secondary nitrate in the rural areas. The source contributions to ultra-fine particle mass PM_0.1 also show clear urban/rural differences. Wood smoke was found to be the major source of PM_0.1 in urban areas while motor vehicle sources were the major contributor of PM_0.1 in rural areas, reflecting the influence from two major highways that transect the Valley.     

Sensitivity analysis of source regions to PM2.5 concentration at Fukue Island,Japan

The authors analyze the sensitivities of source regions in East Asia to PM_2.5 (particulate matter with an aerodynamic diameter of ≤2.5 µm) concentration at Fukue Island located in the western part of Japan by using a regional chemical transport model with emission sensitivity simulations for the year 2010. The temporal variations in PM_2.5 concentration are generally reproduced, but the absolute concentration is underestimated by the model. Chemical composition of PM_2.5 in the model is compared with filter sampling data in spring; simulated sulfate, ammonium, and elemental carbon are consistent with observations, but mass concentration of particulate organic matters is underestimated. The relative contribution from each source region shows the seasonal variation, especially in summer. The contribution from central north China (105°E–124°E, 34°N–42°N) accounts for 50–60% of PM_2.5 at Fukue Island except in summer; it significantly decreases in summer (18%). Central south China (105°E–123°E, 26°N–34°N) has the relative contribution of 15–30%. The contribution from the Korean Peninsula is estimated at about 10% except in summer. The domestic contribution accounts for about 7% in spring and autumn and increases to 19% in summer. We also estimate the relative contribution to daily average concentration in high PM_2.5 days (>35 μg m^?3). Central north China has a significant contribution of 60–70% except in summer. The relative contribution from central south China is estimated at 46% in summer and about 30% in the other seasons. The contributions from central north and south China on high PM_2.5 days are generally larger than those of their seasonal mean contributions. The domestic contribution is smaller than the seasonal mean value in every season; it is less than 10% even in summer. These model results suggest that foreign anthropogenic sources have a substantial impact on attainment of the atmospheric environmental standard of Japan at Fukue Island.

Implications: The contribution from several source regions in East Asia to PM_2.5 concentration at Fukue Island, a remote island located in the western part of Japan and close to the Asian continent, is estimated using a three-dimensional chemical transport model. The model results suggest that PM_2.5 that is attributed to foreign anthropogenic sources have a larger contribution than that of domestic pollution and have a substantial impact on attainment of the atmospheric environmental standard of Japan at Fukue Island.     

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.     

Comparison between sample-species specific uncertainties and estimated uncertainties for the source apportionment of the speciation trends network data

In order to use the US Environmental Protection Agency's speciation trends networks (STN) data in source apportionment studies with positive matrix factorization (PMF), uncertainties for each of the measured data points are required. Since STN data were not accompanied by sample-species specific uncertainties (SSU) prior to July 2003, a comprehensive set of fractional uncertainties was estimated by Kim et al. [2005. Estimation of organic carbon blank values and error structures of the speciation trends network data for source apportionments. Journal of Air and Waste Management Association 55, 1190–1199]. The objective of this study is to compare the use of the estimated fractional uncertainties (EFU) for the source apportionment of PM_2.5 (particulate matter less than 2.5 μm in aerodynamic diameter) measured at the STN monitoring sites with the results obtained using SSU. Thus, the source apportionment of STN PM_2.5 data were performed and their contributions were estimated through the application of PMF for two selected STN sites, Elizabeth, NJ and Baltimore, MD with both SSU and EFU for the elements measured by X-ray fluorescence. The PMF resolved factor profiles and contributions using EFU were similar to those using SSU at both monitoring sites. The comparisons of normalized concentrations indicated that the STN SSU were not well estimated. This study supports the use of EFU for the STN samples to provide useful error structure for the source apportionment studies of the STN data.     

Reconciliation and interpretation of Big Bend National Park particulate sulfur source apportionment: results from the Big Bend Regional Aerosol and Visibility Observational Study--part I

The Big Bend Regional Aerosol and Visibility Observational (BRAVO) study was an intensive monitoring study from July through October 1999 followed by extensive assessments to determine the causes and sources of haze in Big Bend National Park, located in Southwestern Texas. Particulate sulfate compounds are the largest contributor of haze at Big Bend, and chemical transport models (CTMs) and receptor models were used to apportion the sulfate concentrations at Big Bend to North American source regions and the Carbón power plants, located 225 km southeast of Big Bend in Mexico. Initial source attribution methods had contributions that varied by a factor of > or =2. The evaluation and comparison of methods identified opposing biases between the CTMs and receptor models, indicating that the ensemble of results bounds the true source attribution results. The reconciliation of these differences led to the development of a hybrid receptor model merging the CTM results and air quality data, which allowed a nearly daily source apportionment of the sulfate at Big Bend during the BRAVO study. The best estimates from the reconciliation process resulted in sulfur dioxide (SO2) emissions from U.S. and Mexican sources contributing approximately 55% and 38%, respectively, of sulfate at Big Bend. The distribution among U.S. source regions was Texas, 16%; the Eastern United States, 30%; and the Western United States, 9%. The Carbón facilities contributed 19%, making them the largest single contributing facility. Sources in Mexico contributed to the sulfate at Big Bend on most days, whereas contributions from Texas and Eastern U.S. sources were episodic, with their largest contributions during Big Bend sulfate episodes. On the 20% of the days with the highest sulfate concentrations, U.S. and Mexican sources contributed approximately 71% and 26% of the sulfate, respectively. However, on the 20% of days with the lowest sulfate concentrations, Mexico contributed 48% compared with 40% for the United States.     

Evaluations of the chemical mass balance method for determining contributions of gasoline and diesel exhaust to ambient carbonaceous aerosols

The US. Department of Energy Gasoline/Diesel PM Split Study was conducted to assess the sources of uncertainties in using an organic compound-based chemical mass balance receptor model to quantify the relative contributions of emissions from gasoline (or spark ignition [SI]) and diesel (or compression ignition [CI]) engines to ambient concentrations of fine particulate matter (PM2.5) in California's South Coast Air Basin (SOCAB). In this study, several groups worked cooperatively on source and ambient sample collection and quality assurance aspects of the study but worked independently to perform chemical analysis and source apportionment. Ambient sampling included daily 24-hr PM2.5 samples at two air quality-monitoring stations, several regional urban locations, and along freeway routes and surface streets with varying proportions of automobile and truck traffic. Diesel exhaust was the dominant source of total carbon (TC) and elemental carbon (EC) at the Azusa and downtown Los Angeles, CA, monitoring sites, but samples from the central part of the air basin showed nearly equal apportionments of CI and SI. CI apportionments to TC were mainly dependent on EC, which was sensitive to the analytical method used. Weekday contributions of CI exhaust were higher for Interagency Monitoring of Protected Visual Environments (IMPROVE; 41+/-3.7%) than Speciation Trends Network (32+/-2.4%). EC had little effect on SI apportionment. SI apportionments were most sensitive to higher molecular weight polycyclic aromatic hydrocarbons (indeno[123-cd]pyrene, benzo(ghi)perylene, and coronene) and several steranes and hopanes, which were associated mainly with high emitters. Apportionments were also sensitive to choice of source profiles. CI contributions varied from 30% to 60% of TC when using individual source profiles rather than the composites used in the final apportionments. The apportionment of SI vehicles varied from 1% to 12% of TC depending on the specific profile that was used. Up to 70% of organic carbon (OC) in the ambient samples collected at the two fixed monitoring sites could not be apportioned to directly emitted PM emissions.     

Application of an integrated Weather Research and Forecasting (WRF)/CALPUFF modeling tool for source apportionment of atmospheric pollutants for air quality management: A case study in the urban area of Benxi,China

In this study, the authors endeavored to develop an effective framework for improving local urban air quality on meso-micro scales in cities in China that are experiencing rapid urbanization. Within this framework, the integrated Weather Research and Forecasting (WRF)/CALPUFF modeling system was applied to simulate the concentration distributions of typical pollutants (particulate matter with an aerodynamic diameter <10 μm [PM₁₀], sulfur dioxide [SO₂], and nitrogen oxides [NO_x]) in the urban area of Benxi. Statistical analyses were performed to verify the credibility of this simulation, including the meteorological fields and concentration fields. The sources were then categorized using two different classification methods (the district-based and type-based methods), and the contributions to the pollutant concentrations from each source category were computed to provide a basis for appropriate control measures. The statistical indexes showed that CALMET had sufficient ability to predict the meteorological conditions, such as the wind fields and temperatures, which provided meteorological data for the subsequent CALPUFF run. The simulated concentrations from CALPUFF showed considerable agreement with the observed values but were generally underestimated. The spatial-temporal concentration pattern revealed that the maximum concentrations tended to appear in the urban centers and during the winter. In terms of their contributions to pollutant concentrations, the districts of Xihu, Pingshan, and Mingshan all affected the urban air quality to different degrees. According to the type-based classification, which categorized the pollution sources as belonging to the Bengang Group, large point sources, small point sources, and area sources, the source apportionment showed that the Bengang Group, the large point sources, and the area sources had considerable impacts on urban air quality. Finally, combined with the industrial characteristics, detailed control measures were proposed with which local policy makers could improve the urban air quality in Benxi. In summary, the results of this study showed that this framework has credibility for effectively improving urban air quality, based on the source apportionment of atmospheric pollutants.

Implications: The authors endeavored to build up an effective framework based on the integrated WRF/CALPUFF to improve the air quality in many cities on meso-micro scales in China. Via this framework, the integrated modeling tool is accurately used to study the characteristics of meteorological fields, concentration fields, and source apportionments of pollutants in target area. The impacts of classified sources on air quality together with the industrial characteristics can provide more effective control measures for improving air quality.

Through the case study, the technical framework developed in this study, particularly the source apportionment, could provide important data and technical support for policy makers to assess air pollution on the scale of a city in China or even the world.     

Particulate matter source apportionment in a village situated in industrial region of Central Europe

The bilinear receptor model positive matrix factorization (PMF) was used to apportion particulate matter with an aerodynamic diameter of 1–10 μm (PM_1–10) sources in a village, B?ezno, situated in an industrial region of northern Bohemia in Central Europe. The receptor model analyzed the data sets of 90- and 60-min integrations of PM_1–10 mass concentrations and elemental composition for 27 elements. The 14-day sampling campaigns were conducted in the village in summer 2008 and winter 2010. Also, to ensure seasonal and regional representativeness of the data sets recorded in the village, the spatial-temporal variability of the 24-hr PM₁₀ and PM_1–10 within 2008–2010 in winter and summer across the multiple sites was evaluated. There were statistically significant interseasonal differences of the 24-hr PM data, but not intrasummer or intrawinter differences of the 24-hr PM_1–10 data across the multiple sites. PMF resolved seven sources of PM_1–10. They were high-temperature coal combustion; combustion in local heating boilers; marine aerosol; mineral dust; primary biological/wood burning; road dust, car brakes; and gypsum. The main summer factors were assigned to mineral dust (38.2%) and primary biological/wood burning (33.1%). In winter, combustion factors dominated (80%) contribution to PM_1–10. The conditional probability function (CPF) helped to identified local sources of PM_1–10. The source of marine aerosol from the North Sea and English Channel was indicated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT).

Implications: This is the first application of PMF to highly time/size resolved PM data in Czech Republic. The coarse aerosol fraction, PM_1–10, was chosen with regard to industrial character of the region, sampling site near the coal strip mine and coal power stations. Contrary to expectation, source apportionment did not show dominance of emissions from the coal strip mine. The results will enable local authorities and state bodies responsible for air quality assessment to focus on sources most responsible for air pollution in this industrial region.

Supplemental Materials:?Supplemental materials are available for this paper. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for (1) details of measurement campaigns; (2) CPF for each of the sources contributing to PM_1–10; (3) factors contribution to PM_1–10 resolved by PMF; (4) diurnal pattern of road dust, car brake factor in summer and winter; (5) trajectories during the marine aerosol episode in winter 2010; and (6) temporal temperature, concentration, and wind speed relationships during the summer 2008 campaign and winter 2010 campaign.     

Wintertime and summertime São Paulo aerosol source apportionment study

A detailed aerosol source apportionment study was performed with two sampling campaigns, during wintertime and summertime in the heavily polluted metropolitan area of São Paulo, Brazil. In addition to 12 h fine and coarse mode filter sampling, several real time aerosol and trace gas monitors were used. PM₁₀ was sampled using stacked filter units that collects fine (d<2.5 μm) and coarse (2.5<d<10 μm) particulate matter, providing mass, black carbon (BC) and elemental concentration for each aerosol mode. The concentration of about 20 elements was determined using the particle induce X-ray emission technique. Real time aerosol monitors provided PM₁₀ aerosol mass (TEOM), organic and elemental carbon (Carbon Monitor 5400, R&P) and BC concentration (Aethalometer). A complex system of sources and meteorological conditions modulates the heavy air pollution of the urban area of São Paulo. The boundary layer height and the primary emissions by motor vehicles controls the strong pattern of diurnal cycles obtained for PM₁₀, BC, CO, NO_x, and SO₂. Absolute principal factor analysis results showed a very similar source pattern between winter and summer field campaigns, despite the different locations of the sampling sites of both campaigns, pointing that there are no significant change in the main air pollution sources. The source identified as motor vehicle represented 28% and 24% of the PM_2.5 for winter and summer, respectively. Resuspended soil dust accounted for 25% and 30%. The oil combustion source represented 18% and 21%. Sulfates accounts for 23% and 17% and finally industrial emissions contributed with 5% and 6% of PM_2.5, for winter and summer, respectively. The resuspended soil dust accounted for a large fraction (75–78%) of the coarse mode aerosol mass. Certainly automobile traffic and soil dust are the main air pollution sources in São Paulo. The sampling and analytical procedures applied in this study showed that it is possible to perform a quantitative aerosol source apportionment in a complex urban area such as São Paulo.     

Impact of emissions from natural gas production facilities on ambient air quality in the Barnett Shale area: A pilot study

Rapid and extensive development of shale gas resources in the Barnett Shale region of Texas in recent years has created concerns about potential environmental impacts on water and air quality. The purpose of this study was to provide a better understanding of the potential contributions of emissions from gas production operations to population exposure to air toxics in the Barnett Shale region. This goal was approached using a combination of chemical characterization of the volatile organic compound (VOC) emissions from active wells, saturation monitoring for gaseous and particulate pollutants in a residential community located near active gas/oil extraction and processing facilities, source apportionment of VOCs measured in the community using the Chemical Mass Balance (CMB) receptor model, and direct measurements of the pollutant gradient downwind of a gas well with high VOC emissions. Overall, the study results indicate that air quality impacts due to individual gas wells and compressor stations are not likely to be discernible beyond a distance of approximately 100 m in the downwind direction. However, source apportionment results indicate a significant contribution to regional VOCs from gas production sources, particularly for lower-molecular-weight alkanes (<C6). Although measured ambient VOC concentrations were well below health-based safe exposure levels, the existence of urban-level mean concentrations of benzene and other mobile source air toxics combined with soot to total carbon ratios that were high for an area with little residential or commercial development may be indicative of the impact of increased heavy-duty vehicle traffic related to gas production

ImplicationsRapid and extensive development of shale gas resources in recent years has created concerns about potential environmental impacts on water and air quality. This study focused on directly measuring the ambient air pollutant levels occurring at residential properties located near natural gas extraction and processing facilities, and estimating the relative contributions from gas production and motor vehicle emissions to ambient VOC concentrations. Although only a small-scale case study, the results may be useful for guidance in planning future ambient air quality studies and human exposure estimates in areas of intensive shale gas production.     

Estimating uncertainties and uncertainty contributors of CMB PM2.5 source apportionment results

The chemical mass balance (CMB) model was applied for source apportionment of PM_2.5 in Atlanta in order to explore levels and causes of uncertainties in source contributions. Monte Carlo analysis with Latin hypercube sampling (MC-LHS) was performed to evaluate the source impact uncertainties and quantify how uncertainties in ambient measurement and source profile data affect results. In general, uncertainties in the source profile data contribute more to the final uncertainties in source apportionment results than do those in ambient measurement data. Uncertainty contribution estimates suggest that non-linear interactions among source profiles also affect the final uncertainties although their influence is typically less than uncertainties in source profile data.     

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.