On-road Mobile Emissions Research Articles

Integrated assessment of inhalation health risk and economic benefit of improving ambient targeted VOCs in Petrochemical industrial area

AbstractThe Maptaphut industrial area, one of the largest petrochemical complexes in Thailand, is the major cause of the various air pollutants. The larger concern is that a significant volume of air pollution is emitted and that air quality management needs to be improved. This is in part due to a lack of deeper understanding of how anthropogenic emissions are emitted from different sources in this area— especially volatile organic compounds (VOCs). Moreover, it has complicated relationship results of air pollution, disease mechanisms, and health effects. As a result, its available data can only give a rough indication of them. These factors are often assumed to be associated with economic consequences, but assessing the health-related economic losses caused by air pollution remains limited in many ways.Four targeted VOCs were analyzed, including benzene, 1,3-butadiene, 1,2-dichloroethane, and vinyl chloride from industrial and non-industrial sources, namely stacks, flares, storage tanks, wastewater treatment plants, transportation and marketing, fugitive losses, slurry/open equipment/vessel, and on-road mobile emissions. Source apportionment can be conducted using emissions inventory (EI) to establish pollution source databases, the dispersion model, and then imported on the risk model by determining receptors. The AERMOD dispersion model coupled with the IRAP-h view model was used to predict the spatial distribution of the ground-level concentration and analyze the inhalation health risk covering cancer and non-cancer risks— as well as the prioritization of pollutants.The risk assessment results indicated that the highest risk occurred most from 1,3-butadiene for cancer and chronic non-cancer risks contributed to fugitive sources, about 83% and 94%, and most benzenes for acute non-cancer risk contributed to on-road mobile sources, at about 56%.Consequently, the benzene classified as the most important priority depending on its risk results, comprehensive epidemiological studies, and discharge volumes.With the economic benefits assessment, BenMAP-CE was further utilized to estimate the health impacts and economic value of multiple scenarios to facilitate decision-making for benzene reduction. Overall, the 10% rollback policy for benzene concentration, monetized value of about 13.13 billion US dollars for all mortalities, gave the best practical scenario for the most economically viable option based on the B/C (benefit/cost) ratio results in Maptaphut. Ultimately, policymakers need to take additional measures to improve air quality and reduce health impacts while also considering economic benefits, especially benzene reduction.

Estimation of on-road mobile emissions based on the vehicle technology in a high-traffic avenue in Panama City, Panama

This study addresses the emissions from mobile sources in a busy avenue. Latest mobile emission inventories estimated pollutants based on fuel sales activities in the country. While this is an approved methodology, it does not consider the characteristics of vehicles and their emissions control systems. Applying the International Vehicle Emissions (IVE) model involves low costs, the vehicle fleet’s technology features, and the study region’s environmental parameters. The IVE model allows a better understanding of how vehicle technology impacts air quality. This study aims to generate information about vehicle emissions in Panama using a model that considers factors like vehicle technology, driving patterns, and local conditions, all of which influence air pollution in the region. The focuses are on passenger vehicles, the most common in the country, particularly in one of the densest districts. Carbon monoxide (CO), sulfates (SOx), nitrogen oxide (NO, and particulate matter (PMx) emissions were estimated with the IVE model, the first one stood out, represented 98% (6479.82 g/km) of the air pollutants emitted into the atmosphere by these four gases. Finally, it is established that the combination of emission control technologies and vehicle features is what will determine its emission reduction efficiency. Only in diesel vehicles, an increase in PMx emissions was identified.

Dynamic Meteorology-induced Emissions Coupler (MetEmis) development in the Community Multiscale Air Quality (CMAQ): CMAQ-MetEmis

Abstract. There have been consistent efforts to improve the spatiotemporal representations of biogenic/anthropogenic emission sources for photochemical transport modeling for better accuracy of local/regional air quality forecasts. While biogenic emissions, bi-directional NH3 from fertilizer applications, and point source plume rise are dynamically coupled in the Community Multiscale Air Quality (CMAQ) “inline”, there are still known meteorology-induced emissions sectors (e.g., on-road mobile sources, residential heating, and livestock waste), with little or no accounting for the meteorological impacts in the currently operational chemical and aerosol forecasts, but they are represented with static, not weather-aware annual or monthly county total emissions and standard monthly, weekly, or daily temporal allocation profiles to disaggregate them on finer timescales for the hourly air quality forecasts. It often results in poor forecasting performance due to the poor spatiotemporal representations of precursor pollutants during high ozone and PM2.5 episodes. The main focus of this study is to develop a dynamic inline coupler within the CMAQ system for the on-road mobile emission sector that requires significant computational resources in the current modeling application. To improve their accuracy and spatiotemporal representations, we developed the inline coupler module called CMAQ-MetEmis (for meteorology-induced emission sources within CMAQ version 5.3.2 modeling system). It can dynamically estimate meteorology-induced hourly gridded on-road mobile emissions within the CMAQ, using simulated meteorology without any computational burden to the CMAQ modeling system. To understand the impacts of meteorology-driven on-road mobile emissions on local air quality, the CMAQ is applied over the continental U.S. for 2 months (January and July 2019) for two emissions scenarios, namely (a) “static” on-road vehicle emissions based on static temporal profiles and (b) inline CMAQ-MetEmis on-road vehicle emissions. Overall, the CMAQ-MetEmis coupler allows us to dynamically simulate on-road vehicle emissions from the MOtor Vehicle Emission Simulator (MOVES) on-road emission model for CMAQ, with a better spatiotemporal representation based on the simulated meteorology inputs when compared to the static scenario. The domain total of daily volatile organic compound (VOC) emissions from the inline scenario shows that the largest impacts are from the local meteorology, which is approximately 10 % lower than the ones from the static scenario. In particular, the major difference in the VOC estimates was shown over the California region. These local meteorology impacts on the on-road vehicle emissions via CMAQ-MetEmis revealed an improvement in the hourly NO2, daily maximum ozone, and daily average PM2.5 patterns, with a higher agreement and correlation with daily ground observations.

Methodology for Mobile Toxics Deterministic Human Health Risk Assessment and Case Study

Air toxic emissions from on-road mobile sources are significant contributors to the degradation of air quality in urban and dense population centers. Research led by the United States Environmental Protection Agency (EPA) identified more than 1162 hazardous air pollutants (HAPs) in the exhaust and evaporative emissions from on-road mobile sources. However, less than 70 hazardous air pollutants are monitored by regulatory agencies. HAPs emitted from Mobile Sources are known as Mobile Source Air Toxics (MSATs). The EPA estimates that approximately half of the cancer risk and 74% of noncancer health impacts from air toxics is attributed to mobile sources. The quantification of the risk associated with MSATs exposure remains limited to date, and only a few MSATs have ambient air quality standards to protect human health and welfare. This work presents a novel and validated methodology to quantify the myriad health risks associated with exposure to on-road mobile emissions. This methodology is introduced in the form of a pipelined analysis process, which may be employed in existing and new transportation projects. The proposed new methodology integrates results from three different types of models: on-road vehicle emissions inventory models such as MOVES and IVE, air dispersion models such as AERMOD and SCIPUFF, and risk estimate models for human and ecological receptors such as the 2005 Final U.S. EPA Human Health Risk Assessment Protocol for Hazardous Waste Combustion Facilities. The result of this research work is a new methodology that provides regulators and risk analysts with a more detailed awareness of the health impacts of MSATs. A case study of Saint Paul, Minnesota, validated the air dispersion modeled results against monitored data, and the agreement was acceptable (i.e., the estimates were within a factor of two of the observations). Three high-population locations in the Saint Paul area were evaluated for human health risk, with the observation that at two of these locations, the Saint Paul—Ramsey Health Center and Anderson Office Building, the calculated cancer risk is in excess of the target risk level of 1.0E-05 for benzo(a)pyrene. The methodology presented in this paper allows regulators, risk analysts, and air quality engineers to better estimate multi-pathway cancer and noncancer risk associated with acute and chronic exposure to MSATs. Moreover, this work provides a science-based aid to policy decision makers when considering factors that most significantly affect population health and ecology.

Anthropogenic Secondary Organic Aerosol and Ozone Production from Asphalt-Related Emissions.

Liquid asphalt is a petroleum-derived substance commonly used in construction activities. Recent work has identified lower volatility, reactive organic carbon from asphalt as an overlooked source of secondary organic aerosol (SOA) precursor emissions. Here, we leverage potential emission estimates and usage data to construct a bottom-up inventory of asphalt-related emissions in the United States. In 2018, we estimate that hot-mix, warm-mix, emulsified, cutback, and roofing asphalt generated ~380 Gg (317 Gg - 447 Gg) of organic compound emissions. The impacts of these emissions on anthropogenic SOA and ozone throughout the contiguous United States are estimated using photochemical modeling. In several major cities, asphalt-related emissions can increase modeled summertime SOA, on average, by 0.1 - 0.2 μg m-3 (2-4% of SOA) and may reach up to 0.5 μg m-3 at noontime on select days. The influence of asphalt-related emissions on modeled ozone are generally small (~0.1 ppb). We estimate that asphalt paving-related emissions are half of what they were nearly 50 years ago, largely due to the concerted efforts to reduce emissions from cutback asphalts. If on-road mobile emissions continue their multidecadal decline, contributions of urban SOA from evaporative and non-road mobile sources will continue to grow in relative importance.

Emission inventory of semi-volatile and intermediate-volatility organic compounds and their effects on secondary organic aerosol over the Pearl River Delta region

Abstract. Semi-volatile and intermediate-volatility organic compounds (S–IVOCs) are considered critical precursors of secondary organic aerosol (SOA), which is an important component of fine particulate matter (PM2.5). However, knowledge of the contributions of S–IVOCs to SOA is still lacking in the Pearl River Delta (PRD) region, southern China. Therefore, in this study, an emission inventory of S–IVOCs in the PRD region was developed for the first time for the year 2010. The S–IVOC emissions were calculated based on a parameterization method involving the emission factors of POA (primary organic aerosol), emission ratios of S–IVOCs to POA, and domestic activity data. The total emissions of S–IVOCs were estimated to be 323.4 Gg, with major emissions from central cities in the PRD, i.e., Guangzhou, Foshan, and Shenzhen. On-road mobile sources and industries were the two major contributors of S–IVOC emissions, with contributions of ∼42 % and ∼35 %, respectively. Furthermore, uncertainties of the emission inventory were evaluated through Monte Carlo simulation. The uncertainties ranged from −79 % to 229 %, which could be mainly attributed to mass fractions of OC (organic carbon) to PM2.5 from on-road mobile emissions and emission ratios of IVOCs ∕ POA. The developed S–IVOC emission inventory was further incorporated into the Weather Research and Forecasting with Chemistry (WRF-Chem) model with a volatility basis-set (VBS) approach to improve the performance of SOA simulation and to evaluate the influence of S–IVOCs on SOA formation at a receptor site (Wan Qing Sha (WQS) site) in the PRD. The following results could be obtained. (1) The model could resolve about 34 % on average of observed SOA concentrations at WQS after considering the emissions of S–IVOCs, and 18 %–77 % with the uncertainties of the S–IVOC emission inventory considered. (2) The simulated SOA over the PRD region was increased by 161 % with the input of S–IVOC emissions, and it could be decreased to 126 % after the reaction coefficient of S–IVOCs with OH radical was improved. (3) Among all anthropogenic sources of S–IVOCs, industrial emission was the most significant contributor of S–IVOCs for SOA formation, followed by on-road mobile, dust, biomass burning, residential, and off-road mobile emissions. Overall, this study firstly quantified emissions of S–IVOCs and evaluated their roles in SOA formation over the PRD, which contributes towards significantly improving SOA simulation and better understanding of SOA formation mechanisms in the PRD and other regions in China.

Source apportionment of VOCs and their impact on air quality and health in the megacity of Seoul

The source apportionment of volatile organic compounds (VOCs) was examined using receptor models (positive matrix factorization and chemical mass balance) and a chemical transport model (CTM). The receptor model-based analysis was performed using the datasets collected from four different sites from the megacity of Seoul during the years 2013–2015. The contributions of VOC emission sources to ozone (O3) and PM2.5 concentrations and the subsequent health effects in the study area were also assessed during a photochemically active period (June 2015) using a three-dimensional CTM, Community Multi-scale Air Quality (CMAQ), and the Environmental Benefits Mapping and Analysis Program (BenMAP). The solvent use and the on-road mobile emission sources were found to exert dominant controls on the VOC levels observed in the target city. VOCs transported from regions outside of Seoul accounted for a significant proportion (up to approximately 35%) of ambient VOC levels during the study period. The solvent use accounted for 3.4% of the ambient O3 concentrations during the day (daily mean of 2.6%) and made insignificant contributions to PM2.5 (<1%) during the simulation period. Biogenic VOC made insignificant contributions to O3 (<1%) and a small contribution to PM2.5 during the day (5.6% with a daily mean of 2.4%). The number of premature deaths attributed indirectly (O3 and PM2.5 formations via the oxidation of VOCs) to solvent use is expected to be significant.

A Dynamic Dust Emission Allocation Method and Holiday Profiles Applied to Emission Processing for Improving Air Quality Model Performance

ABSTRACT An accurate depiction of temporal and spatial variations in emissions is critical in simulating air quality with atmospheric chemical transport models. Most emission processing systems typically use prescribed profiles to allocate anthropogenic emissions based on the assumptions that the temporal variance is periodical and spatial variance is time-independent. However, these assumptions are not applicable to emission sources heavily influenced by meteorology and holiday activity. In this study, we improved the temporal and spatial allocation of anthropogenic emissions by, first of all, developing a dynamic allocation method for fugitive dust that uses the negative correlation between dust emissions and precipitation, based on hourly rainfall data generated by the Weather Research and Forecasting model. Second, we employed holiday-specific profiles that were established using continuous emission monitoring system and traffic flow monitoring data to allocate power plant and on-road mobile emissions during the Spring Festival period, when human activity differs considerably from that of non-holiday periods. The new dynamic allocation method and holiday-specific profiles were applied to emissions in the Pearl River Delta region as a demonstration. Validated using a chemical transport model, this method obviously improved the model performance for periods with rainfall, with the normalized mean bias (NMB) decreasing by 6.27% for PM10 (particulate matter with a diameter of ≤ 10 µm) and 4.33% for PM2.5 (particulate matter with a diameter of ≤ 2.5 µm). The holiday simulations revealed that the holiday-specific profiles mitigated overestimations of NO2, SO2, and PM10 for the Spring Festival period, with the NMBs decreasing by 37.95%, 18.56%, and 20.83%, respectively. Hence, refining the allocation of emissions improved model simulation and air quality forecasting.

Future year ozone source attribution modeling study using CMAQ-ISAM

ABSTRACTTo 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.

Future-year ozone prediction for the United States using updated models and inputs

ABSTRACTThe relationship between emission reductions and changes in ozone can be studied using photochemical grid models. These models are updated with new information as it becomes available. The primary objective of this study was to update the previous Collet et al. studies by using the most up-to-date (at the time the study was done) modeling emission tools, inventories, and meteorology available to conduct ozone source attribution and sensitivity studies. Results show future-year, 2030, design values for 8-hr ozone concentrations were lower than base-year values, 2011. The ozone source attribution results for selected cities showed that boundary conditions were the dominant contributors to ozone concentrations at the western U.S. locations, and were important for many of the eastern U.S. locations. Point sources were generally more important in the eastern United States than in the western United States. The contributions of on-road mobile emissions were less than 5 ppb at a majority of the cities selected for analysis. The higher-order decoupled direct method (HDDM) results showed that in most of the locations selected for analysis, NOx emission reductions were more effective than VOC emission reductions in reducing ozone levels. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies.Implications: The relationship between emission reductions and changes in ozone can be studied using photochemical grid models, which are updated with new available information. This study was to update the previous Collet et al. studies by using the most current, at the time the study was done, models and inventory to conduct ozone source attribution and sensitivity studies. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies.

The Contribution of on-Road Mobile Emissions to Public Health Impacts from Ambient Fine Particulate Matter in New York City

The Contribution of on-Road Mobile Emissions to Public Health Impacts from Ambient Fine Particulate Matter in New York City

Premature deaths attributed to source-specific BC emissions in six urban US regions

Recent studies have shown that exposure to particulate black carbon (BC) has significant adverse health effects and may be more detrimental to human health than exposure to PM2.5 as a whole. Mobile source BC emission controls, mostly on diesel-burning vehicles, have successfully decreased mobile source BC emissions to less than half of what they were 30 years ago. Quantification of the benefits of previous emissions controls conveys the value of these regulatory actions and provides a method by which future control alternatives could be evaluated. In this study we use the adjoint of the Community Multiscale Air Quality (CMAQ) model to estimate highly-resolved spatial distributions of benefits related to emission reductions for six urban regions within the continental US. Emissions from outside each of the six chosen regions account for between 7% and 27% of the premature deaths attributed to exposure to BC within the region. While we estimate that nonroad mobile and onroad diesel emissions account for the largest number of premature deaths attributable to exposure to BC, onroad gasoline is shown to have more than double the benefit per unit emission relative to that of nonroad mobile and onroad diesel. Within the region encompassing New York City and Philadelphia, reductions in emissions from large industrial combustion sources that are not classified as EGUs (i.e., non-EGU) are estimated to have up to triple the benefits per unit emission relative to reductions to onroad diesel sectors, and provide similar benefits per unit emission to that of onroad gasoline emissions in the region. While onroad mobile emissions have been decreasing in the past 30 years and a majority of vehicle emission controls that regulate PM focus on diesel emissions, our analysis shows the most efficient target for stricter controls is actually onroad gasoline emissions.

Household-level disparities in cancer risks from vehicular air pollution in Miami

Environmental justice (EJ) research has relied on ecological analyses of socio-demographic data from areal units to determine if particular populations are disproportionately burdened by toxic risks. This article advances quantitative EJ research by (a) examining whether statistical associations found for geographic units translate to relationships at the household level; (b) testing alternative explanations for distributional injustices never before investigated; and (c) applying a novel statistical technique appropriate for geographically-clustered data. Our study makes these advances by using generalized estimating equations to examine distributive environmental inequities in the Miami (Florida) metropolitan area, based on primary household-level survey data and census block-level cancer risk estimates of hazardous air pollutant (HAP) exposure from on-road mobile emission sources. In addition to modeling determinants of on-road HAP cancer risk among all survey participants, two subgroup models are estimated to examine whether determinants of risk differ based on disadvantaged minority (Hispanic and non-Hispanic Black) versus non-Hispanic white racial/ethnic status. Results reveal multiple determinants of risk exposure disparities. In the model including all survey participants, renter-occupancy, Hispanic and non-Hispanic black race/ethnicity, the desire to live close to work/urban services or public transportation, and higher risk perception are associated with greater on-road HAP cancer risk; the desire to live in an amenity-rich environment is associated with less risk. Divergent subgroup model results shed light on the previously unexamined role of racial/ethnic status in shaping determinants of risk exposures. While lower socioeconomic status and higher risk perception predict significantly greater on-road HAP cancer risk among disadvantaged minorities, the desire to live near work/urban services or public transport predict significantly greater risk among non-Hispanic whites. Findings have important implications for EJ research and practice in Miami and elsewhere.

High Emitter Light Duty Vehicle Contributions to On-road Mobile Emissions in 2018 and 2030

Quantifying the proportion of normal- and high-emitting vehicles and their emissions is vital for creating an air quality improvement strategy for emission reduction policies. This paper includes the California LEV III and United States Environmental Protection Agency Tier 3 vehicle regulations in this projection of high emitter quantification for 2018 and 2030. Results show high emitting vehicles account for up to 6% of vehicle population and vehicle miles traveled. Yet, they will contribute to over 75% of exhaust and 66% of evaporative emissions. As these high emitting vehicles are gradually retired from service and are removed from the roads, the overall effect on air quality from vehicle emissions will be reduced.

Emissions reduction policies and recent trends in Southern California’s ambient air quality

To assess accountability and effectiveness of air regulatory policies, we reviewed more than 20 years of monitoring data, emissions estimates, and regulatory policies across several southern California communities participating in a long-term study of children’s health. Between 1994 and 2011, air quality improved for NO2 and PM2.5 in virtually all the monitored communities. Average NO2 declined 28% to 53%, and PM2.5 decreased 13% to 54%. Year-to-year PM2.5 variability at lower pollution sites was large compared to changes in long-term trends. PM10 and O3 decreases were largest in communities that were initially among the most polluted. Trends in annual average NO2, PM2.5, and PM10 concentrations in higher pollution communities were generally consistent with NOx, ROG, SOx, PM2.5, and PM10 emissions decreases. Reductions observed at one of the higher PM2.5 sites, Mira Loma, were generally within the range expected from reductions observed in ROG, NOx, SOx, and PM2.5 emissions. Despite a 38% increase in regional motor vehicle activity, vigorous economic growth, and a 30% population increase, total estimated emissions of NOx, ROG, SOx, PM2.5, and PM10 decreased by 54%, 65%, 40%, 21%, and 15%, respectively, during the 20-year time period. Emission control strategies in California have achieved dramatic reductions in ambient NO2, O3, PM2.5, and PM10. However, additional reductions will still be needed to achieve current health-based clean air standards.Implications: For many cities facing the challenge of reducing air pollution to meet health-based standards, the emission control policies and pollution reduction programs adopted in southern California should serve as an example of the potential success of aggressive, comprehensive, and integrated approaches. Policies targeting on-road mobile emissions were the single most important element for observed improvements in the Los Angeles region. However, overall program success was the result of a much broader approach designed to achieve emission reductions across all major pollutants and emissions categories.

Influence of an enhanced traffic volume around beaches in the short period of summer on ozone

The impact of pollutant emissions by the significant amount of road traffic around beaches on the ozone (O3) concentrations in the surrounding regions were evaluated using a numerical modeling approach during 6 days (29 July through 3 August) of the beach opening period (BOP) in 2010. On-road mobile emissions at several roads close to beaches in Busan, Korea during the study period were estimated from the emission factors, vehicle kilometers traveled, and deterioration factors. The emission data was then applied to the 3-D chemical transport model. A process analysis (PA) was also used to assess the contributions of the individual physical and chemical processes to the production or loss of O3 in the study area. The model study suggested the possibility that road traffic emissions near the beach area can have a significant impact on the O3 concentrations in the source regions as well as their surrounding/downwind regions. The maximum negative impact of mobile emissions on the O3 concentrations was predicted near the beach areas: by −9 ppb during the day due to both the high NOx emissions with the high NOx/VOC ratio and meteorological conditions and −9 ppb at night due to the fast titration of O3 by NO. The PA showed that the contribution of chemical process to the decrease in O3 concentrations (up to −5.5 ppb h−1) due to mobile emissions near the beach areas was the most dominant compared to the other physical processes.

NO2 and SO2dispersion modeling and relative roles of emission sources over Map Ta Phut industrial area, Thailand

Map Ta Phut industrial area (MA) is the largest industrial complex in Thailand. There has been concern about many air pollutants over this area. Air quality management for the area is known to be difficult, due to lack of understanding of how emissions from different sources or sectors (e.g., industrial, power plant, transportation, and residential) contribute to air quality degradation in the area. In this study, a dispersion study of NO2 and SO2 was conducted using the AERMOD model. The area-specific emission inventories of NOx and SO2 were prepared, including both stack and nonstack sources, and divided into 11 emission groups. Annual simulations were performed for the year 2006. Modeled concentrations were evaluated with observations. Underestimation of both pollutants was found, and stack emission estimates were scaled to improve the modeled results before quantifying relative roles of individual emission groups to ambient concentration over four selected impacted areas (two are residential and the others are highly industrialized). Two concentration measures (i.e., annual average area-wide concentration or AC, and area-wide robust highest concentration or AR) were used to aggregately represent mean and high-end concentrations for each individual area, respectively. For AC-NO2, on-road mobile emissions were found to be the largest contributor in the two residential areas (36–38% of total AC-NO2), while petrochemical-industry emissions play the most important role in the two industrialized areas (34–51%). For AR-NO2, biomass burning has the most influence in all impacted areas (>90%) except for one residential area where on-road mobile is the largest (75%). For AC-SO2, the petrochemical industry contributes most in all impacted areas (38–56%). For AR-SO2, the results vary. Since the petrochemical industry was often identified as the major contributor despite not being the largest emitter, air quality workers should pay special attention to this emission group when managing air quality for the MA. Implications: Effective air quality management in Map Ta Phut Industrial Area, Thailand requires better understanding of how emissions from various sources contribute to the degradation of ambient air quality. Based on the dispersion study here, petrochemical industry was generally identified as the major contributor to ambient NO2 and SO2. By accounting for all stack and non-stack sources, on-road mobile emissions were found to be important in some particular areas. Supplemental Materials: Supplemental materials are available for this article. Go to the publisher's online edition of the Journal of the Air & Waste Management Association.

Dynamic evaluation of regional air quality models: Assessing changes in O 3 stemming from changes in emissions and meteorology

Regional-scale air quality models are used to estimate the response of air pollutants to potential emission control strategies as part of the decision-making process. Traditionally, the model-predicted pollutant concentrations are evaluated for the “base case” to assess a model's ability to reproduce past observations. Dynamic evaluation approaches, which evaluate a model's ability to accurately simulate air quality changes from given changes in emissions, are critically important to regulatory applications. Here, we investigate approaches to evaluate the Community Multiscale Air Quality (CMAQ) model's predicted ozone (O 3) response to large NO x emission reductions associated with the NO x State Implementation Plan (SIP) Call and on-road mobile emissions. This case has the advantages that emission changes associated with the NO x SIP Call can be well characterized and substantial changes are observed in O 3 levels. To consider the modeled response to emission changes in light of the strong meteorological influences on O 3, two time periods after the NO x SIP Call are included with very different meteorological conditions. The sensitivity to chemical mechanisms is also considered by including simulations with the CB4, SAPRC, and CB05 chemical mechanisms. The evaluation results suggest that the air quality model predictions underestimate the O 3 reductions observed after the NO x SIP Call was implemented. While the emission estimate uncertainties may also be a factor, the results suggest that the contribution of long-range transport of O 3 and precursors is underpredicted, especially when using the CB4 chemical mechanism. Further investigation of the chemical mechanisms’ ability to characterize tropospheric chemistry aloft is recommended. Results based on the most recent CMAQ version 4.6 with CB05 and updated emission inventories show incremental improvements to the modeled O 3 response to NO x emission reductions.

The Impact of GEM and MM5 Modeled Meteorological Conditions on CMAQ Air Quality Modeling Results in Eastern Canada and the Northeastern United States

Abstract The fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) is currently the meteorological model most widely used as input into the Community Multiscale Air Quality (CMAQ) modeling system. In this study, meteorological fields produced by the Global Environmental Multiscale (GEM) meteorological model were compared with those from MM5, and the impact of using the two different modeled datasets as inputs to CMAQ was investigated. Two CMAQ model runs, differing only in meteorological inputs and meteorologically influenced emissions, were conducted for a domain covering eastern Canada and the northeastern United States for a 9-day period in July 1999. Comparison of the two modeled meteorological datasets with surface measurements revealed that GEM and MM5 gave comparable results. For a direct comparison of the two meteorological datasets the differences were small for pressure and temperature but larger for wind speed and relative humidity (RH). The variations in meteorological fields affect emissions and air quality results in differing ways and to differing degrees. The most influential meteorological field on emissions was temperature, which had a minor impact on on-road mobile emissions and a larger impact on biogenic emissions. Performance statistics for O3 and for particulate matter less than 10 μm and less than 2.5 μm (PM10, and PM2.5, respectively) show that GEM-based and MM5-based CMAQ results compare similarly to hourly measurement data, with minor statistical differences. A direct comparison of O3, PM10, PM2.5, and speciated PM2.5 showed that the results correlate to varying degrees and that the differences in RH affect total particulate matter (PM) mass and aerosol species concentrations significantly. Relative humidity affects total particle mass and particle diameters, which in turn affect PM2.5 and PM10 concentrations.

Nonparametric factorial analysis of daily weigh-in-motion traffic: implications for the ozone ?weekend effect? in Southern California

Abstract The Ozone Weekend Effect (OWE) has become increasingly more frequent and widespread in southern California since the mid-1970s. Although a number of hypotheses have been suggested to explain the effect, there remains uncertainty associated with the root factors contributing to elevated weekend ozone concentrations. Targeting the time window of the 1997 Southern California Ozone Study (SCOS97), this paper examines traffic activity data for 14 vehicle classes at 27 weigh-in-motion (WIM) stations in southern California. Nonparametric factorial analyses of light-duty vehicle (LDV) and heavy-duty truck (HDT) traffic volumes indicate significant differences in daily volumes by day of week and between the weekly patterns of daily LDV and HDT volumes. Across WIM stations, the daily LDV volume was highest on Friday and decreased by 10% on weekends compared to that on midweek days. In contrast, daily HDT volumes showed dramatic weekend drops of 53% on Saturday and 64% on Sunday. As a result, LDV to HDT ratios increased by 145% on weekends. Nonparametric tests also suggest that weekly traffic patterns varied significantly between WIM stations located close to (central) and far from (peripheral) the Los Angeles Metro area. Weekend increases in LDV/HDT ratios were more pronounced at central WIM sites due to greater weekend declines of HDT relative to LDV traffic. The implications of these weekly traffic patterns for the OWE in southern California were investigated by estimating daily WIM traffic on-road running exhaust emissions of total organic gas (TOG) and oxides of nitrogen (NOx) using EMFAC2002 emission factors. The results support the California Air Resource Board's (CARB's) NOx reduction hypothesis that greater weekend NOx reductions relative to volatile organic compound (VOC) emissions, in combinations with the VOC-limited ozone system, contribute to the OWE observed in the region. The results from this study can be used to develop weekend on-road mobile emission inventories for the purpose of air quality modeling.