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The Comprehensive Air Quality Model with extensions (CAMx) is an open-source, state-of-the-science photochemical grid model that addresses tropospheric air pollution (ozone, particulates, air toxics) over spatial scales ranging from neighborhoods to continents. CAMx has been in continuous development for over 25 years and has been used by numerous entities ranging from government to industry to academia to support regulatory actions and scientific research addressing a variety of air quality issues. Here, we describe the technical formulation of CAMx v7.20, publicly released in May 2022. To illustrate an example of regional and seasonal model performance for predicted ozone and fine particulate matter (PM2.5), we summarize a model evaluation from a recent 2016 national-scale CAMx application over nine climate zones contained within the conterminous US. We show that statistical performance for warm season maximum 8 h ozone is consistently within benchmark statistical criteria for bias, gross error, and correlation over all climate zones, and often near statistical goals. Statistical performance for 24 h PM2.5 and constituents fluctuate around statistical criteria with more seasonal and regional variability that can be attributed to different sources of uncertainty among PM2.5 species (e.g., weather influences, chemical treatments and interactions, emissions uncertainty, and ammonia treatments). We close with a mention of new features and capabilities that are planned for the next public releases of the model in 2024 and beyond. [ABSTRACT FROM AUTHOR]

The Comprehensive Air Quality Model with extensions (CAMx) is an open-source, state-of-the-science photochemical grid model that addresses tropospheric air pollution (ozone, particulates, air toxics) over spatial scales ranging from neighborhoods to continents. CAMx has been in continuous development for over 25 years and has been used by numerous entities ranging from government to industry to academia to support regulatory actions and scientific research addressing a variety of air quality issues. Here, we describe the technical formulation of CAMx v7.20, publicly released in May 2022. To illustrate an example of regional and seasonal model performance for predicted ozone and fine particulate matter (PM2.5), we summarize a model evaluation from a recent 2016 national-scale CAMx application over nine climate zones contained within the conterminous US. We show that statistical performance for warm season maximum 8 h ozone is consistently within benchmark statistical criteria for bias, gross error, and correlation over all climate zones, and often near statistical goals. Statistical performance for 24 h PM2.5 and constituents fluctuate around statistical criteria with more seasonal and regional variability that can be attributed to different sources of uncertainty among PM2.5 species (e.g., weather influences, chemical treatments and interactions, emissions uncertainty, and ammonia treatments). We close with a mention of new features and capabilities that are planned for the next public releases of the model in 2024 and beyond.

Volatile organic compound (VOC) emissions to the atmosphere cause air pollution associated with adverse health outcomes. Volatile chemical products (VCPs) have emerged as a VOC emission category that is poorly characterized by air pollution models. VCPs are present throughout developed economies in manufactured products that include paints, cleaning agents, printing inks, adhesives and pesticides. Air quality models must accurately represent the atmospheric chemistry of VCPs to develop reliable air quality plans. We develop a chemical mechanism for oxidant formation by VCP compounds that is compatible with version 6 of the Carbon Bond (CB6) mechanism. We analyzed a recent U.S. VCP emission inventory and found that ~67% of the emissions mass can be well-represented by existing CB6 mechanism species but ~33% could be better represented by adding 16 emitted VCP species including alcohols, ethers, esters, alkanes and siloxanes. For larger alkanes, an important VCP category, our mechanism explicitly represents temperature-dependent organic nitrate formation and autoxidation via 1,6 H-shift reactions consistent with current knowledge. We characterized the ozone forming potential of each added VCP species and compared it to the current practice of representing VCP species by surrogate species. Nine of the sixteen added VCP species are less reactive than the current practice, namely i-propanol, dimethyl ether, methyl formate, ethyl formate, methyl acetate, larger esters, i-butane, large alkanes and siloxanes. These less reactive VCP species are characterized by having OH-reactions that form un-reactive products. A total of 7 of the 16 VCP species are more reactive than current practice, namely n-propanol, ethylene glycol, propylene glycol, larger alcohols, diethyl ether, larger ethers and ethyl acetate. These more reactive VCP species are characterized as containing functional groups that promote faster OH-reaction. The VCP chemical mechanism for CB6 can improve how VCP impacts to oxidants are represented and will be incorporated to CB7. Changes in oxidant formation resulting from the mechanism update will depend on how VCP emissions are speciated for modeling, which is uncertain, and impacts may go in opposite directions for specific categories of VCP emissions that have unique chemical speciation characteristics. We provide guidance to help modelers implement the VCP mechanism update. [ABSTRACT FROM AUTHOR]

Styrene, Benzene, Toluene, Ethylbenzene, and Xylenes (SBTEX) are established neurotoxicants. These SBTEX are hazardous air pollutants (HAPs) and released from the petrochemical industry, combustion process, transport emission, and solvent usage sources. Although several SBTEX toxic assessment studies have been conducted, they have mainly relied on ambient measurements to estimate exposure and limiting their scope to specific locations and observational periods. To overcome these spatiotemporal limitations, an air quality modeling system over the U.S. Gulf region was created predicting the the spatially and temporally enhanced SBTEX modeling concentrations from May to September 2012. Due to the incompleteness of SBTEX in the official US EPA National Emission Inventory (NEI), Hazardous Air Pollutions Imputation (HAPI) program was used to identify and estimate the missing HAPs emissions. The improved emission data was processed to generate the chemically-speciated hourly gridded emission inputs for the Comprehensive Air Quality Model with Extensions (CAMx) chemical transport model to simulate the SBTEX concentrations over the Gulf modeling region. SBTEX pollutants were modeled using a "Reactive Tracer" feature in CAMx that accounts for their chemical and physical processes in the atmosphere. The data shows that the major SBTEX emissions in this region are contributed by mobile emission (45%), wildfire (30%), and industry (26%). Most SBTEX emissions are emitted during daytime hours (local time 14:00 -17:00), and the emission rate in the model domain is about 20 - 40 t hr-1, which is about 4 times higher than that in the night-time (local time 24:00 - 4:00, about 4 - 10 t hr-1). High concentrations of SBTEX (above 1 ppb) occurred near the cities close to the I-10 interstate highway (Houston, Beaumont, Lake Charles, Lafayette, Baton Rouge, New Orleans, and Mobile) and other metropolitan cities (Shreveport and Dallas). High Styrene concentrations were co-located with industrial sources, which contribute the most to the Styrene emissions. The HAPI program successfully estimated missing emissions of Styrene from the chemical industry. The change increased total Styrene emissions was increased by 22% resulting in maximum ambient concentrations increasing from 0.035 ppb to 1.75 ppb across the model domain. The predicted SBTEX concentrations with imputed emissions present good agreement with observational data, with a correlation coefficient (R) of 0.75 (0.46 to 0.77 for individual SBTEX species) and normalized mean bias (NMB) of -5.6% (-24.9% to 32.1% for individual SBTEX species), suggesting their value for supporting any SBTEX-related human health studies in the Gulf region. [ABSTRACT FROM AUTHOR]

The main aim of this study is the identification of the most appropriate measures and policies to combat particulate air pollution in the city of Thessaloniki, Greece through a methodology including the calculation of emissions by sector and the application of an air quality modeling system. The identification of the current air quality situation showed that the exceedances of the mean PM10 daily levels occur during the cold winter months with residential heating being the major contributor representing a 73% share of total PM10 emissions. Moreover, the effect of the biomass consumption for heating purposes on PM10 concentrations has been verified and quantified by implementing a regression model identifying that a PM10 emissions reduction by 45% would result in the elimination of the exceedances of the mean PM10 daily values. Based on the above, a set of cost-effective measures and policies were defined and their impact on PM10 emissions was estimated. Finally, the air quality modeling system was applied for the mitigation scenarios selected, leading to a significant reduction of 67% in the number of exceedances observed and ensuring compliance with the limit of 35 exceedances of the daily value limit per year pursuant to European Legislation. [ABSTRACT FROM AUTHOR]

Air quality simulations were performed for the Greater Athens Area in very high spatial resolution using the modeling system WRF-CAMx. Sensitivity runs were performed using the SOAP and VBS schemes for organic gas–aerosol partitioning and oxidation. In January 2019, OA-VBS decreased compared to OA-SOAP because of POA reduction. In July 2019, the OA-VBS increased with respect to OA-SOAP as a result of the increase in SOA levels exceeding the decrease in POA ones. The comparison of the WRF-CAMx results against PM10, PM2.5, and OC surface measurements provides the first indications for improved CAMx performance with the VBS scheme.

Abstract The Center for Air Quality & Control at the Seoul Research Institute of Public Health and the Environment (SIHE) has monitored changes in the concentration of fine dust in Seoul over the past 10 years and investigated meteorological factors as well as fine particulate matter (PM2.5), sulfur dioxide (SO2), and nitrogen dioxide (NO2) concentrations in northeastern China and its contribution to the PM2.5 concentration in Seoul. The concentration of fine dust in Seoul in 2020 was 21 µg/m3, which is down 16% from 2019 and the lowest since 2010. In 2020, China’s emissions of pollutants such as NO2 have decreased significantly due to regional blockades, social distancing, and factory shutdowns caused by COVID-19. As a results, the concentration of precursors such as SO2 and NO2, and PM2.5 in northeastern China are also decreased, which contributed to the reduction in PM2.5 concentration in Seoul caused by westerly winds blowing. In addition, the ratio of east and south winds that usually contain low concentrations of pollutants was more than 30% of the total air currents into Seoul, which is the highest in the last three years. Moreover, the mean wind velocity and the amount of precipitation were also the highest recorded values of 2.4 m/s and 1651.0 mm, respectively. Calculations using Comprehensive Air quality Model with eXtensions (CAMx)-Particulate Source Apportionment Technology (PSAT) show that the contribution of external inflows to the PM2.5 concentration in Seoul was 65%. We believe that the reasons for the low PM2.5 concentration in 2020 are due to meteorological factors and a decrease in air pollution in northeastern China. Meanwhile, the major contribution of emissions in Seoul (resuspended road dust and non-exhaust dust) was high. When the concentration of PM2.5 was high, the contribution of resuspended road dust was reduced due to an increase of secondary generating materials. Currently, data on emission reduction due to the COVID-19 cannot be assessed, which we believe will enable more accurate contribution calculations in the future.

The pollutants emitted during meal preparation in restaurants deteriorate the air quality. Thus, it is an environmental issue that needs to be addressed, especially in areas where these activities are densely located. The purpose of this study is to examine the impact on air quality from commercial cooking activities by performing a qualitative and quantitative analysis of the related parameters. The area of interest is located in the southeastern Mediterranean (Greater Athens area in Greece). Due to the lack of the necessary activity information, a survey was conducted. Emissions from the fuel burnt during the cooking procedures were calculated and it was found that, overall, 940.1 tonnes are attributed to commercial cooking activities annually (generated by classical pollutants, heavy metals, particulates and polycyclic aromatic hydrocarbon emissions). Comparing the contribution of different sources to the pollutants emitted, it was found that commercial cooking is responsible for about 0.6%, 0.8% and 1.0% of the total CO, NOx and PM10 values. Cooking organic aerosol (COA) and volatile organic compound (VOC) emissions from grilled meat were also calculated, accounting for 724.9 tonnes and 37.1 tonnes, respectively. Monthly, daily and hourly profiles of the cooking activities were developed and emissions were spatially disaggregated, indicating the city center as the area with higher values. Numerical simulations were performed with the WRF/CAMx modeling system and the results revealed a contribution of about 6% to the total PM10 concentrations in the urban center, where the majority of restaurants are located. [ABSTRACT FROM AUTHOR]

China has imposed an ultra-low emissions (ULE) standards policy regarding the emission concentrations of the thermal power industry, and the region of the Fen-Wei Plain (China), which is an important area regarding blue-sky protection, is in urgent need of accelerating the transformation of its thermal power units to conform with China's ULE standards. Based on China's high-resolution thermal power industry emission inventory, this study used the Comprehensive Air Quality Model with extensions (CAMX) to examine emissions from the thermal power industry and the associated impacts on the atmospheric environment of the Fen-Wei Plain. (1) Spatially, the highest emissions and the greatest air quality contributions were concentrated in the Shanxi and Henan areas, which are regions that have considerable power generation capacity. (2) In terms of species, NOX represented the largest air quality contribution and registered the smallest reduction. (3) Temporally, emission sources presented the greatest contributions in summer. (4) In terms of policy evaluation, implementation of ULE standards resulted in the reduction of the contribution of thermal power industry emissions to air quality by 56.82%, 27.44%, and 44.55% for SO2, NOX, and PM2.5, respectively. The results reflect the current levels of pollution on the Fen-Wei Plain attributable to the thermal power industry and provide insight in relation to decision-making processes regarding regional air quality management. [ABSTRACT FROM AUTHOR]

The main objective of the present study is the development of an "on-line" heating emissions modeling system based on simulated meteorological data and its integration with air quality modeling systems in order to improve their accuracy. The WRF-CAMx air quality modeling system is applied over Greece for the cold period of 2015 (January–April, October–December) for two emissions scenarios: using the (a) "on-line" heating emissions based on WRF meteorology and (b) "static" heating emissions based on static temporal profiles. The monthly variation in total "on-line" heating emissions followed the temporal pattern of the air temperature over Greece, leading to the highest heating emissions in January and February, while higher differences in emissions between winter and spring/autumn months were identified in comparison with the static ones. The overall evaluation of the WRF-CAMx modeling system using the "on-line" heating emissions revealed satisfactory model performance for the mean daily air quality levels. The comparison between the simulated and observed mean monthly concentrations revealed an improvement in the pattern of mean monthly concentrations for the "on-line" scenario. Higher values of the index of agreement and correlation for the mean daily values were also identified for the "on-line" scenario in most monitoring sites. [ABSTRACT FROM AUTHOR]

The Center for Air Quality & Control at the Seoul Research Institute of Public Health and the Environment (SIHE) has monitored changes in the concentration of fine dust in Seoul over the past 10 years and investigated meteorological factors as well as fine particulate matter (PM2.5), sulfur dioxide (SO2), and nitrogen dioxide (NO2) concentrations in northeastern China and its contribution to the PM2.5 concentration in Seoul. The concentration of fine dust in Seoul in 2020 was 21 µg/m³, which is down 16% from 2019 and the lowest since 2010. In 2020, China's emissions of pollutants such as NO2 have decreased significantly due to regional blockades, social distancing, and factory shutdowns caused by COVID-19. As a results, the concentration of precursors such as SO2 and NO2, and PM2.5 in northeastern China are also decreased, which contributed to the reduction in PM2.5 concentration in Seoul caused by westerly winds blowing. In addition, the ratio of east and south winds that usually contain low concentrations of pollutants was more than 30% of the total air currents into Seoul, which is the highest in the last three years. Moreover, the mean wind velocity and the amount of precipitation were also the highest recorded values of 2.4 m/s and 1651.0 mm, respectively. Calculations using Comprehensive Air quality Model with eXtensions (CAMx)-Particulate Source Apportionment Technology (PSAT) show that the contribution of external inflows to the PM2.5 concentration in Seoul was 65%. We believe that the reasons for the low PM2.5 concentration in 2020 are due to meteorological factors and a decrease in air pollution in northeastern China. Meanwhile, the major contribution of emissions in Seoul (resuspended road dust and non-exhaust dust) was high. When the concentration of PM2.5 was high, the contribution of resuspended road dust was reduced due to an increase of secondary generating materials. Currently, data on emission reduction due to the COVID-19 cannot be assessed, which we believe will enable more accurate contribution calculations in the future. [ABSTRACT FROM AUTHOR]

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The iron and steel industry puts considerable pressure on the regional environment of the BeijingTianjin-Hebei (BTH) area, and the PM2.5 pollution has caused serious harm to public health. To explore a detailed and high-resolution emission inventory of the iron and steel industry in the BTH region, a classification technology method with CAMx modelling system was developed and applied for classifying all the iron and steel enterprises in the BTH region. Besides, simulation scenarios were designed particularly for quantitatively assessing the effectiveness of the environmental protection measures. Results show that the pollutant emission of the iron and steel industry significantly contributes to the PM2.5, SO4 2-, NO3 -, and SOA concentrations in the atmospheric environment in sub-areas. Therefore, the enterprises in western and central sub-areas show high classification coefficients. Restricting pollutant emissions using the developed classification technology method is more effective in reducing the PM2.5 concentration of the BTH region compared with the proportional reduction method. Thus, the classification method should be primarily implemented for reducing the air pollutant emissions of the iron and steel industry in the BTH region. [ABSTRACT FROM AUTHOR]

A partir del inventario de emisiones del Valle de Aburrá (año 2015), ubicado en el departamento de Antioquia – Colombia, en este estudio se presenta la estimación de emisiones de Black Carbón (BC) de la región, así como la dispersión de este contaminante y la evaluación del Modelo de Calidad del Aire Comprehensivo con Extensiones (CAMx) y el modelo BRAMS, en la zona de estudio. Las emisiones totales estimadas de BC fueron de 850 toneladas donde el 97 % de éstas se deben al sector transporte, donde la categoría camiones seguido de la categoría volquetas son los mayores emisores de este contaminante, aportando el 43 % y 37 %, respectivamente. El combustible diésel es el principal responsable por las emisiones de BC con el 95 % del total de las emisiones. La concentración máxima de BC para el 9 de noviembre de 2016 en el punto estudiado, fue de 8.47 mg/m3 a las 7 horas, donde el área de mayor impacto se encuentra localizada en el centro de Medellín y el norte de este municipio. El desempeño del modelo CAMx (inferencia difusa) para predecir las concentraciones de BC para el día de estudio, se encuentra en el 66 %. El modelo BRAMS se ajusta a los datos reales de las variables meteorológicas estudiadas (temperatura y humedad relativa), con errores MAPE menores al 3 %, para el día en que el modelo fue evaluado.

The pollutants emitted during meal preparation in restaurants deteriorate the air quality. Thus, it is an environmental issue that needs to be addressed, especially in areas where these activities are densely located. The purpose of this study is to examine the impact on air quality from commercial cooking activities by performing a qualitative and quantitative analysis of the related parameters. The area of interest is located in the southeastern Mediterranean (Greater Athens area in Greece). Due to the lack of the necessary activity information, a survey was conducted. Emissions from the fuel burnt during the cooking procedures were calculated and it was found that, overall, 940.1 tonnes are attributed to commercial cooking activities annually (generated by classical pollutants, heavy metals, particulates and polycyclic aromatic hydrocarbon emissions). Comparing the contribution of different sources to the pollutants emitted, it was found that commercial cooking is responsible for about 0.6%, 0.8% and 1.0% of the total CO, NOx and PM10 values. Cooking organic aerosol (COA) and volatile organic compound (VOC) emissions from grilled meat were also calculated, accounting for 724.9 tonnes and 37.1 tonnes, respectively. Monthly, daily and hourly profiles of the cooking activities were developed and emissions were spatially disaggregated, indicating the city center as the area with higher values. Numerical simulations were performed with the WRF/CAMx modeling system and the results revealed a contribution of about 6% to the total PM10 concentrations in the urban center, where the majority of restaurants are located.

China has imposed an ultra-low emissions (ULE) standards policy regarding the emission concentrations of the thermal power industry, and the region of the Fen-Wei Plain (China), which is an important area regarding blue-sky protection, is in urgent need of accelerating the transformation of its thermal power units to conform with China’s ULE standards. Based on China’s high-resolution thermal power industry emission inventory, this study used the Comprehensive Air Quality Model with extensions (CAMX) to examine emissions from the thermal power industry and the associated impacts on the atmospheric environment of the Fen-Wei Plain. (1) Spatially, the highest emissions and the greatest air quality contributions were concentrated in the Shanxi and Henan areas, which are regions that have considerable power generation capacity. (2) In terms of species, NOX represented the largest air quality contribution and registered the smallest reduction. (3) Temporally, emission sources presented the greatest contributions in summer. (4) In terms of policy evaluation, implementation of ULE standards resulted in the reduction of the contribution of thermal power industry emissions to air quality by 56.82%, 27.44%, and 44.55% for SO2, NOX, and PM2.5, respectively. The results reflect the current levels of pollution on the Fen-Wei Plain attributable to the thermal power industry and provide insight in relation to decision-making processes regarding regional air quality management.

The main objective of the present study is the development of an “on-line” heating emissions modeling system based on simulated meteorological data and its integration with air quality modeling systems in order to improve their accuracy. The WRF-CAMx air quality modeling system is applied over Greece for the cold period of 2015 (January–April, October–December) for two emissions scenarios: using the (a) “on-line” heating emissions based on WRF meteorology and (b) “static” heating emissions based on static temporal profiles. The monthly variation in total “on-line” heating emissions followed the temporal pattern of the air temperature over Greece, leading to the highest heating emissions in January and February, while higher differences in emissions between winter and spring/autumn months were identified in comparison with the static ones. The overall evaluation of the WRF-CAMx modeling system using the “on-line” heating emissions revealed satisfactory model performance for the mean daily air quality levels. The comparison between the simulated and observed mean monthly concentrations revealed an improvement in the pattern of mean monthly concentrations for the “on-line” scenario. Higher values of the index of agreement and correlation for the mean daily values were also identified for the “on-line” scenario in most monitoring sites.

Northern China experienced a severe sand and dust storm (SDS) on 14/15 March 2021. It was difficult to simulate this severe SDS event accurately. This study compared the performances of three dust-emission schemes on simulating PM10 concentration during this SDS event by implementing three vertical dust flux parameterizations in the Comprehensive Air-Quality Model with Extensions (CAMx) model. Additionally, a statistical gusty-wind model was implemented in the dust-emission scheme, and it was used to quantify the gusty-wind contribution to dust emissions and peak PM10 concentration. As a result, the LS scheme (Lu and Shao 1999) produced the minimum errors for peak PM10 concentrations, the MB scheme (Marticorena and Bergametti 1995) underestimated the PM10 concentrations by 70–90%, and the KOK scheme (Kok et al. 2014) overestimated PM10 concentrations by 10–50% in most areas. The gusty-wind model could reasonably reproduce the probability density function of 2-min wind speeds. There were 5–40% more dust-emission flux and 5–40% more peak PM10 concentrations generated by the gusty wind than the hourly wind in the dust-source regions. The increase of peak PM10 concentration caused by gusty wind in the non-dust-source regions was higher than in the dust-source regions, with 10–50%. Implementing the gusty-wind model could help improve the LS scheme’s performance in simulating PM10 concentrations of this severe SDS event. More work is still needed to investigate the reliability of the gusty-wind model and LS scheme on various SDS events.

A new analytical air pollution modeling system is introduced in this paper to estimate concentrations of primary and secondary air pollutants and using it for further studies in order to improve the knowledge of pollutants emission and dispersion over Tehran, and developing a decision support system. For this purpose, WRF/CAMx modeling system was used to simulate the gas-phase pollutants concentrations including primary and secondary pollutants, over Tehran during a wintertime episode, which is characterized by very high concentrations of pollutants. Pollutants were triggered by meteorological conditions leading to a forced holiday imposed on citywide operations to protect the health of citizens. Based on calculated Values of NMB error, WRF performs acceptable in predicting temperature and wind speed. Generally, time series plots show that WRF performs acceptable in mild selected episode. Also, the daily trends of pollutant concentrations are greatly affected by changes in local meteorological conditions such as planetary boundary layer (PBL) height, temperature, wind, and relative humidity over the Tehran area. An underestimation in prediction of all pollutants concentrations episode at Poonak and Aghdasyeh sites show due to the insufficient emission data at the site position used for the simulation were seen. Results showed that WRF/CAMx modeling system proved to be a useful tool for analyzing urban environmental problems, investigating the impact of air quality control policies, and predicting critical conditions. However, there were weaknesses in input data and modeling system calibration that should be improved before using the system for further studies.

Photochemical grid models are being used in technical analyses by the Visibility Improvement State and Tribal Association of the Southeast (VISTAS), a regional air quality planning organization in the southeastern United States, to support state implementation plans for regional haze and related air quality issues. VISTAS has embarked on a multi-phase process of testing and evaluating regional meteorological, emissions and air quality models that will be used to project visibility improvements as required by the regional haze rule. VISTAS has generated 2002 annual emissions and meteorological inputs for two photochemical grid models, the community multi-scale air quality (CMAQ) and the comprehensive air-quality model with extensions (CAMx), at a 36 km resolution for the continental US and at 12 km resolution for the eastern US. The two models were evaluated using speciated PM measurements from various monitoring networks and detailed analysis was performed for organic carbon (OC) mass using the IMPROVE, STN, and SEARCH networks. The differences in model performance between CMAQ and CAMx were used as a diagnostic tool to investigate performance issues for several compounds. CAMx performed substantially better than CMAQ for OC (defined as 1.4×measured organic carbon) which led to investigations into methods for improving the CMAQ OC model performance. The treatment of secondary organic aerosol (SOA) was identified as an area needing improvements in both models. The impact of replacing the CMAQ SOA parameters with those from CAMx was investigated. Further analysis identified several processes that are potentially important for SOA formation that are not treated in either model including, polymerization of the SOA into non-volatile particles and SOA formation from sesquiterpene, isoprene and other biogenic VOCs. A prototype mechanism for several of these missing processes was developed and the CMAQ SOA module was enhanced to include these SOA formation processes. SOA yields, specifically from biogenic emissions, were increased by the modified SOA module and CMAQ model performance for particulate OC at the IMPROVE, SEARCH, and STN sites in the VISTAS region was improved. © 2006 Elsevier Ltd. All rights reserved.

This study presents a high–resolution (5 km) set of new simulations performed with CAMx v6.40 over the Po Valley area (Northern Italy), aimed to enhance organic aerosol (OA) levels prediction and to gain insight into the sensitivity of CAMx to different uncertain features of the input setup. In particular, we mainly investigated the role of (i) volatility distributions of organic emissions, (ii) parametrizations of semi– and intermediate–volatile organic compounds (S/IVOC) emissions and (iii) different aging schemes, by exploiting the latest experimental information available in the recent scientific literature. Model results were validated against two OA–specific datasets, available for both an urban site (Bologna, February 2013) and a rural one (Ispra, March 2013). We found out a remarkable performance enhancement of modelled OA levels when applying revisions in S/IVOC emission parametrizations together with the new volatility distributions, at both the validation sites. This performance enhancement is associated with a very significant improvement in secondary organic aerosol (SOA) prediction, mainly due to revised IVOC emissions. At Bologna urban site, mean fractional bias (MFB) of OA ranged from −80.1% in the worst run to −10.1% in the best one and index of agreement (IOA) from 0.52 to 0.75. Notable improvements but overall poorer metrics were found for Ispra site, where MFB ranges from −84.2% to −35% and IOA from 0.45 to 0.50. These findings indicate that organic matter in the semi– and intermediate–volatile range are most likely underestimated in official emission inventories for each main source category (i.e. biomass burning, diesel and gasoline vehicles exhaust). Finally, model results did not show a very pronounced sensitivity to aging processes, due to the low photochemical activity typically observed during winter–time. However, we give evidence that enabling aging processes for biomass burning related SOA, which is by default disabled in CAMx v6.40, can help in closing the gap between modelled and observed SOA concentrations. • Latest experimental studies about emissions of organic matter implemented in CAMx. • Remarkable improvement on modelled organic aerosol levels. • S/IVOC emission revisions appear to be the key factor for such improvement. • Enabling aging processes for biomass burning SOA enhances the performance of the model. • VBS provides a better reconstruction of POA and SOA relative contribution to the total. [ABSTRACT FROM AUTHOR]

Evaluating long-term air quality and deposition trends can demonstrate effectiveness of control strategies and guide future air quality management planning. Observations show a reduction of atmospheric concentrations of NO x and SO x species and their wet and dry deposition since monitoring began in 1978 and 1987, respectively, although deposition observations are sparse. This study used a regional model (CAMx) nested within a global model (GEOS-Chem) to characterize regional changes in sulfur and nitrogen deposition due to intercontinental transport and local/regional anthropogenic emissions representing six modeling years spanning five decades (1970–2020). The meteorological year and the natural emissions were fixed at 2005 to isolate the effects of changing anthropogenic emissions. The downward trend from 1970 to 2020 of mean atmospheric SO 2 concentration is 1.5–1.8%; of total S deposition is 1.0–1.7%; and of SO 2 emissions is 1.4–1.8% per year. The rate of decline in NO y deposition of 0.6–1.4% per year is similar to the 0.5–1.6% per year reduction in NO x emissions, thus showing that the changes in deposition have tracked changes in emissions of SO 2 and NO x emissions quite well. Further reducing N deposition could face some challenges due to increasing NH x contribution from NH 3 emissions and the expectation of these to increase globally. Our study also examined the transference ratios of NO y and SO x in the context of the secondary NAAQS for NO x and SO x and found them to be sensitive to emission reductions over the study period. • U.S. emissions contributions to sulfur and oxidized nitrogen deposition have reduced since 1970. • The relative contribution of NH x to total N deposition has increased during this period. • Transference ratios in the context of the secondary NAAQS for NO x and SO x are sensitive to emission reductions. [ABSTRACT FROM AUTHOR]

Abstract With a rapid increase in air traffic, aviation has become an increasingly important contributor to anthropogenic air pollutants (particularly nitrogen oxides (NO X)) over China. This study provides the first overall estimation of the aviation emissions from all civil airports in mainland China as well as the associated contribution to ambient air quality. First, aircraft emissions (NOx, sulfur dioxide (SO 2), carbon monoxide (CO), hydro-carbons (HC), particulate matter (PM 2.5 and PM 10), volatile organic carbons (VOCs) and black carbon (BC)) during landing and take-off cycles (below 3 km) are estimated for both recent (2000–2016) and future (2020) scenarios. Second, the corresponding environmental impacts are measured by the Comprehensive Air Quality Model with extensions (CAMx). The results have insightful policy implications for China's aviation planning. (1) Generally, China's aviation emissions and their effect on air quality have been and will continue to increase. (2) Among species, NOx dominated China's aircraft emissions in terms of both emission amount and environmental impact, while PM 2.5 generated an extensive influence. (3) With respect to spatial distribution, the air quality effect was highly concentrated at emission-intense airports that served economic zones and/or tourist spots. Highlights • China's aviation emissions are estimated for 2000–2016 and 2020 scenarios. • The corresponding environmental contribution is calculated via the CAMx model. • Aviation emissions and environmental impact both followed an upward trend. • The airports serving economic zones and/or tourist spots made a high contribution. • Aviation emissions impacted NOx to a large extent and PM 2.5 in a broad domain. [ABSTRACT FROM AUTHOR]

Abstract Formation of organic aerosol (OA) and ozone were simulated for the greater Houston area in September 2013 and 2028 (summer conditions) using the Comprehensive Air Quality Model with Extensions (CAMx). We also simulated the background concentrations in the absence of US anthropogenic emissions. The 1.5-dimensional volatility basis set scheme was used to represent formation of primary and secondary OA (POA and SOA). The path-integral method for source apportionment was successfully extended to OA formation using the same numerical approach previously used for ozone and then applied to apportion the anthropogenic increment of OA and ozone to six emission source categories. The anthropogenic increment is the difference between the 2013 or 2028 simulation and the background simulation. Averaged over 21 air monitoring sites in Houston, point sources make the largest contribution to monthly average SOA and OA (25%–37%, depending on year) and to monthly maximum 8-h ozone (21%–26%). Onroad and then nonroad sources are the next most important in 2013, but their contributions diminish by 2028. The sources' contributions to SOA correlate much more strongly with their NO x emissions than with their emissions of organic precursor species. Anthropogenic emissions enhance OA formation from biogenic emissions, and this enhancement is 46% and 48% of the total OA concentration in Houston in 2013 and 2028, respectively. Point sources make the largest contribution to the enhancement. Additional results for a larger regional area covering Texas and nearby states are also presented. Graphical abstract Image 1 Highlights • Point sources are the largest anthropogenic contributor to SOA and O 3 in Houston. • NO x emissions are a principal factor in a source's contribution to SOA. • SOA from biogenic emissions is strongly enhanced by anthropogenic emissions. • The path-integral method is extended to source apportionment of SOA and OA. [ABSTRACT FROM AUTHOR]

Air quality modeling at the very local scale within an urban area is performed through a hybrid modeling system (HMS) that combines the CAMx Eulerian model the with AUSTAL2000 Lagrangian model. The enhancements obtained by means of the HMS in the reconstruction of the spatial distribution of fine particles (PM2.5) and elemental carbon (EC) concentration are presented for the case-study of Milan city center in Northern Italy. Modeling results are reported for three receptors (a green area, a residential and shopping area, and a congested crossroad on the inner ring road of the city center) selected in order to represent urban sites characterized by both different features in terms of the surrounding built environment and by different exposure to local emission sources. The peculiarity of the three receptors is further highlighted by source apportionment analysis, developed not only with respect to the kind of emission sources but also to the geographical location of the sources within the whole Northern Italy computational domain. Results show that the outcome of the Eulerian model at the local scale is only representative of a background level, similar to the Lagrangian model’s outcome for the green area receptor, but fails to reproduce concentration gradients and hot-spots, driven by local sources’ emissions.

This study investigated transport pathways and photochemical formation responsible for ozone exceedances during the September 2021 deployment of the Tracking Aerosol Convection Interactions ExpeRiment/Air Quality (TRACER-AQ) campaign in Houston, Texas. We focused on two ozone episodes, September 6th-September 11th ("Episode 1") and September 23rd-September 26th ("Episode 2"), when the maximum daily eight-hour average (MDA8) ozone at surface monitors exceeded 70 ppbv. Long-range transport patterns of air masses during these episodes were from the central/northern US. High-resolution (4 km resolution) trajectory analysis with FLEXible PARTicle (FLEXPART) dispersion model revealed local recirculation of air masses and the accumulation of pollutants across Houston contribute to the ozone exceedances. Comprehensive Air Quality Model with extensions (CAMx) driven by 1.33-km resolution meteorology from the Weather Research and Forecast (WRF) tool simulated elevated ozone production rates during ozone episodes across the Houston metropolitan area, with ozone production hotspots mostly over Houston city and industrial districts of the Houston Ship Channel (HSC). The regional increase in ozone production rates was due to the transport of VOC-rich air masses (via northerly flows) that brought ozone precursors to the region, which ultimately caused a transition in the ozone formation tendency from generally VOC-limited to NO x -limited conditions. However, the city of Houston and the HSC remained in a VOC-limited regime because of local NO x emissions that, to some extent, preponderated the impact of transported VOCs. While approximately 37 % of the elevated ozone production was attributed to local photochemistry, the remaining ∼63 % increase in ozone production was due to the transported ozone to the region during episodes, bringing ozone to the Houston region and contributing to ozone exceedances. The outcomes of this study illustrated the synergy between transport and ozone production, both long-range and local scale, which resulted in ozone exceedances in Houston., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Abstract The U.S. Mid-Atlantic region is affected by transport of ozone and its precursors from upwind states and therefore local emission-reduction strategies are not necessarily the most effective to reach attainment. In this study, we conduct a comprehensive modeling effort with two photochemical models recommended by the U.S. Environmental Protection Agency – the Community Multiscale Air Quality Model (CMAQ) and the Comprehensive Air Quality Model with Extensions (CAMx) – inclusive of source apportionment and localized emission reductions, to study the extent of ozone precursor transport in the Mid-Atlantic and the efficacy of emission-reduction strategies, with a focus on Delaware. Delaware is a small state in the Mid-Atlantic region that is in nonattainment of the 2015 national 8-h ozone standard (0.070 ppm) despite its relatively low local emissions, thus it is an ideal test case to study transport. We found that in Delaware: 1) reducing local emissions of NO x and VOC by 20% is minimally effective; 2) the same emission reduction in each of five upwind states individually lowers ozone but not sufficiently to reach attainment; 3) only a consorted effort by the five upwind states together can lower Delaware ozone significantly; and 4) the emission reduction needed by the five states together is approximately 10%, half that of each individual state. This suggests that coordinated efforts and long-term, multi-state strategies are necessary to protect air quality in the Mid-Atlantic. Highlights • Delaware cannot reduce ozone concentrations by reducing Delaware VOC + NOx emissions. • Reducing VOC + NOx emissions in upwind states is more effective to Delaware ozone. • Coordinated efforts by upwind states more effective than individual state efforts. [ABSTRACT FROM AUTHOR]

Using the Numerical Prediction Models in mineral dust cycle is of prime importance in investigation of aerosol contribution in climatic changes. In this paper, a modelling system is developed to study a local characterization of Shalamceh dust intrusions in PM10 levels in Ahvaz city. The model chain consists of three different modules: the meteorological model (WRF), the dust emission model (COMSALT) and transport/deposition model (CAMx). Applying a physically based parameterization of the vertical dust fluxes emitted from the eroding soil could reduce the need for empirical source functions in dust emission models. For the selected case study, 6/1/2010 and 6/10/2010, the numerical simulations were performed to evaluate the effectiveness of modeling system. The comparison between observation and modeled results shows a good agreement. Different scenarios used to investigate the role of desertification and weak structure soils in air quality. Results show an increase in PM10 levels in Ahvaz due to the growth of wind erodible lands and the reduction of soil cohesive forces. In addition, the dry deposition fluxes of some detected heavy metals in different situations were estimated. Also, dust emission potential was inspected with the absorbing aerosol index data from Ozone Measurement Instrument (OMI) in the studied area. © 2017 American Institute of Chemical Engineers Environ Prog, 37: 1380–1393, 2018 [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM 2.5 ) has become the primary atmospheric pollutant in Beijing in recent years, causing widespread concern in society. Understanding the origin of PM 2.5 is essential for developing effective strategies to reduce PM 2.5 . In this study, we used the Particulate Matter Source Apportionment Technology (PSAT) in Comprehensive Air Quality Model with Extensions (CAMx) to quantify the contributions of different source regions and emission categories to the PM 2.5 concentration in the central six districts of Beijing in January, April, July and October, representing four seasons in 2014. The annual contribution ratios from local, suburb and the surrounding regions of Beijing as well as the outside of boundary region were 47.6, 19.3, 11.4, and 21.7%, respectively, showing significant contribution of regional transport to the PM 2.5 pollution in the central six districts of Beijing. The emission category apportionment results in the central six districts showed distinct seasonal variations with important contribution of coal combustion in winter but minor contribution in the other seasons, dominant contribution of dust in spring, and dominant contribution of the vehicle related sources in the other seasons. Moreover, the detailed contribution proportion of the five emission categories showed clear spatial variation in the suburbs and the surrounding regions. Based on the sensitivity analysis of local emission reduction, the control of the vehicle related sources was the most efficient mitigation measure for the reduction of PM 2.5 during the case study period in autumn, but the efficiency of the local mitigation measures was greatly reduced in the period of heavy PM 2.5 pollution. [ABSTRACT FROM AUTHOR]

This paper presents an atmospheric vulnerability assessment framework based on CAMx that should be helpful to assess potential impacts of changes in human, atmospheric environment, and social economic elements of atmospheric vulnerability. It is also a useful and effective tool that can provide policy-guidance for environmental protection and management to reduce the atmospheric vulnerability. The developed framework was applied to evaluate the atmospheric environment vulnerability of 13 cities in the Beijing-Tianjin-Hebei (BTH) region for verification. The results indicated that regional disparity of the atmospheric vulnerability existed in the study site. More specifically, the central and southern regions show more atmospheric environment vulnerability than the northern regions. The impact factors of atmospheric environment vulnerability in the BTH region mainly derived from increasing population press, frequently unfavorable meteorological conditions, extensive economic growth of secondary industry, increased environmental pollution, and accelerating population aging. The framework shown in this paper is an interpretative and heuristic tool for a better understanding of atmospheric vulnerability. This framework can also be replicated at different spatial and temporal scales using context-specific datasets to straightly support environmental managers with decision-making. [ABSTRACT FROM AUTHOR]

Differences between two air quality modeling systems reveal important uncertainties in model representations of secondary organic aerosol (SOA) fate. Two commonly applied models (CMAQ: Community Multiscale Air Quality; CAMx: Comprehensive Air Quality Model with extensions) predict very different OA concentrations over the eastern U.S., even when using the same source data for emissions and meteorology and the same SOA modeling approach. Both models include an option to output a detailed accounting of how each model process (e.g., chemistry, deposition, etc.) alters the mass of each modeled species, referred to as process analysis. We therefore perform a detailed diagnostic evaluation to quantify simulated tendencies (Gg/hr) of each modeled process affecting both the total model burden (Gg) of semi-volatile organic compounds (SVOC) in the gas ( g ) and aerosol ( a ) phases and the vertical structures to identify causes of concentration differences between the two models. Large differences in deposition (CMAQ: 69.2 Gg/d; CAMx: 46.5 Gg/d) contribute to significant OA bias in CMAQ relative to daily averaged ambient concentration measurements. CMAQ's larger deposition results from faster daily average deposition velocities ( V D ) for both SVOC (g) ( V D,cmaq = 2.15 × V D,camx ) and aerosols ( V D,cmaq = 4.43 × V d,camx ). Higher aerosol deposition velocity would be expected to cause similar biases for inert compounds like elemental carbon (EC), but this was not seen. Daytime low-biases in EC were also simulated in CMAQ as expected but were offset by nighttime high-biases. Nighttime high-biases were a result of overly shallow mixing in CMAQ leading to a higher fraction of EC total atmospheric mass in the first layer (CAMx: 5.1–6.4%; CMAQ: 5.6–6.9%). Because of the opposing daytime and nighttime biases, the apparent daily average bias for EC is reduced. For OA, there are two effects of reduced vertical mixing: SOA and SVOC are concentrated near the surface, but SOA yields are reduced near the surface by nighttime enhancement of NOx. These results help to characterize model processes in the context of SOA and provide guidance for model improvement. [ABSTRACT FROM AUTHOR]

Traditional aerosol mechanisms underestimate the observed organic aerosol concentration, especially due to the lack of information on secondary organic aerosol (SOA) formation and processing. In this study we evaluate the chemical and transport model CAMx during a one-month in winter (February 2013) over a 5 km resolution domain, covering the whole Po valley (Northern Italy). This works aims at investigating the effects of chemical and physical atmospheric processing on modelling results and, in particular, to evaluate the CAMx sensitivity to organic aerosol (OA) modelling schemes: we will compare the recent 1.5D-VBS algorithm (CAMx-VBS) with the traditional Odum 2-product model (CAMx-SOAP). Additionally, the thorough diagnostic analysis of the reproduction of meteorology, precursors and aerosol components was intended to point put strength and weaknesses of the modelling system and address its improvement. Firstly, we evaluate model performance for criteria PM concentration. PM 10 concentration was underestimated both by CAMx-SOAP and even more by CAMx-VBS, with the latter showing a bias ranging between −4.7 and −7.1 μg m −3 . PM 2.5 model performance was to some extent better than PM 10 , showing a mean bias ranging between −0.5 μg m −3 at rural sites and −5.5 μg m −3 at urban and suburban sites. CAMx performance for OA was clearly worse than for the other PM compounds (negative bias ranging between −40% and −75%). The comparisons of model results with OA sources (identified by PMF analysis) shows that the VBS scheme underestimates freshly emitted organic aerosol while SOAP overestimates. The VBS scheme correctly reproduces biomass burning (BBOA) contributions to primary OA concentrations (POA). In contrast VBS slightly underestimates the contribution from fossil-fuel combustion (HOA), indicating that POA emissions related to road transport are either underestimated or associated to higher volatility classes. The VBS scheme under-predictes the SOA too, but to a lesser extent than CAMx-SOAP. SOA underestimation can be related to corresponding underestimation of either aging processes or precursor emissions. This indicates that improvements in the emission inventories for semi- and intermediate-volatility organic compounds are needed for further progress in this area. Finally, the comparison between modelled and observed SOA sources points out the urgency to include processing of OA in particle water phase into SOA formation mechanisms, to reconcile model results and observations. [ABSTRACT FROM AUTHOR]

Personal cars have been considered as a main air pollution sources. The amount of vehicle emissions correlates with urban traffic, which is affect average trip speed. With the use of Tehran emissions model of personal cars, and the online data of speed and travel time, instantaneous NOx, HC and CO mass production were calculated. Emission model was developed based on thirty portable emission tests and speed data were obtained by traffic sensors installed in a few highways of Tehran. The important application of this system is to assessment of transportation emissions reduction scenarios.