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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. © 2021

Ground-level ozone is harmful to both human health and ecological environment, which is formed by reactions of nitrogen oxides (NOx) and volatile organic compounds (VOCs) in the presence of sunlight. With the increasingly rigorous ozone standard in the U.S., it is important to examine ozone pollution control strategies to help air-quality management in a concentrated industrial region, such as Beaumont-Port Arthur (BPA) areas in Texas of USA. In this study, the method of Empirical Kinetics Modeling Approach (EKMA) associated with the comprehensive air quality modeling with extensions (CAMx) have been employed to demonstrate feasible air-quality control strategies to examine the effects of VOCs and NOx abatement on ozone concentration in the BPA area. Case studies included base case simulations as well as those with 25%, 50%, and 75% reductions of anthropogenic NOx and/or VOCs emissions in the BPA area, which were based on the TCEQ-provided meteorological and emission inventories for a high ozone episode. Simulation results indicated that NOx abatement is more effective than VOCs abatement in reducing ozone concentrations for BPA area, which suggestively belongs to the NOx-sensitive regime for ozone pollution. The average 8-hr ozone could be reduced 3.3%, 7.0% and 11.1%, respectively, by 25%, 50% and 75% of both NOx and VOCs emission abatement. The effect of pollutant abatement on ozone reduction is observed to be different at eight monitor stations in BPA region. Also, the nonlinear relationship between ozone and its precursors has been observed. This study could be helpful to provide scientific and technological support for the future development of air-quality management and ozone control strategies in a concentrated industrial region.

The atmospheric mineral aerosol reaction (AMAR) model, which was developed to simulate dust-driven heterogeneous chemistry of SO2 and NOx, was combined with the comprehensive air quality model with...

As much of the population lives in close proximity to high-traffic roads, there is the potential for health impact assessments based on regional air quality modeling to underpredict health impacts. We compare the estimated health impacts from fine particulate matter (PM2.5) using local (0.04 × 0.04 km upscaled to census block group resolution) compared to regional (12 × 12 km resolution) modeled concentrations for three locations in Connecticut: Hartford, New Haven, and Willimantic. We use concentration estimates from the Comprehensive Air Quality Model with Extensions (CAMx) regional model and a hybrid model combining CAMx with a near road model (HYCAMR) in the Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP-CE) to calculate the difference in estimated human health impacts using different resolution air quality estimates from PM2.5 exposure including mortality, emergency room visits, hospitalizations, and asthma exacerbation. This provides an estimate of the potential underprediction of health impacts resulting from not accounting for the sharp concentration gradients in near road environments in urban areas. The fine-scale estimates capture the elevated concentrations near the roadways leading to increased estimates of overall mortality and morbidity in the population. We find an increase in the estimated likelihood of emergency department visits and mortality in the urban core. We also compare the impact of model resolution on the health impact estimates for different demographic groups. Of the locations investigated, we see the largest differences between demographic groups in Willimantic, CT. Our results indicate that using regional air pollutant concentrations may lead to an underprediction of human health impacts from air pollution exposure.

In this study, the downscaling modeling chain for prediction of weather and atmospheric composition is described and evaluated against observations. The chain consists of interfacing models for forecasting at different spatiotemporal scales that run in a semi-operational mode. The forecasts were performed for European (EU) regional and Danish (DK) subregional-urban scales by the offline coupled numerical weather prediction HIRLAM and atmospheric chemical transport CAMx models, and for Copenhagen city-street scale by the online coupled computational fluid dynamics M2UE model. The results showed elevated NOx and lowered O3 concentrations over major urban, industrial, and transport land and water routes in both the EU and DK domain forecasts. The O3 diurnal cycle predictions in both these domains were equally good, although O3 values were closer to observations for Denmark. At the same time, the DK forecast of NOx and NO2 levels was more biased (with a better prediction score of the diurnal cycle) than the EU forecast, indicating a necessity to adjust emission rates. Further downscaling to the street level (Copenhagen) indicated that the NOx pollution was 2-fold higher on weekends and more than 5 times higher during the working day with high pollution episodes. Despite high uncertainty in road traffic emissions, the street-scale model effectively captured the NOx and NO2 diurnal cycles and the onset of elevated pollution episodes. The demonstrated downscaling system could be used in future online integrated meteorology and air quality research and operational forecasting, as well as for impact assessments on environment, population, and decision making for emergency preparedness and safety measures planning.

Rapid sulfate formation is recognized as a key characteristic of severe winter haze in China. However, air quality models tend to underestimate sulfate formation during heavy haze periods, and heterogeneous formation pathways have been proposed as promising mechanisms to reduce gaps between observation and model simulation. In this study, we implemented a reactive SO2 uptake mechanism through the SO2+NO2 heterogeneous reactions in the Comprehensive Air Quality Model with Extensions (CAMx) to improve simulation of sulfate formation in the Yangtze River Delta (YRD) region. Parameterization of the SO2+NO2 heterogeneous reactions is based on observations in Beijing and considered both the impact of relative humidity and aerosol pH on sulfate formation. Ammonia is reported to be critical for the formation of secondary inorganic aerosols. Estimation of ammonia emissions is usually associated with large uncertainties and models tend to underestimate ammonia concentrations substantially. Sensitivity tests were conducted to evaluate the influence of the SO2+NO2 heterogeneous reactions as well as ammonia emissions on modeled sulfate concentrations during a period with several heavy haze episodes in the YRD region. Base case model results show large underestimation of sulfate concentrations by 36 % under polluted conditions in the YRD region. Adding the SO2+NO2 heterogeneous reactions or doubling ammonia emissions alone leads to slight model improvement ( ∼6 %) on simulated sulfate concentrations in the YRD region. However, model performance significantly improved when both the SO2+NO2 heterogeneous reactions and doubled ammonia emissions were included in the simulation: predicted sulfate concentrations during polluted periods increased from 23.1 µ g m −3 in the base scenario to 29.1 µ g m −3 (representing an increase of 26 %). Aerosol pH is crucial for the SO2+NO2 heterogeneous reactions, and our calculated aerosol pH is always acidic and increased by 0.7 with doubled ammonia emissions. Modeling results also show that this reactive SO2 uptake mechanism enhanced sulfate simulations by 1 to 5 µ g m −3 for the majority of the eastern and central parts of China, with more than 20 µ g m −3 increase in sulfate concentrations over the northeastern plain. These findings suggest that the SO2+NO2 heterogeneous reactions could be potentially important for sulfate formation in the YRD region as well as other parts of China. Further studies are needed to constrain the uncertainties associated with the parameterization of the SO2+NO2 heterogeneous reactions based on local data as well as to evaluate this mechanism in other regions. In addition, ammonia emissions were found to be a key driving variable of the spatial patterns of sulfate enhancement due to the new pathway. Substantial efforts are needed to improve the accuracy of the ammonia emission inventory.

Regional transport always plays a crucial role in the formation and dissipation of haze over the Beijing–Tianjin–Hebei (BTH) region. This study, conducted using pollution and meteorological observations and the Weather Research and Forecasting model (WRF) coupled with the Comprehensive Air Quality Model with Extensions (CAMx), investigated the possible meteorological causes for the occurrence of haze pollution and quantitatively assessed the PM2.5 transport contribution to haze episodes that occurred in Beijing in January and July 2015. The results indicated that modeling system reproduced the spatial-temporal variation in PM2.5 concentrations in the BTH region well. During the study period, haze episodes were primarily attributed to meteorological conditions such as planetary boundary layer height, relative humidity, wind vector, and temperature inversion, in the context of pollution emissions. Analysis of surface PM2.5 transport showed that 62.89% of the surface PM2.5 in Beijing was came from local emissions, with the remaining 23.69% and 13.42%, on average, originating from short- and long-range transport during the study period. The percentage of contribution varied with the evolutionary stage of the haze episodes, showing the joint influence of local emissions and regional transport on haze pollution in Beijing. Additionally, investigation of vertical PM2.5 transport identified the following three major pathways: a northwest–southeast pathway in January (at all layers below 1200 m, though it was stronger above 600 m), a southeast–northwest pathway in July (at all layers below 800 m), and a southwest–northeast pathway during both months (at a height of 200–1200 m). Moreover, the magnitude of daily PM2.5 transport fluxes during the haze episodes was generally stronger than the corresponding monthly average. These results provide a scientific basis for strategic control of both multiple cities and provinces and in-depth knowledge of the mechanisms and sources of haze pollution in the BTH region.

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 NOx and SOx 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 SO2 concentration is 1.5–1.8%; of total S deposition is 1.0–1.7%; and of SO2 emissions is 1.4–1.8% per year. The rate of decline in NOy deposition of 0.6–1.4% per year is similar to the 0.5–1.6% per year reduction in NOx emissions, thus showing that the changes in deposition have tracked changes in emissions of SO2 and NOx emissions quite well. Further reducing N deposition could face some challenges due to increasing NHx contribution from NH3 emissions and the expectation of these to increase globally. Our study also examined the transference ratios of NOy and SOx in the context of the secondary NAAQS for NOx and SOx and found them to be sensitive to emission reductions over the study period.

Bengaluru - capital of the state of Karnataka is the original “Silicon Valley” of India. In this paper, we present a comprehensive snapshot of the state of air quality in Bengaluru, along with an emissions inventory for the pollutants necessary for chemical transport modeling at 0.01° grid resolution (approximately 1-km), for an urban airshed covering 60 × 60 grids (4300 km2). For 2015, emission estimates for the city are 31,300 tons of PM2.5, 67,100 tons of PM10, 5300 tons of SO2, 56,900 tons of NOx, 335,550 tons of CO, and 83,500 tons of NMVOCs. Overall, transport is the key emission source for Bengaluru - vehicle exhaust and on-road dust resuspension account for a combined 56% and 70% of total PM2.5 and PM10 emissions; followed by industries (17.8% including the brick kilns), open waste burning (11.0%), and domestic cooking, heating, and lighting (6.5%), in case of PM2.5. We conducted particulate pollution source apportionment of local and non-local sources, using WRF meteorological model and CAMx chemical transport modeling system. A comparison of range of 24-hr average modeled PM2.5 concentrations (36.5 ± 9.0 μg/m3) and monitored PM2.5 concentrations (32.3 ± 24.2 μg/m3) by month, shows that the model catches the quantitative ranges and qualitative trends. The modeled source contributions highlight the vehicle exhaust (28%) and dust (including on-road resuspended dust and construction activities) (23%), and open waste burning (14%), as the key air pollution sources. Unless there is an aggressive strategy to improve urban planning and public transport options, pollutant emissions under the business as usual scenario are expected to increase at least 50% in 2030 and doubling the urban area with PM2.5 annual averages above the national ambient standard of 40 μg/m3.

Fine particle (PM2.5) and ozone (O3) are major air pollutants in China, especially in developed city clusters. A comprehensive field campaign, the Campaign on Air Pollution and Urban Meteorology in Yangtze River Delta (CAPUM-YRD), eastern China is carried out in 2016 to enhance the understanding of regional PM2.5 and O3 pollution. Two super sites in Shanghai, one in Hangzhou, as well as nineteen national monitoring stations in Nanjing and Hefei jointly participate in the campaign. In this study, regional PM2.5 and O3 pollution episodes are characterized based on summer and winter experiments during the CAPUM-YRD. Further, trajectory simulation and source apportionment technology in Comprehensive Air Quality Model with Extensions (CAMx) are applied to explore the source of the pollution episodes. We find that regional synchronous PM2.5 pollution episodes (over 120 μg/m3) occur frequently in YRD. Secondary inorganic and carbonaceous components account for a major proportion (70–80%) in PM2.5. Nitrate concentration is significantly higher (lower) than sulfate in winter (summer). The secondary conversion of sulfur and nitrogen increases alongside elevated PM2.5 levels, with a maximum ratio of 0.28 and 0.18 in winter, respectively. Source apportionment results suggest that the contribution of emissions within YRD dominates in PM2.5 (over 60%) compared to other regions. The inter-regional transport from the north-northwest in eastern China can contribute over 20% to PM2.5 in YRD, with a maximum of 28.4% in Nanjing. Under the transport by enhanced northerly winds, PM2.5 concentrations may increase explosively, with observed peak values in Hefei (312.6 μg/m3) and Nanjing (255.7 μg/m3). Moreover, high levels and remarkable spatial heterogeneity of O3 are observed over YRD in summer, with daily maximum 8-h average O3 above 300 μg/m3 in Nanjing. The occurrence of O3 pollution episodes is significantly impacted by favorable weather conditions and transport at multiple spatial scales. Regional contribution results demonstrate that super-regional transport is prominent (29.4–50.7%) in O3 pollution, especially in coastal cities like Shanghai (30.3–63.0%). Our results suggest that enhanced regional collaboration and efforts are of extreme necessity in long-term and optimized control of severe PM2.5 and O3 pollution in YRD.

With the stringent emission control measures implemented in recent years, the overall air quality in China has been improved greatly. However, high ozone (O3) concentrations have become a more and more severe air pollution issue in the rapidly developing Yangtze River Delta (YRD) region of eastern China including Shanghai, Jiangsu, Zhejiang and Anhui provinces. The 90th percentile of O3-8 h concentration in the YRD region increased from 144 μg/m3 in 2013 to 168 μg/m3 in 2017. To investigate the sources of O3 within the YRD region, we use a tagged-species method in the Comprehensive Air Quality Model with Extensions (CAMx) called Ozone Source Apportionment Technology (OSAT) to quantify O3 contributions by source regions and sectors in Spring, Summer and Fall. We find that the O3 pollution in Shanghai, southern Jiangsu and northern Zhejiang is caused by the joint effect of local to regional precursor emissions combined with super-regional O3 transport. However, these contributions vary among seasons and pollution events. Super regional transport is the major contributor to average O3 concentration while local and upwind adjacent area contributions can dominate during high O3 concentration episodes. Source sector analysis indicates that industry and vehicle emissions are major anthropogenic sources. Within the industrial sector, power plants, boilers, and petroleum industry are the top three contributors. Reducing super-regional O3 transport is of the most importance to lowering the O3 background but local to regional precursor emission reductions are also of great significance to control O3 episodes with collaboration at the regional level offering potential for synergistic benefits to adjacent cities.

With a rapid increase in air traffic, aviation has become an increasingly important contributor to anthropogenic air pollutants (particularly nitrogen oxides (NOX)) 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 (SO2), carbon monoxide (CO), hydro-carbons (HC), particulate matter (PM2.5 and PM10), 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 PM2.5 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.

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 NOx 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.

The aim of this work is to explore the aerosol optical depth (AOD) data provided by different sources, namely satellite observations, air quality modelling and Aerosol Robotic Network (AERONET) observations, in order to improve characterisation of aerosol spatial distribution and to assess the contribution of the dust events on AOD over Portugal. Thus, the spatial and temporal variations of the AOD data were analysed for May 2011 taking into account the occurrence of mineral dust events. Satellite data obtained by Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) instrument and air quality modelling results from the Comprehensive Air Quality Model (CAMx) over Portugal were explored. In this work, AOD values with a temporal resolution of 15 min were obtained from SEVIRI. Additionally, 3D data with 23 vertical layers for each aerosol constituent, size distribution and chemical composition were obtained from the modelling approach and used to compute the AOD at 550 nm by integrating of aerosol extinction coefficient (Qext) over the total atmospheric column. Despite the outbreaks of mineral dust occurring during this period, the overall contribution of organic carbon (OC), black carbon (BC) and sulphate (SO4) compounds to the monthly average AOD values estimated by the model is very important achieving 95% mainly located in the northern part of the studied region. The model outputs and SEVIRI data were validated with AERONET observations presenting correlation coefficients of 0.71 and 0.68 respectively. Three different modes of aerosol were classified based on Angstrom coefficient versus AOD and distinguishing between the dominance of fine and coarse aerosol fractions. The analysis implemented reveal that intercomparison of satellite observations with air quality modelling contribute to better understanding of the discrepancies presented in spatial pattern of AOD.

A three-dimensional chemical transport model, PMCAMx, was used to quantify the contribution of biomass burning organic aerosol (bbOA) to total organic aerosol (OA) concentrations in the continental U.S. Simulations were performed during three seasonally-representative months (April, July, and September 2008). Biomass burning is predicted to contribute 9% of the domain-averaged OA in April, 28% in July and 13% in September. Secondary OA from semivolatile and intermediate volatility organic compounds is the largest contributor to bbOA concentrations for all months simulated, followed by fresh primary OA. PMCAMx bbOA predictions using the Volatility Basis Set were compared to the results of CAMx version 6.10 that assumes that bbOA is nonvolatile and inert. PMCAMx predicts 66%, 113%, and 108% higher average concentration values of bbOA for April, July, and September, respectively. Predicted OA concentrations at biomass-impacted sites were compared to observed values from the STN and IMPROVE networks. The treatment of biomass burning emissions as semivolatile and reactive improved model performance during the spring and summer. During the fall both models overpredicted the OA levels, suggesting that the fire emissions may have been overestimated. In this case the additional SOA produced in PMCAMx resulted in worse performance.

A comprehensive observation was conducted to reveal the characteristics of submicron and fine aerosols and their chemical components in Beijing in autumn. The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) model, Weather Research & Forecasting (WRF) and Comprehensive Air Quality Model with Extension (CAMx) were applied to identify the impacts of emissions from surrounding areas on PM2.5 concentrations in Beijing for different study episodes. These results showed that the monthly average concentration of non-refractory submicron aerosols (NR-PM1) was 60.20 ± 53.48 μg/m3, with organics being the major fraction (42.33%), followed by NO3− (22.87%), SO42− (18.70%), NH4+ (12.24%) and Cl− (3.86%). The PSCF and CWT analysis indicated common high source regions was located in the western Shandong, northern Henan and southern Hebei, and the distribution of the source areas usually varied with species during different episodes. The regional source apportionment results revealed that 52.36% of surface PM2.5 in Beijing was contributed by surrounding sources in terms of monthly mean and the outside contribution increased to 64.56% during the haze days, indicating the strong influence of regional transport on Beijing haze pollution. Note that the PM2.5 inflows for Beijing mainly came from Baoding and Langfang, and outflows towards Chengde and Zhangjiakou, identifying two key transport pathways: the southwest-northeast pathway and the southeast-northwest pathway. The PM2.5 inflow fluxes from surroundings were much higher than outflows from Beijing, leading to the peaking PM2.5 pollution, with the highest concentrations occurring from 00:00 to 11:00 LT, 14 October 2016. Based on the net PM2.5 fluxes and their vertical distributions, we discovered the PM2.5 transport mainly occurred at 400–800 m during the entire episode, while at 600–1000 m for a heavy pollution episode, both followed by the southwest-northeast pathway. However, the PM2.5 fluxes were far lower for a clean episode, and followed by the northwest-southeast pathway.

Recent observation and modeling-based studies have shown how air quality has been positively affected by the containment measures enforced due to the COVID-19 outbreak. This work aims to analyze Lombardy&rsquo, s NO2 atmospheric concentration during the spring lockdown. The region of Lombardy is known for having the largest number of residents in Italy and high levels of pollution. It is also the region where the first European confinement measures were imposed by the Italian government. The modeling suite composed of CAMx (Comprehensive Air Quality Model with Extensions) and WRF (Weather Research and Forecasting model) provides the setting to compare the atmospheric NO2 concentration from mid-February to the end of March with a business as usual situation. The main interest in this work is to investigate the response of NO2 atmospheric concentration to increasingly reduced road traffic. We can simulate, for the first time, a real circumstance of progressively reduced mobility, as well as validating it with measured air quality data. Focusing on the city of Milan, we found that the decrease in NO2 concentration reflects progressively reduced traffic contraction. In the case of a large traffic abatement (71%), the concentration level is reduced by one third. We also find that industrial activities have a relevant impact on NO2 atmospheric concentration, especially in the provinces of Brescia and Bergamo. This study provides an overview of how incisive policies must be implemented to achieve the set environmental targets and protect human health.

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.

This paper provides a detailed, thorough analysis of air pollution by benzo[a]pyrene (BaP) in the Czech Republic. The Czech residential sector is responsible for more than 98.8% of BaP, based on the national emission inventory. According to the data from 48 sites of the National Air Quality Monitoring Network, the range of annual average concentration of BaP ranges from 0.4 ng&middot, m&minus, 3 at a rural regional station to 7.7 ng&middot, 3 at an industrial station. Additionally, short-term campaign measurements in small settlements have recorded high values of daily benzo[a]pyrene concentrations (0.1&ndash, 13.6 ng&middot, 3) in winter months linked to local heating of household heating. The transboundary contribution to the annual average concentrations of BaP was estimated by the CAMx model to range from 46% to 70% over most of the country. However, the contribution of Czech sources can exceed 80% in residential heating hot spots. It is likely that the transboundary contribution to BaP concentrations was overestimated by a factor of 1.5 due to limitations of the modeling approach used. During the period of 2012&ndash, 2018, 35&ndash, 58% of the urban population in the Czech Republic were exposed to BaP concentrations above target. A significant decreasing trend, estimated by the Mann-Kendall test, was found for annual and winter BaP concentrations between 2008 and 2018.

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.

In this study a high resolution modeling system is developed to simulate Quercus pollen concentrations in the greater area of Thessaloniki, Greece, under an a priori oak phenological season. The modeling system consists of three models in series, the Weather Research and Forecasting (WRF) meteorological model, the natural emissions model NEMO for Quercus pollen emissions and the chemistry-transport model CAMx. The modeling system is evaluated with daily meteorological and pollen measurements during the phenological season of 2016 of Quercus taxa. The modeling system's performance is satisfactory on both meteorology and Quercus pollen concentrations, although for the latter the relative uncertainty is slightly above the 50% criterion usually applied in air quality modeling. Additional analysis was performed on three parameters related to pollen emissions, namely the assigned pollen production, the spread of the phenology and the assigned diameter. The analysis shows that the greatest impact on Quercus pollen concentrations, on both near the sources as well at remote areas, is the assigned pollen production, followed by the spread and the assigned diameter.

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 NOx 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.

Research has shown that excess reactive nitrogen (Nr) deposition in the Greater Yellowstone Area (GYA) of the United States has passed critical load thresholds and is adversely affecting sensitive ecosystems in this area. To better understand the sources causing excess Nr deposition, the Comprehensive Air Quality Model with extensions (CAMx), using Western Air Quality Study (WAQS) emission and meteorology inputs, was used to simulate Nr deposition in the GYA. CAMx's Particulate Source Apportionment Technology (PSAT) was employed to estimate contributions from agriculture (AG), oil and gas (OG), fire (Fire), and other (Other) source sectors from 27 regions, including the model boundary conditions (BC) representative of international contributions, to the simulated Nr for 2011. Emissions from the AG and Other source sectors are predominantly from reduced N and oxidized N compounds, respectively. The model evaluation revealed a systematic underestimation in ammonia (NH3) concentrations by 65 % and overestimation in nitric acid concentrations by 108 %. The measured inorganic N wet deposition at National Trend Network sites in the GYA was overestimated by 31–49 %, due at least partially to an overestimation of precipitation. Source apportionment results showed that the AG sector was the single largest contributor to the GYA total Nr deposition, contributing 34 % on an annual basis. Seventy-four percent of the AG contributions originated from the Idaho Snake River valley, with Wyoming, California, and northern Utah contributing another 7 %, 5 %, 20 and 4 % respectively. Contributions from the OG sector were small at about 1 % over the GYA, except in the southern Wind River Mountain Range during winter where they accounted for more than 10 %, with 46 % of these contributions coming from OG activities in Wyoming. Wild and prescribed fires contributed 18 % of the total Nr deposition, with fires within the GYA having the highest impact. The five largest source area contributions to the annual total Nr deposition in the GYA were 1) the Snake River valley (3 8 % with AG 68 %, OG 2 %, Fire 15 %, and Other 16 %); 2) BC (21 %); 3) Wyoming (12 % with AG 19 %, OG 5 %, Fire 38 %, and Other 39 %); 4) California (7 % with AG 26 %, OG 1 %, Fire 14 %, and Other 59 %); and 5) northern Utah (6 % with AG 25 %, OG 2 %, Fire 10 %, and 25 Other 63 %). These results suggest that Nr deposition over the GYA, especially in the western region, was above the critical loads for sensitive ecosystems, and 22 AG from the Snake River valley was the largest contributor. Distant source regions were also important, with large contributions from the BC, i.e., international source regions.

Missing or incomplete data in short or long intervals is a common problem in measuring air pollution. Severe issues may arise when dealing with missing data for time-series prediction schemes or mean analysis. This study aimed to develop a new regression imputation framework to impute missing values in the hourly air quality data set of Tehran and enhance the applicability of Tehran Air Pollution Forecasting System (TAPFS). The proposed framework was designed based on three types of features including measurements of other stations, WRF and CAMx physical models. In this framework, elastic net and neuro-fuzzy networks were efficiently combined in a two-layer structure. The framework was applied on Tehran's air pollution monitoring network. The hourly imputing results of the suggested method were seen to be superior to existing methods according to statistical criteria such as RMSE, MAE and R-values. Average R-values of 0.88, 0.73, 0.76 and 0.79 were obtained for O3, NO, PM2.5 and PM10, respectively. The measurements of other stations had the main predictive power with a modest increase for the two physical models. The benefit of the models was somewhat higher for stations on boundaries of monitoring network. In addition, the central stations had better performance than the boundary stations and an approximately 0.05 increase was obtained in average R-value.

Surface solar radiation (SSR) observations have indicated an increasing trend in Europe since the mid-1980s, referred to as solar "brightening". In this study, we used the regional air quality model, CAMx (Comprehensive Air Quality Model with Extensions) to simulate and quantify, with various sensitivity runs (where the year 2010 served as the base case), the effects of increased radiation between 1990 and 2010 on photolysis rates (with the PHOT1, PHOT2 and PHOT3 scenarios, which represented the radiation in 1990) and biogenic volatile organic compound (BVOC) emissions (with the BIO scenario, which represented the biogenic emissions in 1990), and their consequent impacts on summer surface ozone concentrations over Europe between 1990 and 2010. The PHOT1 and PHOT2 scenarios examined the effect of doubling and tripling the anthropogenic PM2.5 concentrations, respectively, while the PHOT3 investigated the impact of an increase in just the sulfate concentrations by a factor of 3.4 (as in 1990), applied only to the calculation of photolysis rates. In the BIO scenario, we reduced the 2010 SSR by 3% (keeping plant cover and temperature the same), recalculated the biogenic emissions and repeated the base case simulations with the new biogenic emissions. The impact on photolysis rates for all three scenarios was an increase (in 2010 compared to 1990) of 3–6% which resulted in daytime (10:00–18:00 Local Mean Time – LMT) mean surface ozone differences of 0.2–0.7ppb (0.5–1.5%), with the largest hourly difference rising as high as 4–8ppb (10–16%). The effect of changes in BVOC emissions on daytime mean surface ozone was much smaller (up to 0.08ppb, ∼ 0.2%), as isoprene and terpene (monoterpene and sesquiterpene) emissions increased only by 2.5–3 and 0.7%, respectively. Overall, the impact of the SSR changes on surface ozone was greater via the effects on photolysis rates compared to the effects on BVOC emissions, and the sensitivity test of their combined impact (the combination of PHOT3 and BIO is denoted as the COMBO scenario) showed nearly additive effects. In addition, all the sensitivity runs were repeated on a second base case with increased NOx emissions to account for any potential underestimation of modeled ozone production; the results did not change significantly in magnitude, but the spatial coverage of the effects was profoundly extended. Finally, the role of the aerosol–radiation interaction (ARI) changes in the European summer surface ozone trends was suggested to be more important when comparing to the order of magnitude of the ozone trends instead of the total ozone concentrations, indicating a potential partial damping of the effects of ozone precursor emissions' reduction., Atmospheric Chemistry and Physics, 18 (13), ISSN:1680-7375, ISSN:1680-7367

A well-evaluated Comprehensive Air quality Model with extensions (CAMx) was used to simulate concentrations of secondary inorganic aerosols in fine particulate matter (PM2.5) over Pearl River Delta (PRD) region during two separate months (April and October) in 2013. An indicator of adjusted gas ratio (AdjGR) was used to characterize PM chemistry under both NH3-poor (NP) and NH3-rich (NR) conditions as well as to identify their respective spatiotemporal patterns at different PM2.5 levels. The results were as follows: (1) Based on both observed molar ratio of [NH4+]/[SO42−] and modeled AdjGR, NR and NP conditions exhibited diurnal, daily, and seasonal variations. (2) A larger area in PRD had NP conditions over the two months when pollution was apparent; this NP region tended to occur downwind of PRD in October and the central region of PRD in April, with high PM2.5 concentrations in both. (3) This wider NP distribution could be related to higher nitrogen oxidation ratio (NOR), with more NOx converting to nitrate. Under conditions of higher pollution, there were relative lower degree of sulfate neutralization (DSN) and particle neutralization ratio (PNR). This supports the claim that NH3 may not be fully neutralized by SO42−. (4) Modeled AdjGR displayed clear hourly variations, with the lowest levels occurring in the afternoon. Reducing NH3 emission is not as efficient as NOx at increasing evening nitrate concentrations. (5) To mitigate PM2.5 pollution even further, a greater reduction of NH3 should be suggested in chemical regions transiting to NR condition when there are lower SO2 and NOx emissions.

Turnaround operations (start-up and shutdown) are critical operations in olefin plants, which emit large quantities of VOCs, NOx and CO. The emission has great potentials to impact the ozone level in ozone nonattainment areas. This study demonstrates a novel practice to minimize the ozone impact through coordinated scheduling of turnaround operations from multiple olefin plants located in Houston, Texas, an ozone nonattainment area. The study considered two olefin plants scheduled to conduct turnaround operations: one start-up and one shutdown, simultaneously on the same day within a five-hour window. Through dynamic simulations of the turnaround operations using ASPEN Plus Dynamics and air quality simulations using CAMx, the study predicts the ozone impact from the combined effect of the two turnaround operations under different starting-time scenarios. The simulations predict that the ozone impact from planned turnaround operations ranges from a maximum of 11.4 ppb to a minimum of 1.4 ppb. Hence, a reduction of up to 10.0 ppb can be achieved on a single day based on the selected two simulation days. This study demonstrates a cost-effective and environmentally benign ozone control practice for relevant stakeholders, including environmental agencies, regional plant operators, and local communities.

The regional climate model RegCM4.4, including the surface model CLM4.5, was offline coupled to the chemistry transport model CAMx version 6.30 in order to investigate the impact of the urban canopy induced meteorological changes on the longterm summer photochemistry over central Europe for the 2001–2005 period. First, the urban canopy impact on the meteorological conditions was calculated performing a reference experiment without urban landsurface considered and an experiment with urban surfaces modeled with the urban parameterization within the CLM4.5 model. In accordance with expectations, strong increases of urban surface temperatures (up to 2–3 K), decreases of wind speed (up to −1 ms−1) and increases of vertical turbulent diffusion coefficient (up to 60–70 m2s-1) were found. For the impact on chemistry, these three components were considered. Additionally, we accounted for the effect of temperature enhanced biogenic emission increase. Several experiments were performed by adding these effects one-by-one to the total impact: i.e., first, only the urban temperature impact was considered driving the chemistry model; secondly, the wind impact was added and so on. We found that the impact on biogenic emission account for minor changes in the concentrations of ozone (O3), oxides of nitrogen NOx = NO + NO2 and nitric acid (HNO3). On the other hand, the dominating component acting is the increased vertical mixing, resulting in up to 5 ppbv increase of urban ozone concentrations while causing −2 to −3 ppbv decreases and around 1 ppbv increases of NOx and HNO3 surface concentrations, respectively. The temperature impact alone results in reduction of ozone, increase in NO, decrease in NO2 and increases of HNO3. The wind impact leads, over urban areas, to ozone decreases, increases of NOx and a slight increase in HNO3. The overall impact is similar to the impact of increased vertical mixing alone. The Process Analysis (PA) technique implemented in CAMx was adopted to investigate the causes of the modeled impacts in more details. It showed that the main process contributing to the temperature impact on ozone is a dry-deposition enhancement, while the dominating process controlling the wind impact on ozone over cities is the advection reduction. In case of the impact of enhanced turbulence, PA suggests that ozone increases are, again as assumed, the result of increased downward vertical mixing supported by reduced chemical loss. Comparing the model concentrations with measurements over urban areas, a slight improvement of the model performance was achieved during afternoon hours if urban canopy forcing on chemistry via meteorology was accounted for. The study demonstrates that disregarding the urban canopy induced meteorological effects in air-quality oriented modeling studies can lead to erroneous results in the calculated species concentrations. However, it also shows that the individual components are not equally important: urban canopy induced turbulence effects dominate while the wind-speed and temperature related ones are of considerably smaller magnitude.

High surface ozone concentrations, which usually occur when photochemical ozone production takes place, pose a great risk to human health and vegetation. Air quality models are often used by policy makers as tools for the development of ozone mitigation strategies. However, the modeled ozone production is often not or not enough evaluated in many ozone modeling studies. The focus of this work is to evaluate the modeled ozone production in Europe indirectly, with the use of the ozone–temperature correlation for the summer of 2010 and to analyze its sensitivity to precursor emissions and meteorology by using the regional air quality model, the Comprehensive Air Quality Model with Extensions (CAMx). The results show that the model significantly underestimates the observed high afternoon surface ozone mixing ratios (≥ 60 ppb) by 10–20 ppb and overestimates the lower ones (

Sand and dust storms occur frequently in East Asia, and the dust particles could be transported to most areas of East Asia. To quantify the dust emissions in 18 dust source regions in China and Mongolia and their contributions to PM10 concentrations over East Asia, 10 sand and dust storms (SDSs) episodes in 2020 were simulated using the Comprehensive Air Quality Model with Extensions (CAMx). A dust emission scheme and a tagged method were incorporated. The model well captured the variations of PM10 concentrations during the SDSs episodes. The Gobi deserts in Mongolia were the most important sources of sand and dust in East Asia, with the highest dust emissions, contributing more than 60% to the PM10 concentrations over East-Central China, Japan, and South Korea. The dust emission from Inner Mongolia was about 1/3 of that in Mongolia, and contributed 20–30% to PM10 concentrations over East-Central China, Japan, and South Korea. However, more than 50% of the PM10 concentrations in Inner Mongolia originated from Mongolia in the SDSs events. Few dust aerosols from Taklimakan and Eastern Xinjiang could be transported to the areas further than its surrounding area. Because of the larger contribution of Mongolia to Northern China, the variation of the dust storm frequency in Northern China correlated well with the surface conditions in Mongolia. Anthropogenic emissions contributed less than 5% to the PM10 concentrations over most part of East Asia during the SDSs events.

Chemical transport models (CTMs) are widely used in scientific studies and air quality management. A particular application is to assess how pollutant concentrations, particularly ozone and PM, respond to emission controls. As part of a dynamic evaluation, two widely used CTMs, CMAQ and CAMx, were evaluated for how well they captured trends in observed surface ozone, as well as the changes in associated concentrations, between 2001 to 2011 and 2011 to 2016. Those periods were chosen as additional effort was used to improve emissions estimates for all three years. Prior studies found that both emissions inventories and observations indicate reductions in both ozone and NO2 during these periods, but studies have found that NO2 observations have not agreed as well with estimated emissions. In general, given the efforts to harmonize model inputs, the two models performed very similarly and captured the ozone declines for both the 2001–2011 and 2011–2016 periods at the national level, though moderate biases were found in some locations. At the national scale, ozone trends for the 2011–2016 period were better captured by the models than those for the 2001–2011 period. Both models overestimated the observed decrease in ground level NO2 at the higher end of the concentration spectrum. This is linked to, and can cause, the detected tendency of the models to have larger than observed increases in ozone at the lower end over time. At the metropolitan statistical area (MSA) level, the performance of capturing the ozone trends varied. For some MSA's, the models estimated the wrong direction in the trends; e.g., in Denver, where maximum 8-hr average ozone levels increased from 2001 to 2011, the models predicted a decrease. The US EPA recommends location specific Relative Response Factors (RRFs) to adjust results when applying the models for air quality management purposes. At the regional level, the simulated ozone RRFs were up to 8% larger than the observed RRFs for the 2001–2011 period, suggesting that the models underestimated the ozone decrease. For the 2011–2016 period, with a couple of exceptions, the simulated RRFs were up to 9% smaller than observed RRFs, indicating a negative bias in the simulated trend. For individual MSAs, the ratio of the simulated to observed RRFs ranged between 0.86 (Knoxville for 2001–2011) and 1.40 (Los Angeles for 2001–2011). This is possibly linked to potential biases in the estimated emissions trends. Such high biases could lead to similar biases in the estimated emissions controls required for an area to attain the air quality standards. The results indicate that there are both spatial and temporal biases in how well the two models have captured the observed ozone and NO2 trends. Air quality planning agencies should aim to diagnose and reduce such biases before using model results for air quality management.

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 (VD) for both SVOC (g) (VD,cmaq = 2.15 × VD,camx) and aerosols (VD,cmaq = 4.43 × Vd,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.

The compilation of high spatiotemporal resolution soil fugitive dust (SFD) emission inventories is significant for air pollution prevention and control. This study applied our recently compilated SFD emission inventory of “2 + 26” cities in north China to the CAMx model to estimate the contribution of SFD to the urban ambient particulate, and to simultaneously verify the accuracy of the emission inventory compilation method. Typical periods in spring and summer were selected to represent the highest and lowest levels of annual SFD pollution characteristics, respectively. Beijing, Tianjin, Shijiazhuang, Jinan, and Taiyuan were selected as representative cities. The simulation results of PM were consistent with the observations in terms of the concentration trend. In four of the five cities, the simulation results were significantly correlated with the observation results, with a Pearson correlation between 0.26 and 0.69. The contribution of SFD sources to PM2.5 and PM10 in the five cities were 4–12% and 18–36% in spring, and 1–3% and 4–12% in summer, respectively. The SFD contribution results in this study were not obviously different from earlier source apportionment researches. The relative proportions of SFD and industrial source contributions were reasonable in different seasons for different cities. Simultaneously, this study analyzed the regional contribution characteristics of SFD sources. Contributions to the PM in each city, amounting to ~30–65% of the SFD came from outside the city, including ~1–16% from the nearest city. The results of the high spatiotemporal resolution SFD emission inventory used in this study are accurate, proving that the compilation method is reasonable. Thus, this work provides an example for places with arid climates where suffered SFD pollution to estimate dust emission.

The Guanzhong Basin (GZB) has long been considered the most polluted city cluster in northwestern China with exposure to unhealthy levels of ozone (O3) in summer, which is strongly associated with adverse meteorological conditions and massive percussor emissions. In this study, four typical synoptic circulation types (CTs) were identified in the summers of 2014–2019 via the T-mode PCA classification method, including two polluted (southeast high and northeast ridge), one lightly polluted (east high), and one clean (northwest high) type. The impact of CTs on the atmospheric transport and diffusion conditions gradually weakened with decreasing altitude, while local circulation played a critical role near the ground, resulting in dominant northeast and southwest surface winds, high proportions of stagnation conditions (>50%). In particular, the meteorological conditions under the southeast high-type were marked by increasing influences of southerly airflow, high temperatures, low humidities, and the worst diffusion conditions, all of which were favorable for the local production of O3. While, the northeast ridge-type was characterized by easterly airflows in the upper air, which transported O3 and its precursors from upwind polluted areas. The regional transport model CAMx was applied to quantify the O3 sources over the GZB. The heaviest O3 pollution occurred under the southeast high-type, associated with the fast chemical formation rates and significant contributions from local emissions. The enhanced atmospheric oxidative capacity under the southeast high-type was suggested by elevated O3 and Ox (O3 + NO2) concentrations in the atmospheric boundary layer. Although the northeast ridge- and east high-type circulations led to similar chemical productions of O3, the cross-regional transport of O3 was increased under the northeast ridge-type and resulted in severe O3 pollution. This would serve to maximize regional O3 reduction under varying synoptic circulation conditions.

Post-processing techniques can provide significant improvement in the forecast skill of air quality models. In this study, the implementation of an analog-based technique to Comprehensive Air Quality Model with Extensions (CAMx) coupled with Weather Research and Forecasting (WRF) model results is examined. WRF-CAMx runs with a 2-km horizontal grid increment over Greece for one month of every season of the year 2012 (i.e., January, April, July and October). The analog ensemble (AnEn) technique attempts to improve the accuracy of ozone and particulate matter forecasts by using a method that searches for analogs in past forecasts. An optimization process that minimizes Root Mean Square Error (RMSE) metric has been used to find the best AnEn configuration. The corrected forecasts are computed with two approaches, i.e., AnEn ‘mean’ and AnEn ‘bias correction’ (AnEn-bias) approach. The methods are tested with observations from 23 surface stations for ozone, 16 stations for PM10 and 3 stations for PM2.5 for an 11-day period for each month. The results which are very similar for both techniques show an improvement of the forecast skill of all pollutants. The corrected forecasts have smaller RMSE and higher Correlation Coefficient (R). A reduction of 40 and 70% for AnEn RMSE values is found for ozone and particulate matter, respectively. For AnEn R, an improvement of 11% for ozone, 46% for PM10 and 26% for PM2.5 is estimated. These techniques are also successful in drastically reducing the mean bias of raw forecasts to close to zero.

The elevated point and on-road emission sources have been identified to be the dominant anthropogenic categories contributing to ozone formation in Southeast Texas of USA. In this study, additional CAMx simulations were carried out to quantify the reductions of ozone concentration in response to the reductions of the two emission sources in the amount of 25, 50 and 75% from the Southeast region based on the summertime Ozone Episode provided by the Texas Commission on Environmental Quality (TCEQ). The simulation results were analyzed and reported in the form of Empirical Kinetics Modeling Approach (EKMA) diagrams and further confirmed through additional Ozone Source Apportionment Technology (OSAT) simulations available in CAMx. While the results are observed to be highly depending on the monitor station, they have indicated that the control of elevated point emissions is slightly more effective in ozone reduction than that of on-road emissions. Averagely, a sole reduction of 48.3% from the elevated point source, or a sole reduction of 61.0% from the on-road source, or a combined reduction of 30.0% each from the two sources are required to meet a potential future 8-h ozone NAAQS of 65 ppb. The current study has demonstrated that CAMx simulations are powerful for the practice and the developed methodology is beneficial to potential future practice when new ozone episodes become available.

The destruction and removal efficiencies (DREs) for industrial flare combustion could be, in reality, less than the supposed standard values of 98%/99% because of various atmospheric and plant operating conditions. Thus, flaring during chemical plant shutdown (CPS) under low DREs would release larger quantities of VOCs and NOx than expected, which might rapidly worsen the regional ozone pollution under solar radiation. Therefore, it is vital to examine the quantity and sensitivity of ozone impacts owing to low DREs for flare combustion rather than standard values. In this paper, effect of dynamic low DREs on regional ozone impacts during CPS flaring has been systematically conducted by coupling Aspen Plus with CAMx modeling and simulation. Case studies indicated that 8-hr ozone caused by CPS flaring under low DREs could range from 6.08 to 7.28 ppb, which was much greater than that based on the standard DREs ranging from 1.8 to 2.19 ppb. This study also demonstrated that the 8-hr ozone increment could be significantly reduced from the maximum of 6.14 ppb to the minimum of 0.85 ppb by starting the CPS operations at the optimal time. Another important finding was that ozone impacts might slightly increase with the increase of flare stack height due to meteorological conditions including high wind speed and strong solar radiation. This study would provide scientific support for quantitative ozone evaluation caused by CPS flare emissions, which will enrich future solutions for cost-effective regional air-quality management and ozone pollution control.

Evaluating long-term air quality trends can demonstrate effectiveness of control strategies and guide future air quality management planning. Observations have shown that ozone (O3) and fine particulate matter (PM2.5) in the US have declined since as early as 1980 in some areas. But observation trends alone cannot separate effects of changes in local and global emissions to US air quality which are important to air quality planners. This study uses a regional model (CAMx) nested within a global model (GEOS-Chem) to characterize regional changes in O3 and PM2.5 due to the intercontinental transport and local/regional emissions representing six modeling years within five decades (1970–2020). We use the CAMx Source Apportionment Technology (OSAT/PSAT) to estimate contributions from 6 source sectors in 7 source regions plus 6 other groups for a total of 48 tagged contributions. On-road mobile sources consistently make the largest U.S. anthropogenic emissions contribution to O3 in all cities examined even though they decline substantially from 1970 to 2005 and also from 2005 to 2020. Off-road mobile source contributions increase from 1970 to 2005 and then decrease after 2005 in all of the cities. The boundary conditions, mostly from intercontinental transport, contribute more than 20 ppb to high maximum daily 8-h average (MDA8) O3 for all six years. We found that lowering NOx emissions raises O3 formation efficiency (OFE) across all emission categories which will limit potential O3 benefits of local NOx strategies in the near future. PM2.5 benefited from adoption of control devices between 1970 and 1980 and has continued to decline through 2005 and expected to decline further by 2020. Area sources such as residential, commercial and fugitive dust emissions stand out as making large contributions to PM2.5 that are not declining. Inter-regional transport is less important in 2020 than 1990 for both pollutants.

The Goddard Earth Observing System global chemical transport (GEOS-Chem) model was used at 2° × 2.5° resolution to simulate ozone formation for a base case representing year 2010 and a natural background case without worldwide anthropogenic emissions. These simulations provided boundary concentrations for base and natural background simulations with the Comprehensive Air Quality Model with Extensions (CAMx) on a North American domain (one-way nested) at 12 km × 12 km resolution over March–September 2010. The predicted maximum daily average 8 h (MDA8) background ozone for the US is largest in the mountainous areas of Colorado, New Mexico, Arizona, and California. The background MDA8 ozone in some of these locations exceeds 60 ppb, when averaged over the 10 days with the largest base-case ozone (T10base average). The background ozone generally becomes both a larger fraction of the base-case ozone in the western US and a smaller fraction in the eastern US when proceeding from spring to summer to the T10base average. The ozone difference between the base and background cases represents the increment to ozone from all anthropogenic sources. The path-integral method was applied to allocate this anthropogenic ozone increment to US anthropogenic emissions, Canadian/Mexican anthropogenic emissions, and the anthropogenic components of the lateral and top boundary concentrations (BCs). Using the T10base average MDA8 ozone, the relative importance of the sources is generally US emissions > anthropogenic lateral BCs > Canadian/Mexican emissions ≫ anthropogenic top BCs. Specifically, for 10 US urban areas, the source contributions were 12–53 ppb for US emissions, 3–9 ppb for lateral BCs, 0.2–3 ppb for Canadian/Mexican emissions, and ≤ 0.1 ppb for top BCs. The contributions of the lateral BCs are largest for the higher-elevation US sites in the Intermountain West and along the western boundary of the domain. In Denver, for example, the lateral BCs contribute 44 % to the T10base anthropogenic increment. Averaging over the 10 days in the background case with the largest MDA8 ozone (T10bkgd), the contribution from US emissions is reduced to 3–13 ppb at the 10 urban sites, leading to a reduction in the anthropogenic ozone increment. The contribution of the Canadian/Mexican emissions remains about the same (0.3–2 ppb), and the contribution from the lateral BCs increases (5–10 ppb), especially at the lower-elevation urban sites. The net effect at the urban sites is that the relative importance of the anthropogenic lateral BCs is significantly greater for the T10bkgd average than the T10base average. This is also true for rural sites studied, where the anthropogenic lateral BC contribution becomes as large as 68 % of the anthropogenic increment for the T10bkgd average. In addition to the source apportionment, we also used surface and ozonesonde measurements to evaluate GEOS-Chem and CAMx performance.

Vegetation is the leading emitter of volatile organic compounds (VOC), a key ingredient for ozone formation. The contribution of biogenic VOC (BVOC) emissions to regional ozone formation needs better quantification so that air quality regulators can effectively design emission control strategies. One of the key uncertainties for modeling BVOC emissions comes from the estimation of photosynthetically active radiation (PAR) reaching canopy. Satellite insolation retrieval data provide an alternative to prognostic meteorological models for representing the spatial and temporal variations of PAR. In this study, biogenic emission estimates generated with the MEGAN and BEIS biogenic emissions models using satellite or prognostic PAR are used to examine the contribution of BVOC to ozone in the United States. The Comprehensive Air Quality Model with Extensions (CAMx) is applied with Ozone Source Apportionment Technology (OSAT) and brute force zero-out sensitivity runs to quantify the biogenic contributions to ozone formation during May through September 2011. The satellite PAR retrievals are on average lower than modeled PAR and exhibit better agreement with SCAN and SURFRAD network measurements. Using satellite retrievals instead of modeled PAR reduces BEIS and MEGAN estimates of isoprene by an average of 3%–4% and 9%–12%, respectively. The simulations still overestimate observed ground-level isoprene concentrations by a factor of 1.1 for BEIS and 2.6 for MEGAN. The spatial pattern of biogenic ozone contribution diagnosed from OSAT differs from the brute force zero-out sensitivity results, with the former more smoothly distributed and the latter exhibiting peak impacts near metropolitan regions with intense anthropogenic NO x emissions. OSAT tends to apportion less ozone to biogenics as BVOC emissions increase, since that shifts marginal ozone formation toward more NO x -limited conditions. By contrast, zero-out source apportionment of ozone to biogenics increases with BVOC emissions. OSAT simulations with BEIS show that BVOCs typically contribute 10–19% to regional ozone concentrations at nonattainment receptor sites during episode days.

This study uses intake fraction, the fraction of emissions that are inhaled, to compare potential particulate matter exposure among different height emission sources. We use the Particulate Matter Source Apportionment Technology (PSAT) in the Comprehensive Air Quality Model with Extensions (CAMx) to estimate intake fraction for primary and secondary particulate matter species from different height emission sources. We develop an approach to quantify intake fraction for both primary and secondary particulate matter species emitted from all types of emission sources in the contiguous United States. To compute intake fraction for secondary particulate matter species, we consider the inhalation of the precursor gas and condensed species based on the common atomic unit between the emitted gas and particulate matter product. Our calculated intake fraction varies from 1.0 to 4.9 per million for primary particulate matter, 0.4 to almost 6.0 per million for secondary species, including inhalation of both particulate matter and the relevant precursor species. Intake fraction is consistently higher in the winter than the summer for all species from all emission heights. The shortest height sources, which include area sources, display intake fractions over an order of magnitude greater than more elevated sources.

Intercontinental ozone (O3) transport extends the geographic range of O3 air pollution impacts and makes local air pollution management more difficult. Phase 3 of the Air Quality Modeling Evaluation International Initiative (AQMEII-3) is examining the contribution of intercontinental transport to regional air quality by applying regional-scale atmospheric models jointly with global models. We investigate methods for tracing O3 from global models within regional models. The CAMx photochemical grid model was used to track contributions from boundary condition (BC) O3 over a North American modeling domain for calendar year 2010 using a built-in tracer module called RTCMC. RTCMC can track BC contributions using chemically reactive tracers and also using inert tracers in which deposition is the only sink for O3. Lack of O3 destruction chemistry in the inert tracer approach leads to overestimation biases that can exceed 10 ppb. The flexibility of RTCMC also allows tracking O3 contributions made by groups of vertical BC layers. The largest BC contributions to seasonal average daily maximum 8 h averages (MDA8) of O3 over the US are found to be from the mid-troposphere (over 40 ppb) with small contributions (a few ppb) from the upper troposphere–lower stratosphere. Contributions from the lower troposphere are shown to not penetrate very far inland. Higher contributions in the western than the eastern US, reaching an average of 57 ppb in Denver for the 30 days with highest MDA8 O3 in 2010, present a significant challenge to air quality management approaches based solely on local or US-wide emission reductions. The substantial BC contribution to MDA8 O3 in the Intermountain West means regional models are particularly sensitive to any biases and errors in the BCs. A sensitivity simulation with reduced BC O3 in response to 20 % lower emissions in Asia found a near-linear relationship between the BC O3 changes and surface O3 changes in the western US in all seasons and across the US in fall and winter. However, the surface O3 decreases are small: below 1 ppb in spring and below 0.5 ppb in other seasons.

This article presents the results of a detailed source apportionment study of the high particulate matter (PM) event in the Seoul Metropolitan Area (SMA), South Korea, during late February 2014. Using the Comprehensive Air Quality Model with Extensions with its Particulate Source Apportionment Technology (CAMx-PSAT), we defined 10 source regions, including five in China, for spatially and chemically resolved analyses. During the event, the spatially averaged PM10 concentration at all PM10 monitors in the SMA was 129 μg/m3, while the PM10 and PM2.5 concentrations at the BulGwang Supersite were 143 μg/m3 and 123 μg/m3, respectively. CAMx-PSAT showed reasonably good PM model performance in both China and the SMA. For February 23–27, CAMx-PSAT estimated that Chinese contributions to the SMA PM10 and PM2.5 were 84.3 μg/m3 and 80.0 μg/m3, respectively, or 64% and 70% of the respective totals, while South Korea's respective domestic contributions were 36.5 μg/m3 and 23.3 μg/m3. We observed that the spatiotemporal pattern of PM constituent concentrations and contributions did not necessarily follow that of total PM10 and PM2.5 concentrations. For example, Beijing-Tianjin-Hebei produced high nitrate concentrations, but the two most-contributing regions to PM in the SMA were the Near Beijing area and South Korea. In addition, we noticed that the relative contributions from each region changed over time. We found that most ammonium mass that neutralized Chinese sulfate mass in the SMA came from South Korean sources, indicating that secondary inorganic aerosol in the SMA, especially ammonium sulfates, during this event resulted from different major precursors originating from different regions.

Contributions of various anthropogenic sources to the secondary inorganic aerosol (SIA) in Europe as well as the role of biogenic emissions on SIA formation were investigated using the three-dimensional regional model CAMx (comprehensive air quality model with extensions). Simulations were carried out for two periods of EMEP field campaigns, February–March 2009 and June 2006, which are representative of cold and warm seasons, respectively. Biogenic volatile organic compounds (BVOCs) are known mainly as precursors of ozone and secondary organic aerosol (SOA), but their role on inorganic aerosol formation has not attracted much attention so far. In this study, we showed the importance of the chemical reactions of BVOCs and how they affect the oxidant concentrations, leading to significant changes, especially in the formation of ammonium nitrate. A sensitivity test with doubled BVOC emissions in Europe during the warm season showed a large increase in secondary organic aerosol (SOA) concentrations (by about a factor of two), while particulate inorganic nitrate concentrations decreased by up to 35 %, leading to a better agreement between the model results and measurements. Sulfate concentrations decreased as well; the change, however, was smaller. The changes in inorganic nitrate and sulfate concentrations occurred at different locations in Europe, indicating the importance of precursor gases and biogenic emission types for the negative correlation between BVOCs and SIA. Further analysis of the data suggested that reactions of the additional terpenes with nitrate radicals at night were responsible for the decline in inorganic nitrate formation, whereas oxidation of BVOCs with OH radicals led to a decrease in sulfate. Source apportionment results suggest that the main anthropogenic source of precursors leading to formation of particulate inorganic nitrate is road transport (SNAP7; see Table 1 for a description of the categories), whereas combustion in energy and transformation industries (SNAP1) was the most important contributor to sulfate particulate mass. Emissions from international shipping were also found to be very important for both nitrate and sulfate formation in Europe. In addition, we also examined contributions from the geographical source regions to SIA concentrations in the most densely populated region of Switzerland, the Swiss Plateau.

Concentrated agricultural activities and animal feeding operations in the northeastern plains of Colorado represent an important source of atmospheric ammonia (NH3). The NH3 from these sources contributes to regional fine particle formation and to nitrogen deposition to sensitive ecosystems in Rocky Mountain National Park (RMNP), located ∼80 km to the west. In order to better understand temporal and spatial differences in NH3 concentrations in this source region, weekly concentrations of NH3 were measured at 14 locations during the summers of 2010 to 2015 using Radiello passive NH3 samplers. Weekly (biweekly in 2015) average NH3 concentrations ranged from 2.66 to 42.7μ-3, with the highest concentrations near large concentrated animal feeding operations (CAFOs). The annual summertime mean NH3 concentrations were stable in this region from 2010 to 2015, providing a baseline against which concentration changes associated with future changes in regional NH3 emissions can be assessed. Vertical profiles of NH3 were also measured on the 300 m Boulder Atmospheric Observatory (BAO) tower throughout 2012. The highest NH3 concentration along the vertical profile was always observed at the 10 m height (annual average concentration of 4.63 μgm-3), decreasing toward the surface (4.35g μg-3) and toward higher altitudes (1.93g μg-3). The NH3 spatial distributions measured using the passive samplers are compared with NH3 columns retrieved by the Infrared Atmospheric Sounding Interferometer (IASI) satellite and concentrations simulated by the Comprehensive Air Quality Model with Extensions (CAMx). The satellite comparison adds to a growing body of evidence that IASI column retrievals of NH3 provide very useful insight into regional variability in atmospheric NH3, in this case even in a region with strong local sources and sharp spatial gradients. The CAMx comparison indicates that the model does a reasonable job simulating NH3 concentrations near sources but tends to underpredict concentrations at locations farther downwind. Excess NH3 deposition by the model is hypothesized as a possible explanation for this trend., SCOPUS: ar.j, info:eu-repo/semantics/published

One of the main issues arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two data sets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which lasted for about 6 months was held in the greater area of Thessaloniki, Greece. Three multi-axial differential optical absorption spectroscopy (MAX-DOAS) systems performed measurements of tropospheric NO2 columns at different sites representative of urban, suburban and rural conditions. The direct comparison of these ground-based measurements with corresponding products from the Ozone Monitoring Instrument onboard NASA's Aura satellite (OMI/Aura) showed good agreement over the rural and suburban areas, while the comparison with the Global Ozone Monitoring Experiment-2 (GOME-2) onboard EUMETSAT's Meteorological Operational satellites' (MetOp-A and MetOp-B) observations is good only over the rural area. GOME-2A and GOME-2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 10.51 ± 8.32 × 1015 and 10.21 ± 8.87 × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.60 ± 5.71 × 1015 molecules cm−2). The differences found in the comparisons of MAX-DOAS data with the different satellite sensors can be attributed to the higher spatial resolution of OMI, as well as the different overpass times and NO2 retrieval algorithms of the satellites. OMI data were adjusted using factors calculated by an air quality modeling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multiscale photochemical transport model. This approach resulted in significant improvement of the comparisons over the urban monitoring site. The average difference of OMI observations from MAX-DOAS measurements was reduced to −1.68 ± 5.01 × 1015 molecules cm−2.

Source apportionment modeling provides valuable information on the contributions of different source sectors and/or source regions to ozone (O3) or fine particulate matter (PM2.5) concentrations. This information can be useful in designing air quality management strategies and in understanding the potential benefits of reducing emissions from a particular source category. The Comprehensive Air quality Model with Extensions (CAMx) offers unique source attribution tools, called the Ozone and Particulate Source Apportionment Technology (OSAT/PSAT), which track source contributions. We present results from a CAMx source attribution modeling study for a summer month and a winter month using a recently evaluated European CAMx modeling database developed for Phase 3 of the Air Quality Model Evaluation International Initiative (AQMEII). The contributions of several source sectors (including model boundary conditions of chemical species representing transport of emissions from outside the modeling domain as well as initial conditions of these species) to O3 or PM2.5 concentrations in Europe were calculated using OSAT and PSAT, respectively. A 1-week spin-up period was used to reduce the influence of initial conditions. Evaluation focused on 16 major cities and on identifying source sectors that contributed above 5 %. Boundary conditions have a large impact on summer and winter ozone in Europe and on summer PM2.5, but they are only a minor contributor to winter PM2.5. Biogenic emissions are important for summer ozone and PM2.5. The important anthropogenic sectors for summer ozone are transportation (both on-road and non-road), energy production and conversion, and industry. In two of the 16 cities, solvent and product also contributed above 5 % to summertime ozone. For summertime PM2.5, the important anthropogenic source sectors are energy, transportation, industry, and agriculture. Residential wood combustion is an important anthropogenic sector in winter for PM2.5 over most of Europe, with larger contributions in central and eastern Europe and the Nordic cities. Other anthropogenic sectors with large contributions to wintertime PM2.5 include energy, transportation, and agriculture.

This study uses intake fraction, the fraction of emissions that are inhaled from a given source, to quantify how emissions from different regions proportionally contribute to human exposure to both primary and secondary particulate matter species. The intake fraction for secondary species is defined using the common atomic constituents between precursor species and products, allowing estimates to include both primary and secondary species. The Particulate Matter Source Apportionment Technology (PSAT) in the Comprehensive Air Quality Model with Extensions (CAMx) regional air quality model is used to calculate the intake fraction for twenty-five source regions throughout the contiguous United States over four seasons. The calculations use spatially explicit emissions and population density to more accurately capture the variation in intake fraction between regions. The spatially explicit emissions allow for the calculation of spatial trends and variations within the intake fraction. More specifically it allows for the calculation of the amount of intake that occurs within a given distance of the emissions source or source region. Based on the results sulfate inhalation occurs over larger distances than other particulate matter species. For most regions, a substantial fraction (>75%) of the inhalation occurs within 50 km for all seasons, demonstrating that efforts to reduce emissions will have the largest health impact on the local community. Furthermore the distance over which 75% of the inhalation occurs increases by 20% for all species during the winter and a larger percentage of pollutants emitted during the winter are inhaled relative to pollutants emitted during other seasons. This demonstrates that emission reductions during the winter will have a greater impact on health than reductions during other seasons.

Biogenic volatile organic compound (BVOC) emissions are one of the essential inputs for chemical transport models (CTMs), but their estimates are associated with large uncertainties, leading to significant influence on air quality modelling. This study aims to investigate the effects of using different BVOC emission models on the performance of a CTM in simulating secondary pollutants, i.e. ozone, organic, and inorganic aerosols. European air quality was simulated for the year 2011 by the regional air quality model Comprehensive Air Quality Model with Extensions (CAMx) version 6.3, using BVOC emissions calculated by two emission models: the Paul Scherrer Institute (PSI) model and the Model of Emissions of Gases and Aerosol from Nature (MEGAN) version 2.1. Comparison of isoprene and monoterpene emissions from both models showed large differences in their general amounts, as well as their spatial distribution in both summer and winter. MEGAN produced more isoprene emissions by a factor of 3 while the PSI model generated 3 times the monoterpene emissions in summer, while there was negligible difference (∼4 %) in sesquiterpene emissions associated with the two models. Despite the large differences in isoprene emissions (i.e. 3-fold), the resulting impact in predicted summertime ozone proved to be minor (60 ppb). A much larger effect of the different BVOC emissions was found for the secondary organic aerosol (SOA) concentrations. The higher monoterpene emissions (a factor of ∼3) by the PSI model led to higher SOA by ∼110 % on average in summer, compared to MEGAN, and lead to better agreement between modelled and measured organic aerosol (OA): the mean bias between modelled and measured OA at nine measurement stations using Aerodyne aerosol chemical speciation monitors (ACSMs) or Aerodyne aerosol mass spectrometers (AMSs) was reduced by 21 %–83 % at rural or remote stations. Effects on inorganic aerosols (particulate nitrate, sulfate, and ammonia) were relatively small (, Acknowledgements. We would like to thank the TNO for providing anthropogenic emissions, the European Centre for Medium-Range Weather Forecasts (ECMWF) for the access to the meteorological data, the European Environmental Agency (EEA) for the air quality data, and the National Aeronautics and Space Administration (NASA) and its data-contributing agencies (NCAR, UCAR) for the TOMS and MODIS data, the global air quality model data, and the TUV model. Simulations of WRF and CAMx models were performed at the Swiss National Supercomputing Centre (CSCS). We thank the EBAS database of the Norwegian Institute for Air Research (NILU) for the measurement data of isoprene concentration. We are grateful to RAMBOLL for the valuable support for CAMx. We thank the ACSM/AMS data providers, namely Stefania Gilardoni for the Bologna and San Pietro Capofiume stations, Nicolas Marchand and the MASSALYA instrumental platform (https://lce.univ-amu.fr/en/massalya, last access: 12 March 2019 for Marseille, Olivier Favez (INERIS) and the whole SIRTA team for measurements conducted in the Paris area in the frame of the EU FP7 ACTRIS programme under the grant agreement no. 262254, Kalliopi Florou for Finokalia, and Liqing Hao and Annele Virtanen for SMEAR II Hyytiälä. EPA-Ireland (AEROSOURCE, 2016-CCRP-MS-31) is acknowledged, as well as EGAR group from IDAEA-CSIC (special mention to Anna Ripoll and An-drés Alastuey) and Generalitat de Catalunya (AGAUR 2017 SGR41). María Cruz Minguillón acknowledges the Ramón y Cajal fellowship awarded by the Spanish Ministry of Economy, Industry and Competitiveness.

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.