Semivolatile POA and parameterized total combustion SOA in CMAQv5.2: impacts on source strength and partitioning

Modeling the molecular composition of secondary organic aerosol under highly polluted conditions: A case study in the Yangtze River Delta Region in China

A near-explicit mechanism, the master chemical mechanism (MCMv3.3.1), coupled with the Community Multiscale Air Quality (CMAQ) model (CMAQ-MCM-SOA), was applied to investigate the characteristics of secondary organic aerosol (SOA) during a pollution event in the Yangtze River Delta (YRD) region in summer 2018. Model performances in predicting explicit volatile organic compounds (VOCs), organic aerosol (OA), secondary organic carbon (SOC), and other related pollutants in Taizhou, as well as ozone (O3) and fine particulate matter (PM2.5) in multiple cities in this region, were evaluated against observations and model predictions by the CMAQ model coupled with a lumped photochemical mechanism (SAPRC07tic, S07). MCM and S07 exhibited similar performances in predicting gaseous species, while MCM better captured the observed PM2.5 and inorganic aerosols. Both models underpredicted OA concentrations. When excluding data during biomass burning events, SOC concentrations were underpredicted by the CMAQ-MCM-SOA model (-28.4 %) and overpredicted by the CMAQ-S07 model (134.4 %), with better agreement with observations in the trend captured by the CMAQ-MCM-SOA model. Dicarbonyl SOA accounted for a significant fraction of total SOA in the YRD, while organic nitrates originating from aromatics were the most abundant species contributing to the SOA formation from gas-particle partitioning. The oxygen-to‑carbon ratio (O/C) for SOA and OA were 0.68-0.75 and 0.20-0.65, respectively, indicating a higher oxidation state in the areas influenced by biogenic emissions. Finally, the phase state of SOA was examined by calculating the glass transition temperature (Tg) based on its molecular composition. It was found that semi-solid state characterized SOA in the YRD, which could potentially impact their chemical transformation and lifetimes along with those of their precursors.

Using the Multicomponent Aerosol FORmation Model (MAFOR) to Determine Improved VOC Emission Factors in Ship Plumes

International shipping's particulate matter primary emissions have a share in global anthropogenic emissions of between 3% and 4%. Ship emissions of volatile organic compounds (VOCs) can play an important role in the formation of fine particulate matter. Using an aerosol box model for the near-plume scale, this study investigated how the changing VOC emission factor (EF) for ship engines impacts the formation of secondary PM2.5 in ship exhaust plumes that were detected during a measurement campaign. The agreement between measured and modeled particle number size distribution was improved by adjusting VOC emissions, in particular of intermediate-, low-, and extremely low-volatility compounds. The scaling of the VOC emission factor showed that the initial emission factor, based on literature data, had to be multiplied by 3.6 for all VOCs. Information obtained from the box model was integrated into a regional-scale chemistry transport model (CTM) to study the influence of changed VOC ship emissions over the Mediterranean Sea. The regional-scale CTM run with adjusted ship emissions indicated a change in PM2.5 of up to 5% at the main shipping routes and harbor cities in summer. Nevertheless, overall changes due to a change in the VOC EF were rather small, indicating that the size of grid cells in CTMs leads to a fast dilution.

Impact of particulate nitrate photolysis on air quality over the Northern Hemisphere

We use the Community Multiscale Air Quality (CMAQv5.4) model to examine the potential impact of particulate nitrate (pNO3-) photolysis on air quality over the Northern Hemisphere. We estimate the photolysis frequency of pNO3- by scaling the photolysis frequency of nitric acid (HNO3) with an enhancement factor that varies between 10 and 100 depending on pNO3- and sea-salt aerosol concentrations and then perform CMAQ simulations without and with pNO3- photolysis to quantify the range of impacts on tropospheric composition. The photolysis of pNO3- produces gaseous nitrous acid (HONO) and nitrogen dioxide (NO2) over seawater thereby increasing atmospheric HONO and NO2 mixing ratios. HONO subsequently undergoes photolysis, producing hydroxyl radicals (OH). The increase in NO2 and OH alters atmospheric chemistry and enhances the atmospheric ozone (O3) mixing ratio over seawater, which is subsequently transported to downwind continental regions. Seasonal mean model O3 vertical column densities without pNO3- photolysis are lower than the Ozone Monitoring Instrument (OMI) retrievals, while the column densities with the pNO3- photolysis agree better with the OMI retrievals of tropospheric O3 burden. We compare model O3 mixing ratios with available surface observed data from the U.S., Japan, the Tropospheric Ozone Assessment Report - Phase II, and OpenAQ; and find that the model without pNO3- photolysis underestimates the observed data in winter and spring seasons and the model with pNO3- photolysis improves the comparison in both seasons, largely rectifying the pronounced underestimation in spring. Compared to measurements from the western U.S., model O3 mixing ratios with pNO3- photolysis agree better with observed data in all months due to the persistent underestimation of O3 without pNO3- photolysis. Compared to the ozonesonde measurements, model O3 mixing ratios with pNO3- photolysis also agree better with observed data than the model O3 without pNO3- photolysis.

A review of the CAMx, CMAQ, WRF-Chem and NAQPMS models: Application, evaluation and uncertainty factors

With the gradual deepening of the research and governance of air pollution, chemical transport models (CTMs), especially the third-generation CTMs based on the "1 atm" theory, have been recognized as important tools for atmospheric environment research and air quality management. In this review article, we screened 2396 peer-reviewed manuscripts on the application of four pre-selected regional CTMs in the past five years. CAMx, CMAQ, WRF-Chem and NAQPMS models are well used in the simulation of atmospheric pollutants. In the simulation study of secondary pollutants such as O3, secondary organic aerosol (SOA), sulfates, nitrates, and ammonium (SNA), the CMAQ model has been widely applied. Secondly, model evaluation indicators are diverse, and the establishment of evaluation criteria has gone through the long-term efforts of predecessors. However, the model performance evaluation system still needs further specification. Furthermore, temporal-spatial resolution, emission inventory, meteorological field and atmospheric chemical mechanism are the main sources of uncertainty, and have certain interference with the simulation results. Among them, the inventory and mechanism are particularly important, and are also the top priorities in future simulation research.

Assessment of tropospheric ozone simulations in a regional chemical transport model using GEOS-Chem outputs as chemical boundary conditions

Regional chemical transport models (e.g., Community Multiscale Air Quality (CMAQ) Modeling System) are widely used to simulate the physical and chemical process of regional ozone (O3) pollution and its variation trend in recent years. However, chemical boundary condition (CBC) is an important input of these models and contributes to the model bias against observations. In this study, we develop a tool named GC2CMAQ that provides the CMAQ model with the CBCs from the GEOS-Chem simulation. Two experiments using different CBCs were conducted to evaluate their effect on seasonal O3 simulation in China. The Default experiment utilized the model-default static condition (the relatively clean atmosphere in the eastern United States), and the GC experiment employed the GEOS-Chem simulation results. Compared with the observation, the GC experiment has a much better performance in reproducing elevated O3 levels in the higher troposphere and lower stratosphere during different seasons. Near the earth's surface, the simulated concentrations of pollutants O3 (and PM2.5) in the GC experiment were also closer to the observation in April and July. The accuracy of simulation results in provinces close to the boundary was improved by approximately 20 %-30 % relative to the Default experiment. The CBCs provided by GEOS-Chem enabled a better simulation of stratosphere-troposphere O3 exchange in late spring and early summer, which then affected the pollutant concentration near surfaces through vertical transport. This finding was confirmed by a case study in southwestern Tibet on April 28, 2017, in which we quantified the contributions of different physical and chemical processes to O3 variations at different altitudes using the process analysis method. This study highlights the importance of using a reliable CBC for the regional chemical transport model to derive a better performance of O3 simulation.

Source apportionment of anthropogenic and biogenic organic aerosol over the Tokyo metropolitan area from forward and receptor models

Organic aerosol (OA) is a dominant component of PM2.5, and accurate knowledge of its sources is critical for identification of cost-effective measures to reduce PM2.5. For accurate source apportionment of OA, we conducted field measurements of organic tracers at three sites (one urban, one suburban, and one forest) in the Tokyo Metropolitan Area and numerical simulations of forward and receptor models. We estimated the source contributions of OA by calculating three receptor models (positive matrix factorization, chemical mass balance, and secondary organic aerosol (SOA)-tracer method) using the ambient concentrations, source profiles, and production yields of OA tracers. Sensitivity simulations of the forward model (chemical transport model) for precursor emissions and SOA formation pathways were conducted. Cross-validation between the receptor and forward models demonstrated that biogenic and anthropogenic SOA were better reproduced by the forward model with updated modules for emissions of biogenic volatile organic compounds (VOC) and for SOA formation from biogenic VOC and intermediate-volatility organic compounds than by the default setup. The source contributions estimated by the forward model generally agreed with those of the receptor models for the major OA sources: mobile sources, biomass combustion, biogenic SOA, and anthropogenic SOA. The contributions of anthropogenic SOA, which are the main focus of this study, were estimated by the forward and receptor models to have been between 9 % and 15 % in summer 2019. The observed percent modern carbon data indicate that the amounts of anthropogenic SOA produced during daytime have substantially declined from 2007 to 2019. This trend is consistent with the decreasing trend of anthropogenic VOC, suggesting that reduction of anthropogenic VOC has been effective in reducing anthropogenic SOA in the atmosphere.

Modeling of secondary organic aerosols (SOA) based on two commonly used air quality models in China: Consistent S/IVOCs contribution but large differences in SOA aging

Secondary organic aerosol (SOA) is an important component of atmospheric fine particulate matter (PM2.5), with contributions from anthropogenic and biogenic volatile organic compounds (AVOC and BVOC) and semi- (SVOC) and intermediate volatility organic compounds (IVOC). Policymakers need to know which SOA precursors are important but accurate simulation of SOA magnitude and contributions remain uncertain. Findings from existing SOA modeling studies have many inconsistencies due to differing emission inventory methodologies/assumptions, air quality model (AQM) algorithms, and other aspects of study methodologies. To address some of the inconsistencies, we investigated the role of different AQM SOA algorithms by applying two commonly used models, CAMx and CMAQ, with consistent emission inventories to simulate SOA concentrations and contributions for July and November 2018 in China. Both models have a volatility basis set (VBS) SOA algorithm but with different parameters and treatments of SOA photochemical aging. SOA generated from BVOC (i.e., BSOA) is found to be more important in southern China. In contrast, SOA generated from anthropogenic precursors is more prevalent in the North China Plain (NCP), Yangtze River Delta (YRD), Sichuan Basin and Central China. Both models indicate negligible SOA formation from SVOC emissions compared to other precursors. In July, when BVOC emissions are abundant, SOA is predominantly contributed by BSOA (except for NCP), followed by IVOC-SOA (i.e., SOA produced from IVOC) and ASOA (i.e., SOA produced from anthropogenic VOC). In contrast, in November, IVOC became the leading SOA contributor for all selected regions except PRD, illustrating the important contribution of IVOC emissions to SOA formation. While both models generally agree in terms of the spatial distributions and seasonal variations of different SOA components, CMAQ tends to predict higher BSOA, while CAMx generates higher ASOA concentrations. As a result, CMAQ results suggest that BSOA concentration is always higher than ASOA in November, while CAMx emphasizes the importance of ASOA. Utilizing a conceptual model, we found that different treatment of SOA aging between the two models is a major cause of differences in simulated ASOA concentrations. The step-wise SOA aging scheme implemented in the CAMx VBS (based on gas-phase reactions with OH radical and similar to other models) exhibits a strong enhancement effect on simulated ASOA concentrations, and this effect increases with the ambient organic aerosol (OA) concentrations. The CMAQ aerosol module implements a different SOA aging scheme that represents particle-phase oligomerization and has smaller impacts on total OA. Different structures and/or parameters of the SOA aging schemes are being used in current models, which could greatly affect model simulations of OA in ways that are difficult to anticipate. Our results indicate that future control policies should aim at reducing IVOC emissions as well as traditional VOC emissions. In addition, aging schemes are the major driver in CMAQ vs. CAMx treatments of ASOA and their resulting predicted mass. More sophisticated measurement data (e.g., with resolved OA components) and/or chamber experiments (e.g., investigating how aging influences SOA yields) are needed to better characterize SOA aging and constrain model parameterizations.

Reactive organic carbon air emissions from mobile sources in the United States

Mobile sources are responsible for a substantial controllable portion of the reactive organic carbon (ROC) emitted to the atmosphere, especially in urban environments of the United States. We update existing methods for calculating mobile source organic particle and vapor emissions in the United States with over a decade of laboratory data that parameterize the volatility and organic aerosol (OA) potential of emissions from on-road vehicles, nonroad engines, aircraft, marine vessels, and locomotives. We find that existing emission factor information from Teflon filters combined with quartz filters collapses into simple relationships and can be used to reconstruct the complete volatility distribution of ROC emissions. This new approach consists of source-specific filter artifact corrections and state-of-the-science speciation including explicit intermediate-volatility organic compounds (IVOCs), yielding the first bottom-up volatility-resolved inventory of US mobile source emissions. Using the Community Multiscale Air Quality model, we estimate mobile sources account for 20 %-25 % of the IVOC concentrations and 4.4 %-21.4 % of ambient OA. The updated emissions and air quality model reduce biases in predicting fine-particle organic carbon in winter, spring, and autumn throughout the United States (4.3 %-11.3 % reduction in normalized bias). We identify key uncertain parameters that align with current state-of-the-art research measurement challenges.

Substantial short- and long-term health effect due to PM2.5 and the constituents even under future emission reductions in China

Heavy pollution events of fine particulate matter (PM_2.5) frequently occur in China, seriously affecting the human health. However, how meteorological factors and anthropogenic emissions affect PM_2.5 and the major constituents, as well as the subsequent health effect, remains unclear. Here, based on regional climate and air quality models Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ), the PM_2.5 and major constituents in China at present and mid-century under the carbon neutral scenario Shared Socioeconomic Pathways (SSP)1-2.6 are simulated. Due to anthropogenic emission reduction, concentrations of PM_2.5 and the constituents decrease substantially in SSP1-2.6. The long-term exposure premature deaths at present are 2.23 million per year in mainland China, which is projected to increase by 76 % under SSP1-2.6 despite emission reduction, primarily attributable to aging which strikingly offsets the effect of air quality improvement. The number of annual premature deaths resulting from short-term exposure is 228,104 in mainland China at present, which is projected to decrease in the future. Using North China Plain as an example, we identify that among the major constituents of PM_2.5, organic carbon leads to the most short-term exposure deaths considering the largest exposure-response coefficient. Regarding the abnormally meteorological conditions, we find, relative to low relative humidity (RH) and non-stagnation, the compound events, defined as concurrence of high RH and atmospheric stagnation, exhibit an amplified role inducing larger premature deaths compared to the additive effect of the individual event of high RH and atmospheric stagnation. This nonlinear effect occurs at both present and future, but diminished in future due to emission reductions. Our study highlights the importance of considering both the long- and short-term premature deaths associated with PM_2.5 and the constituents, as well as the critical effect of extreme weather events.

Differences between VOCs and NOx transport contributions, their impacts on O3, and implications for O3 pollution mitigation based on CMAQ simulation over the Yangtze River Delta, China

The relationship between O₃ and its precursors during urban polluted episodes remains unclear. In this study, the simultaneous source apportionment of VOCs, NO_x, and O₃ over the Yangtze River Delta (YRD) region during the O₃ polluted episode on July 24-30, 2018, was performed based on the Integrated Source Apportionment Method (ISAM) embedded in the Community Multiscale Air Quality Modeling System (CMAQ). The results of the ISAM were compared with those of the Brute Force Method (BFM) and Positive Matrix Factorization (PMF). Furthermore, the differences between the transport contributions of VOCs and NO_x, and their impacts on O₃ were analyzed. The results indicate that observations of VOCs species can be well captured by simulated VOCs, and the ISAM has a significant advantage in the source apportionment of VOCs, especially for sources emitting highly reactive species. In the clean and polluted periods, the local contribution percentages of VOCs in urban sites ranged from 60 % to 77 %, much higher than those of NO_x (31 %-43 %) and O₃ (16 %-33 %). NO_x and O₃ have strong transport abilities with high and close contribution percentages, which are highly correlated, mainly because oxygen atoms produced by the photolysis of NO₂ in the aged air mass combined rapidly with O₂ to form O₃ during transport. The VOCs chemical loss caused by the oxidation of OH radicals during transport makes the ability of VOCs for long-distance transport much weaker than that of NO_x. Furthermore, owing to the sufficient aging of VOCs, those contributed by long-distance transport have little effect on O₃. To a certain extent, controlling one's NO_x emissions can help other cities more, while controlling one's VOCs emissions can help itself more. Therefore, it is recommended to attach enough importance to joint prevention and control of NO_x among cities and even long-distance areas to alleviate regional O₃ pollution.

Developed compositional source profile and estimated emissions of condensable particulate matter from coal-fired power plants: A case study of Yantai, China

The emission and environmental impact of condensable particulate matter (CPM) from coal-fired power plants (CFPPs) are of increasing concern worldwide. Many studies on the characteristics of CPM emission have been conducted in China, but its source profile remains unclear, and its emission inventory remains high uncertainty. In this work, the latest measurements reported in the latest 33 studies for CPM inorganic and organic species emitted from CFPPs in China were summarized, and then a compositional source profile of CPM for CFPPs was developed for the first time in China, which involved 10 inorganic species and 71 organic species. In addition, the CPM emission inventory of CFPPs in Yantai of China was developed based on surveyed activity data, continuous emission monitoring system (CEMS), and the latest measurement data. The results show that: (1) Inorganic species accounted for 77.64 % of CPM emitted from CFPPs in Yantai, among which SO₄^2- had the highest content, accounting for 23.74 % of CPM, followed by Cl^-, accounting for 11.95 %; (2) Organic matter accounted for 22.36 % of CPM, among which alkanes accounted for the largest proportion of organic fraction (72.7 %); (3) Emission concentration method (EC) and CEMS-based emission ratio method (ER_FPM,CEMS) were recommended to estimate CPM emissions for CFPPs; (4) The estimated CPM emission inventories of Yantai CFPPs in 2020 by the EC method and the ER_FPM,CEMS method were 1231 tons and 929 tons, respectively, with uncertainties of -34 % ∼ 33 % and -27 % ∼ 57 %, respectively; (5) CPM emissions were mainly distributed in the northern coastal areas of Yantai. This developed CPM source profile and emission inventory can provide basic data for assessing the impacts of CPM on air quality and health. In addition, this study can provide an important methodology for developing CPM emission inventories and CPM emission source profiles for stationary combustion sources in other regions.

Characterizing variations in ambient PM2.5 concentrations at the U.S. Embassy in Dhaka, Bangladesh using observations and the CMAQ modeling system

We analyze hourly PM2.5 (particles with an aerodynamic diameter of ≤ 2.5 μm) concentrations measured at the U.S. Embassy in Dhaka over the 2016 - 2021 time period and find that concentrations are seasonally dependent with the highest occurring in winter and the lowest in monsoon seasons. Mean winter PM2.5 concentrations reached ~165-175 μg/m3 while monsoon concentrations remained ~30-35 μg/m3. Annual mean PM2.5 concentration reached ~5-6 times greater than the Bangladesh annual PM2.5 standard of 15 μg/m3. The number of days exceeding the daily PM2.5 standard of 65 μg/m3 in a year approached nearly 50%. Daily-mean PM2.5 concentrations remained elevated (>65 μg/m3) for more than 80 consecutive days. Night-time concentrations were greater than daytime concentrations. The comparison of results obtained from the Community Multiscale Air Quality (CMAQ) model simulations over the Northern Hemisphere using 108-km horizontal grids with observed data suggests that the model can reproduce the seasonal variation of observed data but underpredicts observed PM2.5 in winter months with a normalized mean bias of 13-32%. In the model, organic aerosol is the largest component of PM2.5, of which secondary organic aerosol plays a dominant role. Transboundary pollution has a large impact on the PM2.5 concentration in Dhaka, with an annual mean contribution of ~40 μg/m3.

Comprehensive Assessment for the Impacts of S/IVOC Emissions from Mobile Sources on SOA Formation in China

Semivolatile/intermediate-volatility organic compounds (S/IVOCs) from mobile sources are essential SOA contributors. However, few studies have comprehensively evaluated the SOA contributions of S/IVOCs by simultaneously comparing different parameterization schemes. This study used three SOA schemes in the CMAQ model with a measurement-based emission inventory to quantify the mobile source S/IVOC-induced SOA (MS-SI-SOA) for 2018 in China. Among different SOA schemes, SOA predicted by the 2D-VBS scheme was in the best agreement with observations, but there were still large deviations in a few regions. Three SOA schemes showed the peak value of annual average MS-SI-SOA was up to 0.6 ± 0.3 μg/m³. High concentrations of MS-SI-SOA were detected in autumn, while the notable relative contribution of MS-SI-SOA to total SOA was predicted in the coastal areas in summer, with a regional average contribution up to 20 ± 10% in Shanghai. MS-SI-SOA concentrations varied by up to 2 times among three SOA schemes, mainly due to the discrepancy in SOA precursor emissions and chemical reactions, suggesting that the differences between SOA schemes should also be considered in modeling studies. These findings identify the hotspot areas and periods for MS-SI-SOA, highlighting the importance of S/IVOC emission control in the future upgrading of emission standards.

Tracking Daily Concentrations of PM2.5 Chemical Composition in China since 2000

PM_2.5 chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely updated information on China's PM_2.5 chemical composition is the basis for research and environmental management. Here, we developed a full-coverage near-real-time PM_2.5 chemical composition data set at 10 km spatial resolution since 2000, combining the Weather Research and Forecasting-Community Multiscale Air Quality modeling system, ground observations, a machine learning algorithm, and multisource-fusion PM_2.5 data. PM_2.5 chemical components in our data set are in good agreement with the available observations (correlation coefficients range from 0.64 to 0.75 at a monthly scale from 2000 to 2020 and from 0.67 to 0.80 at a daily scale from 2013 to 2020; most normalized mean biases within ±20%). Our data set reveals the long-term trends in PM_2.5 chemical composition in China, especially the rapid decreases after 2013 for sulfate, nitrate, ammonium, organic matter, and black carbon, at the rate of -9.0, -7.2, -8.1, -8.4, and -9.2% per year, respectively. The day-to-day variability is also well captured, including evolutions in spatial distribution and shares of PM_2.5 components. As part of Tracking Air Pollution in China (http://tapdata.org.cn), this daily-updated data set provides large opportunities for health and climate research as well as policy-making in China.

Measurement-based intermediate volatility organic compound emission inventory from on-road vehicle exhaust in China

Intermediate volatility organic compounds (IVOCs) have great potential to form secondary organic aerosols (SOA) in the atmosphere. Thus, a high-resolution IVOC emission inventory is essential for the accurate simulation of SOA formation. This study developed the first nationwide on-road vehicular IVOC emission inventory in China based on localized measurement of the IVOC emission factors and volatility distributions for various vehicle types. The total vehicular IVOC emissions in China in 2019 were estimated to be 241.2 Gg. Heavy-duty trucks, light-duty trucks, and light-duty passenger vehicles contributed the most, accounting for 47.6%, 24.6%, and 16.9% of total vehicular IVOC emissions, respectively. Although much higher in number, gasoline vehicles contributed 15.0%, which was far less than the contribution of diesel vehicles. The two peaks in volatility bins B₁₂-B₁₃ and B₁₆-B₁₇ accounted for 42.2% and 23.7% of the total IVOC emissions, respectively. By gridding the emission inventory into a relatively high resolution of 0.1° × 0.1°, high-emission areas and hotspots were clearly identified. In general, eastern China had substantially higher vehicular IVOC emissions than western China. High-emission areas with emission intensity >10 Mg·grid^-1 covered most of the North China Plain, Yangtze River Delta, and Pearl River Delta. The emission intensity over the downtown areas of Beijing and Shanghai exceeded 50 Mg·grid^-1. In contrast, IVOC emissions over western China were relatively lower, with a network structure gathering around the traffic arteries serving inter-provincial transportation. This study underscored the importance of having a localized emission factor to better reflect the IVOC emission characteristics from Chinese vehicles and to improve the assessment of their environmental impacts.

Unit-based emissions and environmental impacts of industrial condensable particulate matter in China in 2020

The emission of condensable particulate matter (CPM) and its environmental impacts are arousing concern in China with the effective control of filter particulate matter (FPM). This study established an up-to-date and unit-based CPM emission inventory for industrial sectors and systematically evaluated the effects of CPM on primary and secondary PM_2.5 in China. In 2020, the national CPM emissions total for industrial sectors was estimated to be 0.98 Tg with uncertainty from -49% to 66%, including 0.62 Tg of organic CPM (CPM_org) and 0.36 Tg of inorganic CPM (CPM_in). Totals of 62%, 23% and 8% CPM were emitted from coal-fired power plants, coal-fired industrial boilers and sinter plants, respectively. By filling CPM emissions in PM_2.5 simulation, the normalized mean bias (NMB) of model to observation was improved from -27% to -14% in East, North and Central China. The 4 μg/m³ PM_2.5 concentration was attributed to CPM emissions in this region, accounting for 10% of observations. On "polluted" days (PM_2.5>75 μg/m³), industrial CPM emissions can contribute 7 μg/m³ PM_2.5 in North China. Therefore, China should focus on controlling CPM from coal combustion to ensure continuous air quality improvement.

Watching Paint Dry: Organic Vapor Emissions from Architectural Coatings and their Impact on Secondary Organic Aerosol Formation

Emissions from volatile chemical products (VCPs) are emerging as a major source of anthropogenic secondary organic aerosol (SOA) precursors. Paints and coatings are an important class of VCPs that emit both volatile and intermediate volatility organic compounds (VOCs and IVOCs). In this study, we directly measured I/VOC emissions from representative water- (latex) and oil-based paints used in the U.S. Paint I/VOC emissions vary by several orders of magnitude by both the solvent and gloss level. Oil-based paints had the highest emissions (>10⁵ μg/g-paint), whereas low-gloss interior paints (Flat, Satin, and Semigloss) all emitted ∼10² μg/g-paint. Emissions from interior paints are dominated by VOCs, whereas exterior-use paints emitted a larger fraction of IVOCs. Extended emission tests showed that most I/VOC emissions occur within 12-24 h after paint application, though some paints continue to emit IVOCs for 48 h or more. We used our data to estimate paint I/VOC emissions and the subsequent SOA production in the U.S. Total annual paint I/VOC emissions are 48-155 Gg (0.15-0.48 kg/person). These emissions contribute to the formation of 2.2-7.5 Gg of SOA annually. Oil-based paints contribute 70-98% of I/VOC emissions and 61-99% of SOA formation, even though they only account for a minority of paint usage.

Volatile Chemical Product Enhancements to Criteria Pollutants in the United States

Volatile chemical products (VCPs) are a significant source of reactive organic carbon emissions in the United States with a substantial fraction (>20% by mass) serving as secondary organic aerosol (SOA) precursors. Here, we incorporate a new nationwide VCP inventory into the Community Multiscale Air Quality (CMAQ) model with VCP-specific updates to better model air quality impacts. Model results indicate that VCPs mostly enhance anthropogenic SOA in densely populated areas with population-weighted annual average SOA increasing 15-30% in Southern California and New York City due to VCP emissions (contribution of 0.2-0.5 μg m^-3). Annually, VCP emissions enhance total population-weighted PM_2.5 by ∼5% in California, ∼3% in New York, New Jersey, and Connecticut, and 1-2% in most other states. While the maximum daily 8 h ozone enhancements from VCP emissions are more modest, their influence can cause a several ppb increase on select days in major cities. Printing Inks, Cleaning Products, and Paints and Coatings product use categories contribute ∼75% to the modeled VCP-derived SOA and Cleaning Products, Paints and Coatings, and Personal Care Products contribute ∼81% to the modeled VCP-derived ozone. Overall, VCPs enhance multiple criteria pollutants throughout the United States with the largest impacts in urban cores.

The Impact of Meteorology and Emissions on Surface Ozone in Shandong Province, China, during Summer 2014–2019

China has been experiencing severe ozone pollution problems in recent years. While a number of studies have focused on the ozone-pollution-prone regions such as the North China Plain, Yangtze River Delta, and Pearl River Delta regions, few studies have investigated the mechanisms modulating the interannual variability of ozone concentrations in Shandong Province, where a large population is located and is often subject to ozone pollution. By utilizing both the reanalysis dataset and regional numerical model (WRF-CMAQ), we delve into the potential governing mechanisms of ozone pollution in Shandong Province—especially over the major port city of Qingdao—during summer 2014–2019. During this period, ozone pollution in Qingdao exceeded the tier II standard of the Chinese National Ambient Air Quality (GB 3095-2012) for 75 days. From the perspective of meteorology, the high-pressure ridge over Baikal Lake and to its northeast, which leads to a relatively low humidity and sufficient sunlight, is the most critical weather system inducing high-ozone events in Qingdao. In terms of emissions, biogenic emissions contribute to ozone enhancement close to 10 ppb in the west and north of Shandong Province. Numerical experiments show that the local impact of biogenic emissions on ozone production in Shandong Province is relatively small, whereas biogenic emissions on the southern flank of Shandong Province enhance ozone production and further transport northeastward, resulting in an increase in ozone concentrations over Shandong Province. For the port city of Qingdao, ship emissions increase ozone concentrations when sea breezes (easterlies) prevail over Qingdao, with the 95th percentile reaching 8.7 ppb. The findings in this study have important implications for future ozone pollution in Shandong Province, as well as the northern and coastal areas in China.

Impact of Urbanization on Meteorology and Air Quality in Chengdu, a Basin City of Southwestern China

Rapid urbanization has the potential to fundamentally perturb energy budget and alter urban air quality. While it is clear that urban meteorological parameters are sensitive to urbanization-induced changes in landscapes, a gap exists in our knowledge about how changes in land use and land cover affect the dynamics of urban air quality. Herein, we simulated a severe O3 episode (10–16 July 2017) and a highly polluted PM2.5 episode (25–30 December 2017) and assessed the changes of meteorological phenomenon and evolution of air pollutants induced by urbanization. We found that the urban expansion area (i.e., land use transition from natural to urban surfaces between 2000 and 2017, UEA) has a significant increase in nocturnal 2-m temperature (T2) with maximum values reaching 3 and 4°C in summer and winter, respectively. In contrast, UEA experienced cooling in the daytime with stronger reductions of T2 in winter than in summer. The T2 variability is primarily attributed to the intense thermal inertia and high heat capacity of the urban canopy and the shadowing effect caused by urbanization. Owing to increased surface roughness and decreased surface albedo as well as shadowing effects, the ventilation index (VI) of UEA increased up to 1,200 m2/s in winter while decreased up to 950 m2/s in summer. Changes in meteorological phenomenon alter physical and chemical processes associated with variations in PM2.5 and O3 concentrations. Urbanization leads to enhanced vertical advection process and weakened aerosol production, subsequently causing PM2.5 levels to decrease by 33.2 μg/m3 during the day and 4.6 μg/m3 at night, respectively. Meanwhile, O3 levels increased by 61.4 μg/m3 at 20:00 due to the reduction of horizontal advection induced by urbanization, while O3 concentrations changed insignificantly at other times. This work provides valuable insights into the effects of urbanization on urban meteorology and air quality over typical megacities, which support informed decision-making for urban heat and air pollution mitigation.

Characterizing the distinct modulation of future emissions on summer ozone concentrations between urban and rural areas over China

Previous studies on ozone pollution primarily focus on the characterization of ozone on a large regional scale, yet much less attention has been paid towards the contrast between urban and surrounding suburban-rural areas. As anthropogenic emissions are projected to decrease in the coming decades, the evolutions of ozone concentrations over urban and suburban-rural areas are compared using the Community Multiscale Air Quality (CMAQ) model coupled with the Weather Research and Forecasting (WRF). The top 25 city clusters are firstly identified across China based on the amount of NO_x emissions and population size. At present, the averages of maximum daily 8-h (MDA8) ozone concentrations over the suburban-rural areas (65.74 ppbv) among these city clusters are higher than the corresponding urban areas (62.00 ppbv). The projections in 2050s depend on the scenarios. Under the Shared Socioeconomic Pathways (SSPs) scenarios such as SSP1-2.6, SSP2-4.5 and SSP5-8.5 indicative of primary decreases in anthropogenic emissions, the mean MDA8 ozone concentrations in suburban-rural areas decrease more than urban areas. In contrast, the gap of higher MDA8 ozone concentrations in suburban-rural than urban areas increases under SSP3-7.0 concomitant with increase in anthropogenic emissions. The strongest response to emission changes is found in SSP1-2.6, in which anthropogenic emission reduction leads to lower MDA8 ozone concentrations in the suburban-rural than urban areas, reversing the present state of higher ozone concentrations in the suburban-rural areas. The feature abovementioned regarding changes of mean MDA8 ozone concentrations is largely reproduced in the response of ozone exceedance. The finding highlights different efficacies of anthropogenic emissions in urban from suburban-rural areas. In a region like China where the population density is much higher in urban than suburban-rural regions, the benefit of ozone reduction due to large emission reductions (e.g., SSP1-2.6) is diminished to some extent because the effect is larger in suburban-rural areas.

Human-health impacts of controlling secondary air pollution precursors

Exposure to ozone and fine particle (PM_2.5) air pollution results in premature death. These pollutants are predominantly secondary in nature and can form from nitrogen oxides (NO_X), sulfur oxides (SO_X), and volatile organic compounds (VOCs). Predicted health benefits for emission reduction scenarios often incompletely account for VOCs as precursors as well as the secondary organic aerosol (SOA) component of PM_2.5. Here, we show that anthropogenic VOC emission reductions are more than twice as effective as equivalent fractional reductions of SO_X or NO_X at reducing air pollution-associated cardiorespiratory mortality in the United States. A 25% reduction in anthropogenic VOC emissions from 2016 levels is predicted to avoid 13,000 premature deaths per year, and most (85%) of the VOC-reduction benefits result from reduced SOA with the remainder from ozone. While NO_X (-5.7 ± 0.2 % yr^-1) and SO_X (-12 ± 1 % yr^-1) emissions have declined precipitously across the U.S. since 2002, anthropogenic VOC emissions (-1.8 ± 0.3 % yr^-1) and concentrations of non-methane organic carbon (-2.4 ± 1.0 % yr^-1) have changed less. This work indicates preferentially controlling VOCs could yield significant benefits to human health.

Secondary organic aerosol association with cardiorespiratory disease mortality in the United States

Fine particle pollution, PM2.5, is associated with increased risk of death from cardiorespiratory diseases. A multidecadal shift in the United States (U.S.) PM2.5 composition towards organic aerosol as well as advances in predictive algorithms for secondary organic aerosol (SOA) allows for novel examinations of the role of PM2.5 components on mortality. Here we show SOA is strongly associated with county-level cardiorespiratory death rates in the U.S. independent of the total PM2.5 mass association with the largest associations located in the southeastern U.S. Compared to PM2.5, county-level variability in SOA across the U.S. is associated with 3.5× greater per capita county-level cardiorespiratory mortality. On a per mass basis, SOA is associated with a 6.5× higher rate of mortality than PM2.5, and biogenic and anthropogenic carbon sources both play a role in the overall SOA association with mortality. Our results suggest reducing the health impacts of PM2.5 requires consideration of SOA.

Modeling secondary organic aerosol formation from volatile chemical products

Volatile chemical products (VCPs) are commonly-used consumer and industrial items that are an important source of anthropogenic emissions. Organic compounds from VCPs evaporate on atmospherically relevant time scales and include many species that are secondary organic aerosol (SOA) precursors. However, the chemistry leading to SOA, particularly that of intermediate volatility organic compounds (IVOCs), has not been fully represented in regional-scale models such as the Community Multiscale Air Quality (CMAQ) model, which tend to underpredict SOA concentrations in urban areas. Here we develop a model to represent SOA formation from VCP emissions. The model incorporates a new VCP emissions inventory and employs three new classes of emissions: siloxanes, oxygenated IVOCs, and nonoxygenated IVOCs. VCPs are estimated to produce 1.67 μg m^-3 of noontime SOA, doubling the current model predictions and reducing the SOA mass concentration bias from -75% to -58% when compared to observations in Los Angeles in 2010. While oxygenated and nonoxygenated intermediate volatility VCP species are emitted in similar quantities, SOA formation is dominated by the nonoxygenated IVOCs. Formaldehyde and SOA show similar relationships to temperature and bias signatures indicating common sources and/or chemistry. This work suggests that VCPs contribute up to half of anthropogenic SOA in Los Angeles and models must better represent SOA precursors from VCPs to predict the urban enhancement of SOA.

Regional modeling of secondary organic aerosol formation over eastern China: The impact of uptake coefficients of dicarbonyls and semivolatile process of primary organic aerosol

Capturing the secondary organic aerosol (SOA) concentration using the chemical transport model is difficult due to a large knowledge gap of its formation mechanism. Previous studies demonstrated the uptake of dicarbonyls and semivolatile process of primary organic aerosol (POA) emissions are the significant sources of SOA. However, the uptake coefficients of dicarbonyls have large uncertainties and the SOA from the semivolatile process of POA emission remains unclear. We applied the revised reactive uptake parameterization, with "salting effects" for dicarbonyls, and updated approaches for POA to the Community Multiscale Air Quality Modeling System (CMAQ) simulations for October 2014 to study their impacts on modeling the SOA formation over eastern China. We introduce a method of quantifying crystalized or deliquescent aerosols to further improve the parameterization. The revised glyoxal uptake coefficients results in higher glyoxal SOA in the Beijing-Tianjin-Hebei region, where is typically under low relative humidity (RH) and high aerosol pH conditions. It gives lower glyoxal SOA in the Pearl River Delta region, where is typically under high RH and low pH conditions. The updated parameterization gives negligible methylglyoxal SOA due to the low uptake coefficients. The implementation of semivolatile process of POA and the approach for potential SOA from combustion sources will largely decrease the predicted POA and increase the modeled SOA concentrations over eastern China. The increased SOA from POA emissions could improve the model performance for organic carbon and SOA. It slightly improves the performance in PM_2.5 modeling by compensating the reduction of modeled POA. This study indicates the mixed impact of a parameterization considering "salting effects" on modeling the dicarbonyls SOA in key regions of eastern China. It also demonstrates the improved performance by implementing the POA approaches in aerosol modeling using CMAQ. Meanwhile, the uncertainty in the revised reactive uptake parameterization and POA approaches is discussed.

Improving the representation of HONO chemistry in CMAQ and examining its impact on haze over China

We compare Community Multiscale Air Quality (CMAQ) model predictions with measured nitrous acid (HONO) concentrations in Beijing, China for December 2015. The model with the existing HONO chemistry in CMAQ severely under-estimates the observed HONO concentrations with a normalized mean bias of -97%. We revise the HONO chemistry in the model by implementing six additional heterogeneous reactions in the model: reaction of nitrogen dioxide (NO2) on ground surfaces, reaction of NO2 on aerosol surfaces, reaction of NO2 on soot surfaces, photolysis of aerosol nitrate, nitric acid displacement reaction, and hydrochloric acid displacement reaction. The model with the revised chemistry substantially increases HONO predictions and improves the comparison with observed data with a normalized mean bias of -5%. The photolysis of HONO enhances day-time hydroxyl radical by almost a factor of two. The enhanced hydroxyl radical concentrations compare favourably with observed data and produce additional sulfate via the reaction with sulfur dioxide, aerosol nitrate via the reaction with nitrogen dioxide, and secondary organic aerosols via the reactions with volatile organic compounds. The additional sulfate stemming from revised HONO chemistry improves the comparison with observed concentration; however, it does not close the gap between model prediction and the observation during polluted days.

Diverse response of surface ozone to COVID-19 lockdown in China

Ozone (O3) is a key oxidant and pollutant in the lower atmosphere. Significant increases in surface O3 have been reported in many cities during the COVID-19 lockdown. Here we conduct comprehensive observation and modeling analyses of surface O3 across China for periods before and during the lockdown. We find that daytime O3 decreased in the subtropical south, in contrast to increases in most other regions. Meteorological changes and emission reductions both contributed to the O3 changes, with a larger impact from the former especially in central China. The plunge in nitrogen oxide (NOx) emission contributed to O3 increases in populated regions, whereas the reduction in volatile organic compounds (VOC) contributed to O3 decreases across the country. Due to a decreasing level of NOx saturation from north to south, the emission reduction in NOx (46%) and VOC (32%) contributed to net O3 increases in north China; the opposite effects of NOx decrease (49%) and VOC decrease (24%) balanced out in central China, whereas the comparable decreases (45-55%) in these two precursors contributed to net O3 declines in south China. Our study highlights the complex dependence of O3 on its precursors and the importance of meteorology in the short-term O3 variability.

Predicting the Nonlinear Response of PM2.5 and Ozone to Precursor Emission Changes with a Response Surface Model

Reducing PM2.5 and ozone concentrations is important to protect human health and the environment. Chemical transport models, such as the Community Multiscale Air Quality (CMAQ) model, are valuable tools for exploring policy options for improving air quality but are computationally expensive. Here, we statistically fit an efficient polynomial function in a response surface model (pf-RSM) to CMAQ simulations over the eastern U.S. for January and July 2016. The pf-RSM predictions were evaluated using out-of-sample CMAQ simulations and used to examine the nonlinear response of air quality to emission changes. Predictions of the pf-RSM are in good agreement with the out-of-sample CMAQ simulations, with some exceptions for cases with anthropogenic emission reductions approaching 100%. NOX emission reductions were more effective for reducing PM2.5 and ozone concentrations than SO2, NH3, or traditional VOC emission reductions. NH3 emission reductions effectively reduced nitrate concentrations in January but increased secondary organic aerosol (SOA) concentrations in July. More work is needed on SOA formation under conditions of low NH3 emissions to verify the responses of SOA to NH3 emission changes predicted here. Overall, the pf-RSM performs well in the eastern U.S., but next-generation RSMs based on deep learning may be needed to meet the computational requirements of typical regulatory applications.

Evaluation of the offline-coupled GFSv15-FV3-CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States

As a candidate for the next-generation National Air Quality Forecast Capability (NAQFC), the meteorological forecast from the Global Forecast System with the new Finite Volume Cube-Sphere dynamical core (GFS-FV3) will be applied to drive the chemical evolution of gases and particles described by the Community Multiscale Air Quality modeling system. CMAQv5.0.2, a historical version of CMAQ, has been coupled with the North American Mesoscale Forecast System (NAM) model in the current operational NAQFC. An experimental version of the NAQFC based on the offline-coupled GFS-FV3 version 15 with CMAQv5.0.2 modeling system (GFSv15-CMAQv5.0.2) has been developed by the National Oceanic and Atmospheric Administration (NOAA) to provide real-time air quality forecasts over the contiguous United States (CONUS) since 2018. In this work, comprehensive region-specific, time-specific, and categorical evaluations are conducted for meteorological and chemical forecasts from the offline-coupled GFSv15-CMAQv5.0.2 for the year 2019. The forecast system shows good overall performance in forecasting meteorological variables with the annual mean biases of -0.2 °C for temperature at 2 m, 0.4% for relative humidity at 2 m, and 0.4 m s-1 for wind speed at 10 m compared to the METeorological Aerodrome Reports (METAR) dataset. Larger biases occur in seasonal and monthly mean forecasts, particularly in spring. Although the monthly accumulated precipitation forecasts show generally consistent spatial distributions with those from the remote-sensing and ensemble datasets, moderate-to-large biases exist in hourly precipitation forecasts compared to the Clean Air Status and Trends Network (CASTNET) and METAR. While the forecast system performs well in forecasting ozone (O3) throughout the year and fine particles with a diameter of 2.5 μm or less (PM2.5) for warm months (May-September), it significantly overpredicts annual mean concentrations of PM2.5. This is due mainly to the high predicted concentrations of fine fugitive and coarse-mode particle components. Underpredictions in the southeastern US and California during summer are attributed to missing sources and mechanisms of secondary organic aerosol formation from biogenic volatile organic compounds (VOCs) and semivolatile or intermediate-volatility organic compounds. This work demonstrates the ability of FV3-based GFS in driving the air quality forecasting. It identifies possible underlying causes for systematic region- and time-specific model biases, which will provide a scientific basis for further development of the next-generation NAQFC.

The Community Multiscale Air Quality (CMAQ) model versions 5.3 and 5.3.1: system updates and evaluation

The Community Multiscale Air Quality (CMAQ) model version 5.3 (CMAQ53), released to the public in August 2019 and followed by version 5.3.1 (CMAQ531) in December 2019, contains numerous science updates, enhanced functionality, and improved computation efficiency relative to the previous version of the model, 5.2.1 (CMAQ521). Major science advances in the new model include a new aerosol module (AERO7) with significant updates to secondary organic aerosol (SOA) chemistry, updated chlorine chemistry, updated detailed bromine and iodine chemistry, updated simple halogen chemistry, the addition of dimethyl sulfide (DMS) chemistry in the CB6r3 chemical mechanism, updated M3Dry bidirectional deposition model, and the new Surface Tiled Aerosol and Gaseous Exchange (STAGE) bidirectional deposition model. In addition, support for the Weather Research and Forecasting (WRF) model's hybrid vertical coordinate (HVC) was added to CMAQ53 and the Meteorology-Chemistry Interface Processor (MCIP) version 5.0 (MCIP50). Enhanced functionality in CMAQ53 includes the new Detailed Emissions Scaling, Isolation and Diagnostic (DESID) system for scaling incoming emissions to CMAQ and reading multiple gridded input emission files. Evaluation of CMAQ531 was performed by comparing monthly and seasonal mean daily 8 h average (MDA8) O₃ and daily PM_2.5 values from several CMAQ531 simulations to a similarly configured CMAQ521 simulation encompassing 2016. For MDA8 O₃, CMAQ531 has higher O₃ in the winter versus CMAQ521, due primarily to reduced dry deposition to snow, which strongly reduces wintertime O₃ bias (2-4 ppbv monthly average). MDA8 O₃ is lower with CMAQ531 throughout the rest of the year, particularly in spring, due in part to reduced O₃ from the lateral boundary conditions (BCs), which generally increases MDA8 O₃ bias in spring and fall ( 0.5 μg m^-3). For daily 24 h average PM_2.5, CMAQ531 has lower concentrations on average in spring and fall, higher concentrations in summer, and similar concentrations in winter to CMAQ521, which slightly increases bias in spring and fall and reduces bias in summer. Comparisons were also performed to isolate updates to several specific aspects of the modeling system, namely the lateral BCs, meteorology model version, and the deposition model used. Transitioning from a hemispheric CMAQ (HCMAQ) version 5.2.1 simulation to a HCMAQ version 5.3 simulation to provide lateral BCs contributes to higher O₃ mixing ratios in the regional CMAQ simulation in higher latitudes during winter (due to the decreased O₃ dry deposition to snow in CMAQ53) and lower O₃ mixing ratios in middle and lower latitudes year-round (due to reduced O₃ over the ocean with CMAQ53). Transitioning from WRF version 3.8 to WRF version 4.1.1 with the HVC resulted in consistently higher (1.0-1.5 ppbv) MDA8 O₃ mixing ratios and higher PM_2.5 concentrations (0.1-0.25 μg m^-3) throughout the year. Finally, comparisons of the M3Dry and STAGE deposition models showed that MDA8 O₃ is generally higher with M3Dry outside of summer, while PM_2.5 is consistently higher with STAGE due to differences in the assumptions of particle deposition velocities to non-vegetated surfaces and land use with short vegetation (e.g., grasslands) between the two models. For ambient NH₃, STAGE has slightly higher concentrations and smaller bias in the winter, spring, and fall, while M3Dry has higher concentrations and smaller bias but larger error and lower correlation in the summer.

Estimating US Background Ozone Using Data Fusion

US background (US-B) ozone (O3) is the O3 that would be present in the absence of US anthropogenic (US-A) emissions. US-B O3 varies by location and season and can make up a large, sometimes dominant, portion of total O3. Typically, US-B O3 is quantified using a chemical transport model (CTM) though results are uncertain due to potential errors in model process descriptions and inputs, and there are significant differences in various model estimates of US-B O3. We develop and apply a method to fuse observed O3 with US-B O3 simulated by a regional CTM (CMAQ). We apportion the model bias as a function of space and time to US-B and US-A O3. Trends in O3 bias are explored across different simulation years and varying model scales. We found that the CTM US-B O3 estimate was typically biased low in spring and high in fall across years (2016-2017) and model scales. US-A O3 was biased high on average, with bias increasing for coarser resolution simulations. With the application of our data fusion bias adjustment method, we estimate a 28% improvement in the agreement of adjusted US-B O3. Across the four estimates, we found annual mean CTM-simulated US-B O3 ranging from 30 to 37 ppb with the spring mean ranging from 32 to 39 ppb. After applying the bias adjustment, we found annual mean US-B O3 ranging from 32 to 33 ppb with the spring mean ranging from 37 to 39 ppb.

Reactive organic carbon emissions from volatile chemical products

Volatile chemical products (VCPs) are an increasingly important source of anthropogenic reactive organic carbon (ROC) emissions. Among these sources are everyday items, such as personal care products, general cleaners, architectural coatings, pesticides, adhesives, and printing inks. Here, we develop VCPy, a new framework to model organic emissions from VCPs throughout the United States, including spatial allocation to regional and local scales. Evaporation of a species from a VCP mixture in the VCPy framework is a function of the compound-specific physiochemical properties that govern volatilization and the timescale relevant for product evaporation. We introduce two terms to describe these processes: evaporation timescale and use timescale. Using this framework, predicted national per capita organic emissions from VCPs are 9.5 kg per person per year (6.4 kg C per person per year) for 2016, which translates to 3.05 Tg (2.06 Tg C), making VCPs a dominant source of anthropogenic organic emissions in the United States. Uncertainty associated with this framework and sensitivity to select parameters were characterized through Monte Carlo analysis, resulting in a 95 % confidence interval of national VCP emissions for 2016 of 2.61-3.53 Tg (1.76-2.38 Tg C). This nationwide total is broadly consistent with the U.S. EPA's 2017 National Emission Inventory (NEI); however, county-level and categorical estimates can differ substantially from NEI values. VCPy predicts higher VCP emissions than the NEI for approximately half of all counties, with 5 % of all counties having greater than 55 % higher emissions. Categorically, application of the VCPy framework yields higher emissions for personal care products (150 %) and paints and coatings (25 %) when compared to the NEI, whereas pesticides (-54 %) and printing inks (-13 %) feature lower emissions. An observational evaluation indicates emissions of key species from VCPs are reproduced with high fidelity using the VCPy framework (normalized mean bias of -13 % with r =0.95). Sector-wide, the effective secondary organic aerosol yield and maximum incremental reactivity of VCPs are 5.3 % by mass and 1.58 gO3 g-1, respectively, indicating VCPs are an important, and likely to date underrepresented, source of secondary pollution in urban environments.

Revealing the modulation of boundary conditions and governing processes on ozone formation over northern China in June 2017

In this study, ozonesonde data were used to evaluate the impact of different boundary conditions on the vertical distribution of ozone over urban Beijing. The comparison shows that the clean and static boundary conditions, referred to as PROFILE, apparently underestimate the ozone concentration over the upper troposphere and stratosphere, whereas the global chemical transport model (CTM) provides much more reasonable performance. Further investigation reveals that the boundary conditions exert larger impacts over areas with high altitudes and close distances to boundaries, such as the Tibetan Plateau, while they yield weak impacts on regions relatively far from the boundary, such as the North China Plain (NCP). Process analysis was conducted to investigate the modulation of physical and chemical processes on ozone formation in June 2017, illustrating that during the daytime of the high-O₃ period, the photochemical reactions within the planetary boundary layer (PBL) almost become the only source favorable to ozone accumulation. Motivated by this phenomenon, we constructed a linear regression and found that the maximum daily 8-hr ozone (MDA8) ozone concentration was highly correlated with the surface ozone change rate and chemical reactions in the PBL during the pollution period, with MDA8 ozone exceeding 70 ppbv over NCP. Based on this relationship as well as the design of numerical experiments, we propose a strategy of dynamic emission control. Firstly, the emission reduction during the peak ozone formation period may weaken the fast chemical reactions in the PBL and subsequent surface ozone concentration. Secondly, emission reduction one or two days prior to an episode might achieve larger ozone reduction through the accumulation effect. Lastly, emission control outside of the NCP may surpass the local impact under favorable meteorological conditions. Therefore, the efficacy of dynamic emission control was striking when both the accumulation and transport effect were taken into consideration.

An Episodic Assessment of Vehicle Emission Regulations on Saving Lives in California

Historically, California has been a world leader in the development and application of environmental regulations. Policies to address air pollution have reduced criteria pollutant emissions, improved regional air quality, and benefited public health. To this end, California has imposed strict regulations on light-duty, medium-duty, and heavy-duty vehicles to reduce ambient concentrations of health-damaging pollutants such as ozone and fine particulate matter (PM_2.5). Here, we compare the impact on air quality in California should California not have adopted on-road vehicle regulations (No Regulations Case) with the air quality associated with current regulations (Regulated Case). Simulations of atmospheric chemistry and transport are conducted to evaluate the impact of emissions on ambient levels of ozone and PM_2.5, and a health impact assessment tool is used to quantify and monetize societal impairment. Compared with the "Regulated Case," the "No Regulations Case" results in a maximum peak 8 h ozone level of 162 ppb and 24 h PM_2.5 of 42.7 μg/m³ in summer, and 107 μg/m³ and 24 h PM_2.5 in winter. The associated increases in the daily incidence of human health outcomes are $66 million per day and $116 million per day during peak pollutant formation periods in summer and winter, respectively. Overall, the findings quantitatively establish the role and importance of on-road vehicle regulations in protecting societal well-being.

Source-Receptor Relationship Revealed by the Halted Traffic and Aggravated Haze in Beijing during the COVID-19 Lockdown

The COVID-19 outbreak greatly limited human activities and reduced primary emissions particularly from urban on-road vehicles but coincided with Beijing experiencing "pandemic haze," raising the public concerns about the effectiveness of imposed traffic policies to improve the air quality. This paper explores the relationship between local vehicle emissions and the winter haze in Beijing before and during the COVID-19 lockdown based on an integrated analysis framework, which combines a real-time on-road emission inventory, in situ air quality observations, and a localized numerical modeling system. We found that traffic emissions decreased substantially during the COVID-19 pandemic, but its imbalanced emission abatement of NOx (76%, 125.3 Mg/day) and volatile organic compounds (VOCs, 53%, 52.9 Mg/day) led to a significant rise of atmospheric oxidants in urban areas, resulting in a modest increase in secondary aerosols due to inadequate precursors, which still offset reduced primary emissions. Moreover, the enhanced oxidizing capacity in the surrounding regions greatly increased the secondary particles with relatively abundant precursors, which was transported into Beijing and mainly responsible for the aggravated haze pollution. We recommend that mitigation policies should focus on accelerating VOC emission reduction and synchronously controlling regional sources to release the benefits of local traffic emission control.

Evaluating trends and seasonality in modeled PM2.5 concentrations using empirical mode decomposition

Regional-scale air quality models are being used for studying the sources, composition, transport, transformation, and deposition of fine particulate matter (PM_2.5). The availability of decadal air quality simulations provides a unique opportunity to explore sophisticated model evaluation techniques rather than relying solely on traditional operational evaluations. In this study, we propose a new approach for process-based model evaluation of speciated PM_2.5 using improved complete ensemble empirical mode decomposition with adaptive noise (improved CEEMDAN) to assess how well version 5.0.2 of the coupled Weather Research and Forecasting model-Community Multiscale Air Quality model (WRF-CMAQ) simulates the time-dependent long-term trend and cyclical variations in daily average PM_2.5 and its species, including sulfate (SO₄), nitrate (NO₃), ammonium (NH₄), chloride (Cl), organic carbon (OC), and elemental carbon (EC). The utility of the proposed approach for model evaluation is demonstrated using PM_2.5 data at three monitoring locations. At these locations, the model is generally more capable of simulating the rate of change in the long-term trend component than its absolute magnitude. Amplitudes of the sub-seasonal and annual cycles of total PM_2.5, SO₄, and OC are well reproduced. However, the time-dependent phase difference in the annual cycles for total PM_2.5, OC, and EC reveals a phase shift of up to half a year, indicating the need for proper temporal allocation of emissions and for updating the treatment of organic aerosols compared to the model version used for this set of simulations. Evaluation of sub-seasonal and interannual variations indicates that CMAQ is more capable of replicating the sub-seasonal cycles than interannual variations in magnitude and phase.

Impact of dimethylsulfide chemistry on air quality over the Northern Hemisphere

We implement oceanic dimethylsulfide (DMS) emissions and its atmospheric chemical reactions into the Community Multiscale Air Quality (CMAQv53) model and perform annual simulations without and with DMS chemistry to quantify its impact on tropospheric composition and air quality over the Northern Hemisphere. DMS chemistry enhances both sulfur dioxide (SO2) and sulfate (S O 4 2 - ) over seawater and coastal areas. It enhances annual mean surface SO2 concentration by +46 pptv andS O 4 2 - by +0.33 μg/m3 and decreases aerosol nitrate concentration by -0.07 μg/m3 over seawater compared to the simulation without DMS chemistry. The changes decrease with altitude and are limited to the lower atmosphere. Impacts of DMS chemistry onS O 4 2 - are largest in the summer and lowest in the fall due to the seasonality of DMS emissions, atmospheric photochemistry and resultant oxidant levels. Hydroxyl and nitrate radical-initiated pathways oxidize 75% of the DMS while halogen-initiated pathways oxidize 25%. DMS chemistry leads to more acidic particles over seawater by decreasing aerosol pH. IncreasedS O 4 2 - from DMS enhances atmospheric extinction while lower aerosol nitrate reduces the extinction so that the net effect of DMS chemistry on visibility tends to remain unchanged over most of the seawater.

Criteria pollutant impacts of volatile chemical products informed by near-field modeling

Consumer, industrial, and commercial product usage is a source of exposure to potentially hazardous chemicals. In addition, cleaning agents, personal care products, coatings, and other volatile chemical products (VCPs), evaporate and react in the atmosphere producing secondary pollutants. Here, we show high air emissions from VCP usage (≥ 14 kg person^-1 yr^-1, at least 1.7× higher than current operational estimates) are supported by multiple estimation methods and constraints imposed by ambient levels of ozone, hydroxyl radical (OH) reactivity, and the organic component of fine particulate matter (PM_2.5) in Pasadena, California. A near-field model, which estimates human chemical exposure during or in the vicinity of product use, indicates these high air emissions are consistent with organic product usage up to ~75 kg person^-1 yr^-1, and inhalation of consumer products could be a non-negligible exposure pathway. After constraining the PM_2.5 yield to 5% by mass, VCPs produce ~41% of the photochemical organic PM_2.5 (1.1 ± 0.3 μg m^-3) and ~17% of maximum daily 8-hr average ozone (9 ± 2 ppb) in summer Los Angeles. Therefore, both toxicity and ambient criteria pollutant formation should be considered when organic substituents are developed for VCPs in pursuit of safer and sustainable products and cleaner air.

Secondary organic aerosol formation from evaporated biofuels: comparison to gasoline and correction for vapor wall losses

With an ongoing interest in displacing petroleum-based sources of energy with biofuels, there is a need to measure and model the formation and composition of secondary organic aerosol (SOA) from organic compounds present in biofuels. We performed chamber experiments to study SOA formation from four recently identified biofuel molecules and mixtures and commercial gasoline under high NOx conditions: diisobutylene, cyclopentanone, an alkylfuran mixture, and an ethanol-to-hydrocarbon (ETH) mixture. Cyclopentanone and diisobutylene had a significantly lower potential to form SOA compared to commercial gasoline, with SOA mass yields lower than or equal to 0.2%. The alkylfuran mixture had an SOA mass yield (1.6%) roughly equal to that of gasoline (2.0%) but ETH had an average SOA mass yield (11.5%) that was six times higher than that of gasoline. We used a state-of-the-science model to parameterize or simulate the SOA formation in the chamber experiments while accounting for the influence of vapor wall losses. Simulations performed with vapor wall losses turned off and at atmospherically relevant conditions showed that the SOA mass yields were higher than those measured in the chamber at the same photochemical exposure and were also higher than those estimated using a volatility basis set that was fit to the chamber data. The modeled SOA mass yields were higher primarily because they were corrected for vapor wall losses to the Teflon® chamber.

Predicting secondary organic aerosol phase state and viscosity and its effect on multiphase chemistry in a regional-scale air quality model

Atmospheric aerosols are a significant public health hazard and have substantial impacts on the climate. Secondary organic aerosols (SOAs) have been shown to phase separate into a highly viscous organic outer layer surrounding an aqueous core. This phase separation can decrease the partitioning of semi-volatile and low-volatile species to the organic phase and alter the extent of acid-catalyzed reactions in the aqueous core. A new algorithm that can determine SOA phase separation based on their glass transition temperature (T _g), oxygen to carbon (O : C) ratio and organic mass to sulfate ratio, and meteorological conditions was implemented into the Community Multiscale Air Quality Modeling (CMAQ) system version 5.2.1 and was used to simulate the conditions in the continental United States for the summer of 2013. SOA formed at the ground/surface level was predicted to be phase separated with core-shell morphology, i.e., aqueous inorganic core surrounded by organic coating 65.4 % of the time during the 2013 Southern Oxidant and Aerosol Study (SOAS) on average in the isoprene-rich southeastern United States. Our estimate is in proximity to the previously reported ~ 70 % in literature. The phase states of organic coatings switched between semi-solid and liquid states, depending on the environmental conditions. The semi-solid shell occurring with lower aerosol liquid water content (western United States and at higher altitudes) has a viscosity that was predicted to be 10²-10¹² Pa s, which resulted in organic mass being decreased due to diffusion limitation. Organic aerosol was primarily liquid where aerosol liquid water was dominant (eastern United States and at the surface), with a viscosity < 10² Pa s. Phase separation while in a liquid phase state, i.e., liquid-liquid phase separation (LLPS), also reduces reactive uptake rates relative to homogeneous internally mixed liquid morphology but was lower than aerosols with a thick viscous organic shell. The sensitivity cases performed with different phase-separation parameterization and dissolution rate of isoprene epoxydiol (IEPOX) into the particle phase in CMAQ can have varying impact on fine particulate matter (PM_2.5) organic mass, in terms of bias and error compared to field data collected during the 2013 SOAS. This highlights the need to better constrain the parameters that govern phase state and morphology of SOA, as well as expand mechanistic representation of multiphase chemistry for non-IEPOX SOA formation in models aided by novel experimental insights.

Simulation of organic aerosol formation during the CalNex study: updated mobile emissions and secondary organic aerosol parameterization for intermediate-volatility organic compounds

We describe simulations using an updated version of the Community Multiscale Air Quality model version 5.3 (CMAQ v5.3) to investigate the contribution of intermediate-volatility organic compounds (IVOCs) to secondary organic aerosol (SOA) formation in southern California during the CalNex study. We first derive a model-ready parameterization for SOA formation from IVOC emissions from mobile sources. To account for SOA formation from both diesel and gasoline sources, the parameterization has six lumped precursor species that resolve both volatility and molecular structure (aromatic versus aliphatic). We also implement new mobile-source emission profiles that quantify all IVOCs based on direct measurements. The profiles have been released in SPECIATE 5.0. By incorporating both comprehensive mobile-source emission profiles for semivolatile organic compounds (SVOCs) and IVOCs and experimentally constrained SOA yields, this CMAQ configuration best represents the contribution of mobile sources to urban and regional ambient organic aerosol (OA). In the Los Angeles region, gasoline sources emit 4 times more non-methane organic gases (NMOGs) than diesel sources, but diesel emits roughly 3 times more IVOCs on an absolute basis. The revised model predicts all mobile sources (including on- and off-road gasoline, aircraft, and on- and off-road diesel) contribute ~ 1 μgm-3 to the daily peak SOA concentration in Pasadena. This represents a ~ 70% increase in predicted daily peak SOA formation compared to the base version of CMAQ. Therefore, IVOCs in mobile-source emissions contribute almost as much SOA as traditional precursors such as single-ring aromatics. However, accounting for these emissions in CMAQ does not reproduce measurements of either ambient SOA or IVOCs. To investigate the potential contribution of other IVOC sources, we performed two exploratory simulations with varying amounts of IVOC emissions from nonmobile sources. To close the mass balance of primary hydrocarbon IVOCs, IVOCs would need to account for 12% of NMOG emissions from nonmobile sources (or equivalently 30.7 t d-1 in the Los Angeles-Pasadena region), a value that is well within the reported range of IVOC content from volatile chemical products. To close the SOA mass balance and also explain the mildly oxygenated IVOCs in Pasadena, an additional 14.8% of nonmobile-source NMOG emissions would need to be IVOCs (assuming SOA yields from the mobile IVOCs apply to nonmobile IVOCs). However, an IVOC-to-NMOG ratio of 26.8% (or equivalently 68.5 t d-1 in the Los Angeles-Pasadena region) for nonmobile sources is likely unrealistically high. Our results highlight the important contribution of IVOCs to SOA production in the Los Angeles region but underscore that other uncertainties must be addressed (multigenerational aging, aqueous chemistry and vapor wall losses) to close the SOA mass balance. This research also highlights the effectiveness of regulations to reduce mobile-source emissions, which have in turn increased the relative importance of other sources, such as volatile chemical products.

Resolving ambient organic aerosol formation and aging pathways with simultaneous molecular composition and volatility observations

Organic aerosol (OA) constitutes a significant fraction of atmospheric fine particle mass. However, the precursors and chemical processes responsible for a majority of OA are rarely conclusively identified. We use online observations of hundreds of simultaneously measured molecular components obtained from 15 laboratory OA formation experiments with constraints on their effective saturation vapor concentrations to attribute the VOC precursors and subsequent chemical pathways giving rise to the vast majority of OA mass measured in two forested regions. We find that precursors and chemical pathways regulating OA composition and volatility are dynamic over hours to days, with their variations driven by coupled interactions between multiple oxidants. The extent of physical and photochemical aging, and its modulation by NOx, were key to a uniquely comprehensive combined composition-volatility description of OA. Our findings thus provide some of the most complete mechanistic-level guidance to the development of OA descriptions in air quality and Earth system models.

Time-Resolved Intermediate-Volatility and Semivolatile Organic Compound Emissions from Household Coal Combustion in Northern China

Coal combustion in low-efficiency household stoves results in the emission of large amounts of nonmethane organic compounds (NMOCs), including intermediate-volatility compounds (IVOCs) and semivolatile organic compounds (SVOCs). This conceptual picture is reasonably well established, however, quantitative assessment of I/SVOC emissions from household stoves is rare. We used a proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS) to quantify the emissions of organic gases from a typical Chinese household coal stove operated with anthracite and bituminous coals. Most NMOCs (approximately 64-88%) were dominated by hydrocarbons and emitted during the ignition and flaming phases. The ratio of oxidized hydrocarbons increased during the flaming and smoldering stages due to the elevated combustion efficiency. The average emission factors of NMOCs were 121 ± 25.7 and 3690 ± 930 mg/kg for anthracite and bituminous coals, respectively. I/SVOCs contributed to approximately 30% of the total emitted NMOC mass during bituminous coal combustion, much higher than the contribution of biomass burning (approximately 1.5%). Furthermore, I/SVOCs may contribute over 70% of the secondary organic aerosol (SOA) mass formed from gaseous organic species emitted as a result of bituminous coal combustion. This study highlights the importance of inventorying coal-originated I/SVOCs when conducting SOA formation simulation studies.

The impact of air pollutant deposition on solar energy system efficiency: An approach to estimate PV soiling effects with the Community Multiscale Air Quality (CMAQ) model

Deposition and accumulation of aerosol particles on photovoltaics (PV) panels, which is commonly referred to as "soiling of PV panels," impacts the performance of the PV energy system. It is desirable to estimate the soiling effect at different locations and times for modeling the PV system performance and devising cost-effective mitigation. This study presents an approach to estimate the soiling effect by utilizing particulate matter (PM) dry deposition estimates from air quality model simulations. The Community Multiscale Air Quality (CMAQ) modeling system used in this study was developed by the U.S. Environmental Protection Agency (U.S. EPA) for air quality assessments, rule-making, and research. Three deposition estimates based on different surface roughness length parameters assumed in CMAQ were used to illustrate the soling effect in different land-use types. The results were analyzed for three locations in the U.S. for year 2011. One urban and one suburban location in Colorado were selected because there have been field measurements of particle deposition on solar panels and analysis on the consequent soiling effect performed at these locations. The third location is a coastal city in Texas, the City of Brownsville. These three locations have distinct ambient environments. CMAQ underestimates particle deposition by 40% to 80% when compared to the field measurements at the two sites in Colorado due to the underestimations in both the ambient PM₁₀ concentration and deposition velocity. The estimated panel transmittance sensitivity due to the deposited particles is higher than the sensitivity obtained from the measurements in Colorado. The final soiling effect, which is transmittance loss, is estimated as 3.17 ± 4.20% for the Texas site, 0.45 ± 0.33%, and 0.31 ± 0.25% for the Colorado sites. Although the numbers are lower compared to the measurements in Colorado, the results are comparable with the soiling effects observed in U.S.

Projected changes in particulate matter concentrations in the South Coast Air Basin due to basin-wide reductions in nitrogen oxides, volatile organic compounds, and ammonia emissions

An ozone abatement strategy for the South Coast Air Basin (SoCAB) has been proposed by the South Coast Air Quality Management District (SCAQMD) and the California Air Resources Board (ARB). The proposed emissions reduction strategy is focused on the reduction of nitrogen oxide (NO_x) emissions by the year 2030. Two high PM_2.5 concentration episodes with high ammonium nitrate compositions occurring during September and November 2008 were simulated with the Community Multi-scale Air Quality model (CMAQ). All simulations were made with same meteorological files provided by the SCAQMD to allow them to be more directly compared with their previous modeling studies. Although there was an overall under-prediction bias, the CMAQ simulations were within an overall normalized mean error of 50%; a range that is considered acceptable performance for PM modeling. A range of simulations of these episodes were made to evaluate sensitivity to NO_x and ammonia emissions inputs for the future year 2030. It was found that the current ozone control strategy will reduce daily average PM_2.5 concentrations. However, the targeted NO_x reductions for ozone were not found to be optimal for reducing PM_2.5 concentrations. Ammonia emission reductions reduced PM_2.5 and this might be considered as part of a PM_2.5 control strategy. Implications: The SCAQMD and the ARB have proposed an ozone abatement strategy for the SoCAB that focuses on NO_x emission reductions. Their strategy will affect both ozone and PM_2.5. Two episodes that occurred during September and November 2008 with high PM_2.5 concentrations and high ammonium nitrate composition were selected for simulation with different levels of nitrogen oxide and ammonia emissions for the future year 2030. It was found that the ozone control strategy will reduce maximum daily average PM_2.5 concentrations but its effect on PM_2.5 concentrations is not optimal.

Assessing PM2.5 Model Performance for the Conterminous U.S. with Comparison to Model Performance Statistics from 2007-2015

Previous studies have proposed that model performance statistics from earlier photochemical grid model (PGM) applications can be used to benchmark performance in new PGM applications. A challenge in implementing this approach is that limited information is available on consistently calculated model performance statistics that vary spatially and temporally over the U.S. Here, a consistent set of model performance statistics are calculated by year, season, region, and monitoring network for PM2.5 and its major components using simulations from versions 4.7.1-5.2.1 of the Community Multiscale Air Quality (CMAQ) model for years 2007-2015. The multi-year set of statistics is then used to provide quantitative context for model performance results from the 2015 simulation. Model performance for PM2.5 organic carbon in the 2015 simulation ranked high (i.e., favorable performance) in the multi-year dataset, due to factors including recent improvements in biogenic secondary organic aerosol and atmospheric mixing parameterizations in CMAQ. Model performance statistics for the Northwest region in 2015 ranked low (i.e., unfavorable performance) for many species in comparison to the 2007-2015 dataset. This finding motivated additional investigation that suggests a need for improved speciation of wildfire PM2.5emissions and modeling of boundary layer dynamics near water bodies. Several limitations were identified in the approach of benchmarking new model performance results with previous results. Since performance statistics vary widely by region and season, a simple set of national performance benchmarks (e.g., one or two targets per species and statistic) as proposed previously are inadequate to assess model performance throughout the U.S. Also, trends in model performance statistics for sulfate over the 2007 to 2015 period suggest that model performance for earlier years may not be a useful reference for assessing model performance for recent years in some cases. Comparisons of results from the 2015 base case with results from five sensitivity simulations demonstrated the importance of parameterizations of NH3 surface exchange, organic aerosol volatility and production, and emissions of crustal cations for predicting PM2.5 species concentrations.

Additional Benefits of Federal Air-Quality Rules: Model Estimates of Controllable Biogenic Secondary Organic Aerosol

Atmospheric models that accurately describe the fate and transport of trace species for the right reasons aid in the development of effective air-quality management strategies that safeguard human health. Controllable emissions facilitate the formation of biogenic secondary organic aerosol (BSOA) to enhance the atmospheric fine particulate matter (PM2.5) burden. Previous modeling with the EPA's Community Multiscale Air Quality (CMAQ) model predicted that anthropogenic primary organic aerosol (POA) emissions had the greatest impact on BSOA. That experiment included formation processes involving semivolatile partitioning but not aerosol liquid water (ALW), a ubiquitous PM constituent. We conduct 17 summertime CMAQ simulations with updated chemistry and evaluate changes in BSOA due to the removal of individual pollutants and source sectors for the contiguous U.S. CMAQ predicts SO2 from electricity generating units, and mobile source NOX emissions have the largest impacts on BSOA. The removal of anthropogenic NOX, SO2, and POA emissions during the simulation reduces the nationally averaged BSOA by 23, 14, and 8% and PM2.5 by 9.2, 14, and 5.3%, respectively. ALW mass concentrations decrease by 10 and 35% in response to the removal of NOX and SO2 emissions. This work contributes chemical insight into ancillary benefits of Federal NOX and SO2 rules that concurrently reduce organic PM2.5 mass.

Southeast Atmosphere Studies: learning from model-observation syntheses

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

Regional Similarities and NOx-related Increases in Biogenic Secondary Organic Aerosol in Summertime Southeastern U.S

During the 2013 Southern Oxidant and Aerosol Study, Fourier Transform Infrared Spectroscopy (FTIR) and Aerosol Mass Spectrometer (AMS) measurements of submicron mass were collected at Look Rock (LRK), Tennessee, and Centreville (CTR), Alabama. Carbon monoxide and submicron sulfate and organic mass concentrations were 15-60% higher at CTR than at LRK but their time series had moderate correlations (r~0.5). However, NOx had no correlation (r=0.08) between the two sites with nighttime-to-early-morning peaks 3~10 times higher at CTR than at LRK. Organic mass (OM) sources identified by FTIR Positive Matrix Factorization (PMF) had three very similar factors at both sites: Fossil Fuel Combustion (FFC) related organic aerosols, Mixed Organic Aerosols (MOA), and Biogenic Organic Aerosols (BOA). The BOA spectrum from FTIR is similar (cosine similarity > 0.6) to that of lab-generated particle mass from the photochemical oxidation of both isoprene and monoterpenes under high NOx conditions from chamber experiments. The BOA mass fraction was highest during the night at CTR but in the afternoon at LRK. AMS PMF resulted in two similar pairs of factors at both sites and a third nighttime NOx-related factor (33% of OM) at CTR but a daytime nitrate-related factor (28% of OM) at LRK. NOx was correlated with BOA and LO-OOA for NOx concentrations higher than 1 ppb at both sites, producing 0.5 ± 0.1 μg m-3 for CTR-LO-OOA and 1.0 ± 0.3 μg m-3 for CTR-BOA above 1 ppb additional biogenic OM for each 1 ppb increase of NOx.