Temperature-dependent emissions dominate aerosol and ozone formation in Los Angeles

Despite declines in transportation emissions, urban North America and Europe still face unhealthy air pollution levels. This has challenged conventional understanding of the sources of their volatile organic compound (VOC) precursors. Using airborne flux measurements to map emissions of a wide range of VOCs, we demonstrate that biogenic terpenoid emissions contribute ~60% of emitted VOC OH reactivity, ozone, and secondary organic aerosol formation potential in summertime Los Angeles and that this contribution strongly increases with temperature. This implies that control of nitrogen oxides is key to reducing ozone formation in Los Angeles. We also show some anthropogenic VOC emissions increase with temperature, which is an effect not represented in current inventories. Air pollution mitigation efforts must consider that climate warming will strongly change emission amounts and composition.

Air quality modeling in the metropolitan area of São Paulo, Brazil: A review

Numerous studies have used air quality models to estimate pollutant concentrations in the Metropolitan Area of São Paulo (MASP) by using different inputs and assumptions. Our objectives are to summarize these studies, compare their performance, configurations, and inputs, and recommend areas of further research. We examined 29 air quality modeling studies that focused on ozone (O3) and fine particulate matter (PM2.5) performed over the MASP, published from 2001 to 2023. The California Institute of Technology airshed model (CIT) was the most used offline model, while the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was the most used online model. Because the main source of air pollution in the MASP is the vehicular fleet, it is commonly used as the only anthropogenic input emissions. Simulation periods were typically the end of winter and during spring, seasons with higher O3 and PM2.5 concentrations. Model performance for hourly ozone is good with half of the studies with Pearson correlation above 0.6 and root mean square error (RMSE) ranging from 7.7 to 27.1 ppb. Fewer studies modeled PM2.5 and their performance is not as good as ozone estimates. Lack of information on emission sources, pollutant measurements, and urban meteorology parameters is the main limitation to perform air quality modeling. Nevertheless, researchers have used measurement campaign data to update emission factors, estimate temporal emission profiles, and estimate volatile organic compounds (VOCs) and aerosol speciation. They also tested different emission spatial disaggregation approaches and transitioned to global meteorological reanalysis with a higher spatial resolution. Areas of research to explore are further evaluation of models' physics and chemical configurations, the impact of climate change on air quality, the use of satellite data, data assimilation techniques, and using model results in health impact studies. This work provides an overview of advancements in air quality modeling within the MASP and offers practical approaches for modeling air quality in other South American cities with limited data, particularly those heavily impacted by vehicle emissions.

COVID-19 perturbation on US air quality and human health impact assessment

The COVID-19 stay-at-home orders issued in the United States caused significant reductions in traffic and economic activities. To understand the pandemic's perturbations on US emissions and impacts on urban air quality, we developed near-real-time bottom-up emission inventories based on publicly available energy and economic datasets, simulated the emission changes in a chemical transport model, and evaluated air quality impacts against various observations. The COVID-19 pandemic affected US emissions across broad-based energy and economic sectors and the impacts persisted to 2021. Compared with 2019 business-as-usual emission scenario, COVID-19 perturbations resulted in annual decreases of 10-15% in emissions of ozone (O3) and fine particle (PM2.5) gas-phase precursors, which are about two to four times larger than long-term annual trends during 2010-2019. While significant COVID-induced reductions in transportation and industrial activities, particularly in April-June 2020, resulted in overall national decreases in air pollutants, meteorological variability across the nation led to local increases or decreases of air pollutants, and mixed air quality changes across the United States between 2019 and 2020. Over a full year (April 2020 to March 2021), COVID-induced emission reductions led to 3-4% decreases in national population-weighted annual fourth maximum of daily maximum 8-h average O3 and annual PM2.5. Assuming these emission reductions could be maintained in the future, the result would be a 4-5% decrease in premature mortality attributable to ambient air pollution, suggesting that continued efforts to mitigate gaseous pollutants from anthropogenic sources can further protect human health from air pollution in the future.

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.

Major Regional-Scale Production of O3 and Secondary Organic Aerosol in Remote Amazon Regions from the Dynamics and Photochemistry of Urban and Forest Emissions

The Amazon rainforest suffers increasing pressure from anthropogenic activities. A key aspect not fully understood is how anthropogenic atmospheric emissions within the basin interact with biogenic emissions and impact the forest's atmosphere and biosphere. We combine a high-resolution atmospheric chemical transport model with an improved emissions inventory and in-situ measurements to investigate a surprisingly high concentration of ozone (O₃) and secondary organic aerosol (SOA) 150-200 km downwind of Manaus city in an otherwise pristine forested region. We show that atmospheric dynamics and photochemistry determine a gross production of secondary pollutants seen in the simulation. After sunrise, the erosion of the nocturnal boundary layer mixes natural forest emissions, rich in biogenic volatile organic compounds, with a lofted pollution layer transported overnight, rich in nitrogen oxides and formaldehyde. As a result, O₃ and SOA concentrations greater than ∼47 ppbv and 1.8 μg m^-3, respectively, were found, with maximum concentrations occurring at 2 pm LT, 150-200 km downwind of Manaus city. These high concentrations affect a large primary forested area of about 11,250 km². These oxidative areas are under a NOx-limited regime so that changes in NOx emissions from Manaus have a significant impact on O₃ and SOA production.

Significant contribution of lightning NOx to summertime surface O3 on the Tibetan Plateau

Lightning generates nitrogen oxides (NO_x) in the troposphere, an important precursor of tropospheric ozone (O₃). The Tibetan Plateau (TP) is considered to be a global atmospheric background location with limited anthropogenic influences. However, the observed summertime surface O₃ concentration on the TP is 25% higher than that in highly polluted regions (e.g., southern China). Previous studies have suggested that lightning-produced NO_x (LNO_x) can affect the concentration of surface O₃. We used the Weather Research and Forecasting coupled with chemistry (WRF-Chem) model combined with satellite, ground-based, and airborne observations to evaluate the contribution of LNO_x to the surface O₃ budget on the TP. Our results showed that LNO_x contributed approximately 15% of the surface NO_x emission on the TP in summer. Accordingly, the contribution of LNO_x to the summertime surface daily maximum 8-h average (MDA8) O₃ on the TP was 9.3 ± 7.1 ppb, which was 17.5% ± 14.5% of the total concentration of the surface MDA8 O₃. In addition, our study found that the number of moles of NO produced per lightning flash (LNO_x production efficiency) significantly affected the surface concentration of NO_x, OH, and MDA8 O₃. Increasing the LNO_x production efficiency (PE) from 0 to 330 mol NO flash^-1 increased the concentration of MDA8 O₃ by up to 20% on the TP. Our study revealed that lightning significantly affects the atmospheric chemical processes involving O₃ on the TP.

Global, high-resolution, reduced-complexity air quality modeling for PM2.5 using InMAP (Intervention Model for Air Pollution)

Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM2.5). Designing policies to reduce these deaths relies on air quality modeling for estimating changes in PM2.5 concentrations from many scenarios at high spatial resolution. However, air quality modeling typically has substantial requirements for computation and expertise, which limits policy design, especially in countries where most PM2.5-related deaths occur. Lower requirement reduced-complexity models exist but are generally unavailable worldwide. Here, we adapt InMAP, a reduced-complexity model originally developed for the United States, to simulate annual-average primary and secondary PM2.5 concentrations across a global-through-urban spatial domain: “Global InMAP”. Global InMAP uses a variable resolution grid, with horizontal grid cell widths ranging from 500 km in remote locations to 4km in urban locations. We evaluate Global InMAP performance against both measurements and a state-of-the-science chemical transport model, GEOS-Chem. Against measurements, InMAP predicts total PM2.5 concentrations with a normalized mean error of 62%, compared to 41% for GEOS-Chem. For the emission scenarios considered, Global InMAP reproduced GEOS-Chem pollutant concentrations with a normalized mean bias of 59%–121%, which is sufficient for initial policy assessment and scoping. Global InMAP can be run on a desktop computer; simulations here took 2.6–8.4 hours. This work presents a global, open-source, reduced-complexity air quality model to facilitate policy assessment worldwide, providing a screening tool for reducing air pollution-related deaths where they occur most.

Roles of semivolatile and intermediate-volatility organic compounds in secondary organic aerosol formation and its implication: A review

Secondary organic aerosol (SOA) is a very important component of fine particulate matter (PM_2.5) in the atmosphere. However, the simulations of SOA, which could help to elucidate the detailed mechanism of SOA formation and quantify the roles of various precursors, remains unsatisfactory, as SOA levels are frequently underestimated. It has been found that the performance of SOA formation models can be significantly improved by incorporating the emission and evolution of semivolatile and intermediate-volatility organic compounds (S/IVOCs). In order to explore the roles of S/IVOCs in SOA formation, this study reviews some simulation models which could consider S/IVOCs for SOA formation as well as the development of emission inventories of S/IVOCs and S/IVOC modules for SOA formation. In addition, the future research directions for simulations of the effect of S/IVOCs on SOA formation are suggested.

Ozone control strategies for local formation- and regional transport-dominant scenarios in a manufacturing city in southern China

Given the leveling off of fine particulate matter (PM_2.5), ground-level ozone (O₃) pollution has become one of the most significant atmospheric pollution issues in the Pearl River Delta (PRD) region in China, especially in the manufacturing city of Dongguan, which faces more severe O₃ pollution. The development of strategies to control O₃ precursor emissions, including volatile organic compounds (VOCs) and nitrogen oxide (NO_x), depends to a large extent on the source region of the O₃ pollution. In this study, by combining the Weather Research and Forecasting model coupled with chemistry (WRF-Chem), the Empirical Kinetic Modeling Approach (EKMA), and the Flexible Particle model (FLEXPART), more effective strategies of controlling O₃ precursor emissions were identified under two typical types of O₃ pollution episodes: local formation (LF)-dominant (8-12 September 2019) and regional transport (RT)-dominant (23-27 October 2017) episodes, distinguished by the WRF-FLEXPART model. During the LF-dominant episode, the EKMA revealed that the O₃ formation in Dongguan was in a transitional regime, and the abatement of solvent use-VOCs emissions in the key area of Dongguan was more effective in reducing O₃ levels, with an emission reduction benefit 1.7 times that of total VOCs emission sources throughout Dongguan. With respect to the RT-dominant episode, the reduction in VOCs emissions in the local region did not effectively curb O₃ pollution, although the photochemical regime of the O₃ formation in Dongguan was VOCs-limited. A 50% reduction in NO_x emissions in the upwind regions (parts of Guangzhou and Huizhou) effectively decreased the O₃ concentration in Dongguan by 17%. The results of this study emphasize the importance of the source region of O₃ pollution in the implementation of effective O₃ control strategies and provide valuable insights for region-specific precursor emission policy formulation, not only in Dongguan, but also in other regions facing severe O₃ pollution.

Satellite-Based Diagnosis and Numerical Verification of Ozone Formation Regimes over Nine Megacities in East Asia

Urban photochemical ozone (O3) formation regimes (NOx- and VOC-limited regimes) at nine megacities in East Asia were diagnosed based on near-surface O3 columns from 900 to 700 hPa, nitrogen dioxide (NO2), and formaldehyde (HCHO), which were inferred from measurements by ozone-monitoring instruments (OMI) for 2014–2018. The nine megacities included Beijing, Tianjin, Hebei, Shandong, Shanghai, Seoul, Busan, Tokyo, and Osaka. The space-borne HCHO–to–NO2 ratio (FNR) inferred from the OMI was applied to nine megacities and verified by a series of sensitivity tests of Weather Research and Forecasting model with Chemistry (WRF-Chem) simulations by halving the NOx and VOC emissions. The results showed that the satellite-based FNRs ranged from 1.20 to 2.62 and the regimes over the nine megacities were identified as almost NOx-saturated conditions, while the domain-averaged FNR in East Asia was >2. The results of WRF–Chem sensitivity modeling show that O3 increased when the NOx emissions reduced, whereas VOC emission reduction showed a significant decrease in O3, confirming the characteristics of VOC-limited conditions in all of the nine megacities. When both NOx and VOC emissions were reduced, O3 decreased in most cities, but increased in the three lowest-FNRs megacities, such as Shanghai, Seoul, and Tokyo, where weakened O3 titration caused by NOx reduction had a larger enough effect to offset O3 suppression induced by the decrease in VOCs. Our model results, therefore, indicated that the immediate VOC emission reduction is a key controlling factor to decrease megacity O3 in East Asia, and also suggested that both VOC and NOx reductions may not be of broad utility in O3 abatement in megacities and should be considered judiciously in highly NOx-saturated cities in East Asia.

Assessment of Aerosol Mechanisms and Aerosol Meteorology Feedback over an Urban Airshed in India Using a Chemical Transport Model

The direct aerosol-radiative effects in the WRF-Chem model account for scattering/absorption of solar radiation due to aerosols, while aerosol–cloud interactions result in modifying wet scavenging of the ambient concentrations as an indirect aerosol effect. In this study, impact of aerosol on meteorological parameters, PM10 and ozone concentrations are analysed which revealed (i) that a net decrease in shortwave and longwave radiation by direct feedback results in decrease in temperature up to 0.05 K, (ii) that a net increase due to longwave and shortwave radiation when both direct and indirect effects are taken together results in an increase in temperature up to 0.25 K (where the mean of temperature is 33.5 °C and standard deviation 2.13 °C), (iii) a marginal increase in boundary layer height of 50 m with increase in temperature with feedbacks, (iv) overall net increase in radiation by direct and indirect effect together result in an increase in PM10 concentration up to 12 μg m−3 (with PM10 mean as 84.5 μg m−3 and standard deviation 28 μg m−3) and an increase in ozone concentration up to 3 μg m−3 (with ozone mean as 29.65 μg m−3 and standard deviation 5.2 μg m−3) mainly due to net increase in temperature. Furthermore, impact of sensitivity of different aerosol mechanisms on PM10 concentrations was scrutinized for two different mechanisms that revealed underestimation by both of the mechanisms with MOSAIC scheme, showing less fractional bias than MADE/SORGAM. For the dust storm period, MOSAIC scheme simulated higher mass concentrations than MADE/SORGAM scheme and performed well for dust-storm days while closely capturing the peaks of high dust concentrations. This study is one of the first few to demonstrate the impact of both direct and indirect aerosol feedback on local meteorology and air quality using a meteorology–chemistry modelling framework; the WRF-Chem model in a tropical urban airshed in India located in semi-arid climatic zone. It is inferred that semi-arid climatic conditions behave in a vastly different manner than other climatic zones for direct and indirect radiative feedback effects.

Sensitivity of Simulated PM2.5 Concentrations over Northeast Asia to Different Secondary Organic Aerosol Modules during the KORUS-AQ Campaign

A numerical sensitivity study on secondary organic aerosol formation has been carried out by employing the WRF-Chem (Weather Research and Forecasting model coupled with Chemistry). Two secondary organic aerosol formation modules, the Modal Aerosol Dynamics model for Europe/Volatility Basis Set (MADE/VBS) and the Modal Aerosol Dynamics model for Europe/Secondary Organic Aerosol Model (MADE/SORGAM) were employed in the WRF-Chem model, and surface PM2.5 (particulate matter less than 2.5 μm in size) mass concentration and the composition of its relevant chemical sources, i.e., SO42−, NO3−, NH4+, and organic carbon (OC) were simulated during the Korea-United States Air Quality (KORUS-AQ) campaign period (1 May to 12 June 2016). We classified the KORUS-AQ period into two cases, the stagnant period (16–21 May) which was dominated by local emission and the long-range transport period (25–31 May) which was affected by transport from the leeward direction, and focused on the differences in OC secondary aerosol formation between two modules over Northeast Asia. The simulated surface PM2.5 chemical components via the two modules showed the largest systematic biases in surface OC, with a mean bias of 4.5 μg m−3, and the second largest in SO42− abundance of 2.2 μg m−3 over Seoul. Compared with surface observations at two ground sites located near the western coastal Korean Peninsula, MADE/VBS exhibited the overpredictions in OC by 170–180%, whereas MADE/SORGAM showed underpredictions by 49–65%. OC and sulfate via MADE/VBS were simulated to be much higher than that simulated by MADE/SORGAM by a factor of 2.8–3.5 and 1.5–1.9, respectively. Model verification against KORUS-AQ aircraft measurements also showed large discrepancies in simulated non-surface OC between the two modules by a factor of five, with higher OC by MADE/VBS and lower IC by MADE/SORGAM, whereas much closer MADE/VBS simulations to the KORUS-AQ aircraft measurements were found. On the basis of the aircraft measurements, the aggregated bias (sum of four components) for PM2.5 mass concentrations from the MADE/VBS module indicated that the simulation was much closer to the measurements, nevertheless more elaborate analysis on the surface OC simulation performance would be needed to improve the ground results. Our findings show that significant inconsistencies are present in the secondary organic aerosol formation simulations, suggesting that PM2.5 forecasts should be considered with great caution, as well as in the context of policymaking in the Northeast Asia region.

Impact of the ‘13th Five-Year Plan’ Policy on Air Quality in Pearl River Delta, China: A Case Study of Haizhu District in Guangzhou City Using WRF-Chem

Due to increasingly stringent control policy, air quality has generally improved in major cities in China during the past decade. However, the standards of national regulation and the World Health Organization are yet to be fulfilled in certain areas (in some urban districts among the cities) and/or certain periods (during pollution episode event). A further control policy, hence, has been issued in the 13th Five-Year Plan (2016–2020, hereafter 13th FYP). It will be of interest to evaluate the air quality before the 13th FYP (2015) and to estimate the potential air quality by the end of the 13th FYP (2020) with a focus on the area of an urban district and the periods of severe pollution episodes. Based on observation data of major air pollutants, including SO2 (sulphur dioxide), NO2 (nitrogen dioxide), CO (carbon monoxide), PM10 (particulate matter with aerodynamic diameter equal to or less than 10 μm), PM2.5 (particulate matter with aerodynamic diameter equal to or less than 2.5 µm) and O3 (Ozone), the air quality of Haizhu district [an urban district in the Pearl River Delta (PRD), China] in 2015 suggested that typical heavy pollution occurred in winter and the hot season, with NO2 or PM2.5 as the key pollutants in winter and O3 as the key pollutant in the hot season. We also adopted a state-of-the-art chemical transport model, the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), to predict the air quality in Haizhu District 2020 under different scenarios. The simulation results suggested that among the emission control scenarios, comprehensive measures taken in the whole of Guangzhou city would improve air quality more significantly than measures taken just in Haizhu, under all conditions. In the urban district, vehicle emission control would account more than half of the influence of all source emission control on air quality. Based on our simulation, by the end of the 13th FYP, it is noticeable that O3 pollution would increase, which indicates that the control ratio of volatile organic compounds (VOCs) and nitrogen oxides (NOx) may be unsuitable and therefore should be adjusted. Our study highlights the significance of evaluating the efficacy of current policy in reducing the air pollutants and recommends possible directions for further air pollution control for urban areas during the 13th FYP.

The Effect of Emission Inventory on Modelling of Seasonal Exposure Metrics of Particulate Matter and Ozone with the WRF-Chem Model for Poland

In Poland, high concentrations of particulate matter (with a diameter smaller than 2.5 or 10 μm) exceeding the WHO threshold values are often measured in winter, while ozone (O3) concentrations are high in spring. In winter high PM2.5 and PM10 concentrations are linked to high residential combustion and road transport. The main objective of this study was to assess performance of the Weather Research and Forecasting model with Chemistry (WRF-Chem) model in reproducing observations for a period of 2017-2018 covering various meteorological conditions. We compare modelled and observed exposure metrics for PM2.5, PM10 and O3 for two sets of the WRF-Chem model runs: with coarse and fine resolution emission inventory (European Monitoring and Evaluation Programme (EMEP) and Chief Inspectorate of Environmental Protection (CIEP), respectively). CIEP run reduces the negative bias of PM2.5 and PM10 and improves the model performance for number of days with exceedance of WHO (World Health Organization) threshold for PM2.5 and PM10 24-h mean concentration. High resolution emission inventory for primary aerosols helps to better distinguish polluted urban areas from non-urban ones. There are no large differences for the model performance for O3 and secondary inorganic aerosols, and high-resolution emission inventory does not improve the results in terms of 8-h rolling mean concentrations of ozone.

Added Value of Aerosol-Cloud Interactions for Representing Aerosol Optical Depth in an Online Coupled Climate-Chemistry Model over Europe

Aerosol-cloud interactions (ACI) represent one of the most important sources of uncertainties in climate modelling. In this sense, realistic simulations of ACI are needed for a better understanding of the complex interactions between air pollution and the climate system. This work quantifies the added value of including ACI in an online coupled climate/chemistry model (WRF-Chem, 0.44 ∘ horizontal resolution, years 2003 to 2010) in order to assess whether there is an improvement in the representation of aerosol optical depth (AOD). Modelling results for each species have been evaluated against the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, and AOD at 675 nm has been compared to AERONET data. Results indicate that the improvements of the monthly biases are around 8% for total AOD550 when including ACI, reaching 20% for the monthly bias in AOD550 coming from dust. Moreover, the temporal representation of AOD550 largely improves (increase in the Pearson time correlation coefficients), ranging from 6% to 20% depending on the chemical species considered. The benefits from this improvement overcome the problems derived from the high computational time required in ACI simulations (eight times higher with respect to simulations not including aerosol-cloud interactions).

Evaluation of Regional Air Quality Models over Sydney, Australia: Part 2, Comparison of PM2.5 and Ozone

Accurate air quality modelling is an essential tool, both for strategic assessment (regulation development for emission controls) and for short-term forecasting (enabling warnings to be issued to protect vulnerable members of society when the pollution levels are predicted to be high). Model intercomparison studies are a valuable support to this work, being useful for identifying any issues with air quality models, and benchmarking their performance against international standards, thereby increasing confidence in their predictions. This paper presents the results of a comparison study of six chemical transport models which have been used to simulate short-term hourly to 24 hourly concentrations of fine particulate matter less than and equal to 2.5 µm in diameter (PM2.5) and ozone (O3) for Sydney, Australia. Model performance was evaluated by comparison to air quality measurements made at 16 locations for O3 and 5 locations for PM2.5, during three time periods that coincided with major atmospheric composition measurement campaigns in the region. These major campaigns included daytime measurements of PM2.5 composition, and so model performance for particulate sulfate (SO42−), nitrate (NO3−), ammonium (NH4+) and elemental carbon (EC) was evaluated at one site per modelling period. Domain-wide performance of the models for hourly O3 was good, with models meeting benchmark criteria and reproducing the observed O3 production regime (based on the O3/NOx indicator) at 80% or more of the sites. Nevertheless, model performance was worse at high (and low) O3 percentiles. Domain-wide model performance for 24 h average PM2.5 was more variable, with a general tendency for the models to under-predict PM2.5 concentrations during the summer and over-predict PM2.5 concentrations in the autumn. The modelling intercomparison exercise has led to improvements in the implementation of these models for Sydney and has increased confidence in their skill at reproducing observed atmospheric composition.

Mortality burdens in California due to air pollution attributable to local and nonlocal emissions

Limited research has been conducted on the contributions of local and nonlocal emission sources to ambient fine particulate matter (PM_2.5) and ozone (O₃) and their associated mortality. In this study, we estimated the total mortality resulting from long-term PM_2.5 and O₃ exposures in California in 2012 using multiple concentration response functions (CRFs) and attributed the estimated mortality to different emission groups. The point estimates of PM_2.5-associated mortality in California ranged from 12,700 to 26,700, of which 53% were attributable to in-state anthropogenic emissions. Based on new epidemiological evidence, we estimated that O₃ could be associated with up to 13,700 deaths from diseases of both the respiratory and cardiovascular systems in California. In addition, 75% of the ambient O₃ in California was due to distant emissions outside the western United States, leading to 92% of the O₃-associated mortality. Overall, distant emissions lead to greater mortality burdens of air pollution in California than local anthropogenic emissions.

Impacts of six potential HONO sources on HOx budgets and SOA formation during a wintertime heavy haze period in the North China Plain

The Weather Research and Forecasting/Chemistry (WRF-Chem) model updated with six potential HONO sources (i.e., traffic, soil, biomass burning and indoor emissions, and heterogeneous reactions on aerosol and ground surfaces) was used to quantify the impact of the six potential HONO sources on the production and loss rates of OH and HO₂ radicals and the concentrations of secondary organic aerosol (SOA) in the Beijing-Tianjin-Heibei (BTH) region of China during a winter heavy haze period of Nov. 29-Dec. 3, 2017. The updated WRF-Chem model well simulated the observed HONO concentrations at the Wangdu site, especially in the daytime, and well reproduced the observed diurnal variations of regional-mean O₃ in the BTH region. The traffic emission source was an important HONO source during nighttime but not significant during daytime, heterogeneous reactions on ground/aerosol surfaces were important during nighttime and daytime. We found that the six potential HONO sources led to a significant enhancement in the dominant production and loss rates of HO_x on the wintertime heavy haze and nonhaze days (particularly on the heavy haze day), an enhancement of 5-25 μg m^-3 (75-200%) in the ground SOA in the studied heavy haze event, and an enhancement of 2-15 μg m^-3 in the meridional-mean SOA on the heavy haze day, demonstrating that the six potential HONO sources accelerate the HO_x cycles and aggravate haze events. HONO was the key precursor of primary OH in the BTH region in the studied wintertime period, and the photolysis of HONO produced a daytime mean OH production rate of 2.59 ppb h^-1 on the heavy haze day, much higher than that of 0.58 ppb h^-1 on the nonhaze day. Anthropogenic SOA dominated in the BTH region in the studied wintertime period, and its main precursors were xylenes (42%), BIGENE (31%) and toluene (21%).

Investigating the Urban Air Quality Effects of Cool Walls and Cool Roofs in Southern California

Solar reflective cool roofs and walls can be used to mitigate the urban heat island effect. While many past studies have investigated the climate impacts of adopting cool surfaces, few studies have investigated their effects on air pollution, especially on particulate matter (PM). This research for the first time investigates the influence of widespread deployment of cool walls on urban air pollutant concentrations, and systematically compares cool wall to cool roof effects. Simulations using a coupled meteorology-chemistry model (WRF-Chem) for a representative summertime period show that cool walls and roofs can reduce urban air temperatures, wind speeds, and planetary boundary heights in the Los Angeles Basin. Consequently, increasing wall (roof) albedo by 0.80, an upper bound scenario, leads to maximum daily 8-h average ozone concentration reductions of 0.35 (0.83) ppbv in Los Angeles County. However, cool walls (roofs) increase daily average PM_2.5 concentrations by 0.62 (0.85) μg m^-3. We investigate the competing processes driving changes in concentrations of speciated PM_2.5. Increases in primary PM (elemental carbon and primary organic aerosols) concentrations can be attributed to reductions in ventilation of the Los Angeles Basin. Increases in concentrations of semivolatile species (e.g., nitrate) are mainly driven by increases in gas-to-particle conversion due to reduced atmospheric temperatures.

Modeling Study of the Air Quality Impact of Record-Breaking Southern California Wildfires in December 2017

We investigate the air quality impact of record-breaking wildfires in Southern California during 5-18 December 2017 using the Weather Research and Forecasting model with Chemistry in combination with satellite and surface observations. This wildfire event was driven by dry and strong offshore Santa Ana winds, which played a critical role in fire formation and air pollutant transport. By utilizing fire emissions derived from the high-resolution (375 × 375 m²) Visible Infrared Imaging Radiometer Suite active fire detections, the simulated magnitude and temporal evolution of fine particulate matter (PM_2.5) concentrations agree reasonably well with surface observations (normalized mean bias = 4.0%). Meanwhile, the model could generally capture the spatial pattern of aerosol optical depth from satellite observations. Sensitivity tests reveal that using a high spatial resolution for fire emissions and a reasonable treatment of plume rise (a fair split between emissions injected at surface and those lifted to upper levels) is important for achieving decent PM_2.5 simulation results. Biases in PM_2.5 simulation are relatively large (about 50%) during the period with the strongest Santa Ana wind, due to a possible underestimation of burning area and uncertainty in wind field variation. The 2017 December fire event increases the 14-day averaged PM_2.5 concentrations by up to 231.2 μg/m³ over the downwind regions, which substantially exceeds the U.S. air quality standards, potentially leading to adverse health impacts. The human exposure to fire-induced PM_2.5 accounts for 14-42% of the annual total PM_2.5 exposure in areas impacted by the fire plumes.

Air Quality and Health Cobenefits of Different Deep Decarbonization Pathways in California

As the world's fifth-largest economy, California has committed to reduce its greenhouse gas (GHG) emissions by 80% below 1990 levels by 2050. While previous studies have shown that GHG reductions could synergistically decrease air pollutant emissions and protect public health, limited research has been conducted to compare the health cobenefits of different technology pathways toward deep decarbonization. Using an integrated approach that combines energy and emission technology modeling, high-resolution chemical transport simulation, and health impact assessment, we find that achievement of the 80% GHG reduction target would bring substantial air quality and health cobenefits. The cobenefits, however, highly depend on the selected technology pathway largely because of California's relatively clean energy structure. Compared with the business-as-usual levels, a decarbonization pathway that focuses on electrification and clean renewable energy is estimated to reduce concentrations of fine particulate matter (PM_2.5) by 18-37% in major metropolitan areas of California and subsequently avoid about 12 100 (9600-14 600) premature deaths. In contrast, only a quarter of such health cobenefits, i.e., 2800 (2300-3400) avoided deaths, can be achieved through a pathway focusing more on combustible renewable fuels. After subtracting the cost, the net monetized benefit of the electrification-focused pathway still exceeds that of the renewable fuel-focused pathway, indicating that a cleaner but more expensive decarbonization pathway may be more preferable in California.

Multiscale Applications of Two Online-Coupled Meteorology-Chemistry Models during Recent Field Campaigns in Australia, Part I: Model Description and WRF/Chem-ROMS Evaluation Using Surface and Satellite Data and Sensitivity to Spatial Grid Resolutions

Air pollution and associated human exposure are important research areas in Greater Sydney, Australia. Several field campaigns were conducted to characterize the pollution sources and their impacts on ambient air quality including the Sydney Particle Study Stages 1 and 2 (SPS1 and SPS2), and the Measurements of Urban, Marine, and Biogenic Air (MUMBA). In this work, the Weather Research and Forecasting model with chemistry (WRF/Chem) and the coupled WRF/Chem with the Regional Ocean Model System (ROMS) (WRF/Chem-ROMS) are applied during these field campaigns to assess the models’ capability in reproducing atmospheric observations. The model simulations are performed over quadruple-nested domains at grid resolutions of 81-, 27-, 9-, and 3-km over Australia, an area in southeastern Australia, an area in New South Wales, and the Greater Sydney area, respectively. A comprehensive model evaluation is conducted using surface observations from these field campaigns, satellite retrievals, and other data. This paper evaluates the performance of WRF/Chem-ROMS and its sensitivity to spatial grid resolutions. The model generally performs well at 3-, 9-, and 27-km resolutions for sea-surface temperature and boundary layer meteorology in terms of performance statistics, seasonality, and daily variation. Moderate biases occur for temperature at 2-m and wind speed at 10-m in the mornings and evenings due to the inaccurate representation of the nocturnal boundary layer and surface heat fluxes. Larger underpredictions occur for total precipitation due to the limitations of the cloud microphysics scheme or cumulus parameterization. The model performs well at 3-, 9-, and 27-km resolutions for surface O3 in terms of statistics, spatial distributions, and diurnal and daily variations. The model underpredicts PM2.5 and PM10 during SPS1 and MUMBA but overpredicts PM2.5 and underpredicts PM10 during SPS2. These biases are attributed to inaccurate meteorology, precursor emissions, insufficient SO2 conversion to sulfate, inadequate dispersion at finer grid resolutions, and underprediction in secondary organic aerosol. The model gives moderate biases for net shortwave radiation and cloud condensation nuclei but large biases for other radiative and cloud variables. The performance of aerosol optical depth and latent/sensible heat flux varies for different simulation periods. Among all variables evaluated, wind speed at 10-m, precipitation, surface concentrations of CO, NO, NO2, SO2, O3, PM2.5, and PM10, aerosol optical depth, cloud optical thickness, cloud condensation nuclei, and column NO2 show moderate-to-strong sensitivity to spatial grid resolutions. The use of finer grid resolutions (3- or 9-km) can generally improve the performance for those variables. While the performance for most of these variables is consistent with that over the U.S. and East Asia, several differences along with future work are identified to pinpoint reasons for such differences.

Impacts of potential HONO sources on the concentrations of oxidants and secondary organic aerosols in the Beijing-Tianjin-Hebei region of China

We first coupled indoor emissions and biomass burning emissions into the WRF-Chem model besides the other four potential HONO sources (i.e., traffic emissions, soil emissions, and heterogeneous reactions on aerosol and ground surfaces). Eight simulations were performed in the Beijing-Tianjin-Hebei region (BTH) of China in August of 2006. The results indicated that traffic emissions and heterogeneous reactions on ground and aerosol surfaces were the key sources of HONO at night, accounting for ~41%, ~27% and ~20% of the nighttime simulated HONO concentrations, respectively. The two heterogeneous reactions were the main contributors during the day, accounting for ~66% (ground surfaces) and ~19% (aerosol surfaces) of the daytime simulated HONO concentrations. The indoor emission source could be the second largest contributor during nighttime and led to a maximum hourly enhancement of 0.59 and 0.76 ppb at the central urban sites of Beijing and Tianjin, respectively. The six potential HONO sources enhanced the monthly meridional-mean concentrations of O₃, OH and HO₂ by 5-44%, 5~>150% and 5~>200%, respectively, leading to an enhancement of 1-3 μg m^-3 in the monthly averaged concentrations of secondary organic aerosol (SOA), and that of 10-35 μg m^-3 in the largest hourly concentrations of SOA within 1000 m above the ground in the BTH. The major precursors of the enhanced SOA were Xylenes, Toluene and BIGALK (lumped alkanes C > 3). The inclusion of the six potential HONO sources in the WRF-Chem model considerably improved the HONO simulations at both urban and suburban sites compared with the corresponding observations. The above results suggested that the six potential HONO sources significantly enhanced the atmospheric oxidation capacity and thus accelerated SOA chemical aging in the BTH of China, leading to large enhancements in the hourly SOA concentrations and aggravating haze events in this region.

Parameterized Yields of Semivolatile Products from Isoprene Oxidation under Different NO x Levels: Impacts of Chemical Aging and Wall-Loss of Reactive Gases

We developed a parametrizable box model to empirically derive the yields of semivolatile products from VOC oxidation using chamber measurements, while explicitly accounting for the multigenerational chemical aging processes (such as the gas-phase fragmentation and functionalization and aerosol-phase oligomerization and photolysis) under different NO _x levels and the loss of particles and gases to chamber walls. Using the oxidation of isoprene as an example, we showed that the assumptions regarding the NO _x-sensitive, multigenerational aging processes of VOC oxidation products have large impacts on the parametrized product yields and SOA formation. We derived sets of semivolatile product yields from isoprene oxidation under different NO _x levels. However, we stress that these product yields must be used in conjunction with the corresponding multigenerational aging schemes in chemical transport models. As more mechanistic insights regarding SOA formation from VOC oxidation emerge, our box model can be expanded to include more explicit chemical aging processes and help ultimately bridge the gap between the process-based understanding of SOA formation from VOC oxidation and the bulk-yield parametrizations used in chemical transport models.

Sensitivities of Simulated Source Contributions and Health Impacts of PM2.5 to Aerosol Models

Chemical transport models are useful tools for evaluating source contributions and health impacts of PM_2.5 in the atmosphere. We recently found that concentrations of PM_2.5 compounds over Japan were much better reproduced by a volatility basis set model with an enhanced dry deposition velocity of HNO₃ and NH₃ compared with a two-product yield model. In this study, we evaluated the sensitivities to organic aerosol models of the simulated source contributions to PM_2.5 concentrations and of PM_2.5-related mortality. Overall, the simulated source contributions to PM_2.5 were similar between the two models. However, because of the improvements associated with the volatility basis set model, the contributions of ammonia sources decreased, particularly in winter and spring, and contributions of biogenic and stationary evaporative sources increased in spring and summer. The improved model estimated that emission sources in Japan contributed 35%-48% of the PM_2.5-related mortality in Japan. These values were higher than the domestic contributions to average PM_2.5 concentrations in Japan (26%-33%) because the domestic contributions were higher in higher population areas. These results indicate that control of both domestic and foreign emissions is necessary to reduce health impacts due to PM_2.5 in Japan.

Improving organic aerosol treatments in CESM/CAM5: Development, application, and evaluation

New treatments for organic aerosol (OA) formation have been added to a modified version of the CESM/CAM5 model (CESM-NCSU). These treatments include a volatility basis set treatment for the simulation of primary and secondary organic aerosols (SOAs), a simplified treatment for organic aerosol (OA) formation from glyoxal, and a parameterization representing the impact of new particle formation (NPF) of organic gases and sulfuric acid. With the inclusion of these new treatments, the concentration of oxygenated organic aerosol increases by 0.33 µg m-3 and that of primary organic aerosol (POA) decreases by 0.22 µg m-3 on global average. The decrease in POA leads to a reduction in the OA direct effect, while the increased OOA increases the OA indirect effects. Simulations with the new OA treatments show considerable improvement in simulated SOA, oxygenated organic aerosol (OOA), organic carbon (OC), total carbon (TC), and total organic aerosol (TOA), but degradation in the performance of HOA. In simulations of the current climate period, despite some deviations from observations, CESM-NCSU with the new OA treatments significantly improves the magnitude, spatial pattern, seasonal pattern of OC and TC, as well as, the speciation of TOA between POA and OOA. Sensitivity analysis reveals that the inclusion of the organic NPF treatment impacts the OA indirect effects by enhancing cloud properties. The simulated OA level and its impact on the climate system are most sensitive to choices in the enthalpy of vaporization and wet deposition of SVOCs, indicating that accurate representations of these parameters are critical for accurate OA-climate simulations.

InMAP: A model for air pollution interventions

Mechanistic air pollution modeling is essential in air quality management, yet the extensive expertise and computational resources required to run most models prevent their use in many situations where their results would be useful. Here, we present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations-the air pollution outcome generally causing the largest monetized health damages-attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical information from the output of a state-of-the-science chemical transport model and a variable spatial resolution computational grid to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. In comparisons run here, InMAP recreates comprehensive model predictions of changes in total PM2.5 concentrations with population-weighted mean fractional bias (MFB) of -17% and population-weighted R2 = 0.90. Although InMAP is not specifically designed to reproduce total observed concentrations, it is able to do so within published air quality model performance criteria for total PM2.5. Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. InMAP can be trained to run for any spatial and temporal domain given the availability of appropriate simulation output from a comprehensive model. The InMAP model source code and input data are freely available online under an open-source license.

Chemical transport model simulations of organic aerosol in southern California: model evaluation and gasoline and diesel source contributions

Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we updated the organic aerosol module and organic emissions inventory of a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ), using recent, experimentally derived inputs and parameterizations for mobile sources. The updated model included a revised volatile organic compound (VOC) speciation for mobile sources and secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOCs). The updated model was used to simulate air quality in southern California during May and June 2010, when the California Research at the Nexus of Air Quality and Climate Change (CalNex) study was conducted. Compared to the Traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted organic aerosol (OA) mass concentrations but did substantially improve predictions of OA sources and composition (e.g., POA-SOA split), as well as ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performed similar to a recently released research version of CMAQ (Woody et al., 2016) that did not include the updated VOC and IVOC emissions and SOA data. Mobile sources were predicted to contribute 30-40 % of the OA in southern California (half of which was SOA), making mobile sources the single largest source contributor to OA in southern California. The remainder of the OA was attributed to non-mobile anthropogenic sources (e.g., cooking, biomass burning) with biogenic sources contributing to less than 5 % to the total OA. Gasoline sources were predicted to contribute about 13 times more OA than diesel sources; this difference was driven by differences in SOA production. Model predictions highlighted the need to better constrain multi-generational oxidation reactions in chemical transport models.

Review of Urban Secondary Organic Aerosol Formation from Gasoline and Diesel Motor Vehicle Emissions

Secondary organic aerosol (SOA) is formed from the atmospheric oxidation of gas-phase organic compounds leading to the formation of particle mass. Gasoline- and diesel-powered motor vehicles, both on/off-road, are important sources of SOA precursors. They emit complex mixtures of gas-phase organic compounds that vary in volatility and molecular structure-factors that influence their contributions to urban SOA. However, the relative importance of each vehicle type with respect to SOA formation remains unclear due to conflicting evidence from recent laboratory, field, and modeling studies. Both are likely important, with evolving contributions that vary with location and over short time scales. This review summarizes evidence, research needs, and discrepancies between top-down and bottom-up approaches used to estimate SOA from motor vehicles, focusing on inconsistencies between molecular-level understanding and regional observations. The effect of emission controls (e.g., exhaust aftertreatment technologies, fuel formulation) on SOA precursor emissions needs comprehensive evaluation, especially with international perspective given heterogeneity in regulations and technology penetration. Novel studies are needed to identify and quantify "missing" emissions that appear to contribute substantially to SOA production, especially in gasoline vehicles with the most advanced aftertreatment. Initial evidence suggests catalyzed diesel particulate filters greatly reduce emissions of SOA precursors along with primary aerosol.

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

Mounting evidence from field and laboratory observations coupled with atmospheric model analyses shows that primary combustion emissions of organic compounds dynamically partition between the vapor and particulate phases, especially as near-source emissions dilute and cool to ambient conditions. The most recent version of the Community Multiscale Air Quality model version 5.2 (CMAQv5.2) accounts for the semivolatile partitioning and gas-phase aging of these primary organic aerosol (POA) compounds consistent with experimentally derived parameterizations. We also include a new surrogate species, potential secondary organic aerosol from combustion emissions (pcSOA), which provides a representation of the secondary organic aerosol (SOA) from anthropogenic combustion sources that could be missing from current chemical transport model predictions. The reasons for this missing mass likely include the following: (1) unspeciated semivolatile and intermediate volatility organic compound (SVOC and IVOC, respectively) emissions missing from current inventories, (2) multigenerational aging of organic vapor products from known SOA precursors (e.g., toluene, alkanes), (3) underestimation of SOA yields due to vapor wall losses in smog chamber experiments, and (4) reversible organic compounds-water interactions and/or aqueous-phase processing of known organic vapor emissions. CMAQ predicts the spatially averaged contribution of pcSOA to OA surface concentrations in the continental United States to be 38.6 and 23.6 % in the 2011 winter and summer, respectively. Whereas many past modeling studies focused on a particular measurement campaign, season, location, or model configuration, we endeavor to evaluate the model and important uncertain parameters with a comprehensive set of United States-based model runs using multiple horizontal scales (4 and 12 km), gas-phase chemical mechanisms, and seasons and years. The model with representation of semivolatile POA improves predictions of hourly OA observations over the traditional nonvolatile model at sites during field campaigns in southern California (CalNex, May-June 2010), northern California (CARES, June 2010), the southeast US (SOAS, June 2013; SEARCH, January and July, 2011). Model improvements manifest better correlations (e.g., the correlation coefficient at Pasadena at night increases from 0.38 to 0.62) and reductions in underprediction during the photochemically active afternoon period (e.g., bias at Pasadena from -5.62 to -2.42 μg m^-3). Daily averaged predictions of observations at routine-monitoring networks from simulations over the continental US (CONUS) in 2011 show modest improvement during winter, with mean biases reducing from 1.14 to 0.73μg m^-3, but less change in the summer when the decreases from POA evaporation were similar to the magnitude of added SOA mass. Because the model-performance improvement realized by including the relatively simple pcSOA approach is similar to that of more-complicated parameterizations of OA formation and aging, we recommend caution when applying these more-complicated approaches as they currently rely on numerous uncertain parameters. The pcSOA parameters optimized for performance at the southern and northern California sites lead to higher OA formation than is observed in the CONUS evaluation. This may be due to any of the following: variations in real pcSOA in different regions or time periods, too-high concentrations of other OA sources in the model that are important over the larger domain, or other model issues such as loss processes. This discrepancy is likely regionally and temporally dependent and driven by interferences from factors like varying emissions and chemical regimes.

Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems: multivariable temporal and spatial breakdown

Through the comparison of several regional-scale chemistry transport modeling systems that simulate meteorology and air quality over the European and North American continents, this study aims at (i) apportioning error to the responsible processes using timescale analysis, (ii) helping to detect causes of model error, and (iii) identifying the processes and temporal scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition, and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overallsense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance, and covariance) can help assess the nature and quality of the error. Each of the error components is analyzed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intraday) using the error apportionment technique devised in the former phases of AQMEII. The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impact of model inputs (emission and boundary conditions) and poor representation of the stable boundary layer on model bias, results also highlighted the high interdependencies among meteorological and chemical variables, as well as among their errors. This indicates that the evaluation of air quality model performance for individual pollutants needs to be supported by complementary analysis of meteorological fields and chemical precursors to provide results that are more insightful from a model development perspective. This will require evaluaion methods that are able to frame the impact on error of processes, conditions, and fluxes at the surface. For example, error due to emission and boundary conditions is dominant for primary species (CO, particulate matter (PM)), while errors due to meteorology and chemistry are most relevant to secondary species, such as ozone. Some further aspects emerged whose interpretation requires additional consideration, such as the uniformity of the synoptic error being region- and model-independent, observed for several pollutants; the source of unexplained variance for the diurnal component; and the type of error caused by deposition and at which scale.

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

Mounting evidence from field and laboratory observations coupled with atmospheric model analyses shows that primary combustion emissions of organic compounds dynamically partition between the vapor and particulate phases, especially as near-source emissions dilute and cool to ambient conditions. The most recent version of the Community Multiscale Air Quality model version 5.2 (CMAQv5.2) accounts for the semivolatile partitioning and gas-phase aging of these primary organic aerosol (POA) compounds consistent with experimentally derived parameterizations. We also include a new surrogate species, potential secondary organic aerosol from combustion emissions (pcSOA), which provides a representation of the secondary organic aerosol (SOA) from anthropogenic combustion sources that could be missing from current chemical transport model predictions. The reasons for this missing mass likely include the following: (1) unspeciated semivolatile and intermediate volatility organic compound (SVOC and IVOC, respectively) emissions missing from current inventories, (2) multigenerational aging of organic vapor products from known SOA precursors (e.g., toluene, alkanes), (3) underestimation of SOA yields due to vapor wall losses in smog chamber experiments, and (4) reversible organic compounds-water interactions and/or aqueous-phase processing of known organic vapor emissions. CMAQ predicts the spatially averaged contribution of pcSOA to OA surface concentrations in the continental United States to be 38.6 and 23.6 % in the 2011 winter and summer, respectively. Whereas many past modeling studies focused on a particular measurement campaign, season, location, or model configuration, we endeavor to evaluate the model and important uncertain parameters with a comprehensive set of United States-based model runs using multiple horizontal scales (4 and 12 km), gas-phase chemical mechanisms, and seasons and years. The model with representation of semivolatile POA improves predictions of hourly OA observations over the traditional nonvolatile model at sites during field campaigns in southern California (CalNex, May-June 2010), northern California (CARES, June 2010), the southeast US (SOAS, June 2013; SEARCH, January and July, 2011). Model improvements manifest better correlations (e.g., the correlation coefficient at Pasadena at night increases from 0.38 to 0.62) and reductions in underprediction during the photochemically active afternoon period (e.g., bias at Pasadena from -5.62 to -2.42 μg m^-3). Daily averaged predictions of observations at routine-monitoring networks from simulations over the continental US (CONUS) in 2011 show modest improvement during winter, with mean biases reducing from 1.14 to 0.73μg m^-3, but less change in the summer when the decreases from POA evaporation were similar to the magnitude of added SOA mass. Because the model-performance improvement realized by including the relatively simple pcSOA approach is similar to that of more-complicated parameterizations of OA formation and aging, we recommend caution when applying these more-complicated approaches as they currently rely on numerous uncertain parameters. The pcSOA parameters optimized for performance at the southern and northern California sites lead to higher OA formation than is observed in the CONUS evaluation. This may be due to any of the following: variations in real pcSOA in different regions or time periods, too-high concentrations of other OA sources in the model that are important over the larger domain, or other model issues such as loss processes. This discrepancy is likely regionally and temporally dependent and driven by interferences from factors like varying emissions and chemical regimes.

Quantifying the effect of organic aerosol aging and intermediate-volatility emissions on regional-scale aerosol pollution in China

Secondary organic aerosol (SOA) is one of the least understood constituents of fine particles; current widely-used models cannot predict its loadings or oxidation state. Recent laboratory experiments demonstrated the importance of several new processes, including aging of SOA from traditional precursors, aging of primary organic aerosol (POA), and photo-oxidation of intermediate volatility organic compounds (IVOCs). However, evaluating the effect of these processes in the real atmosphere is challenging. Most models used in previous studies are over-simplified and some key reaction trajectories are not captured, and model parameters are usually phenomenological and lack experimental constraints. Here we comprehensively assess the effect of organic aerosol (OA) aging and intermediate-volatility emissions on regional-scale OA pollution with a state-of-the-art model framework and experimentally constrained parameters. We find that OA aging and intermediate-volatility emissions together increase OA and SOA concentrations in Eastern China by about 40% and a factor of 10, respectively, thereby improving model-measurement agreement significantly. POA and IVOCs both constitute over 40% of OA concentrations, and IVOCs constitute over half of SOA concentrations; this differs significantly from previous apportionment of SOA sources. This study facilitates an improved estimate of aerosol-induced climate and health impacts, and implies a shift from current fine-particle control policies.

Mining in subarctic Canada: airborne PM2.5 metal concentrations in two remote First Nations communities

Airborne particulate matter arising from upwind mining activities is a concern for First Nations communities in the western James Bay region of Ontario, Canada. Aerosol chemical components were collected in 2011 from two communities in northern Ontario. The chemical and mass concentration data of particulate matter collected during this study shows a significant difference in PM2.5 in Attawapiskat compared to Fort Albany. Elemental profiles indicate enhanced levels of some tracers thought to arise from mining activities, such as, K, Ni, and crustal materials. Both communities are remote and isolated from urban and industrial pollution sources, however, Attawapiskat First Nation has significantly enhanced levels of particulate matter, and it is likely that some of this arises from upwind mining activities.

Evaluation of one-dimensional and two-dimensional volatility basis sets in simulating the aging of secondary organic aerosol with smog-chamber experiments

We evaluate the one-dimensional volatility basis set (1D-VBS) and two-dimensional volatility basis set (2D-VBS) in simulating the aging of SOA derived from toluene and α-pinene against smog-chamber experiments. If we simulate the first-generation products with empirical chamber fits and the subsequent aging chemistry with a 1D-VBS or a 2D-VBS, the models mostly overestimate the SOA concentrations in the toluene oxidation experiments. This is because the empirical chamber fits include both first-generation oxidation and aging; simulating aging in addition to this results in double counting of the initial aging effects. If the first-generation oxidation is treated explicitly, the base-case 2D-VBS underestimates the SOA concentrations and O:C increase of the toluene oxidation experiments; it generally underestimates the SOA concentrations and overestimates the O:C increase of the α-pinene experiments. With the first-generation oxidation treated explicitly, we could modify the 2D-VBS configuration individually for toluene and α-pinene to achieve good model-measurement agreement. However, we are unable to simulate the oxidation of both toluene and α-pinene with the same 2D-VBS configuration. We suggest that future models should implement parallel layers for anthropogenic (aromatic) and biogenic precursors, and that more modeling studies and laboratory research be done to optimize the "best-guess" parameters for each layer.

Rapid deposition of oxidized biogenic compounds to a temperate forest

We report fluxes and dry deposition velocities for 16 atmospheric compounds above a southeastern United States forest, including: hydrogen peroxide (H2O2), nitric acid (HNO3), hydrogen cyanide (HCN), hydroxymethyl hydroperoxide, peroxyacetic acid, organic hydroxy nitrates, and other multifunctional species derived from the oxidation of isoprene and monoterpenes. The data suggest that dry deposition is the dominant daytime sink for small, saturated oxygenates. Greater than 6 wt %C emitted as isoprene by the forest was returned by dry deposition of its oxidized products. Peroxides account for a large fraction of the oxidant flux, possibly eclipsing ozone in more pristine regions. The measured organic nitrates comprise a sizable portion (15%) of the oxidized nitrogen input into the canopy, with HNO3 making up the balance. We observe that water-soluble compounds (e.g., strong acids and hydroperoxides) deposit with low surface resistance whereas compounds with moderate solubility (e.g., organic nitrates and hydroxycarbonyls) or poor solubility (e.g., HCN) exhibited reduced uptake at the surface of plants. To first order, the relative deposition velocities of water-soluble compounds are constrained by their molecular diffusivity. From resistance modeling, we infer a substantial emission flux of formic acid at the canopy level (∼1 nmol m(-2)⋅s(-1)). GEOS-Chem, a widely used atmospheric chemical transport model, currently underestimates dry deposition for most molecules studied in this work. Reconciling GEOS-Chem deposition velocities with observations resulted in up to a 45% decrease in the simulated surface concentration of trace gases.

Mass spectral analysis of organic aerosol formed downwind of the Deepwater Horizon oil spill: field studies and laboratory confirmations

In June 2010, the NOAA WP-3D aircraft conducted two survey flights around the Deepwater Horizon (DWH) oil spill. The Gulf oil spill resulted in an isolated source of secondary organic aerosol (SOA) precursors in a relatively clean environment. Measurements of aerosol composition and volatile organic species (VOCs) indicated formation of SOA from intermediate-volatility organic compounds (IVOCs) downwind of the oil spill (Science2011, 331, doi 10.1126/science.1200320). In an effort to better understand formation of SOA in this environment, we present mass spectral characteristics of SOA in the Gulf and of SOA formed in the laboratory from evaporated light crude oil. Compared to urban primary organic aerosol, high-mass-resolution analysis of the background-subtracted SOA spectra in the Gulf (for short, "Gulf SOA") showed higher contribution of C(x)H(y)O(+) relative to C(x)H(y)(+) fragments at the same nominal mass. In each transect downwind of the DWH spill site, a gradient in the degree of oxidation of the Gulf SOA was observed: more oxidized SOA (oxygen/carbon = O/C ∼0.4) was observed in the area impacted by fresher oil; less oxidized SOA (O/C ∼0.3), with contribution from fragments with a hydrocarbon backbone, was found in a broader region of more-aged surface oil. Furthermore, in the plumes originating from the more-aged oil, contribution of oxygenated fragments to SOA decreased with downwind distance. Despite differences between experimental conditions in the laboratory and the ambient environment, mass spectra of SOA formed from gas-phase oxidation of crude oil by OH radicals in a smog chamber and a flow tube reactor strongly resembled the mass spectra of Gulf SOA (r(2) > 0.94). Processes that led to the observed Gulf SOA characteristics are also likely to occur in polluted regions where VOCs and IVOCs are coemitted.