Source apportionment of secondary organic aerosol in China using a regional source-oriented chemical transport model and two emission inventories

Effects of stress factors on biogenic isoprene emissions and their contribution to ozone and secondary organic aerosols in China

Isoprene serves an important part in plant defense against biotic and abiotic stresses, while also exerting a crucial influence on atmospheric photochemical processes and global climate change. The regional climate-chemistry-ecosystem model (RegCM-Chem-YIBs) was employed in the following study to estimate the biogenic isoprene emissions (BISP) in China during 2018-2020. The model explored the relative contributions of various stress factors such as drought, carbon dioxide (CO2), and surface ozone (O3) to isoprene emissions. Furthermore, the potential effects of stress factors on surface O3 and secondary organic aerosol (SOA) were also assessed quantitatively. Investigations revealed that the three-year average BISP in China ranged between 15.38 and 22.23 Tg while considering different stress factors. BISP exhibited obvious seasonal variations, showing higher levels in summer and lower levels in winter, accounting for 55.4 % and 3.2 % of the annual total emissions, respectively. The effects of O3 damage and CO2 inhibition on BISP were found to be more significant as compared to drought stress. The CO2 suppression effect caused annual BISP across China to decrease about 10 %, whereas the largest reduction (-3 mg C m-2 d-1) appeared in southeastern China and eastern Sichuan. BISP in China decreased by about 16.3 % (6.8 %) at high (low) O3 damage sensitivity during 2018-2020. Variations in monthly emissions differed, with the largest decline in summer. If no stressors are considered, BISP leads to a maximum increase of 13 ppb in daily maximum 1 h (MDA1) O3 and 1.5 μg m-3 in SOA in summer. Under the combined effects of multiple factors (drought, CO2, and O3), the relative differences in O3 are over 50 % in central and eastern China, while the SOA formed by isoprene reduced by ~0.15 μgm-3 in China. The outcomes of this work emphasize the significance of multiple stressors on BISP and the resulting air quality.

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.

WITHDRAWN: Insights into the source contributions to the elevated fine particulate matter in Nigeria using a source-oriented chemical transport model

This paper has been withdrawn.

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.

Contributions of local emissions and regional background to summertime ozone in central China

Source contributions and regional transport of maximum daily average 8-h (MDA8) O3 during a high O3 month (June 2019) in Henan province in central China are explored using a source-oriented Community Multiscale Air Quality (CMAQ) model. The monthly average MDA8 O3 exceeds ∼70 ppb in more than half of the areas and shows a clear spatial gradient, with lower O3 concentrations in the southwest and higher in the northeast. Significant contributions of anthropogenic emissions to monthly average MDA8 O3 concentrations of more than 20 ppb are predicted in the provincial capital Zhengzhou, mostly due to emissions from the transportation sector (∼50%) and in the areas in the north and northeast regions where industrial and power generation-related emissions are high. Biogenic emissions in the region only contribute to approximately 1-3 ppb of monthly average MDA8 O3. In industrial areas north of the province, their contributions reach 5-7 ppb. Two CMAQ-based O3-NOx-VOCs sensitivity assessments (the local O3 sensitivity ratios based on the direct decoupled method and the production ratio of H2O2 to HNO3) and the satellite HCHO to NO2 column density ratio consistently show that most of the areas in Henan are in NOx-limited regime. In contrast, the high O3 concentration areas in the north and at the city centers are in the VOC-limited or transition regimes. The results from this study suggest that although reducing NOx emissions to reduce O3 pollution in the region is desired in most areas, VOC reductions must be applied to urban and industrial regions. Source apportionment simulations with and without Henan anthropogenic emissions show that the benefit of local anthropogenic NOx reduction might be lower than expected from the source apportionment results because the contributions of Henan background O3 increase in response to the reduced local anthropogenic emissions due to less NO titration. Thus, collaborative O3 controls in neighboring provinces are needed to reduce O3 pollution problems in Henan effectively.

Mortality burden due to ambient nitrogen dioxide pollution in China: Application of high-resolution models

BACKGROUND

A large gap exists between the latest Global Air Quality Guidelines (AQG 2021) and Chinese air quality standards for NO₂. Assessing whether and to what extent air quality standards for NO₂ should be tightened in China requires a comprehensive understanding of the spatiotemporal characteristics of population exposure to ambient NO₂ and related health risks, which have not been studied to date.

OBJECTIVE

We predicted ground NO₂ concentrations with high resolution in mainland China, explored exposure characteristics to NO₂ pollution, and assessed the mortality burden attributable to NO₂ exposure.

METHODS

Daily NO₂ concentrations in 2019 were predicted at 1-km spatial resolution in mainland China using random forest models incorporating multiple predictors. From these high-resolution predictions, we explored the spatiotemporal distribution of NO₂, population and area percentages with NO₂ exposure exceeding criterion levels, and premature deaths attributable to long- and short-term NO₂ exposure in China.

RESULTS

The cross-validation R²and root mean squared error of the NO₂ predicting model were 0.80 and 7.78 μg/m³, respectively,at the daily level in 2019.The percentage of people (population number) with annual NO₂ exposure over 40 μg/m³ in mainland China in 2019 was 10.40 % (145,605,200), and it reached 99.68 % (1,395,569,840) with the AQG guideline value of 10 μg/m³. NO₂ levels and population exposure risk were elevated in urban areas than in rural. Long- and short-term exposures to NO₂ were associated with 285,036 and 121,263 non-accidental deaths, respectively, in China in 2019. Tightening standards in steps gradually would increase the potential health benefit.

CONCLUSION

In China, NO₂ pollution is associated with significant mortality burden. Spatial disparities exist in NO₂ pollution and exposure risks. China's current air quality standards may no longer objectively reflect the severity of NO₂ pollution and exposure risk. Tightening the national standards for NO₂ is needed and will lead to significant health benefits.

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.

Impacts of the differences in PM2.5 air quality improvement on regional transport and health risk in Beijing-Tianjin-Hebei region during 2013-2017

Due to the implementation of different air pollution control measures in the Beijing-Tianjin-Hebei (BTH) region during 2013-2017, the air quality exhibited varied improvements in each province, indicating substantial changes in the interprovincial regional transport of PM_2.5. In this study, we investigated these changes by using the Community Multiscale Air Quality (CMAQ) model coupled with the integrated source apportionment method (ISAM) during this period. The results showed that the concentrations of primary particles, SO₄^2-, and NO₃^- decreased by 41.5, 40.8, and 1.8%, respectively due to the air pollutants emission reduction. Local air pollutant emissions were the predominant contributors of PM_2.5 for each region in BTH, accounting for 41.3-47.6, 38.1-40.6, 50.6-53.6, and 54.0-57.1% of PM_2.5 in Beijing, Tianjin, and northern and southern Hebei, respectively. Total PM_2.5 has been mitigated by 7.1-12.3 and 5.1-11.7 μg/m³ from local and regional emission reduction, respectively in the BTH. Moreover, diverse local meteorological conditions variation increased the PM_2.5 concentration by 5.3 μg/m³ in Tianjin and decreased it by 7.6, 2.0, and 4.9 μg/m³ in Beijing, and northern and southern Hebei, respectively. Estimation by integrated exposure-response function revealed that the number of premature deaths attributable to PM_2.5 exposure decreased by approximately 3000 in the BTH region during 2013-2017. Additional policies that focus on PM_2.5-O₃ coordinated control and stringent regional joint air pollution regulation are required to substantially reduce the health impacts, especially in southern Hebei.

A review of secondary organic aerosols formation focusing on organosulfates and organic nitrates

Secondary organic aerosols (SOA) are crucial constitution of fine particulate matter (PM), which are mainly derived from photochemical oxidation products of primary organic matter and volatile organic compounds (VOCs), and can induce terrible impacts to human health, air quality and climate change. As we know, organosulfates (OSs) and organic nitrates (ON) are important contributors for SOA formation, which could be possibly produced through various pathways, resulting in extremely complex formation mechanism of SOA. Although plenty of research has been focused on the origins, spatial distribution and formation mechanisms of SOA, a comprehensive and systematic understanding of SOA formation in the atmosphere remains to be detailed explored, especially the most important OSs and ON dedications. Thus, in this review, we systematically summarize the recent research about origins and formation mechanisms of OSs and ON, and especially focus on their contribution to SOA, so as to have a clearer understanding of the origin, spatial distribution and formation principle of SOA. Importantly, we interpret the complex interaction with coexistence effect of SO_x and NO_x on SOA formation, and emphasize the future insights for SOA research to expect a more comprehensive theory and practice to alleviate SOA burden.

Deep Journalism and DeepJournal V1.0: A Data-Driven Deep Learning Approach to Discover Parameters for Transportation

We live in a complex world characterised by complex people, complex times, and complex social, technological, economic, and ecological environments. The broad aim of our work is to investigate the use of ICT technologies for solving pressing problems in smart cities and societies. Specifically, in this paper, we introduce the concept of deep journalism, a data-driven deep learning-based approach, to discover and analyse cross-sectional multi-perspective information to enable better decision making and develop better instruments for academic, corporate, national, and international governance. We build three datasets (a newspaper, a technology magazine, and a Web of Science dataset) and discover the academic, industrial, public, governance, and political parameters for the transportation sector as a case study to introduce deep journalism and our tool, DeepJournal (Version 1.0), that implements our proposed approach. We elaborate on 89 transportation parameters and hundreds of dimensions, reviewing 400 technical, academic, and news articles. The findings related to the multi-perspective view of transportation reported in this paper show that there are many important problems that industry and academia seem to ignore. In contrast, academia produces much broader and deeper knowledge on subjects such as pollution that are not sufficiently explored in industry. Our deep journalism approach could find the gaps in information and highlight them to the public and other stakeholders.

Evaluation of a highly condensed SAPRC chemical mechanism and two emission inventories for ozone source apportionment and emission control strategy assessments in China

The response of summertime O₃ to changes in the nitrogen oxides (NO_x) and volatile organic compounds (VOC) emissions, and contributions of different NO_x and VOC sources to O₃ in China are studied using a highly condensed photochemical mechanism in the Statewide Air Pollution Research Center (SAPRC) family (CS07A) and two popular anthropogenic emission inventories, the Multi-resolution Emission Inventory for China (MEIC) and Regional Emission inventory in ASia (REAS). Although CS07A predicts slightly lower O₃ concentrations than the standard fix-parameter version of the SAPRC-11 mechanism, the two mechanisms predict almost identical relative responses to daily maximum 8-hour O₃ (O₃-8h) due to NO_x and VOC emission reductions. A source-oriented version of the CS07A is applied to determine source contributions of NO_x and VOCs to O₃ using MEIC and REAS. The two inventories lead to similar model performance of O₃, with MEIC predicting higher O₃ in Beijing and Shanghai, especially on high O₃ days. Source apportionment results show that industry and transportation are the top two contributors to non-background O₃ for both inventories, followed by power and biogenic emissions. In general, the two inventories lead to similar source contribution estimations to O₃ attributable to NO_x. However, their estimations of relative contributions to VOC-related O₃ differ for the industrial and transportation sectors. Differences in the source apportionment results are more significant in some urban areas, although both emissions capture the spatial variations in the source contributions. Our results suggest that future emission control policies should be assessed using multiple emission inventories, and the condensed CS07A is suitable for policy applications when a large number of simulations are needed.

Estimation of Aromatic Secondary Organic Aerosol Using a Molecular Tracer-A Chemical Transport Model Assessment

A modified community multiscale air quality model, which can simulate the regional distributions of 2,3-dihydroxy-4-oxopentanoic acid (DHOPA), a marker species for monoaromatic secondary organic aerosol (SOA), was applied to assess the applicability of using the DHOPA to aromatic SOA mass ratio (f_SOA) from smog chamber experiments to estimate aromatic SOA during a three-week wintertime air quality campaign in urban Shanghai. The modeled daily DHOPA concentrations based on the chamber-derived mass yields agree well with the organic marker field measurements (R = 0.79; MFB = 0.152; and MFE = 0.440). Two-thirds of the DHOPA are from the oxidation of ARO1 (lumped less-reactive aromatic species; mostly toluene), with the rest from ARO2 (lumped more-reactive aromatic species; mostly xylenes). Modeled DHOPA is mainly in the particle phase under ambient organic aerosol (OA) loading but could exhibit significant gas-particle partitioning when a higher estimation of the DHOPA vapor pressure is used. The modeled f_SOA shows a strong dependence on the OA loading when only semivolatile aromatic SOA components are included in the f_SOA calculations. However, this OA dependence becomes weaker when non-volatile oligomers and dicarbonyl SOA products are considered. A constant f_SOA value of ∼0.002 is determined when all aromatic SOA components are included, which is a factor of 2 smaller than the commonly applied chamber-based f_SOA value of 0.004 for toluene. This model-derived f_SOA value does not show much spatial variation and is not sensitive to alternative estimates of DHOPA vapor pressures and SOA yields, and thus provides an appropriate scaling factor to assess aromatic SOA from DHOPA measurements. This result helps refine the quantification of SOA attributable to monoaromatic hydrocarbons in urban environments and thereby facilitates the evaluation of control measures targeting these specific precursors.

Evaluation of regional transport of PM2.5 during severe atmospheric pollution episodes in the western Yangtze River Delta, China

During winter 2018, the 16 prefecture-level cities in Anhui Province, Western Yangtze River Delta region, China had very high PM_2.5 concentrations and prolonged pollution days. The impact of regional transport in the formation, accumulation, as well as dispersion of fine particulate matter (PM_2.5) in Anhui Province was very significant. This study quantified and analyzed the vertical transport of PM_2.5 in three major cities (Hefei, Fuyang, and Suzhou) of Anhui Province in January and July 2018 using the Weather Research and Forecasting (WRF) model coupled with the Community Multiscale Air Quality (CMAQ) model. The results of the inter-regional transport of PM_2.5 revealed the dominant transport pathways for the three cities. The flux mainly flowed into Fuyang from Henan (2.23 and 1.42 kt/day in January and July, respectively) and Bozhou (1.96 and 1.21 kt/day in January and July, respectively), while the main flux from Fuyang flowed into Henan (-2.15 kt/day) and Lu'an (-1.91 kt/day) in January and Henan (-0.34 kt/day) and Bozhou (-0.29 kt/day) in July. In addition, the dominant transport pathways and the heights at which they occurred were identified: the northwest-southeast and northeast-south pathways in both winter and summer at both lower (˂300 m) and higher (≥300 m) levels for Fuyang; the northwest-south and northeast-southwest pathways in winter (at both lower and upper levels) and northwest-east and northeast-southwest pathways in summer at lower and upper levels for Hefei; and the northwest-southeast and northeast-south pathways in both winter (from 50 m up to the top level) and summer (between 100 and 300 m) for Suzhou. Furthermore, the intensities of daily PM_2.5 transport fluxes in Fuyang during the atmospheric pollution episode (APE1) were stronger than the monthly average. These results show that joint emission controls across multiple cities along the identified pathways are urgently needed to reduce winter episodes.

Quantifying the impacts of inter-city transport on air quality in the Yangtze River Delta urban agglomeration, China: Implications for regional cooperative controls of PM2.5 and O3

The Yangtze River Delta (YRD) urban agglomeration is one of the most developed regions in China. During recent decades, this region has experienced severe regional haze and photochemical smog pollution problems. In this study, we used a source-oriented chemical transport model to quantitatively estimate the effects of inter-city transport on fine particulate matter (PM_2.5) and ozone (O₃) among the 41 cities in the YRD urban agglomeration during the EXPLORE-YRD (EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation, and their Effects in the Yangtze River Delta) campaign (May 17 to June 17, 2018). The results show that inter-city transport is very significant in the YRD region. On average, the emissions from the local city, the other YRD cities, and the regions outside of the YRD contribute 25.3%, 49.9%, and 24.8% to the PM_2.5, respectively, and they contribute 33.7%, 46.8%, and 19.5% of the non-background O₃, respectively. On PM_2.5 or O₃ pollution days, the transport contribution from the non-local YRD cities becomes much more important, while the local emissions and the transport from non-YRD emissions become less important. The results also suggest that the cities within a distance of 184 km and 94 km contribute 60% of the PM_2.5 and O₃, respectively. Therefore, we recommend that regional cooperative control programs in the YRD consider emission controls over cities within these ranges. The range for primary PM_2.5 (92 km) is very different from that for secondary PM_2.5 (515 km)_. Cooperative emission controls of SO₂ and NO_x on a much larger regional scale are required to reduce the secondary PM_2.5 in the YRD.

Reapportioning the sources of secondary components of PM2.5: A combined application of positive matrix factorization and isotopic evidence

Secondary particles account for a considerable proportion of fine particles (PM_2.5) and reasonable reapportioning them to primary sources is critical for designing effective strategies for air quality improvement. This study developed a method which can reapportion secondary sources of PM_2.5 solved by positive matrix factorization (PMF) to primary sources based on the isotopic signals of nitrate, ammonium and sulfate. Actual PM_2.5 data in Beijing were used as a case study to assess the feasibility and capacity of this method. In the case, 20 chemical components were used to apportion PM_2.5 sources and source contributions of nitrate were applied to reapportion secondary source to primary sources. The model performance was also estimated by radiocarbon measurement (¹⁴C) of organic (OC) and elemental (EC) carbons of eight samples. The PMF apportioned seven sources: the secondary source (36.1%), vehicle exhausts (18.7%), industrial sources (13.6%), biomass burning (11.4%), coal combustion (8.10%), construction dust (7.93%) and fuel oil combustion (4.24%). After the reapportionment of the secondary source, vehicle exhausts (28.7%) contributed the most to PM_2.5, followed by biomass burning (25.1%) and industrial sources (18.9%). Fossil oil combustion and coal combustion increased to 8.00% and 11.4%, respectively, and construction dust contributed the least. The average gap between contributions of identified sources to OC and EC and the ¹⁴C measurements decreased 2.5 ± 1.2% after the reapportionment than 13.2 ± 10.8%, indicating the good performance of the developed method.

Explosive Secondary Aerosol Formation during Severe Haze in the North China Plain

Severe haze events with exceedingly high-levels of fine aerosols occur frequently over the past decades in the North China Plain (NCP), exerting profound impacts on human health, weather, and climate. The development of effective mitigation policies requires a comprehensive understanding of the haze formation mechanisms, including identification and quantification of the sources, formation, and transformation of the aerosol species. Haze evolution in this region exhibits distinct physical and chemical characteristics from clean to polluted periods, as evident from increasing stagnation and relative humidity, but decreasing solar radiation as well as explosive secondary aerosol formation. The latter is attributed to highly elevated concentrations of aerosol precursor gases and is reflected by rapid increases in the particle number and mass concentrations, both corresponding to nonequilibrium chemical processes. Considerable new knowledge has been acquired to understand the processes regulating haze formation, particularly in light of the progress in elucidating the aerosol formation mechanisms. This review synthesizes recent advances in understanding secondary aerosol formation, by highlighting several critical chemical/physical processes, that is, new particle formation and aerosol growth driven by photochemistry and aqueous chemistry as well as the interaction between aerosols and atmospheric stability. Current challenges and future research priorities are also discussed.

Study of Secondary Organic Aerosol Formation from Chlorine Radical-Initiated Oxidation of Volatile Organic Compounds in a Polluted Atmosphere Using a 3D Chemical Transport Model

The impact of chlorine (Cl) chemistry on the formation of secondary organic aerosol (SOA) during a severe wintertime air pollution episode is investigated in this study. The Community Multiscale Air Quality (CMAQ) model v5.0.1 with a modified SAPRC-11 gas-phase mechanism and heterogeneous reactions for reactive chlorine species is updated to include the formation of chlorine radical (Cl^•)-initiated SOA (Cl-SOA) from aromatic compounds, terpenes, and isoprene. Reported SOA yield data on Cl-SOA formation from environmental chamber studies are used to derive the mass yield and volatility data for the two-product equilibrium-partitioning model. The heterogeneous reaction of particulate chloride (pCl^-) leads to a significant increase in the Cl^• and hydroxyl radical (OH) concentrations throughout the domain. Monthly Cl-SOA concentrations range from 0.7 to 3.0 μg m^-3, with increasing anthropogenic Cl emissions leading to higher Cl-SOA concentrations. Indirectly, this also leads to an increase of monthly SOA by up to 2.5-3.0 g μm^-3 from the traditional OH oxidation pathways as well as the surface uptake of glyoxal and methylglyoxal. Increased OH concentrations, however, do not always lead to higher overall SOA concentrations in the entire domain. High OH reduces the lifetime of glyoxal/methylglyoxal (GLY/MGLY), making them less available to form SOA. In the Sichuan Basin (SCB) and part of Southwest China where high O₃ concentrations meet high pCl emissions, a higher Cl^•/OH ratio leads to net O₃ loss from the Cl^• + O₃ reaction, thus reducing SOA formation from the O₃ oxidation of volatile organic compounds (VOCs). Also, the competition between Cl^• and OH for VOCs could lead to lower overall SOA because the molar yields of the semivolatile products in Cl-VOC reactions are lower than their OH + VOC reaction counterparts. When Cl^• concentrations are further increased with higher emissions of Cl, precursor gases can be depleted and become the limiting factor in SOA formation. This study reveals the direct and indirect impacts of chlorine chemistry on SOA in polluted winter conditions, which are greatly affected by the Cl emissions, the ambient O₃ level, and the availability of SOA precursors.

Wintertime nitrate formation pathways in the north China plain: Importance of N2O5 heterogeneous hydrolysis

Strict emission control measures have been implemented in the North China Plain (NCP) to improve air quality since 2013. However, heavy particulate matter (PM) pollution still frequently occurs in the region especially during wintertime, and the nitrate contribution to fine PM (PM_2.5) has substantially increased in recent several years. Nitrate aerosols, which are formed via nitric acid (HNO₃) to balance inorganic cations in the particle phase, have become a major fraction of PM_2.5 during wintertime haze events in the NCP. HNO₃ is mainly produced through homogeneous (NO₂+OH, NO₃+VOCs) and heterogeneous pathways (N₂O₅ heterogeneous hydrolysis) in the atmosphere, but the contribution of the two pathways to the nitrate formation remains elusive. In this study, the Weather Research and Forecasting model with Chemistry (WRF-Chem) was applied to simulate a heavy haze episode from 16 to December 31, 2016 in the North China Plain, and the source-oriented method (SOM) and brute force method (BFM) were both used to evaluate contributions of the heterogeneous pathway to the nitrate formation. The results demonstrated that the near-surface nitrate contributions of the heterogeneous pathway were about 30.8% based on the BFM, and 51.6% based on the SOM, indicating that the BFM might be subject to underestimating importance of the heterogeneous pathway to the nitrate formation. The SOM simulations further showed that the heterogeneous pathway dominated the nighttime HNO₃ production in the planetary boundary layer, with an average contribution of 83.0%. Although N₂O₅ was photolytically liable during daytime, the heterogeneous N₂O₅ hydrolysis still contributed 10.1% of HNO₃, which was caused by substantial attenuation of incident solar radiation by clouds and high PM_2.5 mass loading. Our study highlighted the significantly important role of N₂O₅ heterogeneous hydrolysis in the nitrate formation during wintertime haze days.

Importance of Wintertime Anthropogenic Glyoxal and Methylglyoxal Emissions in Beijing and Implications for Secondary Organic Aerosol Formation in Megacities

Atmospheric glyoxal (GLY) and methylglyoxal (MGLY) are key precursors of secondary organic aerosol (SOA). However, anthropogenic emissions of GLY and MGLY and their contribution to surface GLY and MGLY concentrations, as well as the secondary organic aerosol (SOA) formation, are not well quantified. By developing an emission inventory of anthropogenic GLY and MGLY and improving the Community Multiscale Air Quality Model (CMAQ) with SOA formation from irreversible surface uptake of GLY and MGLY, as well as a precursor-origin resolved technique, we quantified the source contributions of GLY and MGLY and their impact on wintertime SOA formation in Beijing, China. The total emissions of GLY and MGLY in Beijing in 2017 are 1.1 × 10⁴ kmol and 7.0 × 10³ kmol, respectively. Anthropogenic primary emissions are found to be the dominant contributor to wintertime GLY and MGLY concentrations (∼74% for GLY and ∼63% for MGLY). Anthropogenic primary emissions of GLY and MGLY contributes to 30% of GLY/MGLY SOA daily average concentration and accounts for up to 45% of nighttime GLY/MGLY SOA in winter. The study suggests that the anthropogenic GLY and MGLY emissions, mainly from gasoline vehicles and cooking, are important for SOA formation and shall be strictly controlled in Chinese megacities.

Contribution of biogenic sources to secondary organic aerosol in the summertime in Shaanxi, China

A revised Community Multi-scale Air Quality (CMAQ) model with updated secondary organic aerosol (SOA) yields and a more detailed description of SOA formation from isoprene (ISOP) oxidation was applied to study the spatial distribution of SOA, its components and precursors in Shaanxi in July of 2013. The emissions of biogenic volatile organic compounds (BVOCs) were generated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN), of which ISOP and monoterpene (MONO) were the top two, with 1.73 × 10⁹ mol and 1.82 × 10⁸ mol, respectively. The spatial distribution of BVOCs emission was significantly correlated with the vegetation coverage distribution. ISOP and its intermediate semi-volatile gases were up to ∼7.0 and ∼1.4 ppb respectively in the ambient. SOA was generally 2-6 μg/m³, of which biogenic SOA (BSOA) accounted for as high as 84% on average. There were three main BVOCs Precursors including ISOP (58%) and MONO (8%) emit in the studied domain, and ISOP (9%) transported. The Guanzhong Plain had the highest BSOA concentrations of 3-5 μg/m³, and the North Shaanxi had the lowest of 2-3 μg/m³. More than half of BSOA was due to reactive surface uptake of ISOP epoxide (0.2-0.7 μg/m³, ∼19%), glyoxal (GLY) (0.2-0.5 μg/m³, ∼11%) and methylglyoxal (MGLY) (0.4-1.4 μg/m³, ∼32%), while the remaining was due to the traditional equilibrium partitioning of semi-volatile components (0.1-1.2 μg/m³, ∼25%) and oligomerization (0.2-0.4 μg/m³, ∼12%). Overall, SOA formed from ISOP contributed 1-3 μg/m³ (∼80%) to BSOA.

Source apportionment and regional transport of anthropogenic secondary organic aerosol during winter pollution periods in the Yangtze River Delta, China

Since the concentrations of primary particles and secondary inorganic aerosol components have been reduced significantly due to stringent emission controls, quantifying the source contributions and regional transport of secondary organic aerosol (SOA) is critical to further improve air quality in eastern China. In this study, the Community Multiscale Air Quality (CMAQ) model coupled with the updated SAPRC-11 photochemical mechanism and a revised SOA module was applied to investigate the emission sector and regional contributions to SOA in winter 2015 (January 5-26, 2015) and 2016 (December 20, 2015-January 20, 2016) in the Yangtze River Delta (YRD). The model is generally capable of reproducing the observed SOA concentrations at the Qingpu Supersite in Shanghai. The observed and predicted SOA concentrations are 6.4 μg/m³ and 6.9 μg/m³ in winter 2015, and 5.7 μg/m³ and 9.6 μg/m³ in winter 2016. The mean fraction bias (MFB) of the hourly SOA predictions is 0.22 and 0.32, respectively. High SOA concentrations in the wintertime of YRD are mainly due to aromatic compounds and dicarbonyls (glyoxal and methylglyoxal), which, on average, account for 43% and 53% of total SOA, respectively. The average contributions of industrial, residential, and transportation sectors in the YRD region during the entire simulation periods are 61%, 22%, and 17%, respectively. At the Qingpu Supersite in Shanghai, the industrial sector contributes to as much as 65% of total SOA in the heavy pollution episode of 2016. The contributions from transportation and residential sectors are 16% and 17%, respectively, during the same episode. The industry emissions from the Jiangsu, Zhejiang, and Shanghai are major contributors to the SOA at the Qingpu supersite during the heavy-polluted episodes, accounting for 31%, 19%, and 14% of the total predicted SOA. This study represents the first detailed regional modeling study of source region contributions to SOA in the YRD region and the detailed analyses of SOA in two winters months complement the previous SOA source apportionment studies focusing on seasonal average contributions.

Sources and health risks of ambient polycyclic aromatic hydrocarbons in China

Polycyclic aromatic hydrocarbons (PAHs) in the environment are of significant concerns due to their high toxicity to human health. PAHs measurements at limited air quality monitoring stations alone are insufficient to gain a complete understanding of ambient levels and public exposure of PAHs in China. This study simulated the concentrations of PAHs in China, identified the source contributions, and estimated the health risks. Anthropogenic emissions of 16 priority PAHs directly associated with health risks were generated from the global high-resolution PKU-FUEL-2007 inventory. Open biomass burning emissions were generated from the Fire Inventory from NCAR (FINN). PAHs concentrations in January, April, July, and October 2013 were simulated using the Community Multiscale Air Quality (CMAQ) model after incorporation of chemistry, partitioning, and deposition of PAHs. Predicted PAHs were in good agreement with seasonal and annual averaged observations from previous studies. The surface concentrations of 16-PAHs were higher in winter, with population weight average of 0.8 μg/m³ and peak value of 2.0 μg/m³ in urban areas in the North China Plain (NCP) and the Yangtze River Delta (YRD). Summer and spring exhibited lower concentrations of approximately 0.2 μg/m³ in most areas. The most important sources to PAHs were biomass burning and coal combustion in winter and industrial processes and oil and gas activities in summer. The cancer risk due to inhalation exposure of naphthalene (NAPH) and seven carcinogenic PAHs was significant, with the incremental lifetime cancer risk (ILCR) of >5 × 10^-4 in many urban and industrial areas. Exposure to PAHs was estimated to result in 15,198 excess lifetime cancer cases in China. Oil and gas burning associated with transport, residential and commercial activities were major contributors to ILCR in China. Coal combustion was predominant in Shanxi but less important in other regions.

Source apportionment to support air quality planning: Strengths and weaknesses of existing approaches

Information on the origin of pollution constitutes an essential step of air quality management as it helps identifying measures to control air pollution. In this work, we review the most widely used source-apportionment methods for air quality management. Using theoretical and real-case datasets we study the differences among these methods and explain why they result in very different conclusions to support air quality planning. These differences are a consequence of the intrinsic assumptions that underpin the different methodologies and determine/limit their range of applicability. We show that ignoring their underlying assumptions is a risk for efficient/successful air quality management as these methods are sometimes used beyond their scope and range of applicability. The simplest approach based on increments (incremental approach) is often not suitable to support air quality planning. Contributions obtained through mass-transfer methods (receptor models or tagging approaches built in air quality models) are appropriate to support planning but only for specific pollutants. Impacts obtained via "brute-force" methods are the best suited but it is important to assess carefully their application range to make sure they reproduce correctly the prevailing chemical regimes.

Unveiling tropospheric ozone by the traditional atmospheric model and machine learning, and their comparison:A case study in hangzhou, China

Tropospheric ozone in the surface air has become the primary atmospheric pollutant in Hangzhou, China, in recent years. Previous analysis is not enough to decode it for better regulation. Therefore, we use the traditional atmospheric model, Weather Research and Forecasting coupled with Community Multi-scale Air Quality (WRF-CMAQ), and machine learning models, Extreme Learning Machine (ELM), Multi-layer Perceptron (MLP), Random Forest (RF) and Recurrent Neural Network (RNN) to analyze and predict the ozone in the surface air in Hangzhou, China, using meteorology and air pollutants as input. We firstly quantitatively demonstrate that the dew-point deficit, instead of temperature and relative humidity, is the predominant meteorological factor in shaping tropospheric ozone. Urban heat island, daily direct solar radiation time, wind speed and wind direction play trivial role in impacting tropospheric ozone. NO₂ is the primary influential factors both for hourly ozone and daily O₃-8 h due to the titration effect. The most environmental-friendly way to mitigate the ozone pollution is to lower the volatile organic compounds (VOCs) with the highest ozone formation potentials. We deduce that the tropospheric ozone formation process tends to be not only non-linear but also non-smooth. Compared with the traditional atmospheric models, machine learning, whose characteristics are rapid convergence, short calculating time, adaptation of forecasting episodes, small program memory, higher accuracy and less cost, is able to predict tropospheric ozone more accurately.

Contributions of inter-city and regional transport to PM2.5 concentrations in the Beijing-Tianjin-Hebei region and its implications on regional joint air pollution control

Regional transport plays an important role in the serious PM_2.5 pollutions in the Beijing-Tianjin-Hebei (BTH) region, China. Practical regional joint emission control strategies require quantitative assessments of the transport contribution among cities and regions. The Community Multiscale Air Quality model equipped with the Integrated Source Apportionment Model is used to simulate the contributions from 5 major emission sectors in 13 cities of the BTH region, and 4 surrounding provinces outside BTH for the year 2014. Annual averaged local contribution ranges from 32% to 63% for the 13 cities in the BTH region, where secondary components contributing more than primary components. Regional contribution ratio becomes larger and the transport distance longer in July and October than in January and March. For Beijing, local contributions are 62% and 69% in January and March respectively, and the regional transports are mainly from nearby cities such as Zhangjiakou, Baoding and Langfang. In July and October, local contributions in Beijing are only 33% and 38% respectively, and a large range of regions in the south have substantial contributions, where Shandong Province and Henan Province contribute 3.6-5.3 μg/m³. Analysis of daily contributions suggests that regional transport is stronger under higher PM_2.5 concentrations. During heavy pollution, local emissions in Beijing contribute 61%, 49%, 23% and 25% in January, march, July and October respectively, while during the clean days, the ratios are 88%, 88%, 76% and 57% respectively. Southerly regional transport during the rising phase of "saw tooth" pattern might be enhanced by weak cold high pressure and its easterly, northerly moving path. Among the major emission sectors, in winter, local domestic combustion is the most important source for Beijing, Tianjin and Shijiazhuang. In summer, transportation and domestic combustion are two important local sources for Beijing, while joint control in other cities should focus on industry.