Characterization of ozone in the lower troposphere during the 2016 G20 conference in Hangzhou

The effect of cross-regional transport on ozone and particulate matter pollution in China: A review of methodology and current knowledge

China is currently one of the countries impacted by severe atmospheric ozone (O3) and particulate matter (PM) pollution. Due to their moderately long lifetimes, O3 and PM can be transported over long distances, cross the boundaries of source regions and contribute to air pollution in other regions. The reported contributions of cross-regional transport (CRT) to O3 and fine PM (PM2.5) concentrations often exceed those of local emissions in the major regions of China, highlighting the important role of CRT in regional air pollution. Therefore, further improvement of air quality in China requires more joint efforts among regions to ensure a proper reduction in emissions while accounting for the influence of CRT. This review summarizes the methodologies employed to assess the influence of CRT on O3 and PM pollution as well as current knowledge of CRT influence in China. Quantifying CRT contributions in proportion to O3 and PM levels and studying detailed CRT processes of O3, PM and precursors can be both based on targeted observations and/or model simulations. Reported publications indicate that CRT contributes by 40-80 % to O3 and by 10-70 % to PM2.5 in various regions of China. These contributions exhibit notable spatiotemporal variations, with differences in meteorological conditions and/or emissions often serving as main drivers of such variations. Based on trajectory-based methods, transport pathways contributing to O3 and PM pollution in major regions of China have been revealed. Recent studies also highlighted the important role of horizontal transport in the middle/high atmospheric boundary layer or low free troposphere, of vertical exchange and mixing as well as of interactions between CRT, local meteorology and chemistry in the detailed CRT processes. Drawing on the current knowledge on the influence of CRT, this paper provides recommendations for future studies that aim at supporting ongoing air pollution mitigation strategies in China.

Identification of particle distribution pattern in vertical profile via unmanned aerial vehicles observation

Below the boundary layer, the air pollutants have been confirmed to present the decreasing trend with the height in most situaitons. However, the disperiosn rate of air pollutants in the vertical profile is rarely investigated in detail, especially through in-situ measurement. With this consideration, we employed an unmanned aerial vehicle equipped with portable monitoring equipments to scrutinize the vertical distribution of PM2.5. Based on the original data, we found that PM2.5 concentration decreases gradually with altitude below the boundary layer and demonstrated an obvious linear correlation. Therefore, the vertical distribution of PM2.5 was quantified by representing the distribution of PM2.5 with the slope of PM2.5 vertical distribution. We used backward trajectories to reveal the causes of outliers (PM2.5 increasing with altitude), and found that PM2.5 in the high altitude came from the southwest. Besides, the relationship between the vertical distribution of PM2.5 and various meteorological factors was investigated using stepwise regression analysis. The results show that the four meteorological factors most strongly correlated with the slope values are: (a) the difference in relative humidity between the ground and the air; (b) the difference in temperature between the ground and the air; (c) the height of the boundary layer; and (d) the wind speed. The slope values increase with increasing the difference in relative humidity between ground and air and the difference in temperature between the ground and the air, and decrease with increasing boundary layer height and wind speed. According to the Random Forest calculations, the ground-to-air relative humidity difference is the most important at 0.718; the wind speed is the least important at 0.053; and the ground-to-air temperature difference and boundary layer height are 0.140 and 0.088, respectively.

Vertical Evolution of Ozone Formation Sensitivity Based on Synchronous Vertical Observations of Ozone and Proxies for Its Precursors: Implications for Ozone Pollution Prevention Strategies

Photochemical ozone (O3) formation in the atmospheric boundary layer occurs at both the surface and elevated altitudes. Therefore, the O3 formation sensitivity is needed to be evaluated at different altitudes before formulating an effective O3 pollution prevention and control strategy. Herein, we explore the vertical evolution of O3 formation sensitivity via synchronous observations of the vertical profiles of O3 and proxies for its precursors, formaldehyde (HCHO) and nitrogen dioxide (NO2), using multi-axis differential optical absorption spectroscopy (MAX-DOAS) in urban areas of the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions in China. The sensitivity thresholds indicated by the HCHO/NO2 ratio (FNR) varied with altitude. The VOC-limited regime dominated at the ground level, whereas the contribution of the NOx-limited regime increased with altitude, particularly on heavily polluted days. The NOx-limited and transition regimes played more important roles throughout the entire boundary layer than at the surface. The feasibility of extreme NOx reduction to mitigate the extent of the O3 pollution was evaluated using the FNR-O3 curve. Based on the surface sensitivity, the critical NOx reduction percentage for the transition from a VOC-limited to a NOx-limited regime is 45-72%, which will decrease to 27-61% when vertical evolution is considered. With the combined effects of clean air action and carbon neutrality, O3 pollution in the YRD and PRD regions will transition to the NOx-limited regime before 2030 and be mitigated with further NOx reduction.

A hybrid deep learning model for regional O3 and NO2 concentrations prediction based on spatiotemporal dependencies in air quality monitoring network

Short-term prediction of urban air quality is critical to pollution management and public health. However, existing studies have failed to make full use of the spatiotemporal correlations or topological relationships among air quality monitoring networks (AQMN), and hence exhibit low precision in regional prediction tasks. With this consideration, we proposed a novel deep learning-based hybrid model of Res-GCN-BiLSTM combining the residual neural network (ResNet), graph convolutional network (GCN), and bidirectional long short-term memory (BiLSTM), for predicting short-term regional NO₂ and O₃ concentrations. Auto-correlation analysis and cluster analysis were first utilized to reveal the inherent temporal and spatial properties respectively. They demonstrated that there existed temporal daily periodicity and spatial similarity in AQMN. Then the identified spatiotemporal properties were sufficiently leveraged, and monitoring network topological information, as well as auxiliary pollutants and meteorology were also adaptively integrated into the model. The hourly observed data from 51 air quality monitoring stations and meteorological data in Shanghai were employed to evaluate it. Results show that the Res-GCN-BiLSTM model was better adapted to the pollutant characteristics and improved the prediction accuracy, with nearly 11% and 17% improvements in mean absolute error for NO₂ and O₃, respectively compared to the best performing baseline model. Among the three types of monitoring stations, traffic monitoring stations performed the best for O₃, but the worst for NO₂, mainly due to the impacts of intensive traffic emissions and the titration reaction. These findings illustrate that the hybrid architecture is more suitable for regional pollutant concentration.

Ambient Environmental Ozone and Variation of Fractional Exhaled Nitric Oxide (FeNO) in Hairdressers and Healthcare Workers

Fractional exhaled nitric oxide (FeNO) is a breath-related biomarker of eosinophilic asthma. The aim of this study was to investigate FeNO variations due to environmental or occupational exposures in respiratory healthy subjects. Overall, 14 hairdressers and 15 healthcare workers in Oslo were followed for 5 workdays. We registered the levels of FeNO after commuting and arriving at the workspace and after ≥3 h of work, in addition to symptoms of cold, commuting method, and hair treatments that were performed. Both short- and intermediate-term effects after exposure were evaluated. Environmental assessment of daily average levels of air quality particulate matter 2.5 (PM_2.5), particulate matter 10 (PM₁₀), nitrogen dioxide (NO₂), sulphur dioxide (SO₂), and ozone (O₃) indicated a covariation in ozone and FeNO in which a 35-50% decrease in ozone was followed by a near 20% decrease in FeNO with a 24-h latency. Pedestrians had significantly increased FeNO readings. Symptoms of cold were associated with a significant increase in FeNO readings. We did not find any FeNO increase of statistical significance after occupational chemical exposure to hair treatments. The findings may be of clinical, environmental and occupational importance.

Vertical profiles of O3, NO2 and PM in a major fine chemical industry park in the Yangtze River Delta of China detected by a sensor package on an unmanned aerial vehicle

The vertical profiles and diurnal variations of air pollutants at different heights in the fine chemical industry park (FCIP) were systematically studied in this study. Air pollutants in a major FCIP in the Yangtze River Delta of China within 500 m above ground level (AGL) detected by a sensor package on an unmanned aerial vehicle (UAV). The air pollutants including ozone (O₃), nitrogen dioxide (NO₂), particulate matter (PM), total volatile organic compounds (TVOCs) and carbon monoxide (CO), respectively, had been measured through more than one hundred times of vertical flights from Aug. 2020 to Jul. 2021. The concentrations of NO₂ and CO generally decreased with the height while the concentrations of O₃ increased with the height within 500 m AGL. The photochemical reaction resulted in a strong inverse relationship between the vertical profiles of O₃ and that of NO₂. The concentrations of PM_2.5 and TVOCs generally decreased with the height below 100 m AGL and were fully mixed above 100 m AGL. The vertical profiles of different particle sizes were well consistent with the R² value of 0.97 between PM₁ and PM_2.5 and 0.93 between PM_2.5 and PM₁₀. The NO₂ and PM_2.5 concentrations sometimes increased with height maybe due to the influence of temperature inversion layer or long-distance transportation from northern China. The diurnal variations of NO₂, O₃, TVOCs and CO concentrations at different heights within 500 m AGL were basically consistent. The diurnal variations range of PM_2.5 concentrations below 100 m AGL was large and different from other heights, which should be greatly influenced by the local emissions. The unstable atmospheric stability was accompanied by strong photochemical reactions and convective activities, resulting in low concentrations of NO₂ and PM_2.5, while high concentrations of O₃.

Does Ozone Pollution Share the Same Formation Mechanisms in the Bay Areas of China?

As important regions of transition between land and sea, the three bay areas of Bohai Bay (BHB), Hangzhou Bay (HZB), and Pearl River Estuary (PRE) in China often suffer from severe photochemical pollution despite scarce anthropogenic emissions. To understand the causes of high ozone (O₃) concentrations, the high O₃ episode days associated with special synoptic systems in the three bays were identified via observations and simulated by the weather research and forecasting coupled with community multiscale air quality (WRF-CMAQ) model. It was revealed that the interaction between synoptic winds and mesoscale breezes resulted in slow wind speeds over the HZB and PRE, where air pollutants transported from upwind cities gained a long residence time and subsequently participated in intensive photochemical reactions. The net O₃ production rates within the bay areas were even comparable to those in surrounding cities. This finding was also applicable to BHB but with lower net O₃ production rates, while high levels of background O₃ and the regional transport from farther upwind BHB partially elevated the O₃ concentrations. Hence, these three bay areas served as O₃ "pools" which caused the accumulation of air pollutants via atmospheric dynamics and subsequent intense photochemical reactions under certain meteorological conditions. The results may be applicable to other similar ecotones around the world.

The use of generalized synthetic control method to evaluate air pollution control measures of G20 Hangzhou Summit

The traditional campaign-style enforcement in environmental governance has been debated whether its rebound effect is likely to eat away the short-term environmental benefits and subsequently bring about severer pollution. There are methodological challenges in assessing the effect of temporary environmental intervention. By applying the generalized synthetic control method (GSCM), we quantified and characterized the effectiveness of environmental regulations implemented for the G20 Hangzhou Summit held on 4-5 September, 2016. The summit was successful in reducing Air Quality Composite Index by 17.40% (95% CI: 9.53%, 24.60%), 13.30% (95% CI: 4.23%, 21.50%), and 10.09% (95% CI: 2.01%, 17.51%) in the core, strictly-regulated and regulated areas respectively, comparing with the index expected under a "No-G20" scenario during the preparatory period and the summit period (July-September 2016), and the reduction of the levels in specific pollutants (PM₁₀, PM_2.5, NO₂, and CO) was also observed. Besides, the environmental benefits lasted for at least 3 months after the summit. This study demonstrates that the pollution control measures during the G20 Hangzhou Summit improved air quality immediately and continuously, and the GSCM provides a useful tool for evaluating the intervention effects of environmental regulations.

Impacts of TROPOMI-Derived NO X Emissions on NO2 and O3 Simulations in the NCP during COVID-19

NO₂ and O₃ simulations have great uncertainties during the COVID-19 epidemic, but their biases and spatial distributions can be improved with NO₂ assimilations. This study adopted two top-down NO _X inversions and estimated their impacts on NO₂ and O₃ simulation for three periods: the normal operation period (P1), the epidemic lockdown period following the Spring Festival (P2), and back to work period (P3) in the North China Plain (NCP). Two TROPOspheric Monitoring Instrument (TROPOMI) NO₂ retrievals came from the Royal Netherlands Meteorological Institute (KNMI) and the University of Science and Technology of China (USTC), respectively. Compared to the prior NO _X emissions, the two TROPOMI posteriors greatly reduced the biases between simulations with in situ measurements (NO₂ MREs: prior 85%, KNMI -27%, USTC -15%; O₃ MREs: Prior -39%, KNMI 18%, USTC 11%). The NO _X budgets from the USTC posterior were 17-31% higher than those from the KNMI one. Consequently, surface NO₂ levels constrained by USTC-TROPOMI were 9-20% higher than those by the KNMI one, and O₃ is 6-12% lower. Moreover, USTC posterior simulations showed more significant changes in adjacent periods (surface NO₂: P2 vs P1, -46%, P3 vs P2, +25%; surface O₃: P2 vs P1, +75%, P3 vs P2, +18%) than the KNMI one. For the transport flux in Beijing (BJ), the O₃ flux differed by 5-6% between the two posteriori simulations, but the difference of NO₂ flux between P2 and P3 was significant, where the USTC posterior NO₂ flux was 1.5-2 times higher than the KNMI one. Overall, our results highlight the discrepancies in NO₂ and O₃ simulations constrained by two TROPOMI products and demonstrate that the USTC posterior has lower bias in the NCP during COVD-19.

Using Stable Sulfur Isotope to Trace Sulfur Oxidation Pathways during the Winter of 2017-2019 in Tianjin, North China

After the implementation of the Coal Replacing Project (CRP) in the northern parts of China in 2017, its effect on PM_2.5 composition is still unclear. In the study, water-soluble ionic components (WSICs) and stable sulfur isotope ratios (δ³⁴S) of SO₄^2- in PM_2.5 collected during the domestic heating period before and after the implementation of CRP in Tianjin were analyzed. Results showed that the average concentrations of both PM_2.5 and WSICs have dropped dramatically after the CRP, especially for the SO₄^2- (by approximately 57-60%). After the CRP, the range of δ³⁴S_sulfate was significantly narrowed to 4.1-7.5‱ in January 2018 and 1.4-6.1‱ in January 2019, which suggested that the sulfur source was becoming simple. It was interesting that the δ³⁴S_sulfate value in the pollution period before the CRP was higher than that in the clean period, whereas it showed the opposite tendency after the CRP, which implied that the contribution of sea salt was high during the pollution period before the CRP. The MIXSIAR model calculated that the contributions of the transition-metal ion (TMI) oxidation and NO₂ oxidation pathways in the three sampling stages were higher than those of the OH radical oxidation and H₂O₂/O₃ oxidation pathways, indicating that the formation pathway of sulfate was mainly dominated by heterogeneous oxidation. Before the CRP, the NO₂ oxidation pathway was the dominant sulfate oxidation pathway during a haze episode, and the TMI oxidation pathway dominated the formation of sulfates after the CRP.

Spatiotemporal neural network for estimating surface NO2 concentrations over north China and their human health impact

Atmospheric nitrogen dioxide (NO₂) is an important reactive gas pollutant harmful to human health. The spatiotemporal coverage provided by traditional NO₂ monitoring methods is insufficient, especially in the suburban and rural areas of north China, which have a high population density and experience severe air pollution. In this study, we implemented a spatiotemporal neural network (STNN) model to estimate surface NO₂ from multiple sources of information, which included satellite and in situ measurements as well as meteorological and geographical data. The STNN predicted NO₂ with high accuracy, with a coefficient of determination (R²) of 0.89 and a root mean squared error of 5.8 μg/m³ for sample-based 10-fold cross-validation. Based on the surface NO₂ concentration determined by the STNN, we analyzed the spatial distribution and temporal trends of NO₂ pollution in north China. We found substantial drops in surface NO₂ concentrations ranging between 9.1% and 33.2% for large cities during the 2020 COVID-19 lockdown when compared to those in 2019. Moreover, we estimated the all-cause deaths attributed to NO₂ exposure at a high spatial resolution of about 1 km, with totals of 6082, 4200, and 18,210 for Beijing, Tianjin, and Hebei Provinces in 2020, respectively. We observed remarkable regional differences in the health impacts due to NO₂ among urban, suburban, and rural areas. Generally, the STNN model could incorporate spatiotemporal neighboring information and infer surface NO₂ concentration with full coverage and high accuracy. Compared with machine learning regression techniques, STNN can effectively avoid model overfitting and simultaneously consider both spatial and temporal correlations of input variables using deep convolutional networks with residual blocks. The use of the proposed STNN model, as well as the surface NO₂ dataset, can benefit air quality monitoring, forecasting, and health burden assessments.

Interannual variations, sources, and health impacts of the springtime ozone in Shanghai

In spring, ozone (O₃) pollution frequently occurrs in eastern China, but key drivers remain uncertain. In this study, interannual variations in springtime ozone in Shanghai, China, from 2013 to 2021, were investigated to assess the health impacts and the effectiveness of recent air pollution control measures. A combination of ground-level measurements of regulated air pollutants, lidar observations, and backward trajectories of air masses was used to identify the key drivers for enhancing springtime O₃. The results show that external imports of O₃ driven by atmospheric circulation are notable sources of springtime surface O₃. For example, the downward transport from the free troposphere could contribute to over 50% of surface O₃ in the morning. The surface O₃ mixing ratios in spring exhibited an upward trend of 0.93 ppb yr^-1 (p < 0.05) from 2013 to 2021. The change in meteorological variables, particularly the increase in air temperature, could explain nearly 87% of the springtime O₃ upward trend. The change in anthropogenic emissions of precursors only contributed to a small fraction (<13%) of the increase in springtime O₃. The cumulative exposure of urban residents to O₃ in spring also exhibited a significant upward trend (111 ppb yr^-1, p < 0.05). With the rapid increase in surface O₃, premature respiratory mortality attributable to O₃ exposure has fluctuated at approximately 2933 deaths per year since 2016, even though the total deaths from respiratory diseases have significantly declined. Long-term exposure to high O₃ concentrations is a significant contributor to premature respiratory mortality.

Analysis of the Effect of Economic Development on Air Quality in Jiangsu Province Using Satellite Remote Sensing and Statistical Modeling

In recent decades, the economy of China has developed rapidly, but this has brought widespread damage to the environment, which forces us to explore a sustainable, green, economic development model. Therefore, it is particularly necessary to clarify the relationship between economic development and environmental pollution. In this paper, we used satellite remote sensing tropospheric NO2 vertical column density (VCD) as an air quality indicator; the total exports, total imports, and industrial electricity consumption as the economic indicators; and the wind speed, temperature, and planetary boundary layer height as the meteorological factors to perform a Generalized Additive Modeling (GAM) analysis. By deducing the influence of meteorological factors, the relationship between economic indicators and the air quality indicator can be determined. When total exports increased by one billion USD (United States Dollar), the tropospheric NO2 VCDs of Nanjing and Suzhou increased by about 15% and 6%, respectively. The tropospheric NO2 VCDs of Suzhou increased by about 5% when the total imports increased by one billion USD. In addition, when the industrial electricity consumption increased by one billion kWh, the tropospheric NO2 VCDs of Nanjing, Suzhou and Xuzhou increased by about 25%, 12%, and 59%, respectively. This study provides a method to quantify the contribution of economic growth to air pollution, which is helpful for better understanding of the relationship between economic development and air quality.

Modeling of spatial and temporal variations of ozone-NOx-VOC sensitivity based on photochemical indicators in China

Comprehensive air quality model with extensions (CAMx)-decoupled direct method (DDM) was used to simulate ozone-NO_x-VOCs sensitivity of for May-November in 2016-2018 in China. Based on the relationship between the simulated ozone (O₃) sensitivity values and the ratio of formaldehyde (HCHO) to NO₂ (FNR) and the ratio of production rate of hydrogen peroxide (H₂O₂) to production rate of nitric acid (HNO₃) ( [Formula: see text] ), the localized range of FNR and [Formula: see text] thresholds in different regions in China were obtained. The overall simulated FNR values are about 1.640-2.520, and [Formula: see text] values are about 0.540-0.830 for the transition regime. Model simulated O₃ sensitivities or region specific FNR or [Formula: see text] thresholds should be applied to ensure the accurate local O₃ sensitivity regimes. Using the tropospheric column FNR values from ozone monitoring instrument (OMI) satellite data as an indicator with the simulated threshold values, the spatial distributions of O₃ formation regimes in China are determined. The O₃ sensitivity regimes from eastern to central China are gradually from VOC-limited, transition to NO_x-limited spatially, and moving toward to transition or NO_x-limited regime from 2005 to 2019 temporally.

First global observation of tropospheric formaldehyde from Chinese GaoFen-5 satellite: Locating source of volatile organic compounds

Satellite remote sensing is an important technique providing long-term and large-scale information of formaldehyde (HCHO), which plays a crucial role in atmospheric chemistry. Low signal-to-noise ratio and poor stability of the Environmental Trace Gases Monitoring Instrument (EMI) On board Gaofen-5 satellite, the first Chinese space-borne spectrometer, make HCHO retrieval extremely difficult. Here we firstly retrieved HCHO vertical column densities (VCDs) from EMI through in-flight spectral calibration, retrieval setting optimization and stripe correction. Retrieved EMI HCHO VCDs correlate well with those measured by Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) with normalize mean bias (NMB) below 25%. EMI HCHO VCDs are comparable with those observed by Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI). This study reveals that HCHO can be observed successfully by algorithm optimization despite of poor performance of space-borne spectrometer. The retrieved EMI HCHO VCDs are applied to locate emission sources of volatile organic compounds (VOCs).

Numerical Simulation of Topography Impact on Transport and Source Apportionment on PM2.5 in a Polluted City in Fenwei Plain

The unique energy structure, high intensity of coal production, and complex terrain, make Fenwei Plain a highly polluted region in China. In this study, we characterized the transport characteristic and sources of PM2.5 (the fraction of particulate matter ≤ 2.5 μm) in Sanmenxia, a polluted city in canyon terrain. The results showed that special topography in Sanmenxia had an important role in the transport of particulates. Sanmenxia is located between two northeast-southwest facing mountains, showing a special local circulation. The local circulation was dominated by a downslope wind at nighttime, while the cross−mountain airflow and zonal wind were dominant during the daytime in the canyon terrain. PM2.5 accumulated near Sanmenxia with the influence of downslope, zonal wind, and topography. The main regional transport paths could be summarized into an eastern path, a northern path, and a western path during the severe haze episodes. The PM2.5 source apportionment revealed by an on-line tracer-tagged of the Nested Air Quality Prediction Model System (NAQPMS) showed that the main regional sources of Sanmenxia were Yuncheng, Sanmenxia, and Weinan. The contribution to PM2.5 concentration in Sanmenxia was 39%, 25%, and 11%, respectively. The northern path had the most important impact on Sanmenxia. The results can provide scientific basis for the establishment of severe haze control in Sanmenxia and regional joint control.

Variations of Urban NO2 Pollution during the COVID-19 Outbreak and Post-Epidemic Era in China: A Synthesis of Remote Sensing and In Situ Measurements

Since the COVID-19 outbreak in 2020, China’s air pollution has been significantly affected by control measures on industrial production and human activities. In this study, we analyzed the temporal variations of NO2 concentrations during the COVID-19 lockdown and post-epidemic era in 11 Chinese megacities by using satellite and ground-based remote sensing as well as in situ measurements. The average satellite tropospheric vertical column density (TVCD) of NO2 by TROPOMI decreased by 39.2–71.93% during the 15 days after Chinese New Year when the lockdown was at its most rigorous compared to that of 2019, while the in situ NO2 concentration measured by China National Environmental Monitoring Centre (CNEMC) decreased by 42.53–69.81% for these cities. Such differences between both measurements were further investigated by using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) remote sensing of NO2 vertical profiles. For instance, in Beijing, MAX-DOAS NO2 showed a decrease of 14.19% (versus 18.63% by in situ) at the ground surface, and 36.24% (versus 36.25% by satellite) for the total tropospheric column. Thus, vertical discrepancies of atmospheric NO2 can largely explain the differences between satellite and in situ NO2 variations. In the post-epidemic era of 2021, satellite NO2 TVCD and in situ NO2 concentrations decreased by 10.42–64.96% and 1.05–34.99% compared to 2019, respectively, possibly related to the reduction of the transportation industry. This study reveals the changes of China’s urban NO2 pollution in the post-epidemic era and indicates that COVID-19 had a profound impact on human social activities and industrial production.

Opposite impact of emission reduction during the COVID-19 lockdown period on the surface concentrations of PM2.5 and O3 in Wuhan, China

To prevent the spread of the COVID-19 epidemic, the Chinese megacity Wuhan has taken emergent lockdown measures starting on January 23, 2020. This provided a natural experiment to investigate the response of air quality to such emission reductions. Here, we decoupled the influence of meteorological and non-meteorological factors on main air pollutants using generalized additive models (GAMs), driven by data from the China National Environmental Monitoring Center (CNEMC) network. During the lockdown period (Jan. 23 - Apr. 8, 2020), PM_2.5, PM₁₀, NO₂, SO₂, and CO concentrations decreased significantly by 45 %, 49 %, 56 %, 39 %, and 18 % compared with the corresponding period in 2015-2019, with contributions by S(meteos) of 15 %, 17 %, 13 %, 10 %, and 6 %. This indicates an emission reduction of NO_x at least 43 %. However, O₃ increased by 43 % with a contribution by S(meteos) of 6 %. In spite of the reduced volatile organic compound (VOC) emissions by 30 % during the strict lockdown period (Jan. 23 - Feb. 14, 2020), which likely reduced the production of O₃, O₃ concentrations increased due to a weakening of the titration effect of NO. Our results suggest that conventional emission reduction (NO_x reduction only) measures may not be sufficient to reduce (or even lead to an increase of) surface O₃ concentrations, even if reaching the limit, and VOC-specific measures should also be taken.

Characteristics of boundary layer ozone and its effect on surface ozone concentration in Shenzhen, China: A case study

In late September 2019, the longest and most extensive ozone (O₃) pollution process occurred at Pearl River Delta. Base on the observational data, surface-level O₃, vertical distribution characteristics boundary layer O₃ as well as its effect on surface-level O₃ are thoroughly analyzed. The O₃ lidar results showed similar vertical O₃ profiles both in pollution episodes and clean periods, from which a high O₃ concentration layer between 300 and 500 m and a sub-high O₃ concentration layer between 1300 and 1700 m (near the top of the mixing layer) can be found. Besides, the downward O₃ transport paths from the high/sub-high O₃ concentration layers could be observed along with the boundary layer evolution: At nighttime, large amounts of O₃ were effectively stored into the residual layer (RL). Due to the upward development of Mixing layer (ML) in early morning, atmospheric vertical mixing carried the O₃ inside the RL down to the surface, which led to a rapid increase in the surface-level O₃. The sub-high O₃ layer began the downward mixing at noon, and became well-mixed after the boundary layer was fully developed in the afternoon, by which the near surface O₃ pollution deteriorated again. Further analysis of the heavy O₃ pollution episodes show that, the high O₃ concentration inside the RL contributed 54% ± 6% of the surface-level O₃ at 9:00 LT and the average contribution of O₃ in the sub-high concentration layer to the surface-level O₃ at 14:00 LT was 26% ± 9%. Based on the quantitative analysis of the observational data, this paper focus to reveal the importance of the contribution of O₃ inside the RL and near the top of the ML to the surface O₃.

Effects of Anthropogenic and Biogenic Volatile Organic Compounds on Los Angeles Air Quality

Assessing the role of volatile organic compounds (VOCs) in production of ozone and secondary organic aerosol (SOA) is especially important in light of ongoing policy goals. Here, we estimated the ozone formation potential (OFP) and SOA formation potential (SOAP) of anthropogenic and biogenic VOC emissions to evaluate (1) anthropogenic VOCs and associated sectors that dominate OFP and SOAP and (2) the potential impacts of enhanced biogenic VOCs from urban greening programs on air quality in Los Angeles county. In the present-day scenario, ethylene had the largest OFP followed by m & p-xylene, toluene, propylene, and formaldehyde. The top five contributors to SOAP were toluene, mineral spirits, benzene, heptadecane, and hexadecane. Mobile and solvent sources were the dominant VOC sources for both OFP and SOAP. The potential increases in biogenic VOC emissions due to future urban greening had significant effects on urban air quality that offset the benefits of reducing anthropogenic VOC emissions. This study demonstrates that urban greening programs in Los Angeles county, and likely other cities as well, need to account for both anthropogenic and biogenic VOC contributions to secondary pollution, and greening cities should consider using vegetation types with low VOC emissions to avoid further degradation to urban air quality.

Observations by Ground-Based MAX-DOAS of the Vertical Characters of Winter Pollution and the Influencing Factors of HONO Generation in Shanghai, China

Analyzing vertical distribution characters of air pollutants is conducive to study the mechanisms under polluted atmospheric conditions. Nitrous acid (HONO) is a kind of crucial species in photochemical cycles. Exploring the influence and sources of HONO in air pollution at different altitudes offers some insights into the research of tropospheric oxidation chemistry processes. Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements were conducted in Shanghai, China, from December 2017 to March 2018 to investigate vertical distributions and diurnal variations of trace gases (NO2, HONO, HCHO, SO2, and water vapor) and aerosol extinction coefficient in the boundary layer. Aerosol and NO2 showed decreasing profile exponentially, SO2 and HCHO concentrations were observed relatively high values in the middle layer. SO2 was caused by industrial emissions, while HCHO was from secondary sources. As for HONO, below 0.82 km, the heterogeneous reactions of NO2 impacted on forming HONO, while in the upper layers, vertical diffusion might be the dominant source. The contribution of OH production from HONO photolysis at different altitudes was mainly controlled by the concentration of HONO. MAX-DOAS measurements characterize the vertical structure of air pollutants in Shanghai and provide further understanding for HONO formation, which can help deploy advanced measurement platforms of regional air pollution over eastern China.

A high-resolution typical pollution source emission inventory and pollution source changes during the COVID-19 lockdown in a megacity, China

To control the spread of COVID-19, China has imposed national lockdown policies to restrict the movement of its population since the Chinese New Year of January 2020. In this study, we quantitatively analyzed the changes of pollution sources in Shanghai during the COVID-19 lockdown; a high-resolution emission inventory of typical pollution sources including stationary source, mobile source, and oil and gas storage and transportation source was established based on pollution source data from January to February 2020. The results show that the total emissions of sulfur dioxide (SO₂), nitrogen oxides (NO_x), particulate matter (PM), and volatile organic compounds (VOCs) were 9520.2, 37,978.6, 2796.7, and 7236.9 tons, respectively, during the study period. Affected by the COVID-19 lockdown, the mobile source experienced the largest decline. The car mileage and oil sales decreased by about 80% during the COVID-19 lockdown (P3) when compared with those during the pre-Spring Festival (P1). The number of aircraft activity decreased by approximately 50%. The impact of the COVID-19 epidemic on industries such as iron and steel and petrochemicals was less significant, while the greater impact was on coatings, chemicals, rubber, and plastic. The emissions of SO₂, NO_x, PM_2.5, and VOCs decreased by 11%, 39%, 37%, and 47%, respectively, during P3 when compared with those during P1. The results show that the measures to control the spread of the COVID-19 epidemic made a significant contribution to emission reductions. This study may provide a reference for other countries to assess the impact of the COVID-19 epidemic on emissions and help establish regulatory actions to improve air quality.

Characteristics and source attribution of PM2.5 during 2016 G20 Summit in Hangzhou: Efficacy of radical measures to reduce source emissions

A field campaign was conducted to study the PM_2.5 and atmospheric gases and aerosol's components to evaluate the efficacy of radical measures implemented by the Chinese government to improve air quality during the 2016 G20 Summit in Hangzhou China. The lower level of PM_2.5 (32.48 ± 11.03 µg/m³) observed during the control period compared to pre-control and post-control periods showed that PM_2.5 was alleviated by control policies. Based on the mass concentrations of particulate components, the emissions of PM_2.5 from local sources including fossil fuel, coal combustion, industry and construction were effectively reduced, but non-exhaust emission was not reduced as effectively as expected. The accumulation of SNA (SO₄^2-, NO₃^-, NH₄⁺) was observed during the control period, due to the favourable synoptic weather conditions for photochemical reactions and heterogeneous hydrolysis. Because of transboundary transport during the control period, air masses from remote areas contributed significantly to local PM_2.5. Although, secondary organic carbon (OC_sec) exhibited more sensitivity than primary organic carbon (OC_pri) to control measures, and the increased nitrogen oxidation ratio (NOR) implied the regional transport of aged secondary aerosols to the study area. Overall, the results from various approaches revealed that local pollution sources were kept under control, indicating that the implementation of mitigation measures were helpful in improving the air quality of Hangzhou during G20 summit. To reduce ambient levels of PM_2.5 further in Hangzhou, regional control policies may have to be taken so as to reduce the impact of long-range transport of air masses from inland China.

Quantifying Contributions of Local Emissions and Regional Transport to NOX in Beijing Using TROPOMI Constrained WRF-Chem Simulation

Air quality is strongly influenced by both local emissions and regional transport. Atmospheric chemical transport models can distinguish between emissions and regional transport sources in air pollutant concentrations. However, quantifying model inventories is challenging due to emission changes caused by the recent strict control measures taken by the Chinese government. In this study, we use NO2 column observations from the Tropospheric Monitoring Instrument to retrieve top-down nitrogen oxide (NOX) emissions and quantify the contributions of local emissions and regional transport to NOx in Beijing (BJ), from 1 November 2018 to 28 February 2019 (W_2018) and 1 November 2019 to 29 February 2020 (W_2019). In W_2018 and W_2019, the BJ bottom-up NOX emissions from the multi-resolution emission inventory for China in 2017 were overestimated by 11.8% and 40.5%, respectively, and the input of NOX from other cities to BJ was overestimated by 10.9% and 51.6%, respectively. The simulation using our adjusted inventory exhibited a much higher spatial agreement (slope = 1.0, R2 = 0.79) and reduced a mean relative error by 45% compared to those of bottom-up NOX emissions. The top-down inventory indicated that (1) city boundary transport contributes approximately 40% of the NOX concentration in BJ; (2) in W_2019, NOX emissions and transport in BJ decreased by 20.4% and 17.2%, respectively, compared to those of W_2018; (3) in W_2019, NOX influx substantially decreased (−699 g/s) in BJ compared to that of W_2018 despite negative meteorological conditions that should have increased NOx influx by +503 g/s. Overall, the contribution of intercity input to NOx in BJ has declined with decreasing emissions in the surrounding cities due to regional cooperative control measures, and the role of local emissions in BJ NOx levels was more prominent. Our findings indicate that local emissions may play vital roles in regional center city air quality.

Ozone profile retrievals from TROPOMI: Implication for the variation of tropospheric ozone during the outbreak of COVID-19 in China

During the outbreak of the coronavirus disease 2019 (COVID-19) in China in January and February 2020, production and living activities were drastically reduced to impede the spread of the virus, which also caused a strong reduction of the emission of primary pollutants. However, as a major species of secondary air pollutant, tropospheric ozone did not reduce synchronously, but instead rose in some region. Furthermore, higher concentrations of ozone may potentially promote the rates of COVID-19 infections, causing extra risk to human health. Thus, the variation of ozone should be evaluated widely. This paper presents ozone profiles and tropospheric ozone columns from ultraviolet radiances detected by TROPOospheric Monitoring Instrument (TROPOMI) onboard Sentinel 5 Precursor (S5P) satellite based on the principle of optimal estimation method. We compare our TROPOMI retrievals with global ozonesonde observations, Fourier Transform Spectrometry (FTS) observation at Hefei (117.17°E, 31.7°N) and Global Positioning System (GPS) ozonesonde sensor (GPSO₃) ozonesonde profiles at Beijing (116.46°E, 39.80°N). The integrated Tropospheric Ozone Column (TOC) and Stratospheric Ozone Column (SOC) show excellent agreement with validation data. We use the retrieved TOC combining with tropospheric vertical column density (TVCD) of NO₂ and HCHO from TROPOMI to assess the changes of tropospheric ozone during the outbreak of COVID-19 in China. Although NO₂ TVCD decreased by 63%, the retrieved TOC over east China increase by 10% from the 20-day averaged before the lockdown on January 23, 2020 to 20-day averaged after it. Because the production of ozone in winter is controlled by volatile organic compounds (VOCs) indicated by monitored HCHO, which did not present evident change during the lockdown, the production of ozone did not decrease significantly. Besides, the decrease of NO_x emission weakened the titration of ozone, causing an increase of ozone.

Ozone profile retrievals from TROPOMI: Implication for the variation of tropospheric ozone during the outbreak of COVID-19 in China

During the outbreak of the coronavirus disease 2019 (COVID-19) in China in January and February 2020, production and living activities were drastically reduced to impede the spread of the virus, which also caused a strong reduction of the emission of primary pollutants. However, as a major species of secondary air pollutant, tropospheric ozone did not reduce synchronously, but instead rose in some region. Furthermore, higher concentrations of ozone may potentially promote the rates of COVID-19 infections, causing extra risk to human health. Thus, the variation of ozone should be evaluated widely. This paper presents ozone profiles and tropospheric ozone columns from ultraviolet radiances detected by TROPOospheric Monitoring Instrument (TROPOMI) onboard Sentinel 5 Precursor (S5P) satellite based on the principle of optimal estimation method. We compare our TROPOMI retrievals with global ozonesonde observations, Fourier Transform Spectrometry (FTS) observation at Hefei (117.17°E, 31.7°N) and Global Positioning System (GPS) ozonesonde sensor (GPSO₃) ozonesonde profiles at Beijing (116.46°E, 39.80°N). The integrated Tropospheric Ozone Column (TOC) and Stratospheric Ozone Column (SOC) show excellent agreement with validation data. We use the retrieved TOC combining with tropospheric vertical column density (TVCD) of NO₂ and HCHO from TROPOMI to assess the changes of tropospheric ozone during the outbreak of COVID-19 in China. Although NO₂ TVCD decreased by 63%, the retrieved TOC over east China increase by 10% from the 20-day averaged before the lockdown on January 23, 2020 to 20-day averaged after it. Because the production of ozone in winter is controlled by volatile organic compounds (VOCs) indicated by monitored HCHO, which did not present evident change during the lockdown, the production of ozone did not decrease significantly. Besides, the decrease of NO_x emission weakened the titration of ozone, causing an increase of ozone.

Association between exposure to airborne pollutants and COVID-19 in Los Angeles, United States with ensemble-based dynamic emission model

This study aims to find the association between short-term exposure to air pollutants, such as particulate matters and ground-level ozone, and SARS-CoV-2 confirmed cases. Generalized linear models (GLM), a typical choice for ecological modeling, have well-established limitations. These limitations include apriori assumptions, inability to handle multicollinearity, and considering differential effects as the fixed effect. We propose an Ensemble-based Dynamic Emission Model (EDEM) to address these limitations. EDEM is developed at the intersection of network science and ensemble learning, i.e., a specialized approach of machine learning. Generalized Additive Model (GAM), i.e., a variant of GLM, and EDEM are tested in Los Angeles and Ventura counties of California, which is one of the biggest SARS-CoV-2 clusters in the US. GAM depicts that a 1 μg/m³, 1 μg/m³, and 1 ppm increase (lag 0-7) in PM 2.5, PM 10, and O3 is associated with 4.51% (CI: 7.01 to -2.00) decrease, 1.62% (CI: 2.23 to -1.022) decrease, and 4.66% (CI: 0.85 to 8.47) increase in daily SARS-CoV-2 cases, respectively. Subsequent increment in lag resulted in the negative association between pollutants and SARS-CoV-2 cases. EDEM results in an R2 score of 90.96% and 79.16% on training and testing datasets, respectively. EDEM confirmed the negative association between particulates and SARS-CoV-2 cases; whereas, the O3 depicts a positive association; however, the positive association observed through GAM is not statistically significant. In addition, the county-level analysis of pollutant concentration interactions suggests that increased emissions from other counties positively affect SARS-CoV-2 cases in adjoining counties as well. The results reiterate the significance of uniformly adhering to air pollution mitigation strategies, especially related to ground-level ozone.

Investigation of atmospheric ozone during summer and autumn in Guangdong Province with a lidar network

The overall ozone concentration in China has increased significantly in recent years, as has the atmospheric oxidization, and both of these changes are impacting human activities. Measurements based on differential absorption lidar (DIAL) were conducted from June to October 2019 in order to investigate the vertical distribution of ozone in Guangdong Province. The vertical and horizontal distributions of ozone in six different cities were systematically examined during the summer and autumn and analyzed the two different ozone characteristics (local pollution and regional transport). TrajStat was used to analyze the ozone transport directions and potential contributions of in the summer and autumn, and the following results were obtained. In the cities of Guangzhou and Jiangmen, the ozone concentrations climbed significantly higher in autumn than in summer, with the ozone concentration reaching a height of 1000 m in autumn and 600 m in summer. The diurnal variation of ozone in Yangjiang City in summer was not obvious, whereas in other cities, high levels of ozone were concentrated in the afternoon. The average summer ozone concentration at the Guangzhou site was the highest, approximately 92.57 μg/m³, whereas the average at the Dongguan site was the lowest. The average ozone concentration at the Guangzhou site in autumn was also the highest among the six cities, reaching 133.34 μg/m³. In terms of local pollution, the high-concentration ozone mainly occurred near the ground. The maximum ozone concentration was approximately 162.1 μg/m³ at about 350 m, and the ozone was evenly distributed above 1500 m. The external transport of ozone primarily occurred from 500 to 1100 m and above 1100 m. During summer, the southwest airflow trajectory was dominant, whereas northeast airflow predominated in autumn.

Transport and boundary layer interaction contribution to extremely high surface ozone levels in eastern China

Vertical measurements of ozone (O₃) within the 3000-m lower troposphere were obtained using an O₃ lidar to investigate the contribution of the interactions between the transport and boundary layer processes to the surface O₃ levels in urban Shanghai, China during July 23-28, 2017. An extremely severe pollution episode with a maximum hourly O₃ mixing ratio of 160.4 ppb was observed. In addition to enhanced local photochemical production, both downward and advection transport in the lower troposphere may have played important roles in forming the pollution episode. The O₃-rich air masses in the lower free troposphere primarily originated from central China and the northern Yangtze River Delta (YRD) region. The downward transport of O₃ from the lower free troposphere may have an average contribution of up to 49.1% to the daytime (09:00-16:00 local time) surface O₃ in urban Shanghai during the pollution episode (July 23-26, 2017). As for the advection transport, large amounts of O₃ were transported outward from Shanghai in the planetary boundary layer under the influence of southeasterly winds during the field study. In this condition, the boundary-layer O₃ that was transported downward from the free troposphere in Shanghai could be transported back to the northern YRD region and accumulated therein, leading to the occurrence of severe O₃ pollution events over the whole YRD region. Our results indicate that effective regional emission control measures are urgently required to mitigate O₃ pollution in the YRD region.

Effect of emission control measures on ozone concentrations in Hangzhou during G20 meeting in 2016

The effect of emission control measures on ozone (O₃) concentrations in Hangzhou during G20 (The Group of Twenty Finance Ministers and Central Bank Governors) meeting during 24 August to 6 September of 2016 was evaluated using the nested version of a global chemical transport model. During G20, observed concentrations of PM₁₀, PM_2.5, SO₂, NO₂, and CO were all below national air quality standards, whereas those of MDA8 O₃ were above national standard (with an averaged value of 160.2 μg m^-3) but had a decreasing trend. Model sensitivity studies show that, MDA8 O₃ concentrations in Hangzhou during G20 were reduced by 11.3 μg m^-3 (6.8%), 14.8 μg m^-3 (8.9%), and 19.5 μg m^-3 (11.7%) with emission control measures in the core area, Zhejiang province, and the Yangtze River Delta (YRD) region, respectively, indicating that control measures were the most effective when carried out jointly in YRD. Considering the ratios of NO_x to VOCs during G20, Hangzhou and most areas of Zhejiang province were in transitional regime; reductions in either NO_x or VOCs could reduce O₃ concentrations. We also quantified how sensitive O₃ concentrations respond to emission reductions in sectors of industry, power, residential and transportation in the whole of YRD during G20. The removal of emissions in industry and transportation sectors would lead to the largest reductions of 17.6 μg m^-3 (10.5%) and 12.3 μg m^-3 (7.4%) in MDA8 O₃ concentrations in Hangzhou during G20, respectively. This study has important implications for the control of high O₃ levels in eastern China.

First observation of tropospheric nitrogen dioxide from the Environmental Trace Gases Monitoring Instrument onboard the GaoFen-5 satellite

The Environmental Trace Gases Monitoring Instrument (EMI) is the first Chinese satellite-borne UV-Vis spectrometer aiming to measure the distribution of atmospheric trace gases on a global scale. The EMI instrument onboard the GaoFen-5 satellite was launched on 9 May 2018. In this paper, we present the tropospheric nitrogen dioxide (NO2) vertical column density (VCD) retrieval algorithm dedicated to EMI measurement. We report the first successful retrieval of tropospheric NO2 VCD from the EMI instrument. Our retrieval improved the original EMI NO2 prototype algorithm by modifying the settings of the spectral fit and air mass factor calculations to account for the on-orbit instrumental performance changes. The retrieved EMI NO2 VCDs generally show good spatiotemporal agreement with the satellite-borne Ozone Monitoring Instrument and TROPOspheric Monitoring Instrument (correlation coefficient R of ~0.9, bias < 50%). A comparison with ground-based MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) observations also shows good correlation with an R of 0.82. The results indicate that the EMI NO2 retrieval algorithm derives reliable and precise results, and this algorithm can feasibly produce stable operational products that can contribute to global air pollution monitoring.

Summertime ozone pollution in the Yangtze River Delta of eastern China during 2013-2017: Synoptic impacts and source apportionment

Severe ozone (O₃) pollution in China has magnified global concerns over the past years. Exploring the synoptic impacts and quantifying the source contributions are important for mitigating O₃ pollution. This study focuses on the summertime O₃ pollution over the Yangtze River Delta (YRD) in eastern China. We identify six predominant synoptic weather patterns (SWPs) over the YRD during 2013-2017 using the self-organising map (SOM) approach. We conduct O₃ source attribution based on ozone source apportionment technology (OSAT) in a regional transport model. Surface O₃ pollution is found to be sensitive to the predominant SWPs, including four O₃-polluted types (northeasterly, northerly and southwesterly and anticyclone) and two O₃-clean types (cyclone and the Meiyu front). The integrated influences of local chemistry and regional transport are important in O₃ pollution under different SWPs. Daily maximum 8-h average (MDA8) O₃ holds strong negative and positive correlations with relative humidity and sunshine duration, respectively. Among the six SWPs, the concentration and exceedance of MDA8 O₃ reach their maxima under the northerly type on a regional average. Higher O₃ levels, particularly under the northerly and northeasterly types, are primarily related to regional transport on various spatial scales. Local production accounts for the largest proportion of O₃ sources under the anticyclone type. Under the southwesterly type, favourable weather conditions superimposed on regional transport lead to severe O₃ pollution in coastal cities. The impact of super-regional transport is most pronounced along the eastern coast under the cyclone type. Source category analysis shows that transportation and industrial emissions play a prime role in surface O₃ formation. This study illustrates the imperative implementation of joint emission control over eastern China to reduce O₃ pollution.

A high temporal-spatial emission inventory and updated emission factors for coal-fired power plants in Shanghai, China

With the implementation of the ultra-low emission policy in China, emission factors (EFs) of power plant pollutants are constantly changing. Emission inventories developed using the recommended EFs contain high levels of uncertainty and it is difficult to achieve a high temporal resolution. Detailed sulfur dioxide (SO₂), nitrogen oxides (NOx), and particulate matter (PM) emission data based on a continuous emission monitoring system (CEMS) were obtained from 33 units at 13 power plants in Shanghai in 2017. The data were used to develop an hourly unit-based emission inventory and to devise updated EFs for coal-fired power plants. Emissions of SO₂, NOx, and PM typically met the ultra-low emission limit, with total emissions of SO₂, NOx, and PM of 2895.0, 5348.3, and 503.8 tons, respectively. Emission proportions of SO₂ and NOx for 300-600, 600-1000, and above 1000 MW units were similar, while the emission proportion of PM decreased with an increase in unit capacity. Emissions of SO₂, NOx, and PM displayed similar monthly variations, peaking in winter and summer. Diurnal hourly variations of SO₂, NOx, and PM emissions displayed a bimodal trend, with higher emissions at night on weekends than on weekdays. EFs based on CEMS (EF_C) of SO₂, NOx, and PM were 0.10, 0.36, and 0.04 g kg^-1 of coal, respectively, which were one or two orders of magnitude lower than the widely-used EFs and 4-30 times lower than EFs based on the mass balance approach. After replacing the recommended fixed decontamination efficiencies with individually fitted values, the calculated EFs were consistent with the corresponding EF_C and discrepancies were further reduced. The new inventory and updated EFs will enable a better understanding of the temporal variations of power plant emissions and reduce the uncertainty caused by the overestimation of EFs after the implementation of ultra-low emissions technology.

Spatial Distribution of Secondary Organic Aerosol Formation Potential in China Derived from Speciated Anthropogenic Volatile Organic Compound Emissions

Fine particulate matter (PM_2.5), largely composed of secondary organic aerosol (SOA), is currently one of the most intractable environmental problems in China. As crucial precursors for SOA, understanding the formation propensity of various volatile organic compound (VOC) species and sources is useful for pollution control. In this work, we estimated the SOA formation potential (SOAP) of anthropogenic VOC emissions based on an improved speciated VOC emission inventory and investigated its distribution in China. According to our estimates, toluene had the largest SOAP, followed by n-dodecane, m-/p-xylene, styrene, n-decane, and n-undecane, while passenger cars, chemical fiber manufacturing, asphalt paving, and building coating were the top five SOAP-contributing sources nationwide. The spatial distribution of SOAP in China shows a distinct pattern of high values in the southeast and low values in the northwest. Beijing-Tianjin-Hebei and surroundings, the Yangtze River Delta, Pearl River Delta, and Sichuan-Chongqing District were found to have the highest SOAP, particularly in urban areas. The major SOAP-contributing species and sources differed among these regions, which was attributed to local industrial and energy structures. Our results suggest that to mitigate PM_2.5 pollution in China, more efficient SOAP-based control measures should be implemented instead of current emissions-based policies, and VOC control strategies should be adapted to local conditions.