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Severe airborne particulate matter (PM, including PM 2.5 and PM 10) pollution in India has caused widespread concern. Accurate PM concentrations are fundamental for scientific policymaking and health impact assessment, while surface observations in India are limited due to scarce sites and uneven distribution. In this work, a simple structured, efficient, and robust model based on the Light Gradient-Boosting Machine (LightGBM) was developed to fuse multisource data and estimate long-term (1980–2022) historical daily ground PM concentrations in India (LongPMInd). The LightGBM model shows good accuracy with out-of-sample, out-of-site, and out-of-year cross-validation (CV) test R2 values of 0.77, 0.70, and 0.66, respectively. Small performance gaps between PM 2.5 training and testing (delta RMSE of 1.06, 3.83, and 7.74 µgm-3) indicate low overfitting risks. With great generalization ability, the openly accessible, long-term, and high-quality daily PM 2.5 and PM 10 products were then reconstructed (10 km, 1980–2022). This showed that India has experienced severe PM pollution in the Indo-Gangetic Plain (IGP), especially in winter. PM concentrations have significantly increased (p<0.05) in most regions since 2000 (0.34 µgm-3yr-1). The turning point occurred in 2018 when the Indian government launched the National Clean Air Programme, and PM 2.5 concentrations declined in most regions (-0.78 µgm-3yr-1) during 2018–2022. Severe PM 2.5 pollution caused continuous increased attributable premature mortalities, from 0.73 (95 % confidence interval (CI) [0.65, 0.80]) million in 2000 to 1.22 (95 % CI [1.03, 1.41]) million in 2019, particularly in the IGP, where attributable mortality increased from 0.36 million to 0.60 million. LongPMInd has the potential to support multiple applications of air quality management, public health initiatives, and efforts to address climate change. The daily and monthly PM 2.5 and PM 10 concentrations are publicly accessible at 10.5281/zenodo.10073944 (Wang et al., 2023a). [ABSTRACT FROM AUTHOR]

Aerosol particles play critical roles in climate and human health. However, aerosol composition and evolution, particularly secondary organic aerosol (SOA), and aerosol interactions with clouds in high-altitude background areas in China remain less understood. Here, we conducted real-time measurements of submicron aerosols (PM 1) using aerosol mass spectrometers at a forested mountain site (1128 m a.s.l.) in southeastern China in November 2022. The average (±1σ) PM 1 mass concentration was 4.3±4.8 µ g m -3 , which was ubiquitously lower than that at other mountain sites in China. Organic aerosol (OA) constituted the largest fraction of PM 1 (42.9 %) and was predominantly secondary, as indicated by the high oxygen-to-carbon (O / C) ratio (0.85–0.96) and carbon oxidation state (0.21–0.49). Notably, the remarkably enhanced PM 1 concentrations observed during the daytime on cloudless days were identified to be likely to be produced from cloud evaporation. While more oxidized oxygenated OA was scavenged efficiently during cloud events, cloud evaporation was found to release a significant amount of less oxidized oxygenated OA from air masses transported from polluted regions. The distinct decrease in OA / Δ CO with the increase in O / C during the cloud evaporative period further demonstrates that OA remaining in cloud droplets is generally in a moderate oxidation state. Moreover, organic nitrates were also estimated and showed a higher contribution to the total nitrate during the cloudy period (27 %) than during the evaporative period (3 %). Overall, our results demonstrate the importance of SOA and the influences of cloud processes in regional mountain areas in southeastern China. [ABSTRACT FROM AUTHOR]

Chemical transport models (CTMs) are widely used for air pollution modeling, which suffer from significant biases due to uncertainties in simplified parameterization, meteorological fields, and emission inventories. Accurate diagnosis of simulation biases is critical for the improvement of models, interpretation of results, and management of air quality, especially for the simulation of fine particulate matter (PM 2.5). In this study, an efficient method with high speed and a low computational resource requirement based on the tree-based machine learning (ML) method, the light gradient boosting machine (LightGBM), was designed to diagnose CTM simulation biases. The drivers of the Community Multiscale Air Quality (CMAQ) model biases are compared to observations obtained by simulating PM 2.5 concentrations from the perspectives of meteorology, chemical composition, and emission sources. The source-oriented CMAQ was used to diagnose the influences of different emission sources on PM 2.5 biases. The model can capture the complex relationship between input variables and simulation bias well; meteorology, PM 2.5 components, and source sectors can partially explain the simulation bias. The CMAQ model underestimates PM 2.5 by - 19.25 to - 2.66 µgm-3 in 2019, especially in winter and spring and during high-PM 2.5 events. Secondary organic components showed the largest contribution to the PM 2.5 simulation bias for different regions and seasons (13.8 %–22.6 %) of all components. Relative humidity, cloud cover, and soil surface moisture were the main meteorological factors contributing to PM 2.5 bias in the North China Plain, Pearl River Delta, and northwestern China, respectively. Primary and secondary inorganic components from residential sources showed the two largest contributions to this bias (12.05 % and 12.78 %), implying large uncertainties in this sector. The ML-based methods provide valuable complements to traditional-mechanism-based methods for model improvement, with high efficiency and low reliance on prior information. [ABSTRACT FROM AUTHOR]

Since non-methane hydrocarbons (NMHCs) include numerous species of volatile organic compounds (VOCs), they are the only indicators that can characterize the total amount of VOCs in ambient air. More than 90 % of NMHC instruments in the market use the indirect method for NMHC determination, utilizing a gas chromatograph to determine the concentrations of total hydrocarbons (THCs) and methane in air. However, we found indirect NMHC measurements incorrectly characterized the low NMHC concentrations in the urban air. These measurements were hindered by the uncertain changes in the errors associated with low THC concentrations, humidity and macroscopic substances (oxygen) in the atmosphere. In this study, we conducted intercomparisons between 10 instruments in the market using different operation principles; among these, two used the direct method, and eight used the indirect method. For the indirect method, experiments showed that when the NMHC concentration was 50 ppbC , the errors in the measurement results were 32 % (CH4) and 98 % (THC) when compared to theoretical values. The oxygen content in the sample gas directly affected the response of the THC. The effect of increased oxygen content on the analysis of oxygen-containing substances was more significant than that of the increase in hydrocarbon substances. The response of dry zero was blank, and the response value increased non-linearly with relative humidity (RH). RH had a great impact on low NMHC concentrations of nearly 50 %. For the direct method, although various flow designs were applied for different instruments, the results indicated that they generally showed lower interference and higher accuracy for the ambient NMHC measurements. With the online direct methods, we obtained more reliable data and characteristics for low-concentration NMHCs in downtown Shanghai. The median of hourly data was 163.1 ppbC , and the highest ratio of the maximum and minimum concentrations of NMHCs reached 9.56 in a single day. [ABSTRACT FROM AUTHOR]

In the autumn of 2019, a 5 d long-lasting dust event was observed using a synergy of field measurement techniques in Shanghai. This particular dust event stood out from others due to its unique characteristics, including low wind speed, high relative humidity, elevated levels of gaseous precursors, and contrasting wind patterns at different altitudes. During this event, three distinct dust stages were identified. The first stage was a typical dust invasion characterized by high concentrations of particulate matters but relatively short duration. In contrast, the second stage exhibited an unusual enhancement of ozone, attributed to compound causes of a weak synoptic system, transport from the ocean, and subsidence of high-altitude ozone downdrafted by dust. Consequently, gas-phase oxidation served as the major formation pathway of sulfate and nitrate. In the third stage of dust, a noteworthy phenomenon known as dust backflow occurred. The dust plume originated from the Shandong Peninsula and slowly drifted over the Yellow Sea and the East China Sea before eventually returning to Shanghai. Evidence of this backflow was found through the enrichment of marine vessel emissions (V and Ni) and increased solubility of calcium. Under the influence of humid oceanic breezes, the formation of nitrate was dominated by aqueous processing. Additionally, parts of nitrate and sulfate were directly transported via sea salts, evidenced by their co-variation with Na + and confirmed through thermodynamic modeling. The uptake of NH 3 on particles, influenced by the contributions of alkali metal ions and aerosol pH, regulated the formation potential of secondary aerosol. By developing an upstream–receptor relationship method, the quantities of transported and secondarily formed aerosol species were separated. This study highlights that the transport pathway of dust, coupled with environmental conditions, can significantly modify the aerosol properties, especially at the complex land–sea interface. [ABSTRACT FROM AUTHOR]

Exposure to elemental carbon (EC) and NO x is a public health issue that has been gaining increasing interest, with high exposure levels generally observed in traffic environments, e.g., roadsides. Shanghai, home to approximately 25 million in the Yangtze River Delta (YRD) region in eastern China, has one of the most intensive traffic activity levels in the world. However, our understanding of the trend in vehicular emissions and, in particular, in response to the strict Covid-19 lockdown is limited partly due to the lack of a long-term observation dataset and application of advanced mathematical models. In this study, NO x and EC were continuously monitored at a sampling site near a highway in western Shanghai for 5 years (2016–2020). The long-term dataset was used to train the machine learning model, rebuilding NO x and EC in a business-as-usual (BAU) scenario for 2020. The reduction in NO x and EC attributable to the lockdown was found to be smaller than it appeared because the first week of the lockdown overlapped with the Lunar New Year holiday, whereas, at a later stage of the lockdown, the reduction (50 %–70 %) attributable to the lockdown was more significant, consistent with the satellite monitoring of NO 2 showing reduced traffic on a regional scale. In contrast, the impact of the lockdown on vehicular emissions cannot be represented well by simply comparing the concentration before and during the lockdown for conventional campaigns. This study demonstrates the value of continuous air pollutant monitoring at a roadside on a long-term basis. Combined with the advanced mathematical model, air quality changes due to future emission control and/or event-driven scenarios are expected to be better predicted. [ABSTRACT FROM AUTHOR]

Chemical transport models (CTMs) are widely used for air pollution modeling, which suffer from significant biases due to uncertainties in simplified parameterization, meteorological fields, and emission inventories. Accurate diagnosis of simulation biases is critical for improvement of models, interpretation of results, and efficient air quality management, especially for the simulation of fine particulate matter (PM2.5). In this study, an efficient method based on machine learning (ML) was designed to diagnose the drivers of the Community Multiscale Air Quality (CMAQ) model biases in simulating PM2.5 concentrations from three perspectives of meteorology, chemical composition, and emission sources. The source-oriented CMAQ were used to diagnose influences of different emission sources on PM2.5 biases. The ML models showed good fitting ability with small performance gap between training and validation. The CMAQ model underestimates PM2.5 by -19.25 to -2.66 μg/m3 in 2019, especially in winter and spring and high PM2.5 events. Secondary organic components showed the largest contribution to PM2.5 simulation bias for different regions and seasons (13.8–22.6 %) among components. Relative humidity, cloud cover, and soil surface moisture were the main meteorological factors contributing to PM2.5 bias in the North China Plain, Pearl River Delta, and northwestern, respectively. Both primary and secondary inorganic components from residential sources showed the largest contribution (12.05 % and 12.78 %), implying large uncertainties in this sector. The ML-based methods provide valuable complements to traditional mechanism-based methods for model improvement, with high efficiency and low reliance on prior information. [ABSTRACT FROM AUTHOR]

Since non-methane hydrocarbons (NMHCs) include numerous species of volatile organic compounds (VOCs), they are the only indicators that can characterize the total amount of VOCs in ambient air. More than 90 % of NMHC instruments in the market use the indirect method for NMHC determination, utilizing a gas chromatograph to determine the concentrations of total hydrocarbons (THCs) and methane in air. However, we found indirect NMHC measurements incorrectly characterized the low NMHC concentrations in the urban air. These measurements were hindered by the uncertain changes in the errors associated with low THC concentrations, humidity, and macroscopic substances (oxygen) in the atmosphere. In this study, we conducted intercomparisons between 10 instruments in the market using different operation principles; among these, two used the direct method and eight used the indirect method. For the indirect method, experiments showed that when the NMHC concentration was 50 ppbC, the errors in the measurement results were 32 % (CH4) and 98 % (THC) when compared to theoretical values. The oxygen content in the sample gas directly affected the response of the THC. The effect of increased oxygen content on the analysis of oxygen-containing substances was more significant than that of the increase in hydrocarbon substances. The response of dry zero was blank, and the response value increased non-linearly with relative humidity (RH). RH had a great impact on low NMHC concentrations of nearly 50 %. For the direct method, although various flow designs were applied for different instruments, the results indicated that they generally showed lower interference and higher accuracy for the ambient NMHC measurements. With the online direct methods, we obtained more reliable data and characteristics for low-concentration NMHCs in downtown Shanghai. The median of hourly data was 163.1 ppbC, and the highest ratio of the maximum and minimum concentrations of NMHCs reached 9.56 in a single day. [ABSTRACT FROM AUTHOR]

Exposure to element carbon (EC) and NOx is a public health issue that has been gaining increasing interest, with high exposure levels generally observed in traffic environments e.g., roadsides. Shanghai, home to approximately 25 million in the Yangtze River Delta (YRD) region in east China, has one of the most intensive traffic activities in the world. However, our understanding of the trend in vehicular emissions and, in particular, in response to the strict Covid-19 lockdown is limited partly due to a lack of long-term observation dataset and application of advanced mathematical models. In this study, NOx and EC were continuously monitored at a near highway sampling site in west Shanghai for 5 years (2016–2020). The long-term dataset was used to train the machine learning model, rebuilding the NOx and EC in a business-as-usual (BAU) scenario in 2020. The reduction in NOx and EC attributable to lockdown was found to be smaller than it appeared because the first week of lockdown overlapped with the lunar new year holiday, whereas, at a later stage of lockdown, the reduction (50–70 %) attributable to the lockdown was more significant, confirmed by satellite monitoring of NO2. In contrast, the impact of the lockdown on vehicular emissions cannot be well represented by simply comparing the concentration before and during the lockdown for conventional campaigns. This study demonstrates the value of continuous air pollutant monitoring at a roadside on a long-term basis. Combined with the advanced mathematical model, air quality changes upon future emission control and/or event-driven scenarios are expected to be better predicted. [ABSTRACT FROM AUTHOR]

A five-days long-lasting dust event was observed with a synergy of field measurements techniques in Shanghai in the autumn of 2019. Different from most dust events, this dust was an unusual one characterized of low wind speed, high relative humidity, high concentrations of gaseous precursors, and contrasting wind vectors between low and high altitudes. Three dust stages were identified and the first stage was a normal dust invasion with high particulate concentrations and short duration. In contrast, unusual enhancement of ozone was observed in the second stage, due to compound causes of weak synoptic system, transport from the ocean, and subsidence of high-altitude O3 down drafted by dust. As a result, sulfate and nitrate moderately correlated with O3 while had almost no correlation with aerosol liquid water content, indicating the dominant role of gas phase oxidations. During the third stage of dust, a special phenomenon of dust backflow was observed that the dust plume drifted from the Shandong Peninsula and travelled slowly over the Yellow Sea and the East China Sea, finally returning to Shanghai. The dust backflow was evidenced by the enrichment of marine vessel emissions (V and Ni) and increased solubility of calcium. Under the humid oceanic breezes, the formation of nitrate was dominated by aqueous processing, while the strong correlation between SO42- and Na+ suggested that a considerable part of sulfate was aged and directly transported. Based on the thermodynamic modeling, sea salts probably involved more in the secondary aerosol formation than the dust heterogeneous reactions. By developing an upstream-receptor relationship method, the amounts of transported and secondarily formed aerosol species were separated. This study highlights that the transport pathway of dust and environmental conditions could significantly modify the aerosol properties, especially at the complex land-sea interface. [ABSTRACT FROM AUTHOR]

Formaldehyde (HCHO) is an important trace gas that affects the abundance of HO 2 radicals and ozone, leads to complex photochemical processes, and yields a variety of secondary atmospheric pollutants. In a 2021 summer campaign at the Dianshan Lake (DSL) Air Quality Monitoring Supersite in a suburban area of Shanghai, China, we measured atmospheric formaldehyde (HCHO) by a commercial Aero-Laser formaldehyde monitor, methane, and a range of non-methane hydrocarbons (NMHCs). Ambient HCHO showed a significant diurnal cycle with an average concentration of 2.2 ± 1.8 ppbv (parts per billion by volume). During the time period with the most intensive photochemistry (10:00–16:00 LT), secondary production of HCHO was estimated to account for approximately 69.6 % according to a multi-linear regression method based on ambient measurements of HCHO, acetylene (C 2 H 2), and ozone (O 3). The average secondary HCHO production rate was estimated to be 0.73 ppbv h -1 during the whole campaign (including daytime and nighttime), with a dominant contribution from reactions between alkenes and OH radicals (66.3 %), followed by OH-radical-initiated reactions with alkanes and aromatics (together 19.0 %), OH-radical-initiated reactions with oxygenated volatile organic compounds (OVOCs; 8.7 %), and ozonolysis of alkenes (6.0 %). An overall HCHO loss, including HCHO photolysis, reactions with OH radicals, and dry deposition, was estimated to be 0.49 ppbv h -1. Calculated net HCHO production rates were in relatively good agreement with the observed rates of HCHO concentration change throughout the sunny days, indicating that HCHO was approximately produced by oxidation of the 24 hydrocarbons we took into account at the DSL site during the campaign, whereas calculated net HCHO production rates prevailed over the observed rates of HCHO concentration change in the morning/midday hours on the cloudy and rainy days, indicating a missing loss term, most likely due to HCHO wet deposition. Our results suggest the important role of secondary pollution in the suburbs of Shanghai, where alkenes are likely key precursors for HCHO. [ABSTRACT FROM AUTHOR]

To investigate the physical and chemical processes of fine particle matter (PM) at the mid-upper planetary boundary layer (PBL), we conducted 1-year continuous measurements of fine PM, the chemical composition of non-refractory submicron aerosol (NR-PM 1) , and some gas species (including sulfur dioxide, nitrogen oxides, and ozone) at an opening observatory (∼ 600 m) at the top of Shanghai Tower (SHT), which is China's first and the world's second highest building located in the typical financial central business district of Shanghai, China. This is the first report on the characteristics of fine particles based on continuous and sophisticated online measurements at the mid-upper level of the urban PBL. The observed PM 2.5 and PM 1 mass concentrations at SHT were 25.5 ± 17.7 and 17.3 ± 11.7 µ g m -3 , respectively. Organics, nitrate (NO 3) , and sulfate (SO 4) occupied the first three leading contributions to NR-PM 1 at SHT, accounting for 35.8 %, 28.6 %, and 20.8 %, respectively. The lower PM 2.5 concentration was observed at SHT by 16.4 % compared with that near the surface during the observation period. It was attributed to the decreased nighttime PM 2.5 concentrations (29.4 % lower than the surface) at SHT in all seasons due to the complete isolations from both emissions and gas precursors near the surface. However, daytime PM 2.5 concentrations at SHT were 12.4 %–35.1 % higher than those near the surface from June to October, resulted from unexpected larger PM 2.5 levels during early to middle afternoon at SHT than at the surface. We suppose the significant chemical production of secondary aerosols existed in the mid-upper PBL, because strong solar irradiance, adequate gas precursors (e.g., NOx), and lower temperature were observed at SHT, favorable for both photochemical production and gas-to-particle partitioning. This was further demonstrated by the significant increasing rate of oxygenated organic aerosols and NO 3 observed at SHT during 08:00–12:00 in spring (7.4 % h -1 and 12.9 % h -1) , fall (9.3 % h -1 and 9.1 % h -1) , and summer (13.0 % h -1 and 11.4 % h -1) , which cannot be fully explained by vertical mixing. It was noted that extremely high NO 3 was observed at SHT both in daytime and nighttime in winter, accounting for 37.2 % in NR-PM 1 , suggesting the efficient pathway from heterogeneous and gas oxidation formation. Therefore, we highlight the priority of NOx reduction in Shanghai for the further improvement of air quality. This study reported greater daytime PM 2.5 concentrations at the height of 600 m in the urban PBL compared with surface measurement, providing insight into their potential effects on local air quality, radiation forcing, and cloud and/or fog formations. We propose that the efficient production of secondary aerosol in the mid-upper PBL should be cognized and explored more comprehensively by synergetic observations in future. [ABSTRACT FROM AUTHOR]

The wide spread of the coronavirus (COVID-19) has significantly impacted the global human activities. Compared to numerous studies on conventional air pollutants, atmospheric mercury that has matched sources from both anthropogenic and natural emissions is rarely investigated. At a regional site in eastern China, an intensive measurement was performed, showing obvious decreases in gaseous elemental mercury (GEM) during the COVID-19 lockdown, while it was not as significant as most of the other measured air pollutants. Before the lockdown, when anthropogenic emissions dominated, GEM showed no correlation with temperature and negative correlations with wind speed and the height of the boundary layer. In contrast, GEM showed significant correlation with temperature, while the relationship between GEM and the wind speed/boundary layer disappeared during the lockdown, suggesting the enhanced natural emissions of mercury. By applying a machine learning model and the SHAP (SHapley Additive exPlanations) approach, it was found that the mercury pollution episodes before the lockdown were driven by anthropogenic sources, while they were mainly driven by natural sources during and after the lockdown. Source apportionment results showed that the absolute contribution of natural surface emissions to GEM unexpectedly increased (44 %) during the lockdown. Throughout the whole study period, a significant negative correlation was observed between the absolute contribution of natural and anthropogenic sources to GEM. We conclude that the natural release of mercury could be stimulated to compensate for the significantly reduced anthropogenic GEM via the surface–air exchange in the balance of mercury. [ABSTRACT FROM AUTHOR]

To investigate impact factors and source area of secondary organic aerosols in the Yangtze River Delta (YRD) region, a world-class urban agglomeration in China, long-term measurements of organic carbon (OC) and elementary carbon (EC) in particulate matter of less than 2.5 µ m (PM 2.5) with hourly time resolution were conducted at a regional site in Shanghai from 2016 to 2020. Based on the 5-year measurements, the interannual, monthly, seasonal, and diurnal variations in OC and EC, as well as OC subtypes, i.e. secondary OC (SOC) and primary OC (POC), apportioned by the novel statistical model of the minimum R2 method, and the formation pathways of SOC, are presented. By examining the relationship between SOC and temperature, as well as relative humidity (RH), we show that SOC formation is greatly enhanced at high temperatures (> 30 ∘ C), whereas it correlates inversely with RH. In particular, we show that the photochemical formation of SOC is the major formation pathway even in winter, when solar radiation was supposedly less intense than in summer, which is different from that in the north China plain, where aqueous phase chemistry is found to be an important SOC formation pathway. Moreover, increased SOC concentrations are also found to be associated with high wind speed (> 5 m s -1) in winter, which is increased by 29.1 % (2.62 µ g m -3) when compared with that during lower winds, suggesting regional sources of SOC in winter. By analysing the potential source regions using the concentration-weighted trajectory (CWT), the geographic regions of SOC are found to be mainly associated with transport from outside Shanghai (SOC > 3.5 µ g m -3) including central and southern Anhui, Zhejiang, and Fujian. The results from this study provide critical information about the long-term trend of carbonaceous aerosol, in particular, SOC, in one of the largest megacities in the world, and are helpful for developing pollution control measures from a long-term planning perspective. [ABSTRACT FROM AUTHOR]

The widespread of coronavirus (COVID-19) has significantly impacted the global human activities. Compared to numerous studies on conventional air pollutants, atmospheric mercury that has matched sources from both anthropogenic and natural emissions is rarely investigated. At a regional site in Eastern China, an intensive measurement was performed, showing obvious decreases of gaseous elemental mercury (GEM) during the COVID-19 lockdown, while not as significant as the other air pollutants. Before the lockdown when anthropogenic emissions dominated, GEM showed no correlation with temperature and negative correlations with wind speed and the height of boundary layer. In contrast, GEM showed significant correlation with temperature while the relationship between GEM and wind speed/boundary layer disappeared during the lockdown, suggesting the enhanced natural emissions of mercury. By applying a machine learning model and the Shapley Additive ExPlanation Approach, it was found that the mercury pollution episodes before the lockdown were driven by anthropogenic sources, while they were mainly driven by natural sources during and after the lockdown. Source apportionment results showed that the absolute contribution of natural surface emissions to GEM unexpectedly increased (44%) during the lockdown. Throughout the whole study period, a significant negative correlation was observed between the absolute contribution of natural and anthropogenic sources to GEM. We conclude that natural release of mercury could be stimulated to compensate the significantly reduced anthropogenic GEM via the surface - air exchange balance of mercury. [ABSTRACT FROM AUTHOR]

To investigate the physical and chemical processes of fine particle matters at mid-upper planetary boundary layer (PBL), we conducted one-year continuous measurements of fine particle matters (PM), chemical composition of non-refractory submicron aerosol (NR-PM1) and some gas species (including sulfur dioxide, nitrogen oxides and ozone) at an opening observatory (~600 m) at the top of Shanghai Tower (SHT), which is the Chinese 1st and World's 2nd highest building located in the typical financial central business district of Shanghai, China. This is the first report for the characteristics of fine particles based on continuous and sophisticated online measurements at the mid-upper level of urban PBL. The observed PM2.5 and PM1 mass concentrations at SHT were 25.5±17.7 and 17.3±11.7 μg m-3 respectively. Organics, nitrate (NO3) and sulfate (SO4) occupied the first three leading contributions to NR-PM1 at SHT, accounting for 35.8 %, 28.6 % and 20.8 % respectively. The lower PM2.5 concentration was observed at SHT by 16.4 % compared with that near surface during the observation period. It was attributed to the decreased nighttime PM2.5 concentrations (29.4 % lower than surface) at SHT in all seasons due to the complete isolations from both emissions and gas precursors near surface. However, daytime PM2.5 concentrations at SHT were 12.4–35.1 % higher than those near surface from June to October, resulted from unexpected larger PM2.5 levels during early to middle afternoon at SHT than surface. We suppose the significant chemical production of secondary aerosols existed in mid-upper PBL because strong solar irradiance, adequate gas precursors (e.g., NOx) and lower temperature were observed at SHT favorable for both photochemical production and gas-to-particle partitioning. This was further demonstrated by the significant increasing rate of oxygenated organic aerosols and NO3 observed at SHT during 8:00–12:00 in spring (7.4 % h-1 and 12.9 % h-1), autumn (9.3 % h-1 and 9.1 % h-1) and summer (13.0 % h-1 and 11.4 % h-1), which cannot be fully explained by vertical mixing. It was noting that extremely high NO3 was observed at SHT both in daytime and nighttime in winter, accounting for 37.2 % in NR-PM1, suggesting the efficient pathway from heterogeneous and gas oxidated formation. Therefore, we highlight the priority of NOx reduction in Shanghai for the further improvement of air quality. This study reported greater daytime PM2.5 concentrations at the height of 600 m in urban PBL compared with surface measurement, providing insight into their potential effects on local air quality, radiation forcing, and cloud/fog formations. We propose that the efficient production of secondary aerosol in mid-upper PBL should be cognized and explored more comprehensively by synergetic observations in future. [ABSTRACT FROM AUTHOR]

Nitrate aerosol plays an increasingly important role in wintertime haze pollution in China. Despite intensive research on wintertime nitrate chemistry in recent years, quantitative constraints on the formation mechanisms of nitrate aerosol in the Yangtze River Delta (YRD), one of the most developed and densely populated regions in eastern China, remain inadequate. In this study, we identify the major nitrate formation pathways and their key controlling factors during the winter haze pollution period in the eastern YRD using 2-year (2018–2019) field observations and detailed observation-constrained model simulations. We find that the high atmospheric oxidation capacity, coupled with high aerosol liquid water content (ALWC), made both the heterogeneous hydrolysis of dinitrogen pentoxide (N 2 O 5) and the gas-phase OH oxidation of nitrogen dioxide (NO 2) important pathways for wintertime nitrate formation in this region, with contribution percentages of 69 % and 29 % in urban areas and 63 % and 35 % in suburban areas during the haze pollution episodes, respectively. We further find that the gas-to-particle partitioning of nitric acid (HNO 3) was very efficient so that the rate-determining step in the overall formation process of nitrate aerosol was the oxidation of NO x to HNO 3 through both heterogeneous and gas-phase processes. The atmospheric oxidation capacity (i.e., the availability of O 3 and OH radicals) was the key factor controlling the production rate of HNO 3 from both processes. During the COVID-19 lockdown (January–February 2020), the enhanced atmospheric oxidation capacity greatly promoted the oxidation of NO x to nitrate and hence weakened the response of nitrate aerosol to the emission reductions in urban areas. Our study sheds light on the detailed formation mechanisms of wintertime nitrate aerosol in the eastern YRD and highlights the demand for the synergetic regulation of atmospheric oxidation capacity and NO x emissions to mitigate wintertime nitrate and haze pollution in eastern China. [ABSTRACT FROM AUTHOR]

In recent years, ozone pollution has become one of the most severe environmental problems in China. Evidence from observations have showed increased frequency of high O 3 levels in suburban areas of the Yangtze River Delta (YRD) region. To better understand the formation mechanism of local O 3 pollution and investigate the potential role of isoprene chemistry in the budgets of ROx (OH+HO2+RO2) radicals, synchronous observations of volatile organic compounds (VOCs), formaldehyde (HCHO), and meteorological parameters were conducted at a suburban site of the YRD region in 2018. Five episodes with elevated O 3 concentrations under stagnant meteorological conditions were identified; an observation-based model (OBM) with the Master Chemical Mechanism was applied to analyze the photochemical processes during these high O 3 episodes. The high levels of O 3 , nitrogen oxides (NO x), and VOCs facilitated strong production and recycling of RO x radicals with the photolysis of oxygenated VOCs (OVOCs) being the primary source. Our results suggest that local biogenic isoprene is important in suburban photochemical processes. Removing isoprene could drastically slow down the efficiency of RO x recycling and reduce the concentrations of RO x. In addition, the absence of isoprene chemistry could further lead to a decrease in the daily average concentrations of O 3 and HCHO by 34 % and 36 %, respectively. Therefore, this study emphasizes the importance of isoprene chemistry in the suburban atmosphere, particularly with the participation of anthropogenic NO x. Moreover, our results provide insights into the radical chemistry that essentially drives the formation of secondary pollutants (e.g., O 3 and HCHO) in suburban areas of the YRD region. [ABSTRACT FROM AUTHOR]

Identification of various emission sources and quantification of their contributions comprise an essential step in formulating scientifically sound pollution control strategies. Most previous studies have been based on traditional offline filter analysis of aerosol major components (usually inorganic ions, elemental carbon – EC, organic carbon – OC, and elements). In this study, source apportionment of PM 2.5 using a positive matrix factorization (PMF) model was conducted for urban Shanghai in the Yangtze River Delta region, China, utilizing a large suite of molecular and elemental tracers, together with water-soluble inorganic ions, OC, and EC from measurements conducted at two sites from 9 November to 3 December 2018. The PMF analysis with inclusion of molecular makers (i.e., MM-PMF) identified 11 pollution sources, including 3 secondary-source factors (i.e., secondary sulfate; secondary nitrate; and secondary organic aerosol, SOA, factors) and 8 primary sources (i.e., vehicle exhaust, industrial emission and tire wear, industrial emission II, residual oil combustion, dust, coal combustion, biomass burning, and cooking). The secondary sources contributed 62.5 % of the campaign-average PM 2.5 mass, with the secondary nitrate factor being the leading contributor. Cooking was a minor contributor (2.8 %) to PM 2.5 mass while a significant contributor (11.4 %) to the OC mass. Traditional PMF analysis relying on major components alone (PMF t) was unable to resolve three organics-dominated sources (i.e., biomass burning, cooking, and SOA source factors). Utilizing organic tracers, the MM-PMF analysis determined that these three sources combined accounted for 24.4 % of the total PM 2.5 mass. In PMF t , this significant portion of PM mass was apportioned to other sources and thereby was notably biasing the source apportionment outcome. Backward trajectory and episodic analysis were performed on the MM-PMF-resolved source factors to examine the variations in source origins and composition. It was shown that under all episodes, secondary nitrate and the SOA factor were two major source contributors to the PM 2.5 pollution. Our work has demonstrated that comprehensive hourly data of molecular markers and other source tracers, coupled with MM-PMF, enables examination of detailed pollution source characteristics, especially organics-dominated sources, at a timescale suitable for monitoring episodic evolution and with finer source breakdown. [ABSTRACT FROM AUTHOR]

Ammonia in the atmosphere is essential for the formation of fine particles that impact air quality and climate. Despite extensive prior research to disentangle the relationship between ammonia and haze pollution, the role of ammonia in haze formation in high ammonia-emitting regions is still not well understood. Aiming to better understand secondary inorganic aerosol (sulfate, nitrate, ammonium – SNA) formation mechanisms under high-ammonia conditions, 1-year hourly measurement of water-soluble inorganic species (gas and particle) was conducted at a rural supersite in Shanghai. Exceedingly high levels of agricultural ammonia, constantly around 30 µ g m -3 , were observed. We find that gas-particle partitioning of ammonia (ε (NH4+)), as opposed to ammonia concentrations, plays a critical role in SNA formation during the haze period. From an assessment of the effects of various parameters, including temperature (T), aerosol water content (AWC), aerosol pH, and activity coefficient, it seems that AWC plays predominant regulating roles for ε (NH4+). We propose a self-amplifying feedback mechanism associated with ε (NH4+) for the formation of SNA, which is consistent with diurnal variations in ε (NH4+) , AWC, and SNA. Our results imply that a reduction in ammonia emissions alone may not reduce SNA effectively, at least at rural agricultural sites in China. [ABSTRACT FROM AUTHOR]

The fine particles (PM 2.5) in China have decreased significantly in recent years as a result of the implementation of Chinese Clean Air Action Plan since 2013, while the O3 pollution is getting worse, especially in megacities such as Beijing and Shanghai. Better understanding of the elevated O3 pollution in Chinese megacities and its response to emission change is important for developing an effective emission control strategy in the future. In this study, we analyze the significant increasing trend of daily maximum O3 concentration from 2006 to 2015 in the megacity Shanghai with the variability of 0.8–1.3 ppbv yr -1. It could likely be attributed to the notable reduction in NOx concentrations with the decreasing rate of 1.86–2.15 ppbv yr -1 accompanied by the small change in VOCs during the same period by excluding the weak trends of meteorological impacts on local dispersion (wind speed), regional transport (wind direction), and O3 photolysis (solar radiation). It is further illustrated by using a state-of-the-art regional chemical and dynamical model (WRF-Chem) to explore the O3 variation response to the reduction in NOx emissions in Shanghai. The control experiment conducted for September of 2009 shows excellent performance for O3 and NOx simulations, including both the spatial distribution pattern and the day-by-day variation through comparison with six in situ measurements from the MIRAGE-Shanghai field campaign. Sensitivity experiments with 30 % reduction in NOx emissions from 2009 to 2015 in Shanghai estimated by Shanghai Environmental Monitoring Center shows that the calculated O3 concentrations exhibit obvious enhancement by 4–7 ppbv in urban zones with increasing variability of 0.96–1.06 ppbv yr -1 , which is consistent with the observed O3 trend as a result of the strong VOC-limited condition for O3 production. The large reduction in NOx combined with less change in VOCs in the past 10 years promotes the O3 production in Shanghai to move towards an NOx -limited regime. Further analysis of the WRF-Chem experiments and O3 isopleth diagram suggests that the O3 production downtown is still under a VOC-limited regime after 2015 despite the remarkable NOx reduction, while it moves to the transition regime between NOx -limited and VOC-limited in sub-urban zones. Supposing the insignificant VOC variation persists, the O3 concentration downtown would keep increasing until 2020 with the further 20 % reduction in NOx emission after 2015 estimated by Shanghai Clean Air Action Plan. The O3 production in Shanghai will switch from a VOC-limited to an NOx -limited regime after 2020 except for downtown area, which is likely close to the transition regime. As a result the O3 concentration will decrease by 2–3 ppbv in sub-urban zones and by more than 4 ppbv in rural areas as a response to a 20 % reduction in NOx emission after 2020, whereas it is not sensitive to both NOx and VOC changes downtown. This result reveals that the control strategy of O3 pollution is a very complex process and needs to be carefully studied. [ABSTRACT FROM AUTHOR]

Growing shipping activities in port areas have generated negative impacts on climate, air quality and human health. To better evaluate the environmental impact of ship emissions, an experimental characterization of air pollution from ships was conducted in Shanghai Port in the summer of 2016. The ambient concentrations of gaseous NO, NO2 , SO2 and O3 in addition to fine particulate matter concentrations (PM 2.5), particle size distributions and the chemical composition of individual particles from ship emission were continuously monitored for 3 months. Ship emission plumes were visible at the port site in terms of clear peaks in the gaseous species and particulate matter concentrations. The SO2 and vanadium particle numbers were found to correlate best with ship emissions in Shanghai Port. Single-particle data showed that ship emission particles at the port site mainly concentrated in a smaller size range (<0.4 µ m), where their number contributions were more important than their mass contributions to ambient particulate matter. The composition of ship emission particles at the port site suggested that they were mostly freshly emitted particles: their mass spectra were dominated by peaks of sulfate, elemental carbon (EC), and trace metals such as V, Ni, Fe and Ca, in addition to displaying very low nitrate signals. The gaseous NOx composition in some cases of plumes showed evidence of atmospheric transformation by ambient O3 , which subsequently resulted in O3 depletion in the area. Quantitative estimations in this study showed that ship emissions contributed 36.4 % to SO2 , 0.7 % to NO, 5.1 % to NO2 , -0.9 % to O3 , 5.9 % to PM 2.5 and 49.5 % to vanadium particles in the port region if land-based emissions were included, and 57.2 % to SO2 , 71.9 % to NO, 30.4 % to NO2 , -16.6 % to O3 , 27.6 % to PM 2.5 and 77.0 % to vanadium particles if land-based emissions were excluded. [ABSTRACT FROM AUTHOR]

The Yangtze River Delta (YRD) and the megacity of Shanghai are host to one of the busiest port clusters in the world; the region also suffers from high levels of air pollution. The goal of this study was to estimate the contributions of shipping to regional emissions, air quality, and population exposure and to characterize the importance of the geographic spatiality of shipping lanes and different types of ship-related sources for the baseline year of 2015, which was prior to the implementation of China's Domestic Emission Control Areas (DECAs) in 2016. The WRF-CMAQ model, which combines the Weather Research and Forecasting model (WRF) and the Community Multi-scale Air Quality (CMAQ) model, was used to simulate the influence of coastal and inland-water shipping, port emissions and ship-related cargo transport on air quality and on the population-weighted concentrations (which is a measure of human exposure). Our results showed that the impact of shipping on air quality in the YRD was primarily attributable to shipping emissions within 12 NM (nautical miles) of shore, but emissions coming from the coastal area between 24 and 96 NM still contributed substantially to ship-related PM 2.5 concentrations in the YRD. The overall contribution of ships to the PM 2.5 concentration in the YRD could reach 4.62 µ g m -3 in summer when monsoon winds transport shipping emissions onshore. In Shanghai city, inland-water going ships were major contributors (40 %–80 %) to the shipping impact on urban air quality. Given the proximity of inland-water ships to the urban populations of Shanghai, the emissions of inland-water ships contributed more to population-weighted concentrations. These research results provide scientific evidence to inform policies for controlling future shipping emissions; in particular, in the YRD region, expanding the boundary of 12 NM from shore in China's current DECA policy to around 100 NM from shore would include most of shipping emissions affecting air pollutant exposure, and stricter fuel standards could be considered for the ships on inland rivers and other waterways close to residential regions. [ABSTRACT FROM AUTHOR]

Speciated atmospheric mercury including gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), and particulate-bound mercury (PBM) were measured continuously for a 1-year period at a suburban site, representing a regional transport intersection zone, in east China. Annual mean concentrations of GEM, PBM, and GOM reached 2.77 ng m -3 , 60.8 pg m -3 , and 82.1 pg m -3 , respectively. GEM concentrations were elevated in all the seasons except autumn. High mercury concentrations were related to winds from the south, southwest, and north of the measurement site. Combining analysis results from using various source apportionment methods, it was found that GEM concentration was higher when quasi-local sources dominated over long-range transport. Six source factors belonging to the anthropogenic sources of GEM were identified, including the common sectors previously identified (industrial and biomass burning, coal combustion, iron and steel production, cement production, and incineration), as well as an additional factor of shipping emissions (accounting for 19.5 % of the total), which was found to be important in east China where marine vessel shipping activities are intense. Emissions of GEM from natural surfaces were also found to be as important as those from anthropogenic sources for GEM observed at this site. Concurrences of high GOM concentrations with elevated O3 and temperature, along with the lagged variations in GEM and GOM during daytime demonstrated that the very high GOM concentrations were partially ascribed to intense in situ oxidation of GEM. Strong gas–particle partitioning was also identified when PM 2.5 was above a threshold value, in which case GOM decreased with increasing PM 2.5. [ABSTRACT FROM AUTHOR]

Atmospheric oxidation capacity is the basis for converting freshly emitted substances into secondary products and is dominated by reactions involving hydroxyl radicals (OH) during daytime. In this study, we present in situ measurements of ROx radical (hydroxy OH, hydroperoxy HO2 , and organic peroxy RO2) precursors and products; the measurements are carried out in four Chinese megacities (Beijing, Shanghai, Guangzhou, and Chongqing) during photochemically polluted seasons. The atmospheric oxidation capacity is evaluated using an observation-based model and radical chemistry precursor measurements as input. The radical budget analysis illustrates the importance of HONO and HCHO photolysis, which account for ∼50 % of the total primary radical sources. The radical propagation is efficient due to abundant NO in urban environments. Hence, the production rate of secondary pollutants, that is, ozone (and fine-particle precursors (H2SO4 , HNO3 , and extremely low volatility organic compounds, ELVOCs) is rapid, resulting in secondary air pollution. The ozone budget demonstrates its high production in urban areas; also, its rapid transport to downwind areas results in rapid increase in local ozone concentrations. The O3 – NOx –VOC (volatile organic compound) sensitivity tests show that ozone production is VOC-limited and that alkenes and aromatics should be mitigated first for ozone pollution control in the four studied megacities. In contrast, NOx emission control (that is, a decrease in NOx) leads to more severe ozone pollution. With respect to fine-particle pollution, the role of the HNO3 – NO3 partitioning system is investigated using a thermal dynamic model (ISORROPIA 2). Under high relative humidity (RH) and ammonia-rich conditions, nitric acid converts into nitrates. This study highlights the efficient radical chemistry that maintains the atmospheric oxidation capacity in Chinese megacities and results in secondary pollution characterized by ozone and fine particles. [ABSTRACT FROM AUTHOR]

Aerosol-associated non-polar organic compounds (NPOCs), including 15 polycyclic aromatic hydrocarbons (PAHs), 30 n-alkanes, 2 iso-alkanes, 5 hopanes and 5 steranes, were identified and quantified in PM2.5 samples using the thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) method. The samples were mainly collected in autumn and winter in a typical city of eastern China. The total concentrations of NPOCs were 31.7-388.7 ng m-3, and n-alkanes were the most abundant species (67.2%). The heavy-molecular-weight PAHs (four- and five-ring) contributed 67.9% of the total PAHs, and the middle-chain-length n-alkanes (C25-C34) were the most abundant (72.3%) in n-alkanes. PAHs and n-alkanes were mainly distributed in the 0.56-1.00 µm fraction, while ∑ (hopanes+steranes) were associated with the 0.32-1.00 µm fraction, suggesting condensation of combustion products was their important origin. The ratio-ratio plots indicated that NPOCs in the local area were affected by photochemical degradation. To reduce the uncertainty caused by only particle NPOC data for source apportionment, the particle and predicted gaseous-phase NPOCs, incorporated with other PM2.5 compound were used as input data for the positive matrix factorization (PMF) model. Eight factors were extracted for both cases: secondary aerosol formation, vehicle exhaust, industrial emission, coal combustion, biomass burning, ship emission, and dust and light NPOCs. These findings highlight the emissions from different aerosol-associated NPOC origins, which caused different size-specific distributions, photodegradation and gas-particle partitioning, which further affect PM2.5 source apportionment. Considering these effects on organic tracers will help us accurately identify the potential sources of aerosols and then asses the contributions from each source. [ABSTRACT FROM AUTHOR]

Near-surface and vertical in situ measurements of atmospheric particles were conducted in Shanghai during 19-23 March 2010 to explore the transport and chemical evolution of dust particles in a super dust storm. An air quality model with optimized physical dust emission scheme and newly implemented dust chemistry was utilized to study the impact of dust chemistry on regional air quality. Two discontinuous dust periods were observed with one traveling over northern China (DS1) and the other passing over the coastal regions of eastern China (DS2). Stronger mixing extents between dust and anthropogenic emissions were found in DS2, reflected by the higher SO2 /PM10 and NO2 /PM10 ratios as well as typical pollution elemental species such as As, Cd, Pb, and Zn. As a result, the concentrations of SO2-4 and NO-3 and the ratio of Ca2+ = Ca were more elevated in DS2 than in DS1 but opposite for the [NH+4] / [SO2-4 + NO-3] ratio, suggesting the heterogeneous reactions between calcites and acid gases were significantly promoted in DS2 due to the higher level of relative humidity and gaseous pollution precursors. Lidar observation showed a columnar effect on the vertical structure of particle optical properties in DS1 that dust dominantly accounted for ***80-90% of the total particle extinction from near the ground to ***700 m. In contrast, the dust plumes in DS2 were restrained within lower altitudes while the extinction from spherical particles exhibited a maximum at a high altitude of ***800 m. The model simulation reproduced relatively consistent results with observations that strong impacts of dust heterogeneous reactions on secondary aerosol formation occurred in areas where the anthropogenic emissions were intensive. Compared to the sulfate simulation, the nitrate formation on dust is suggested to be improved in the future modeling efforts. [ABSTRACT FROM AUTHOR]

The vertical distribution of SO2, NO, NO2, O3, CO, PM2.5, black carbon, particle sizedistribution, species of PM1 within 0-1000m as well as meteorological parameters weremeasured simultaneously on tethered balloon at Wangdu County, Baoding City, NorthChina Plain, as part of the winter field campaign which hold during December2018.During December 18 to 21, the ground monitoring data demonstrated sharp increase of NO,CO and PM2.5 concentration during the nighttime and decrease in the daytime,while the diurnal variation of ozone concentration was the opposite. The increasedconcentrations of pollutants at night mostly due to the much lower boundary layerduring nights, which could be as low as 100 meters. Except for the worse verticaldiffusion at night, the low wind speed also contributed to the increase of pollutantsconcentrations.The organic component accounted for up to 60% of PM2.5 at night, which was the maincontribution to the increased PM2.5. The significant increase of NO, CO and organic may dueto the emission from home heating at night.The vertical detection demonstrated very low boundary layer and inversion layer during theobservation period. The vertical distribution of pollutant in the boundary layer and upper theboundary layer are quite different at night. The concentrations of gaseous pollutants (CO,SO2, NO and NO2) and PM2.5 were higher in the nocturnal boundary layer, and theproportion of organic component, black carbon and chloride were significantly higher thanthat upper the boundary layer. During the daytime, with the development of the boundarylayer, the favorable horizontal and vertical diffusion condition lead to the decreased pollutantsconcentrations. In addition, pollutants with high concentrations were found at high altitudes,where the proportion of secondary components such as nitrates, sulfates and ammoniumwere higher than that of the ground. It may attributed to air mass from regionaltransport. [ABSTRACT FROM AUTHOR]