Human activity's impact on urban vegetation in China during the COVID-19 lockdown: An atypical anthropogenic disturbance

The COVID-19 lockdown led to reduced industrial and transportation emissions in Chinese cities, improving air quality and affecting large-scale vegetation. This study examines changes in net primary productivity (NPP) across 283 prefecture-level cities in China (PCC) during the lockdown, focusing on aerosol optical depth (AOD), nighttime light (NTL), temperature, and precipitation. Results from spring 2020 show that 53.5% of cities experienced increased NPP, with greater gains in cities with high industrial and traffic activity due to reduced AOD. Structural equation modeling revealed that urban characteristics, particularly industrial levels, influenced NPP primarily through changes in AOD, with human activity shifts playing a larger role than climate factors. In cities with substantial NPP changes, human activity effects were especially pronounced. These findings highlight the complex interactions among urban characteristics, environmental changes, and vegetation responses, offering insights for ecological management and urban planning in the face of future disruptions.

Vertical distribution of aerosols and association with atmospheric boundary layer structures during regional aerosol transport over central China

Atmospheric boundary layer (ABL) structure was a crucial factor in altering the vertical aerosol distribution and modulating the impact of regional aerosol transport on the atmospheric environment in the receptor region. The long-term characteristics of ABL structures for different vertical aerosol distributions and the distinct influencing mechanisms between daytime and nighttime aerosol transport interacting with the diurnal ABL transition have rarely been studied in the receptor regions. Based on 9-year (2013-2021) satellite-retrieved profiles of aerosol extinction coefficients and meteorological sounding data, we targeted Wuhan, an urban city with noteworthy transport contribution in central China, to reveal the general wintertime transport height of ∼500 m and the corresponding unstable ABL structure during regional transport. By comparing typical daytime and nighttime aerosol transport with high-resolution Lidar observations, the aerosol transport near the ABL top coupled with intense mechanical mixing provided sufficient meteorological conditions for heavy aerosol pollution formation in the receptor regions, which was more favorable during nighttime transport followed by the adequate ABL development after sunrise. These findings enhance our comprehension of the ABL impact on air pollution in the receptor regions, which have implications for the precise prevention and control of the regional atmospheric environment.

Characterization of winter PM2.5 source contributions and impacts of meteorological conditions and anthropogenic emission changes in the Sichuan Basin, 2002-2020

In this study, the Weather Research and Forecasting (WRF) model and Community Multiscale Air Quality-Integrated Source Apportionment Method (CMAQ-ISAM) were utilized, which were integrated with the Multiresolution Emission Inventory for China (MEIC) emission inventory, to simulate winter PM2.5 concentrations, regional transport, and changes in emission source contributions in the Sichuan basin (SCB) from 2002 to 2020, considering variations in meteorological conditions and anthropogenic emissions. The results indicated a gradual decrease in the basin's winter average PM2.5 concentration from 300 μg/m3 to 120 μg/m3, with the most significant decrease occurring after 2014, reflecting the actual impact of China's air pollution control measures. Spatially, the main pollution area shifted from Chongqing to Chengdu and the western basin. The sources of PM2.5 at the eastern and western margins of the basin have remained stable and have been dominated by local emissions for many years, while the sources of PM2.5 in the central part of the basin have evolved from a multiregional co-influenced source during the early period to a high proportion of local emissions; except for boundary condition sources, residential sources were the main PM2.5 sources in the basin (approximately 29.70 %), followed by industrial sources (approximately 14.11 %). Industrial sources exhibited higher contributions in Chengdu and Chongqing and gradually stabilized with residential sources over the years, while residential sources dominated in the eastern and western parts of the basin and exhibited a declining trend. Meteorological conditions exacerbated pollution in the whole basin from 2008 to 2014, especially in the west (21-40 μg/m3). The eastern basin and Chongqing exhibited more years with alleviated meteorological pollution, including a 40+ μg/m3 decrease in Chongqing from 2002 to 2005. Reduced anthropogenic emissions alleviated annual pollution levels, with a greater reduction (> -20 μg/m3) after 2011 due to pollution control measures.

Quantifying the effect of administrative approval reforms on SO2 emissions: a quasi-experiment in Chinese cities

The effects of the Administrative Examination and Approval System Reform on economic growth and entry of businesses have drawn much attention. However, few scholars pay attention to the impacts of this policy on SO₂ emissions. Keeping in view the existing research gap, a spatial difference-in-difference (SDID) model is employed to assess the effects of the Administrative Examination and Approval System Reform on SO₂ emissions in 297 Chinese cities during the period 1995-2020 from the perspective of spatial spillover effects. The results show that the establishment of Administrative Examination and Approval Center (AEAC) has significantly positive effects on the local SO₂ emissions. The significant indirect (spatial spillover) effects are confirmed. That is, the establishment of AEAC of a given city has a significant positive impact on the SO₂ emissions of neighboring cities. The findings are confirmed by several robustness tests. Our study findings have significant implications for the cross-border coordination of environmental policies that aim to improve the quality of the environment across borders.

Source analysis of the tropospheric NO2 based on MAX-DOAS measurements in northeastern China

Ground-based Multi-Axis Differential Optical Absorption Spectroscopy (Max-DOAS) measurements of nitrogen dioxide (NO₂) were continuously obtained from January to November 2019 in northeastern China (NEC). Seasonal variations in the mean NO₂ vertical column densities (VCDs) were apparent, with a maximum of 2.9 × 10¹⁶ molecules cm^-2 in the winter due to enhanced NO₂ emissions from coal-fired winter heating, a longer photochemical lifetime and atmospheric transport. Daily maximum and minimum NO₂ VCDs were observed, independent of the season, at around 11:00 and 13:00 local time, respectively, and the most obvious increases and decreases occurred in the winter and autumn, respectively. The mean diurnal NO₂ VCDs at 11:00 increased to at 08:00 by 1.6, 5.8, and 6.7 × 10¹⁵ molecules cm^-2 in the summer, autumn and winter, respectively, due to increased NO₂ emissions, and then decreased by 2.8, 4.2, and 5.1 × 10¹⁵ molecules cm^-2 at 13:00 in the spring, summer, and autumn, respectively. This was due to strong solar radiation and increased planetary boundary layer height. There was no obvious weekend effect, and the NO₂ VCDs only decreased by about 10% on the weekends. We evaluated the contributions of emissions and transport in the different seasons to the NO₂ VCDs using a generalized additive model, where the contributions of local emissions to the total in the spring, summer, autumn, and winter were 89 ± 12%, 92 ± 11%, 86 ± 12%, and 72 ± 16%, respectively. The contribution of regional transport reached 26% in the winter, and this high contribution value was mainly correlated with the northeast wind, which was due to the transport channel of air pollutants along the Changbai Mountains in NEC. The NO₂/SO₂ ratio was used to identify NO₂ from industrial sources and vehicle exhaust. The contribution of industrial NO₂ VCD sources was >66.3 ± 16% in Shenyang due to the large amount of coal combustion from heavy industrial activity, which emitted large amounts of NO₂. Our results suggest that air quality management in Shenyang should consider reductions in local NO₂ emissions from industrial sources along with regional cooperative control.

Estimating Full-Coverage PM2.5 Concentrations Based on Himawari-8 and NAQPMS Data over Sichuan-Chongqing

Fine particulate matter (PM2.5) has attracted extensive attention due to its harmful effects on humans and the environment. The sparse ground-based air monitoring stations limit their application for scientific research, while aerosol optical depth (AOD) by remote sensing satellite technology retrieval can reflect air quality on a large scale and thus compensate for the shortcomings of ground-based measurements. In this study, the elaborate vertical-humidity method was used to estimate PM2.5 with the spatial resolution 1 km and the temporal resolution 1 hour. For vertical correction, the scale height of aerosols (Ha) was introduced based on the relationship between the visibility data and extinction coefficient of meteorological observations to correct the AOD of the Advance Himawari Imager (AHI) onboard the Himawari-8 satellite. The hygroscopic growth factor (f(RH)) was fitted site-by-site and month by month (1–12 months). Meanwhile, the spatial distribution of the fitted coefficients can be obtained by interpolation assuming that the aerosol properties vary smoothly on a regional scale. The inverse distance weighted (IDW) method was performed to construct the hygroscopic correction factor grid for humidity correction so as to estimate the PM2.5 concentrations in Sichuan and Chongqing from 09:00 to 16:00 in 2017–2018. The results indicate that the correlation between “dry” extinction coefficient and PM2.5 is slightly improved compared to the correlation between AOD and PM2.5, with r coefficient values increasing from 0.12–0.45 to 0.32–0.69. The r of hour-by-hour verification is between 0.69 and 0.85, and the accuracy of the afternoon is higher than that of the morning. Due to the missing rate of AOD in the southwest is very high, this study utilized inverse variance weighting (IVW) gap-filling method combine satellite estimation PM2.5 and the nested air-quality prediction modeling system (NAQPMS) simulation data to obtain the full-coverage hourly PM2.5 concentration and analyze a pollution process in the fall and winter.

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.

Persistent pollution episodes, transport pathways, and potential sources of air pollution during the heating season of 2016-2017 in Lanzhou, China

As one of the most important industrial cities in Northwest China, Lanzhou currently suffers from serious air pollution. This study analyzed the formation mechanism and potential source areas of persistent air pollution in Lanzhou during the heating period from November 1, 2016 to March 31, 2017 based on the air pollutant concentrations and relevant meteorological data. Our findings indicate that particulate pollution was extremely severe during the study period. The daily PM_2.5 and PM₁₀ concentrations had significantly negative correlations with daily temperature, wind speed, maximum daily boundary layer height, while the daily PM_2.5 and PM₁₀ concentrations showed significantly positive correlations with daily relative humidity. Five persistent pollution episodes were identified and classified as either stagnant accumulation or explosive growth types according to the mechanism of pollution formation and evolution. The PM_2.5 and PM₁₀ concentrations and PM_2.5/PM₁₀ ratio followed a growing "saw-tooth cycle" pattern during the stagnant accumulation type event. Dust storms caused abrupt peaks in PM₁₀ and a sharp decrease in the PM_2.5/PM₁₀ ratio in explosive growth type events. The potential sources of PM₁₀ were mainly distributed in the Kumtag Desert in Xinjiang Uygur Autonomous Region, the Qaidam Basin and Hehuang Valley in Qinghai Province, and the western and eastern Hexi Corridor in Gansu Province. The contributions to PM₁₀ were more than 120 μg/m³. The important potential sources of PM_2.5 were located in Hehuang Valley in Qinghai and Linxia Hui Autonomous Prefecture in Gansu; the concentrations of PM_2.5 were more than 60 μg/m³.

Changes in the Distribution Pattern of PM2.5 Pollution over Central China

The extent of PM2.5 pollution has reduced in traditional polluted regions such as the North China Plain (NCP), Yangtze River Delta (YRD), Sichuan Basin (SB), and Pearl River Delta (PRD) over China in recent years. Despite this, the Twain-Hu Basin (THB), which covers the lower flatlands in Hubei and Hunan provinces in central China, was found to be a high PM2.5 pollution region, with annual mean PM2.5 concentrations of 41–63 μg·m−3, which is larger than the values in YRD, SB, and PRD during 2014–2019, and high aerosol optical depth values (>0.8) averaged over 2000–2019 from the MODIS products. Heavy pollution events (HPEs) are frequently observed in the THB, with HPE-averaged concentrations of PM2.5 reaching up to 183–191 μg·m−3, which exceeds their counterparts in YRD, SB, and PRD for 2014–2019, highlighting the THB as a center of heavy PM2.5 pollution in central China. During 2014–2019, approximately 65.2% of the total regional HPEs over the THB were triggered by the regional transport of PM2.5 over Central and Eastern China (CEC). This occurred in view of the co-existing HPEs in the NCP and the THB, with a lag of almost two days in the THB-PM2.5 peak, which is governed by the strong northerlies of the East Asian monsoon (EAM) over CEC. Such PM2.5 transport from upstream source regions in CEC contributes 60.3% of the surface PM2.5 pollution over the THB receptor region. Hence, a key PM2.5 receptor of the THB in regional pollutant transport alters the distribution patterns of PM2.5 pollution over China, which is attributable to the climate change of EAMs. This study indicates a complex relationship between sources and receptors of atmospheric aerosols for air quality applications.

Variations in Nocturnal Residual Layer Height and Its Effects on Surface PM2.5 over Wuhan, China

Large amounts of aerosols remain in the residual layer (RL) after sunset, which may be the source of the next day’s pollutants. However, the characteristics of the nocturnal residual layer height (RLH) and its effect on urban environment pollution are unknown. In this study, the characteristics of the RLH and its effect on fine particles with diameters <2.5 μm (PM2.5) were investigated using lidar data from January 2017 to December 2019. The results show that the RLH is highest in summer (1.55 ± 0.55 km), followed by spring (1.40 ± 0.58 km) and autumn (1.26 ± 0.47 km), and is lowest in winter (1.11 ± 0.44 km). The effect of surface meteorological factors on the RLH were also studied. The correlation coefficients (R) between the RLH and the temperature, relative humidity, wind speed, and pressure were 0.38, −0.18, 0.15, and −0.36, respectively. The results indicate that the surface meteorological parameters exhibit a slight correlation with the RLH, but the high relative humidity was accompanied by a low RLH and high PM2.5 concentrations. Finally, the influence of the RLH on PM2.5 was discussed under different aerosol-loading periods. The aerosol optical depth (AOD) was employed to represent the total amount of pollutants. The results show that the RLH has an effect on PM2.5 when the AOD is small but has almost no effect on PM2.5 when the AOD is high. In addition, the R between the nighttime mean RLH and the following daytime PM2.5 at low AOD is −0.49, suggesting that the RLH may affect the following daytime surface PM2.5. The results of this study have a guiding significance for understanding the interaction between aerosols and the boundary layer.

Spatial-temporal characteristics of urban air pollution in 337 Chinese cities and their influencing factors

Urban air pollution, especially in the form of haze events, has become a serious threat to socio-economic development and public health in most developing countries. It is of great importance to assess the frequency of urban air pollution occurrence and its influencing factors. The objective of our study is to develop consistent methodologies for constructing an index system and for assessing the influencing factors of the urban air pollution occurrence based on the Driver-Pressure-State-Impact-Response (DPSIR) framework by incorporating spatial analysis, geographical detector, and geographically weighted regression models. The 27 influencing factors were selected for assessing their influences on the urban air pollution occurrence in 337 Chinese cities. The results indicate that the spatial pattern of the urban air pollution in China was mostly consistent with the Chinese population-based Hu Line. Urban air pollution frequently occurred in North China, Central China, Northeast China, and East China, and displayed strong seasonality. The influencing factors of urban air pollution were complex and diverse, varying from season to season. Influencing factor analysis also shows that the explanatory power between any two influencing factors was greater than that of a single influencing factor of the urban air pollution. Furthermore, most influencing factors had both positive and negative effects and local effects on urban air pollution. Finally, we put forward five suggestions on reducing urban air pollution occurrence, which can provide the basis and reference for the government to make policies on urban air pollution control in China.

Associations between winter atmospheric teleconnections in drought and haze pollution over Southwest China

In the early 21st century, Southwest China (SWC) frequently experienced extreme droughts and severe haze pollution events. Although the meteorological causes of these extreme droughts have been widely investigated, previous studies have yet to understand the causes of haze pollution events over SWC. Moreover, the associations between winter atmospheric teleconnections during drought and haze pollution event across SWC has received negligible attention and therefore warrants investigation. This study examines the associations between the atmospheric teleconnections with respect to winter droughts and winter haze pollution over SWC. Our main conclusions are as follows. (1) Winter precipitation and winter haze days (WHD) over SWC had three major fluctuations from 1959 to 2016. (2) The atmospheric circulation pattern over the Eurasian (EU) continent associated with WHD over SWC resembled that of winter droughts over SWC, where both can be characterized by an EU teleconnection pattern. The Arctic Oscillation (AO) mainly induced the atmospheric circulation pattern over the EU continent that is associated with WHD over SWC. (3) The sea surface temperature (SST) and low circulation anomalies in the Pacific and north Atlantic associated with WHD were similar to those associated with winter droughts over SWC. La Niña events and negative phases of the North Atlantic Oscillation (NAO) may induce winter drought and increase the WHD over SWC. (4) Compared with winter drought over SWC, the variation in the WHD was more complex and the factors affecting WHD were more diverse, and winter drought and its related atmospheric circulations were important factors that induced haze pollution over SWC. Overall, this study not only fills a gap in the literature with respect to the associations between the atmospheric teleconnections of winter drought and winter haze pollution over SWC, but also provides an important scientific basis for the development of potential predictions of local monthly haze pollution, which improves the forecast accuracy of local short-term haze pollution and enriches the theoretical understanding of the meteorological causes of local haze pollution.

Satellite-based ground PM2.5 estimation using a gradient boosting decision tree

Fine particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5) is one of the major air pollutants risks to human health worldwide. Satellite-based aerosol optical depth (AOD) products are an effective metric for acquiring PM_2.5 information, featuring broad coverage and high resolution, which compensate for the sparse and uneven distribution of existing monitoring stations. In this study, a gradient boosting decision tree (GBDT) model for estimating ground PM_2.5 concentration directly from AOD products across China in 2017, integrating human activities and various natural variables was proposed. The GBDT model performed well in estimating temporal variability and spatial contrasts in daily PM_2.5 concentrations, with relatively high fitted model (10-fold cross-validation) coefficients of determination of 0.98 (0.81), low root mean square errors of 3.82 (11.57) μg/m³, and mean absolute error of 1.44 (7.45) μg/m³. Seasonal examinations revealed that summer had the cleanest air with the highest estimation accuracies, whereas winter had the most polluted air with the lowest estimation accuracies. The model successfully captured the PM_2.5 distribution pattern across China in 2017, showing high levels in southwest Xinjiang, the North China Plain, and the Sichuan Basin, especially in winter. Compared with other models, the GBDT model showed the highest performance in the estimation of PM_2.5 with a 3-km resolution. This algorithm can be adopted to improve the accuracy of PM_2.5 estimation with higher spatial resolution, especially in summer. In general, this study provided a potential method of improving the accuracy of satellite-based ground PM_2.5 estimation.

Importance of regional PM2.5 transport and precipitation washout in heavy air pollution in the Twain-Hu Basin over Central China: Observational analysis and WRF-Chem simulation

With observational analysis and WRF-Chem simulation on a heavy air pollution event in January 2019 over the Twain-Hu Basin (THB) in Central China, this study characterized the regional transport of PM_2.5 emitted from the North China Plain (NCP) to the THB region in Central China and quantitatively assessed the influence of the regional PM_2.5 transport and precipitation washout on PM_2.5 change in the wintertime heavy air pollution over the THB. It was found that the THB's heavy air pollution event was exacerbated by the strong northeasterly winds driving a quasi 2-day time lag of regional PM_2.5 transport from the NCP to the THB. The multi-scale atmospheric circulations of cold air invasion influenced by East Asian winter monsoon and the terrain block of THB altered the structures of regional PM_2.5 transport in deteriorating air quality to the THB. It was assessed for the THB region that the enhancing contribution of regional PM_2.5 transport to the high air pollution level reached up to 70.5% in the heavy air pollution, and the precipitation washout could contribute the 55.3% PM_2.5 removal to dissipating the PM_2.5 pollution over the THB with frequent precipitation and wet environment, distinguishing from the dominance of wind-cleaning air pollution in the other regions in China.

Importance of meteorology in air pollution events during the city lockdown for COVID-19 in Hubei Province, Central China

Compared with the 21-year climatological mean over the same period during 2000-2020, the aerosol optical depth (AOD) and Angstrom exponent (AE) during the COVID-19 lockdown (January 24-February 29, 2020) decreased and increased, respectively, in most regions of Central-Eastern China (CEC). The AOD (AE) values decreased (increased) by 39.2% (29.4%) and 31.0% (45.3%) in Hubei and Wuhan, respectively, because of the rigorous restrictions. These inverse changes reflected the reduction of total aerosols in the air and the contribution of the increase in fine-mode particles during the lockdown. The surface PM_2.5 had a distinct spatial distribution over CEC during the lockdown, with high concentrations in North China and East China. In particular, relatively high PM_2.5 concentrations were notable in the lower flatlands of Hubei Province in Central China, where six PM_2.5 pollution events were identified during the lockdown. Using the observation data and model simulations, we found that 50% of the pollution episodes were associated with the long-range transport of air pollutants from upstream CEC source regions, which then converged in the downstream Hubei receptor region. However, local pollution was dominant for the remaining episodes because of stagnant meteorological conditions. The long-range transport of air pollutants substantially contributed to PM_2.5 pollution in Hubei, reflecting the exceptional importance of meteorology in regional air quality in China.

Improvement in hourly PM2.5 estimations for the Beijing-Tianjin-Hebei region by introducing an aerosol modeling product from MASINGAR

This study improves traditional PM_2.5 estimation models by combining an hourly aerosol optical depth from the Advanced Himawari Imager onboard Himawari-8 with a newly introduced predictor to estimate hourly PM_2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) region from November 1, 2018 to October 31, 2019. The new predictor is an hourly PM_2.5 forecasting product from the Model of Aerosol Species IN the Global AtmospheRe (MASINGAR). Comparative experiments were conducted by utilizing three extensively used regression models, namely, multiple linear regression (MLR), geographically weighted regression (GWR), and linear mixed effects (LME). A ten-fold cross validation (CV) demonstrated that the MASINGAR product significantly improved the performances of these models. The introduced product increased the model's determination coefficients (from 0.316 to 0.379 for MLR, from 0.393 to 0.445 for GWR, and from 0.718 to 0.765 for LME), decreased their root mean square errors (from 38.2 μg/m³ to 36.4 μg/m³ for MLR, from 36.0 μg/m³ to 34.4 μg/m³ for GWR, and from 24.5 μg/m³ to 22.4 μg/m³ for LME) and mean absolute errors (from 25.2 μg/m³ to 23.3 μg/m³ for MLR, from 23.5 μg/m³ to 21.8 μg/m³ for GWR, and from 15.2 μg/m³ to 13.7 μg/m³ for LME). Then, a well-trained LME model was utilized to estimate the spatial distributions of hourly PM_2.5 concentrations. Highly polluted localities were clustered in the central and southern areas of the BTH region, and the least polluted area was in northwestern Hebei. Seasonal PM_2.5 levels averaged from the hourly estimations exhibited the highest concentrations (55.4 ± 56.8 μg/m³) in the winter and lowest concentrations (25.1 ± 18.2 μg/m³) in the summer. MAIN FINDING: Introducing the PM_2.5 products from MASINGAR can significantly improve the performance of traditional models for surface PM_2.5 estimations by 7-20%.

Adoption and Implementation of Sustainable Development Goals (SDGs) in China—Agenda 2030

The present research is conducted on the Chinese corporate sector and raises the basic questions associated with the adoption and implementation of corporate disclosure practices such as SDGs. The sample for this research consisted of 100 Chinese companies, which are listed in the Shanghai Stock Exchange from 2016 to 2018. For this purpose, content analysis is developed. More specifically, a quantitative approach is applied to quantify and identify certain contents or words in the given text. Our results show that Chinese companies seem to be more focused on certain aspects of the UN SDGs at the cost of others, but the overall situation is, at best, not encouraging. The focus of attention of Chinese companies seems to be infrastructure development, industrial innovation, and economic growth, along with the provision of a dignified and respectable working environment, affordable and clean energy, and peace, justice, and strong institutions. The results can be used as guidelines by Chinese companies to determine the actual presence or absence of SDGs implementation inside the process of value creation as an integral part of their practices about corporate disclosure. The main contribution of this research relates to the analysis of the adoption and implementation efforts to report SDGs and the contribution of such reporting towards the fulfillment of the UN Agenda 2030. This can be of interest to researchers working on the given topic. It is of utmost importance for government policymakers and corporate decision-makers, who want to support companies that are contributing towards the achievement and adaptation of SDGs as part of their overall objectives.

Significant Contribution of Primary Sources to Water-Soluble Organic Carbon During Spring in Beijing, China

Despite the significant role water-soluble organic carbon (WSOC) plays in climate and human health, sources and formation mechanisms of atmospheric WSOC are still unclear; especially in some heavily polluted areas. In this study, near real-time WSOC measurement was conducted in Beijing for the first time with a particle-into-liquid-sampler coupled to a total organic carbon analyzer during the springtime, together with collocated online measurements of other chemical components in fine particulate matter with a 1 h time resolution, including elemental carbon (EC), organic carbon (OC), multiple metals, and water-soluble ions. Good correlations of WSOC with primary OC, as well as carbon monoxide, indicated that major sources of WSOC were primary instead of secondary during the study period. The positive matrix factorization model-based source apportionment results quantified that 68 ± 19% of WSOC could be attributed to primary sources, with predominant contributions by biomass burning during the study period. This finding was further confirmed by the estimate with the modified EC-tracer method, suggesting significant contribution of primary sources to WSOC. However, the relative contribution of secondary source to WSOC increased during haze episodes. The WSOC/OC ratio exhibited similar diurnal distributions with O3 and correlated well with secondary WSOC, suggesting that the WSOC/OC ratio might act as an indicator of secondary formation when WSOC was dominated by primary sources. This study provided evidence that primary sources could be major sources of WSOC in some polluted megacities, such as Beijing. From this study, it can be seen that WSOC cannot be simply used as a surrogate of secondary organic aerosol, and its major sources could vary by season and location.

Aerosol Optical Properties and Contribution to Differentiate Haze and Haze-Free Weather in Wuhan City

Haze is an atmospheric phenomenon in which different types of particulates obscure the sky, and hence affect almost all human activities. Over a couple of recent decades, China has witnessed increasingly worse air quality as well as atmospheric haziness in its cities. There are various haze contributing factors including the rapid industrialization, excessive biomass burning, and an increase in the number of vehicles. This study proposes a methodology based on the aerosols scattering and absorption properties, to predict the likelihood of an episode of hazy days. This case study employs the aerosol optical properties data from integrated nephelometer and aethalometer sensors from December 2009 to September 2014 over Wuhan. The role and contribution of each aerosol optical parameter (e.g., aerosol scattering and absorption coefficients, single scattering albedo, scattering, and absorption Ångström exponents, backscatter ratio, and asymmetry factor) in distinguishing haze and haze-free conditions has been quantitatively determined based on a machine learning approach. Each aerosol optical parameter was classified independently by the support vector machine (SVM) algorithm, and the aerosol scattering (85.37%) and absorption (74.53%) coefficients were found to be primary potential indicators. Through the Kolmogorov-Smirnov test and traditional statistical analysis, the aerosol scattering and absorption coefficients were then verified as important indicators in distinguishing haze and haze-free days. Finally, through a probability density diagram and frequency histogram, we propose a simple quantitative standard to distinguish between haze and haze-free conditions based on the aerosol scattering coefficient and absorption coefficient in Wuhan City. The accuracy of the standard was determined to be 81.49% after testing, which indicates an accurate result. An error in aerosol optical properties may lead to an error in the calculation of aerosol radiative forcing, the earth’s energy budget, and climate prediction. Therefore, understanding of the aerosol properties during haze-free and haze-days will help policymakers to make new policies to control urban pollution and their effects on human health.

Long-Term (2005–2017) View of Atmospheric Pollutants in Central China Using Multiple Satellite Observations

The air quality in China has experienced dramatic changes during the last few decades. To improve understanding of distribution, variations, and main influence factors of air pollution in central China, long-term multiple satellite observations from moderate resolution imaging spectroradiometer (MODIS) and ozone monitoring instrument (OMI) are used to characterize particle pollution and their primary gaseous precursors, sulfur dioxide (SO2), and nitrogen dioxide (NO2) in Hubei province during 2005–2017. Unlike other regions in eastern China, particle and gaseous pollutants exhibit distinct spatial and temporal patterns in central China due to differences in emission sources and control measures. OMI SO2 of the whole Hubei region reached the highest value of ~0.2 Dobson unit (DU) in 2007 and then declined by more than 90% to near background levels. By contrast, OMI NO2 grew from ~3.2 to 5.9 × 1015 molecules cm−2 during 2005–2011 and deceased to ~3.9 × 1015 molecules cm−2 in 2017. Unlike the steadily declining SO2, variations of OMI NO2 flattened out in 2016 and increased ~0.5 × 1015 molecules cm−2 during 2017. As result, MODIS AOD at 550 nm increased from 0.55 to the peak value of 0.7 during 2005–2011 and then decreased continuously to 0.38 by 2017. MODIS AOD and OMI SO2 has a high correlation (R > 0.8), indicating that annual variations of SO2 can explain most changes of AOD. The air pollution in central China has notable seasonal variations, which is heaviest in winter and light in summer. While air quality in eastern Hubei is dominated by gaseous pollution such as O3 and NOx, particle pollutants are mainly concentrated in central Hubei. The high consistency with ground measurements demonstrates that satellite observation can well capture variations of air pollution in regional scales. The increasing ozone (O3) and NO2 since 2016 suggests that more control measures should be made to reduce O3-related emissions. To improve the air quality in regional scale, it is necessary to monitor the dynamic emission sources with satellite observations at a finer resolution.

Influence of Spatial Resolution and Retrieval Frequency on Applicability of Satellite-Predicted PM2.5 in Northern China

Satellite aerosol optical depth (AOD) products have been widely used in estimating fine particulate matter (PM2.5) concentrations near the surface at a regional scale, and perform well compared with ground measurements. However, the influence of limitations such as retrieval frequency and the spatial resolution of satellite AODs on the applicability of predicted PM2.5 values has been rarely considered. With three widely used MODIS AOD products, including Multi-Angle Implementation of Atmospheric Correction (MAIAC), Deep Blue (DB) and Dark Target (DT), here we evaluate the influence of their spatial resolution and sampling frequency by estimating daily PM2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) region of northern China during 2017 utilizing a mixed effects model. The daily concentrations of PM2.5 derived from MAIAC, DB and DT AOD all have high correlations (R2: 0.78, 0.8, and 0.78) with the observed values, but the predicted annual PM2.5 exhibits a distinct spatial distribution. DT estimation obviously underestimates annual PM2.5 in polluted areas due to lower sampling of heavy pollution events. By contrast, the retrieval frequency (~40-60%) of MAIAC and DB AOD can represent well annual PM2.5 in nearly all 83 sites tested. However, MAIAC and DB-derived PM2.5 have a larger bias compared with observed values than DT, indicating that the large spatial variation of aerosol properties can exert an influence on the reliability of the statistical AOD-PM2.5 relationship. Also, there is notable difference between MAIAC and DB PM2.5 due to their different cloud screening methods. The MAIAC PM2.5 with high spatial resolution at 1 km can capture much finer hotpots than DB and DT at 10 km. Our results suggest that it is crucial to consider the applicability of satellite-predicted PM2.5 values derived from different aerosol products according to the specific requirements besides modeling the AOD-PM2.5 relationship.

Reversal of Aerosol Properties in Eastern China with Rapid Decline of Anthropogenic Emissions

The clean air actions of the Chinese government since 2013 have led to rapid reduction in anthropogenic emissions during the last five years. In this study, we present a regional-scale insight into the transition of aerosol properties during this special period based on integrated Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), and ground-based AERONET (AErosol RObotic NETwork) observations. As a response, aerosols in eastern China have exhibited notable reversal in both the amount and optical properties. Regional haze pollution with Aerosol Optical Depth (AOD) > 1.0 in northern China declined from more than ~80 days per year to less than ~30 days. While fine-mode particles exhibited a continuous decrease by ~30-40% during the time period of 2013–2018, the levels of coarse aerosols had no regular variations. MISR fraction AOD of different size modes shows that there has been an obvious overall decline in coarse particles over eastern China, but natural sources such as long-range dust transport make a considerable contribution. The Single Scattering Albedo (SSA) increased steadily from 2001 to 2012 by more than ~0.05. In contrast, aerosol absorption has been getting stronger since 2013, with SSA increasing by ~0.03, due to a much larger reduction in sulfate and nitrate. The drastic transition of aerosol properties has greatly changed aerosol radiative forcing (ARF) in eastern China. The negative ARF at the top (TOA) and bottom (BOA) of the atmosphere decreased by ~30 and ~50 W/m2, respectively, in Beijing during the 2001–2012 period. Although aerosol loading continued to decline after 2013, the magnitudes of TOA and BOA ARF have increased by ~10 and ~30 W/m2, respectively, since 2013, due largely to the enhanced aerosol absorption. Our results suggest that more comprehensive observations are needed to improve understanding of the intense climate and environment effects of dramatic aerosol properties in eastern China.

Exploring the regional pollution characteristics and meteorological formation mechanism of PM2.5 in North China during 2013-2017

In the last decade, North China (NC) has been one of the most populated and polluted regions in the world. The regional air pollution has had a serious impact on people's health; thus, all levels of government have implemented various pollution prevention measures since 2013. Based on multi-city in situ environmental and meteorological data, as well as the meteorological reanalysis dataset from 2013 to 2017, regional pollution characteristics and meteorological formation mechanisms were analyzed to provide a more comprehensive understanding of the evolution of PM_2.5 in NC. The domain-averaged PM_2.5 was 79 ± 17 µg m^-3 from 2013 to 2017, with a decreasing rate of 10 μg m^-3 yr^-1. Two automatic computer algorithms were established to identify 6 daily regional pollution types (DRPTs) and 48 persistent regional pollution events (PRPEs) over NC during 2014-2017. The average PM_2.5 concentration for the Large-Region-Pollution type (including the Large-Moderate-Region-Pollution and Large-Severe-Region-Pollution types) was 113 ± 40 µg m^-3, and more than half of Large-Region-Pollution days and PRPEs occurred in winter. The PRPEs in NC mainly developed from the area south of Hebei. The number of Large-Region-Pollution days decreased notably from 2014 to 2017, the annual number of days varying between 194 and 97 days, whereas a slight decline was observed in winter. In addition, the averaged PM_2.5 concentrations and the numbers and durations of the PRPEs decreased. Lamb-Jenkinson weather typing was used to reveal the impact of synoptic circulations on PM_2.5 across NC. Generally, the contributions of the variations in circulation to the reduction in PM_2.5 levels over NC between 2013 and 2017 were 64% and 45% in summer and winter, respectively. The three most highly polluted weather types were types C, S and E, with an average PM_2.5 concentration of 137 ± 40 µg m^-3 in winter. Furthermore, three typical circulation dynamics were categorized in the peak stage of the PRPEs, namely, the southerly airflow pattern, the northerly airflow pattern and anticyclone pattern; the averaged relative humidity, recirculation index, wind speed and boundary layer height were 63%, 0.33, 2.0 m s^-1 and 493 m, respectively. Our results imply that additional emission reduction measures should be implemented under unfavorable meteorological situations to attain ambient air quality standards in the future.

Stacking machine learning model for estimating hourly PM2.5 in China based on Himawari 8 aerosol optical depth data

Aerosol optical depth (AOD) from polar orbit satellites and meteorological factors have been widely used to estimate concentrations of surface particulate matter with an aerodynamic diameter <2.5 μm (PM_2.5). However, estimations with high temporal resolution remain lacking because of the limitations of satellite observations. Here, we used AOD data with a temporal resolution of 1 h provided by a geostationary satellite called Himawari 8 to overcome this problem. We developed a stacking model, which contained three submodels of machine learning, namely, AdaBoost, XGBoost and random forest, stacked through a multiple linear regression model. Then, we estimated the hourly concentrations of PM_2.5 in Central and Eastern China. The accuracy evaluation showed that the proposed stacking model performed better than the single models when applied to the test set, with an average coefficient of determination (R²) of 0.85 and a root-mean-square error (RMSE) of 17.3 μg/m³. Model precision reached its peak at 14:00 (local time), with an R² (RMSE) of 0.92 (12.9 μg/m³). In addition, the spatial and temporal distributions of PM_2.5 in Central and Eastern China were plotted in this study. The North China Plain was determined to be the most polluted area in China, with an annual mean PM_2.5 concentration of 58 μg/m³ during daytime. Moreover, the pollution level of PM_2.5 was the highest in winter, with an average concentration of 73 μg/m³.

Long-term (2006-2015) variations and relations of multiple atmospheric pollutants based on multi-remote sensing data over the North China Plain

In this analysis, the Aqua/MODIS aerosol optical thickness (AOD), Aura/OMI tropospheric NO₂ and SO₂ column concentration from 2006 to 2015 were used to statistically analyze the spatial distribution characteristics and variation trends of three polluted parameters from three temporal scales of monthly, seasonal and annual average. The results showed that the minimum values of NO₂ and SO₂ column concentrations both appeared in July and August, and the maximum values appeared in December and January, which was contrary to the variations in AOD. The highly polluted levels were mainly distributed in Shijiazhuang, Xingtai, and Yancheng cities of Hebei Province, and gradually transported to Zhengzhou, Henan Province, north and southwest of Shandong Province, and Tianjin, along the main line of Taiyuan-Linyi, Shanxi Province. AOD and NO₂ had significant differences on the seasonal average scale, whereas SO₂ had little changes. These pollutants had declined year by year since 2011, in the 10-year period, AOD and SO₂ respectively decreased by 17.14% and 10.57%, and only NO₂ rose from 8.69 × 10¹⁵ molecules/cm² in 2006 to 9.10 × 10¹⁵ molecules/cm² in 2015 with the increase rate of 4.79%. Integrated with MODIS-released fire products and the Multi-resolution Emission Inventory for China (MEIC), high AOD values in summer were usually accompanied by frequent biomass burning, and heavy heating demand of coal burning led to largest NO₂ and SO₂ levels in winter. Both inter-annual variations of MEIC NOx and OMI-observed NO₂ responded to emission reductions of vehicle exhaustions positively, but vehicle population in Henan and Shandong provinces need to be further controlled. The significant decline of SO₂ is mainly attributed to the enforcement of de-sulfurization devices in power plants. Our study found that in the treatment of complex atmospheric pollution, in addition to strict control of common sources of emissions from AOD, NO₂ and SO₂, it is also necessary to consider their individual characteristics.

Influence of biomass burning on local air pollution in mainland Southeast Asia from 2001 to 2016

In this study, various remote sensing data, modeling data and emission inventories were integrated to analyze the tempo-spatial distribution of biomass burning in mainland Southeast Asia and its effects on the local ambient air quality from 2001 to 2016. Land cover changes have been considered in dividing the biomass burning into four types: forest fires, shrubland fires, crop residue burning and other fires. The results show that the monthly average number of fire spots peaked at 34,512 in March and that the monthly variation followed a seasonal pattern, which was closely related to precipitation and farming activities. The four types of biomass burning fires presented different tempo-spatial distributions. Moreover, the monthly Aerosol Optical Depth (AOD), concentration of particulate matter with a diameter less than 2.5 μm (PM_2.5) and carbon monoxide (CO) total column also peaked in March with values of 0.62, 45 μg/m³ and 3.25 × 10¹⁸ molecules/cm², respectively. There are significant correlations between the monthly means of AOD (r = 0.74, P < 0.001), PM_2.5 concentration (r = 0.88, P < 0.001), and CO total column (r = 0.82, P < 0.001) and the number of fire spots in the fire season. We used Positive Matrix Factorization (PMF) model to resolve the sources of PM_2.5 into 3 factors. The result indicated that the largest contribution (48%) to annual average concentration of PM_2.5 was from Factor 1 (dominated by biomass burning), followed by 27% from Factor 3 (dominated by anthropogenic emission), and 25% from Factor 2 (long-range transport/local nature source). The annually anthropogenic emission of CO and PM_2.5 from 2001 to 2012 and the monthly emission from the Emission Database for Global Atmosphere Research (EDGAR) were consistent with PMF analysis and further prove that biomass burning is the dominant cause of the variation in the local air quality in mainland Southeast Asia.

Retrieval of 500 m Aerosol Optical Depths from MODIS Measurements over Urban Surfaces under Heavy Aerosol Loading Conditions in Winter

Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products are used worldwide for their reliable accuracy. However, the aerosol optical depth (AOD) usually retrieved by the operational dark target (DT) algorithm of MODIS has been missing for most of the urban regions in Central China. This was due to a high surface reflectance and heavy aerosol loading, especially in winter, when a high cloud cover fraction and the frequent occurrence of haze events reduce the number of effective satellite observations. The retrieval of the AOD from limited satellite data is much needed and important for further aerosol investigations. In this paper, we propose an improved AOD retrieval method for 500 m MODIS data, which is based on an extended surface reflectance estimation scheme and dynamic aerosol models derived from ground-based sun-photometric observations. This improved method was applied to retrieve AOD during heavy aerosol loading and effectively complements the scarcity of AOD in correspondence with urban surface of a higher spatial resolution. The validation results showed that the retrieved AOD was consistent with MODIS DT AOD (R = ~0.87; RMSE = ~0.11) and ground measurements (R = ~0.89; RMSE = ~0.15) from both the Terra and the Aqua satellite. The method can be easily applied to different urban environments affected by air pollution and contributes to the research on aerosol.

Satellite-Derived Correlation of SO2, NO2, and Aerosol Optical Depth with Meteorological Conditions over East Asia from 2005 to 2015

Intense economic and industrial development in China has been accompanied by severe local air pollution, as well as in other downwind countries in East Asia. This study analyzes satellite observational data of sulfur dioxide (SO2), nitrogen dioxide (NO2), and aerosol optical depth (AOD) to explore the spatial distribution, long-term temporal variation, and correlation to meteorological conditions over this region over the period 2005–2015. SO2 and NO2 data are retrieved from the ozone monitoring instrument (OMI) onboard the National Aeronautics and Space Administration (NASA) Aura satellite, while AOD data are from the moderate-resolution imaging spectroradiometer (MODIS) onboard the NASA Aqua satellite. Spatial distributions of SO2, NO2, and AOD show the highest levels in the North China Plain (NCP), with hotspots also in Southeastern China (SC) and the Sichuan Basin (SB). Biomass burning also contributes to a high level of AOD in Southeast Asia in spring and in Equatorial Asia in fall. Considering the correlation of pollutant levels to meteorological conditions, monitoring data show that higher temperature and higher relative humidity (RH) favor the conversion of SO2 and NO2 to sulfate and nitrate aerosol, respectively. The impact of stronger lower tropospheric stability facilitates the accumulation of SO2 and NO2 in NCP and SC. Transport of SO2 and NO2 from intense source regions to relatively clean regions is highly influential over East Asia; such transport from the NCP leads to a considerable increase of pollutants in SC, SB, Taiwan Island (TW), and Taiwan Strait (TWS), particularly in winter. Aerosols generated by biomass burning in Southeast Asia and anthropogenic aerosol in SC are transported to TW and TWS and lead to the increase of AOD, with the highest levels of AOD in SC, TW, and TWS occurring in spring. Precipitation results in the removal of pollutants, especially in highly polluted regions, the effect of which is most significant in winter and spring.

Does China become the "pollution heaven" in South-South trade? Evidence from Sino-Russian trade

The South-South trade has witnessed a rapid development over the years, but its impacts on the participating countries remain unknown. Taking Sino-Russian trade as evidence, a multiregional input-output model is adopted and three types of non-carbon pollutant are chosen to investigate whether China has become the "pollution heaven" in South-South trade. After investigating the industry structure distribution and trade flows of embodied pollution during 2000-2014, the driving factors of the changes in embodied pollutant are further explored by Structural Decomposition Analysis (SDA). The results showed that China has gradually lost the win-win situation of trade surplus and pollution reduction. Since the year 2007, China has totally become a net exporter of embodied pollutions, and has become to bear the environmental costs in the trade with Russia. The expansion of exports to Russia is the main cause of increasing embodied pollutant emission in China, and the progress of emissions reduction technology effect is not sufficient to offset the increase in embodied pollutant emissions. From the sectoral aspect, we find that the exports of textiles, leather, chemical, machinery and electronics are the main causes of pollution outflows. Meanwhile, imports of mineral, transport, metals, coke, petroleum and nuclear fuel to a certain extent eased the pressure of pollution reduction in China.

Recent changes of trans-boundary air pollution over the Yellow Sea: Implications for future air quality in South Korea

The influence of air pollutants originating from the Chinese region on air quality over South Korea has been a major concern for policymakers. To investigate the inter-annual trends of the long-distance transport of air pollutants from China to South Korea, multi-year trend analysis was carried out for Aerosol Optical Depth (AOD, as a proxy of particulate matter), and CO (a water-insoluble air pollutant) and SO₂ (a partially water-soluble air pollutant), over three regions in Northeast Asia. Air pollutants are typically long-range transported from the highly polluted parts of China to South Korea through the Yellow Sea. Taking advantage of this geographical merit, we carried out the multi-year trend analysis with a special focus on the Yellow Sea region. Decreasing trends of about 5-10%, 13-17% and 55-61% during the last decade were observed in surface CO, AOD and tropospheric SO₂ columns over the North China Plain (NCP), Yellow Sea (YS), and South Korea (SK), respectively. Such decreasing trends were also found consistently during the last three, five, and seven years, indicating that the changes in pollution levels are likely in response to recent policy measures taken by the Chinese and Korean governments to improve air quality over the regions. Due to these efforts, the amounts of air pollutants transported from China to South Korea are expected to decrease in future years, to the likely rates of 1.50 ppb yr^-1, 0.05 DU yr^-1, and 0.56 μg m^-3 yr^-1 over the YS region for CO, SO₂, and PM_2.5, respectively. Given the ambitious plans recently announced by the Chinese government for the 21st meeting of Conference of Parties (COP21) and its co-control effects, the suggested percentage rates may even be conservative numbers. This analysis is expected to provide South Korean policymakers with valuable information to establish new air pollution policies in South Korea.

Estimation of spatiotemporal PM1.0 distributions in China by combining PM2.5 observations with satellite aerosol optical depth

Particulates smaller than 1.0 μm (PM_1.0) have strong associations with public health and environment, and considerable exposure data should be obtained to understand the actual environmental burden. This study presented a PM_1.0 estimation strategy based on the generalised regression neural network model. The proposed strategy combined ground-based observations of PM_2.5 and satellite-derived aerosol optical depth (AOD) to estimate PM_1.0 concentrations in China from July 2015 to June 2017. Results indicated that the PM_1.0 estimates agreed well with the ground-based measurements with an R² of 0.74, root mean square error of 19.0 μg/m³ and mean absolute error of 11.4 μg/m³ as calculated with the tenfold cross-validation method. The diurnal estimation performance displayed remarkable single-peak variation with the highest R² of 0.80 at noon, and the seasonal estimation performance showed that the proposed method could effectively capture high-pollution events of PM_1.0 in winter. Spatially, the most polluted areas were clustered in the North China Plain, where the average estimates presented a bimodal distribution during daytime. In addition, the quality of satellite-derived AOD, the robustness of the interpolation algorithm and the proportion of PM_1.0 in PM_2.5 were confirmed to affect the estimation accuracy of the proposed model.

Spatiotemporal patterns of aerosol optical depth throughout China from 2003 to 2016

With China's rapid economic growth, particle pollution, especially fine particulate matter (PM_2.5), which is known to have adverse health impacts, has become an increasingly serious issue. Satellite aerosol optical depth (AOD), an important physical property of aerosol particles, can serve as a proxy for investigating particle pollution because it can provide observations with comprehensive spatial and temporal coverage compared with ground-level measurements. This study used an improved 14-year high-resolution AOD dataset to examine the spatial characteristics and temporal dynamics of the dominant pollutants in China from 2003 to 2016 using advanced statistical methods. The improved AOD dataset combines the Moderate Resolution Imaging Spectroradiometer (MODIS) 3-km dark target AOD and 10-km deep blue AOD datasets, which enables a comparison of aerosol loading between eastern and western China. Pixel-based analysis indicates a significant difference between eastern and western China: high AOD values were generally observed in the east with a notable decrease, while low aerosol loadings were found in western China with no distinct change. The most particle polluted areas were the North China Plain, Hubei-Hunan region, Sichuan Basin, and Guangxi-Guangdong region in eastern China and western Qinghai and Tarim Basin in western China, with changes in the national AOD average center shifting to the northwest from 2013 to 2016. The impact factor analysis based on geographically weighted regression indicates that the effect of topography on the spatial characteristics of AOD is negative and more important in eastern China, which has low elevations. Built-up areas significantly exacerbate air pollution in the areas between eastern and western China, and there is no apparent AOD-vegetation relation dominates the country. This study thus provides a comprehensive understanding of the spatiotemporal variations of particle concentrations and can facilitate environmental management, policies to alleviate particle pollution, and health risk assessment studies.

Environmental responsibility for sulfur dioxide emissions and associated biodiversity loss across Chinese provinces

Recent years have witnessed a growing volume in Chinese interregional trade, along with the increasing disparities in environmental pressures. This has prompted an increased attention on where the responsibilities for environmental impacts should be placed. In this paper, we quantify the environmental responsibility of SO₂ emissions and biodiversity impacts due to terrestrial acidification at the provincial level for the first time. We examine the environmental responsibility from the perspectives of production, consumption, and income generation by employing a Multi-Regional Input-Output (MRIO) model for 2007, 2010, and 2012. The results indicate that ∼40% of SO₂ emissions were driven by the consumption in provinces other than where the emissions discharged. In particular, those developed provinces were net importers of SO₂ emissions and mainly outsourced their emissions to nearby developing provinces. Over the period of analysis, environmental inequality among 30 provinces was larger than GDP inequality. Furthermore, environmental inequality continued to increase while GDP inequality decreased over the time period. The results of a shared income- and consumption-based responsibility approach suggest that the environmental responsibility of SO₂ emissions and biodiversity impacts for developed provinces can reach up to ∼4- to 93-fold the environmental pressure occurred within those provinces. This indicates that under these accounting principles the developed northern provinces in China would bear a much larger share of the environmental responsibility.

The contribution of the Beijing, Tianjin and Hebei region's iron and steel industry to local air pollution in winter

The Beijing, Tianjin and Hebei region (BTH) in China is a highly populated area that has recently experienced frequent haze episodes in winter. With high production capacities, the iron and steel industry (ISI) has long been a key source of air pollutants in BTH and is thus considered responsible for the degradation of local air quality. Here, we conducted a cross-disciplinary research combining the Weather Research and Forecasting with Chemistry (WRF/Chem) model, the multiregional input-output model (MRIO) and the health assessment model to explore the impacts of the ISI on air pollution in the BTH region in January 2012. Our results show large increases in air pollution due to direct ISI emissions, with up to a 90 μg/m³ monthly average of fine particulate matter (PM_2.5) and sulfur dioxide (SO₂) in eastern Tangshan and western Handan. In addition to direct emissions, the ISI has induced large quantities of indirect emissions from upstream sectors (e.g., the electricity and transportation sectors), leading to PM_2.5, SO₂ and NO_x increases of 2-10 μg/m³ in BTH. Considering the direct and indirect emissions, we estimated that 275 (233-313) PM_2.5-related mortalities occurred in January, and approximately 42% of these premature deaths occurred in Tangshan. A high rate of premature deaths also occurred in urban Beijing due to its high population density. Revealing the great health burden caused by the ISI, our results underscore the necessity for the Chinese government to reduce air pollutant emissions from the ISI and its upstream industries in BTH.

Scanning vertical distributions of typical aerosols along the Yangtze River using elastic lidar

In recent years, China has experienced heavy air pollution, especially haze caused by particulate matter (PM). The compositions, horizontal distributions, transport, and chemical formation mechanisms of PM and its precursors have been widely investigated in China based on near-ground measurements. However, the understanding of the distributions and physical and chemical processes of PM in the vertical direction remains limited. In this study, an elastic lidar was employed to investigate the vertical profiles of aerosols along the Yangtze River during the Yangtze River Campaign of winter 2015. Some typical aerosols were identified and some events were analyzed in three cases. Dust aerosols can be transported from the Gobi Desert to the Yangtze River basin across a long distance at both low and high altitudes in early December. The transport route was perpendicular to the ship track, suggesting that the dust aerosols may have affected a large area. Moreover, during transport, some dust was also affected by the areas below its transport route since some anthropogenic pollutants were mixed with the dust and changed some of its optical properties. Biomass-burning aerosols covering a distant range along the Yangtze River were identified. This result directly shows the impact areas of biomass-burning aerosols in some agricultural fields. Some directly emitted aerosol plumes were observed, and direct effects of such plumes were limited both temporally and spatially. In addition, an aerosol plume with very low linear depolarization ratios, probably formed through secondary processes, was also observed. These results can help us better understand aerosols in large spatial scales in China and can be useful to regional haze studies.

Vertical characteristics of VOCs in the lower troposphere over the North China Plain during pollution periods

In recent years, photochemical smog and gray haze-fog have frequently appeared over northern China. To determine the spatial distribution of volatile organic compounds (VOC) during a pollution period, tethered balloon flights were conducted over a suburban site on the North China Plain. Statistical analysis showed that the VOCs concentrations peaked at the surface, and decreased with altitude. A rapid decrease appeared from the surface to 400 m, with concnetrations of alkanes, alkenes, aromatics and halocarbons decreasing by 48.0%, 53.3%, 43.3% and 51.1%, respectively. At heights in the range of 500-1000 m, alkenes concnetrations decline by 40.2%; alkanes and halocarbons concnetrations only decreased by 24.8% and 6.4%, respectively; and aromatics increased slightly by 5.5%. High concentrations VOCs covered a higher range of height (400 m) on heavy pollution days due to lacking of diffusion power. The VOCs concentrations decreased by 50% at 200 m on light pollution days. The transport of air mass affected the composition and concentration of high-altitude VOCs, especially on lightly polluted days. These air masses originated in areas with abundant traffic and combustion sources. Reactive aromatics (k_OH>20,000 ppm^-1 min^-1 and k_OH<20,000 ppm^-1 min^-1) were the main contributor to the ozone formation, accounting for 37%, on the surface on light pollution days. The contribution increased to 52% with pollution aggravated, and increased to 64% with height. The contributions of reactive aromatics were influenced by the degree of air mass aging. Under the umbrella of aging air mass, the contribution of reactive aromatics increased with height.

Characteristics of air pollution in different zones of Sichuan Basin, China

Sichuan Basin, located in southwest China, has been ranked as the fourth of heavily air polluted regions in China partly due to its deep mountain-basin topography. However, spatial-temporal distribution of air pollution over the basin is still unclear due to the lack of monitoring data and poor knowledge. Since January 2015, six criteria air pollutants began to be monitored in 20 cities across the basin. The measured data enable us to analyze the basin-wide spatial-temporal distribution characteristics of these air pollutants. Results revealed heavy air pollution in the bottom zone, medium in the slope zone, and light pollution in the edge zone of the Basin in terms of the altitudes of air quality monitoring stations across the Basin. The average concentrations of PM_2.5 and PM₁₀ were 55.87μg/m³ and 86.49μg/m³ in the bottom, 33.76μg/m³ and 63.33μg/m³ in the slope, and 19.71μg/m³ and 35.06μg/m³ in the edge, respectively. In the bottom and slope of the basin, high PM_2.5 concentration events occurred most frequently in winter_. While in summer, ozone became primary pollutant. Among the six air pollutants, concentrations of PM_2.5 and PM₁₀ decrease dramatically with increasing altitude which was fitted by a nonlinear relationship between particulate matter (PM) concentrations and altitude. This relationship was validated by extinction coefficient profiles from CALIPSO observations and EV-lidar data, and hence used to reflect vertical distribution of air PM concentrations. It has been found that the thickness of higher PM concentrations is less than 500m in the basin. In the bottom of the basin, PM concentrations exhibited stronger horizontal homogeneities as compared with those in the North China Plain and Yangtze River Delta. However, gaseous pollutants seemed not to show clear relationships between their concentrations and altitudes in the basin. Their horizontal homogeneities were less significant compared to PM.

Chemical composition, source, and process of urban aerosols during winter haze formation in Northeast China

The characteristics of aerosol particles have been poorly evaluated even though haze episodes frequently occur in winter in Northeast China. OC/EC analysis, ion chromatography, and transmission electron microscopy (TEM) were used to investigate the organic carbon (OC) and elemental carbon (EC), and soluble ions in PM_2.5 and the mixing state of individual particles during a severe wintertime haze episode in Northeast China. The organic matter (OM), NH₄⁺, SO₄^2-, and NO₃^- concentrations in PM_2.5 were 89.5 μg/m³, 24.2 μg/m³, 28.1 μg/m³, and 32.8 μg/m³ on the haze days, respectively. TEM observations further showed that over 80% of the haze particles contained primary organic aerosols (POAs). Based on a comparison of the data obtained during the haze formation, we generate the following synthetic model of the process: (1) Stable synoptic meteorological conditions drove the haze formation. (2) The early stage of haze formation (light or moderate haze) was mainly caused by the enrichment of POAs from coal burning for household heating and cooking. (3) High levels of secondary organic aerosols (SOAs), sulfates, and nitrates formation via heterogeneous reactions together with POAs accumulation promoted to the evolution from light or moderate to severe haze. Compared to the severe haze episodes over the North China Plain, the PM_2.5 in Northeast China analyzed in the present study contained similar sulfate, higher SOA, and lower nitrate contents. Our results suggest that most of the POAs and secondary particles were likely related to emissions from coal-burning residential stoves in rural outskirts and small boilers in urban areas. The inefficient burning of coal for household heating and cooking should be monitored during wintertime in Northeast China.

Aerosol pollution and its potential impacts on outdoor human thermal sensation: East Asian perspectives

Aerosols affect the insolation at ground and thus the Aerosol Optical Depth (AOD, a measure of aerosol pollution) plays an important role on the variation of the Physiological Equivalent Temperature (PET) at locations with different aerosol climatology. The aerosol effects upon PET were studied for the first time at four East Asian cities by coupling a radiative transfer model and a human thermal comfort model which were previously well evaluated. Evident with the MODIS and AERONET AOD observations, the aerosol pollution at Beijing and Seoul was higher than at Chiayi (Taiwan) and Hong Kong. Based on the AERONET data, with background AOD levels the selected temperate cities had similar clear-sky PET values especially during summertime, due to their locations at similar latitudes. This also applied to the sub-tropical cities. Increase in the AOD level to the seasonal average one led to an increase in diffuse solar radiation and in turn an increase in PET for people living in all the cities. However, the heavy aerosol loading environment in Beijing and Seoul in summertime (AODs > 3.0 in episodic situations) reduced the total radiative flux and thus PET values in the cities. On the contrary, relatively lower episodic AOD levels in Chiayi and Hong Kong led to strong diffuse and still strong direct radiative fluxes and resulted in higher PET values, relative to those with seasonal averaged AOD levels. People tended to feel from "hot" to "very hot" during summertime when the AOD reached their average levels from the background level. This implies that in future aerosol effects add further burden to the thermal environment apart from the effects of greenhouse gas-induced global warming. Understanding the interaction between ambient aerosols and outdoor thermal environment is an important first step for effective mitigation measures such as urban greening to reduce the risk of human heat stress. It is also critical to make cities more attractive and enhancing to human well-being to achieve enhancing sustainable urbanization as one of the principal goals for the Nature-based Solutions.

High Levels of Daytime Molecular Chlorine and Nitryl Chloride at a Rural Site on the North China Plain

Molecular chlorine (Cl₂) and nitryl chloride (ClNO₂) concentrations were measured using chemical ionization mass spectrometry at a rural site over the North China Plain during June 2014. High levels of daytime Cl₂ up to ∼450 pptv were observed. The average diurnal Cl₂ mixing ratios showed a maximum around noon at ∼100 pptv. ClNO₂ exhibited a strong diurnal variation with early morning maxima reaching ppbv levels and afternoon minima sustained above 60 pptv. A moderate correlation (R² = 0.31) between Cl₂ and sulfur dioxide was observed, perhaps indicating a role for power plant emissions in the generation of the observed chlorine. We also observed a strong correlation (R² = 0.83) between daytime (10:00-20:00) Cl₂ and ClNO₂, which implies that both of them were formed from a similar mechanism. In addition, Cl₂ production is likely associated with a photochemical mechanism as Cl₂ concentrations varied with ozone (O₃) levels. The impact of Cl₂ and ClNO₂ as Cl atom sources is investigated using a photochemical box model. We estimated that the produced Cl atoms oxidized slightly more alkanes than OH radicals and enhanced the daily concentrations of peroxy radicals by 15% and the O₃ production rate by 19%.

Evaluation of aerosol optical depth and aerosol models from VIIRS retrieval algorithms over North China Plain

The first Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on Suomi National Polar-orbiting Partnership (S-NPP) satellite in late 2011. Similar to the Moderate resolution Imaging Spectroradiometer (MODIS), VIIRS observes top-of-atmosphere spectral reflectance and is potentially suitable for retrieval of the aerosol optical depth (AOD). The VIIRS Environmental Data Record data (VIIRS_EDR) is produced operationally by NOAA, and is based on the MODIS atmospheric correction algorithm. The "MODIS-like" VIIRS data (VIIRS_ML) are being produced experimentally at NASA, from a version of the "dark-target" algorithm that is applied to MODIS. In this study, the AOD and aerosol model types from these two VIIRS retrieval algorithms over the North China Plain (NCP) are evaluated using the ground-based CE318 Sunphotometer (CE318) measurements during 2 May 2012 - 31 March 2014 at three sites. These sites represent three different surface types: urban (Beijing), suburban (XiangHe) and rural (Xinglong). Firstly, we evaluate the retrieved spectral AOD. For the three sites, VIIRS_EDR AOD at 550 nm shows a positive mean bias (MB) of 0.04-0.06 and the correlation of 0.83-0.86, with the largest MB (0.10-0.15) observed in Beijing. In contrast, VIIRS_ML AOD at 550 nm has overall higher positive MB of 0.13-0.14 and a higher correlation (0.93-0.94) with CE318 AOD. Secondly, we evaluate the aerosol model types assumed by each algorithm, as well as the aerosol optical properties used in the AOD retrievals. The aerosol model used in VIIRS_EDR algorithm shows that dust and clean urban models were the dominant model types during the evaluation period. The overall accuracy rate of the aerosol model used in VIIRS_ML over NCP three sites (0.48) is higher than that of VIIRS_EDR (0.27). The differences in Single Scattering Albedo (SSA) at 670 nm between VIIRS_ML and CE318 are mostly less than 0.015, but high seasonal differences are found especially over the Xinglong site. The values of SSA from VIIRS_EDR are higher than that observed by CE318 over all sites and all assumed aerosol modes, with a positive bias of 0.02-0.04 for fine mode, 0.06-0.12 for coarse mode and 0.03-0.05 for bi-mode at 440nm. The overestimation of SSA but positive AOD MB of VIIRS_EDR indicate that other factors (e.g. surface reflectance characterization or cloud contamination) are important sources of error in the VIIRS_EDR algorithm, and their effects on aerosol retrievals may override the effects from non-ideality in these aerosol models.

Evolutionary processes and sources of high-nitrate haze episodes over Beijing, Spring

Rare and consecutive high-nitrate haze pollution episodes were observed in Beijing in spring 2012. We present detailed characterization of the sources and evolutionary mechanisms of this haze pollution, and focus on an episode that occurred between 15 and 26 April. Submicron aerosol species were found to be substantially elevated during haze episodes, and nitrates showed the largest increase and occupation (average: 32.2%) in non-refractory submicron particles (NR-PM₁), which did not occur in other seasons as previously reported. The haze episode (HE) was divided into three sub-episodes, HEa, HEb, and HEc. During HEa and HEc, a shallow boundary layer, stagnant meteorological conditions, and high humidity favored the formation of high-nitrate concentrations, which were mainly produced by three different processes - daytime photochemical production, gas-particle partitioning, and nighttime heterogeneous reactions - and the decline in visibility was mainly induced by NR-PM_1. However, unlike HEa and HEc, during HEb, the contribution of high nitrates was partly from the transport of haze from the southeast of Beijing - the transport pathway was observed at ~800-1000m by aerosol Lidar - and the decline in visibility during HEb was primarily caused by PM_2.5. Our results provide useful information for air quality improvement strategies in Beijing during Spring.

Emission of volatile organic compounds from domestic coal stove with the actual alternation of flaming and smoldering combustion processes

Volatile organic compounds (VOCs) emissions from the chimney of a prevailing domestic stove fuelled with raw bituminous coal were measured under flaming and smoldering combustion processes in a farmer's house. The results indicated that the concentrations of VOCs quickly increased after the coal loading and achieved their peak values in a few minutes. The peak concentrations of the VOCs under the smoldering combustion process were significantly higher than those under the flaming combustion process. Alkanes accounted for the largest proportion (43.05%) under the smoldering combustion, followed by aromatics (28.86%), alkenes (21.91%), carbonyls (5.81%) and acetylene (0.37%). The emission factors of the total VOCs under the smoldering combustion processes (5402.9 ± 2031.8 mg kg^-1) were nearly one order of magnitude greater than those under the flaming combustion processes (559.2 ± 385.9 mg kg^-1). Based on the VOCs emission factors obtained in this study and the regional domestic coal consumption, the total VOCs emissions from domestic coal stoves was roughly estimated to be 1.25 × 10⁸ kg a^-1 in the Beijing-Tianjin-Hebei region.

The burden of lung cancer mortality attributable to fine particles in China

Although studies have examined the associations between fine particles (PM_2.5) and lung cancer mortality in US and European countries, the evidence is still limited for China. In addition, no study has provided estimates of spatial variation in lung cancer mortality attributable to PM_2.5 in China. In this study, we quantified the associations between lung cancer mortality and PM_2.5, using a spatiotemporal model with observed data of lung cancer mortality from 75 communities from the National Cancer Registration of China from 1990 to 2009 and the annual concentrations of PM_2.5 at 0.5°×0.5° spatial resolution. We also estimated lung cancer mortality burden attributable to PM_2.5 in China, with predicted county level lung cancer deaths in 2005. We found that the PM_2.5-lung cancer mortality associations were non-linear, with thresholds of 40μg/m³ overall, 45μg/m³ for male, 42μg/m³ for female, 45μg/m³ for those aged 30-64years, 48μg/m³ for those aged 65-74years, and 40μg/m³ for those aged 75years and more, above which the relative risks were 1.08 (95% CI: 1.07, 1.09), 1.07 (95% CI: 1.05, 1.08), 1.12 (95% CI: 1.1, 1.14), 1.05 (95% CI: 1.04, 1.07), 1.07 (95% CI: 1.06, 1.09), and 1.14 (95% CI: 1.12, 1.16) respectively. There were 51,219 (95% CI: 45,745-56,512) lung cancer deaths attributed to PM_2.5 in 2005, with attributable fractions of 13.7% (95% CI: 12.23-15.11%) overall, 10.01% (95% CI: 8.37-11.58%) for men, 18.06% (95% CI: 15.81-20.18%) for women, 8.35% (95% CI: 6.07-10.51%) for those aged 65-74years, 9.73% (95% CI: 7.6-11.75%) for those aged 65-74years, 21.7% (95% CI: 19.27-23.99%) for those aged 75years or more. In conclusion, assuming a causal relation a reduction in exposure levels of PM_2.5 below thresholds would avert a substantial number of deaths from lung cancer in China.

Formation, features and controlling strategies of severe haze-fog pollutions in China

With rapid industrialization and urbanization, China is facing a great challenge with regard to severe fog-haze pollutions, which were characterized by high fine particulate concentration level and visibility impairment. The control strategies for atmosphere pollutions in China were not only cutting-edge topics of atmospheric research, but also an urgent issue to be addressed by the Chinese government and the public. Focused on the core scientific issues of the haze and fog pollution, this paper reviews the main studies conducted in China, especially after 2010, including formation mechanisms, evolution features, and factors contributing to the fog-haze pollutions. Present policy and control strategies were synoptically discussed. The major challenges ahead will be stated and recommendations for future research directions are proposed at the end of this Review.

Ground Level PM2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO₂ and Enhanced Vegetation Index (EVI)

Highly accurate data on the spatial distribution of ambient fine particulate matter (<2.5 μm: PM2.5) is currently quite limited in China. By introducing NO₂ and Enhanced Vegetation Index (EVI) into the Geographically Weighted Regression (GWR) model, a newly developed GWR model combined with a fused Aerosol Optical Depth (AOD) product and meteorological parameters could explain approximately 87% of the variability in the corresponding PM2.5 mass concentrations. There existed obvious increase in the estimation accuracy against the original GWR model without NO₂ and EVI, where cross-validation R² increased from 0.77 to 0.87. Both models tended to overestimate when measurement is low and underestimate when high, where the exact boundary value depended greatly on the dependent variable. There was still severe PM2.5 pollution in many residential areas until 2015; however, policy-driven energy conservation and emission reduction not only reduced the severity of PM2.5 pollution but also its spatial range, to a certain extent, from 2014 to 2015. The accuracy of satellite-derived PM2.5 still has limitations for regions with insufficient ground monitoring stations and desert areas. Generally, the use of NO₂ and EVI in GWR models could more effectively estimate PM2.5 at the national scale than previous GWR models. The results in this study could provide a reasonable reference for assessing health impacts, and could be used to examine the effectiveness of emission control strategies under implementation in China.