Investigating the Benefit-Risk Profile of Drugs: From Spontaneous Reporting Systems to Real-World Data for Pharmacovigilance.

Rapid and detailed post-marketing surveillance of drugs and vaccine is required to enable assessment of their real-world safety and effectiveness. Spontaneous reporting from healthcare professionals and citizens is recognized as the basic method in the passive post-marketing surveillance of drugs and vaccines, allowing the identification of rare adverse drug reactions (ADRs) and adverse events following immunization (AEFIs). According to the current law, online platforms for ADRs and AEFI reporting and related databases are available in every country and at the global level. Recently, the use of electronic health records and the establishment of networks of databases as different sources of real-world data is emerging allowing high-quality, large-scale evaluations and providing real-world evidence on questions of clinical and regulatory interests. Here, we summarize the adverse event pharmacovigilance reporting systems in place at the global, European and in some European countries, and provide examples from recent literature of how the analysis of pharmacovigilance reports can provide evidence for unexpected and novel adverse drug reactions. Furthermore, we discuss the role of real-world data to generate real-world evidence in pharmacovigilance and regulatory activities.

Rapid reduction of air pollution and short-term exposure risks in China.

With the continuous control of anthropogenic emissions, China's air quality has improved significantly in recent years. Given this background, research on how the short-term exposure risks caused by air pollution in China have changed is insufficient. This study utilized hourly concentration data from ground observation stations and the official air quality guidelines of the Ministry of Ecology and Environment of China and the World Health Organization as standards to systematically investigate the spatiotemporal characteristics and short-term exposure risks of air pollution in China from 2015 to 2022. The results indicate that various atmospheric pollutants except for ozone showed a decreasing trend yearly. Nationwide, both single pollutant air pollution days (SAPDs) and multiple pollutant air pollution days (MAPDs) showed varying degrees of reduction within 15 and 25 days, respectively. SAPD was dominated mainly by excessive PM2.5 and PM10 pollutants, while MAPD was dominated mainly by excessive pollutant combinations, including PM2.5 + PM10, CO + PM2.5 + PM10, and SO2 + PM2.5 + PM10. As the concentration of atmospheric pollutants decreased, the total excess risk (ER) decreased yearly from 2015 to 2022, but there were significant regional differences. Now, the ER is less than 0.25% in southern China, in the range of 0.25%-0.5% in the North China Plain and some cities in the northeast, and higher than 1% in the northwest. Particulate matter is currently the primary pollutant posing short-term exposure risk in China, especially due to the impact of sandstorm weather. This study indicates that China's atmospheric cleaning action is significantly beneficial for reducing health risks.

Real-road NOx and CO2 emissions of city and highway China-6 heavy-duty diesel vehicles.

The emission of heavy-duty vehicles has raised great concerns worldwide. The complex working and loading conditions, which may differ a lot from PEMS tests, raised new challenges to the supervision and control of emissions, especially during real-world applications. On-board diagnostics (OBD) technology with data exchange enabled and strengthened the monitoring of emissions from a large number of heavy-duty diesel vehicles. This paper presents an analysis of the OBD data collected from more than 800 city and highway heavy-duty vehicles in China using remote OBD data terminals. Real-world NOx and CO2 emissions of China-6 heavy-duty vehicles have been examined. The results showed that city heavy-duty vehicles had higher NOx emission levels, which was mostly due to longer time of low SCR temperatures below 180°C. The application of novel methods based on 3B-MAW also found that heavy-duty diesel vehicles tended to have high NOx emissions at idle. Also, little difference had been found in work-based CO2 emissions, and this may be due to no major difference were found in occupancies of hot running.

Changes in source contributions to the oxidative potential of PM2.5 in urban Xiamen, China.

The toxicity of PM2.5 does not necessarily change synchronously with its mass concentration. In this study, the chemical composition (carbonaceous species, water-soluble ions, and metals) and oxidative potential (dithiothreitol assay, DTT) of PM2.5 were investigated in 2017/2018 and 2022 in Xiamen, China. The decrease rate of volume-normalized DTT (DTTv) (38%) was lower than that of PM2.5 (55%) between the two sampling periods. However, the mass-normalized DTT (DTTm) increased by 44%. Clear seasonal patterns with higher levels in winter were found for PM2.5, most chemical constituents and DTTv but not for DTTm. The large decrease in DTT activity (84%-92%) after the addition of EDTA suggested that water-soluble metals were the main contributors to DTT in Xiamen. The increased gap between the reconstructed and measured DTTv and the stronger correlations between the reconstructed/measured DTT ratio and carbonaceous species in 2022 were observed. The decrease rates of the hazard index (32.5%) and lifetime cancer risk (9.1%) differed from those of PM2.5 and DTTv due to their different main contributors. The PMF-MLR model showed that the contributions (nmol/(min·m3)) of vehicle emission, coal + biomass burning, ship emission and secondary aerosol to DTTv in 2022 decreased by 63.0%, 65.2%, 66.5%, and 22.2%, respectively, compared to those in 2017/2018, which was consistent with the emission reduction of vehicle exhaust and coal consumption, the adoption of low-sulfur fuel oil used on board ships and the reduced production of WSOC. However, the contributions of dust + sea salt and industrial emission increased.

Quantitative impacts of meteorology and emissions on the long-term trend of O3 in the Yangtze River Delta (YRD), China from 2015 to 2022.

Extensive spatiotemporal analyses of long-trend surface ozone in the Yangtze River Delta (YRD) region and its meteorology-related and emission-related have not been systematically analyzed. In this study, by using 8-year-long (2015-2022) surface ozone observation data, we attempted to reveal the variation of multiple timescale components using the Kolmogorov-Zurbenko filter, and the effects of meteorology and emissions were quantitatively isolated using multiple linear regression with meteorological variables. The results showed that the short-term, seasonal, and long-term components accounted for daily maximum 8-hr average O3 (O3-8 hr) concentration, 46.4%, 45.9%, and 1.0%, respectively. The meteorological impacts account for an average of 71.8% of O3-8 hr, and the YRD's eastern and northern sections are meteorology-sensitive areas. Based on statistical analysis technology with empirical orthogonal function, the contribution of meteorology, local emission, and transport in the long-term component of O3-8 hr were 0.21%, 0.12%, and 0.6%, respectively. The spatiotemporal analysis indicated that a distinct decreasing spatial pattern could be observed from coastal cities towards the northwest, influenced by the monsoon and synoptic conditions. The central urban agglomeration north and south of the YRD was particularly susceptible to local pollution. Among the cities studied, Shanghai, Anqing, and Xuancheng, located at similar latitudes, were significantly impacted by atmospheric transmission-the contribution of Shanghai, the maximum accounting for 3.6%.

Spatial differentiation of carbon emissions from energy consumption based on machine learning algorithm: A case study during 2015-2020 in Shaanxi, China.

Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide. Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem. Previous studies relied on statistical regression models that failed to capture the complex nonlinear relationships between carbon emissions and characteristic variables. In this study, we propose a machine learning algorithm for carbon emissions, a Bayesian optimized XGboost regression model, using multi-year energy carbon emission data and nighttime lights (NTL) remote sensing data from Shaanxi Province, China. Our results demonstrate that the XGboost algorithm outperforms linear regression and four other machine learning models, with an R2 of 0.906 and RMSE of 5.687. We observe an annual increase in carbon emissions, with high-emission counties primarily concentrated in northern and central Shaanxi Province, displaying a shift from discrete, sporadic points to contiguous, extended spatial distribution. Spatial autocorrelation clustering reveals predominantly high-high and low-low clustering patterns, with economically developed counties showing high-emission clustering and economically relatively backward counties displaying low-emission clustering. Our findings show that the use of NTL data and the XGboost algorithm can estimate and predict carbon emissions more accurately and provide a complementary reference for satellite remote sensing image data to serve carbon emission monitoring and assessment. This research provides an important theoretical basis for formulating practical carbon emission reduction policies and contributes to the development of techniques for accurate carbon emission estimation using remote sensing data.

Insights into the seasonal characteristics of single particle aerosols in Chengdu based on SPAMS.

To investigate the seasonal characteristics in air pollution in Chengdu, a single particle aerosol mass spectrometry was used to continuously observe atmospheric fine particulate matter during one-month periods in summer and winter, respectively. The results showed that, apart from O3, the concentrations of other pollutants (CO, NO2, SO2, PM2.5 and PM10) were significantly higher in winter than in summer. All single particle aerosols were divided into seven categories: biomass burning (BB), coal combustion (CC), Dust, vehicle emission (VE), K mixed with nitrate (K-NO3), K mixed with sulfate and nitrate (K-SN), and K mixed with sulfate (K-SO4) particles. The highest contributions in both seasons were VE particles (24%). The higher contributions of K-SO4 (16%) and K-NO3 (10%) particles occurred in summer and winter, respectively, as a result of their different formation mechanisms. S-containing (K-SO4 and K-SN), VE, and BB particles caused the evolution of pollution in both seasons, and they can be considered as targets for future pollution reduction. The mixing of primary sources particles (VE, Dust, CC, and BB) with secondary components was stronger in winter than in summer. In summer, as pollution worsens, the mixing of primary sources particles with 62 [NO3]- weakened, but the mixing with 97 [HSO4]- increased. However, in winter, the mixing state of particles did not exhibit an obvious evolution rules. The potential source areas in summer were mainly distributed in the southern region of Sichuan, while in winter, besides the southern region, the contribution of the western region cannot be ignored.

Establishment and verification of anthropogenic speciated VOCs emission inventory of Central China.

Improving the accuracy of anthropogenic volatile organic compounds (VOCs) emission inventory is crucial for reducing atmospheric pollution and formulating control policy of air pollution. In this study, an anthropogenic speciated VOCs emission inventory was established for Central China represented by Henan Province at a 3 km × 3 km spatial resolution based on the emission factor method. The 2019 VOCs emission in Henan Province was 1003.5 Gg, while industrial process source (33.7%) was the highest emission source, Zhengzhou (17.9%) was the city with highest emission and April and August were the months with the more emissions. High VOCs emission regions were concentrated in downtown areas and industrial parks. Alkanes and aromatic hydrocarbons were the main VOCs contribution groups. The species composition, source contribution and spatial distribution were verified and evaluated through tracer ratio method (TR), Positive Matrix Factorization Model (PMF) and remote sensing inversion (RSI). Results show that both the emission results by emission inventory (EI) (15.7 Gg) and by TR method (13.6 Gg) and source contribution by EI and PMF are familiar. The spatial distribution of HCHO primary emission based on RSI is basically consistent with that of HCHO emission based on EI with a R-value of 0.73. The verification results show that the VOCs emission inventory and speciated emission inventory established in this study are relatively reliable.

Chemical characteristics and sources apportionment of volatile organic compounds in the primary urban area of Shijiazhuang, North China Plain.

VOCs (Volatile organic compounds) exert a vital role in ozone and secondary organic aerosol production, necessitating investigations into their concentration, chemical characteristics, and source apportionment for the effective implementation of measures aimed at preventing and controlling atmospheric pollution. From July to October 2020, online monitoring was conducted in the main urban area of Shijiazhuang to collect data on VOCs and analyze their concentrations and reactivity. Additionally, the PMF (positive matrix factorization) method was utilized to identify the VOCs sources. Results indicated that the TVOCs (total VOCs) concentration was (96.7 ± 63.4 µg/m3), with alkanes exhibiting the highest concentration of (36.1 ± 26.4 µg/m3), followed by OVOCs (16.4 ± 14.4 µg/m3). The key active components were alkenes and aromatics, among which xylene, propylene, toluene, propionaldehyde, acetaldehyde, ethylene, and styrene played crucial roles as reactive species. The sources derived from PMF analysis encompassed vehicle emissions, solvent and coating sources, combustion sources, industrial emissions sources, as well as plant sources, the contribution of which were 37.80%, 27.93%, 16.57%, 15.24%, and 2.46%, respectively. Hence, reducing vehicular exhaust emissions and encouraging neighboring industries to adopt low-volatile organic solvents and coatings should be prioritized to mitigate VOCs levels.

Assessment of internal exposure risk from metals pollution of occupational and non-occupational populations around a non-ferrous metal smelting plant.

Non-ferrous metal smelting poses significant risks to public health. Specifically, the copper smelting process releases arsenic, a semi-volatile metalloid, which poses an emerging exposure risk to both workers and nearby residents. To comprehensively understand the internal exposure risks of metal(loid)s from copper smelting, we explored eighteen metal(loid)s and arsenic metabolites in the urine of both occupational and non-occupational populations using inductively coupled plasma mass spectrometry with high-performance liquid chromatography and compared their health risks. Results showed that zinc and copper (485.38 and 14.00 µg/L), and arsenic, lead, cadmium, vanadium, tin and antimony (46.80, 6.82, 2.17, 0.40, 0.44 and 0.23 µg/L, respectively) in workers (n=179) were significantly higher compared to controls (n=168), while Zinc, tin and antimony (412.10, 0.51 and 0.15 µg/L, respectively) of residents were significantly higher than controls. Additionally, workers had a higher monomethyl arsenic percentage (MMA%), showing lower arsenic methylation capacity. Source appointment analysis identified arsenic, lead, cadmium, antimony, tin and thallium as co-exposure metal(loid)s from copper smelting, positively relating to the age of workers. The hazard index (HI) of workers exceeded 1.0, while residents and control were approximately at 1.0. Besides, all three populations had accumulated cancer risks exceeding 1.0 × 10-4, and arsenite (AsIII) was the main contributor to the variation of workers and residents. Furthermore, residents living closer to the smelting plant had higher health risks. This study reveals arsenic exposure metabolites and multiple metals as emerging contaminants for copper smelting exposure populations, providing valuable insights for pollution control in non-ferrous metal smelting.

Rising frequency of ozone-favorable synoptic weather patterns contributes to 2015-2022 ozone increase in Guangzhou.

Objective weather classification methods have been extensively applied to identify dominant ozone-favorable synoptic weather patterns (SWPs), however, the consistency of different classification methods is rarely examined. In this study, we apply two widely-used objective methods, the self-organizing map (SOM) and K-means clustering analysis, to derive ozone-favorable SWPs at four Chinese megacities in 2015-2022. We find that the two algorithms are largely consistent in recognizing dominant ozone-favorable SWPs for four Chinese megacities. In the case of classifying six SWPs, the derived circulation fields are highly similar with a spatial correlation of 0.99 between the two methods, and the difference in the mean frequency of each SWP is less than 7%. The six dominant ozone-favorable SWPs in Guangzhou are all characterized by anomaly higher radiation and temperature, lower cloud cover, relative humidity, and wind speed, and stronger subsidence compared to climatology mean. We find that during 2015-2022, the occurrence of ozone-favorable SWPs days increases significantly at a rate of 3.2 day/year, faster than the increases in the ozone exceedance days (3.0 day/year). The interannual variability between the occurrence of ozone-favorable SWPs and ozone exceedance days are generally consistent with a temporal correlation coefficient of 0.6. In particular, the significant increase in ozone-favorable SWPs in 2022, especially the Subtropical High type which typically occurs in September, is consistent with a long-lasting ozone pollution episode in Guangzhou during September 2022. Our results thus reveal that enhanced frequency of ozone-favorable SWPs plays an important role in the observed 2015-2022 ozone increase in Guangzhou.

Combustion aerosols and suspended dust with controlled processes in Lhasa: Elemental analysis and size distribution characteristics.

To explore air contamination resulting from special biomass combustion and suspended dust in Lhasa, the present study focused on the size distribution and chemical characteristics of particulate matter (PM) emission resulting from 7 types of non-fossil pollution sources. We investigated the concentration and size distribution of trace elements from 7 pollution sources collected in Lhasa. Combining Lhasa's atmospheric particulate matter data, enrichment factors (EFs) have been calculated to examine the potential impact of those pollution sources on the atmosphere quality of Lhasa. The highest mass concentration of total elements of biomass combustion appeared at PM0.4, and the second highest concentration existed in the size fraction 0.4-1 µm; the higher proportion (12 %) of toxic metals was produced by biomass combustion. The elemental composition of suspended dust and atmospheric particulate matter was close (except for As and Cd); the highest concentration of elements was all noted in PM2.5-10 (PM3-10). Potassium was found to be one of the main biomass markers. The proportion of Cu in suspended dust is significantly lower than that of atmospheric particulate matter (0.53 % and 3.75 %), which indicates that there are other anthropogenic sources. The EFs analysis showed that the Cr, Cu, Zn, and Pb produced by biomass combustion were highly enriched (EFs > 100) in all particle sizes. The EFs of most trace elements increased with decreasing particle size, indicating the greater influence of humanfactors on smaller particles.

Carbon emissions in China's steel industry from a life cycle perspective: Carbon footprint insights.

China is the most important steel producer in the world, and its steel industry is one of the most carbon-intensive industries in China. Consequently, research on carbon emissions from the steel industry is crucial for China to achieve carbon neutrality and meet its sustainable global development goals. We constructed a carbon dioxide (CO2) emission model for China's iron and steel industry from a life cycle perspective, conducted an empirical analysis based on data from 2019, and calculated the CO2 emissions of the industry throughout its life cycle. Key emission reduction factors were identified using sensitivity analysis. The results demonstrated that the CO2 emission intensity of the steel industry was 2.33 ton CO2/ton, and the production and manufacturing stages were the main sources of CO2 emissions, accounting for 89.84% of the total steel life-cycle emissions. Notably, fossil fuel combustion had the highest sensitivity to steel CO2 emissions, with a sensitivity coefficient of 0.68, reducing the amount of fossil fuel combustion by 20% and carbon emissions by 13.60%. The sensitivities of power structure optimization and scrap consumption were similar, while that of the transportation structure adjustment was the lowest, with a sensitivity coefficient of less than 0.1. Given the current strategic goals of peak carbon and carbon neutrality, it is in the best interest of the Chinese government to actively promote energy-saving and low-carbon technologies, increase the ratio of scrap steel to steelmaking, and build a new power system.

Exposure of individuals aged 18-44 years to personal care products in Beijing, China: Exposure profiles, possible influencing factors, and risk assessment.

Personal care products (PCPs) are a class of emerging pollutants that have attracted public concern owing to their harmful effects on humans and the environment. Biomonitoring data is valuable for insight the levels of PCPs in the human body and can be crucial for identifying potential health hazards. To gain a better understanding of timely exposure profiles and health risk of reproductive-age population to PCPs, we determined six parabens, six benzophenone-type ultraviolet filters, and three disinfectants in 256 urine samples collected from young adults aged 18-44 years in Beijing, China. The urinary levels of benzophenone-3 (BP-3) and 4-hydroxybenzophenone (4-OHBP) were significantly higher in summer compared to winter, suggesting these compounds have different seasonal usage patterns. Moreover, the total concentration of 15 PCPs in female was 430 ng/mL, approximately two times higher than that in male. P­chloro-m-xylenol (PCMX), as a new type of antibacterial agent, has the greatest level among all target analytes, indicating the increasingly use of this antibacterial alternative recently. Five potential influencing factors that lead to the elevated exposure level of PCPs were identified. Over 19% of the target population had a high hazard index value (greater than 1) which was attributed to exposure to propyl paraben (PrP), benzophenone-1 (BP-1), BP-3 and PCMX, indicating that PCPs may pose a relatively high exposure risk at environmental levels that should be a cause for concern.

Emission characteristics and probabilistic health risk of volatile organic compounds from leather sofa.

Furniture is identified as a vital volatile organic compound (VOC) emission source in the indoor environment. Leather has become the most common raw and auxiliary fabric material for upholstered furniture, particularly with extensive consumption in sofas, due to its abundant resources and efficient functions. Despite being widely traded across the world, little research has been conducted on the VOCs released by leather materials and their health risk assessment in the indoor environment. Accordingly, this study investigated the VOC emissions of leather with different grades and the health risk of the inhalation exposure. Based on the ultra-fast gas phase electronic nose (EN) and GC-FID/Qtof, the substantial emissions of aliphatic aldehyde ketones (Aks), particularly hexanal, appear to be the cause of off-flavor in medium and low grade (MG and LG) sofa leathers. The health risk assessment indicated that leather materials barely pose non-carcinogenic and carcinogenic effects to residents. Given the abundance of VOC sources and the accumulation of health risks in the indoor environment, more stringent specifications concerning qualitative and quantitative content should be extended to provide VOC treatment basic for the manufacturing industry and obtain better indoor air quality.

Mercury contents and potential exposure risk of rice-containing food products.

Mercury (Hg), especially methylmercury (MeHg), accumulation in rice grain due to rice paddy possessing conditions conducive to Hg methylation has led to human Hg exposure through consumption of rice-based daily meals. In addition to being a food staple, rice is widely used as a raw material to produce a vast variety of processed food products. Little is known about Hg levels in snacking rice-food products and potential Hg exposure from consumption of them, besides previous studies on infant rice cereals. Aiming to provide complementary information for a more complete assessment on Hg exposure risk originated from Hg-containing rice, this study determined total Hg (THg) and MeHg levels in 195 rice-containing and rice-free processed food products covering all major types of snack foods marketed in China and the estimated daily intake (EDI) of dietary Hg from the consumption of these foods. The results clearly showed THg and MeHg contents in rice-containing foods were significantly higher than rice-free products, suggesting the transfer of Hg and MeHg from the rice to the end products, even after manufacturing processes. Moreover, significant positive correlations were observed between THg, MeHg, or MeHg/THg ratio and rice content for samples containing multiple grains as ingredients, further indicating the deciding role of rice for Hg levels in the end food products. Although the EDI of THg and MeHg via rice-based food products were relatively low compared to the reference dose, it should be considered these snacking food products would contribute additive Hg intake outside of the daily regular meals.

Emission control status and future perspectives of diesel trucks in China.

Chinese diesel trucks are the main contributors to NOx and particulate matter (PM) vehicle emissions. An increase in diesel trucks could aggravate air pollution and damage human health. The Chinese government has recently implemented a series of emission control technologies and measures for air quality improvement. This paper summarizes recent control technologies and measures for diesel truck emissions in China and introduces the comprehensive application of control technologies and measures in Beijing-Tianjin-Hebei and surrounding regions. Remote online monitoring technology has been adopted according to the China VI standard for heavy-duty diesel trucks, and control measures such as transportation structure adjustment and heavy pollution enterprise classification control continue to support the battle action plan for pollution control. Perspectives and suggestions are provided for promoting pollution control and supervision of diesel truck emissions: adhere to the concept of overall management and control, vigorously promote the application of systematic and technological means in emission monitoring, continuously facilitate cargo transportation structure adjustment and promote new energy freight vehicles. This paper aims to accelerate the implementation of control technologies and measures throughout China. China is endeavouring to control diesel truck exhaust pollution. China is willing to cooperate with the world to protect the global ecological environment.

Investigation of spatiotemporal distribution and formation mechanisms of ozone pollution in eastern Chinese cities applying convolutional neural network.

Severe ground-level ozone (O3) pollution over major Chinese cities has become one of the most challenging problems, which have deleterious effects on human health and the sustainability of society. This study explored the spatiotemporal distribution characteristics of ground-level O3 and its precursors based on conventional pollutant and meteorological monitoring data in Zhejiang Province from 2016 to 2021. Then, a high-performance convolutional neural network (CNN) model was established by expanding the moment and the concentration variations to general factors. Finally, the response mechanism of O3 to the variation with crucial influencing factors is explored by controlling variables and interpolating target variables. The results indicated that the annual average MDA8-90th concentrations in Zhejiang Province are higher in the northern and lower in the southern. When the wind direction (WD) ranges from east to southwest and the wind speed (WS) ranges between 2 and 3 m/sec, higher O3 concentration prone to occur. At different temperatures (T), the O3 concentration showed a trend of first increasing and subsequently decreasing with increasing NO2 concentration, peaks at the NO2 concentration around 0.02 mg/m3. The sensitivity of NO2 to O3 formation is not easily affected by temperature, barometric pressure and dew point temperature. Additionally, there is a minimum [Formula: see text] at each temperature when the NO2 concentration is 0.03 mg/m3, and this minimum [Formula: see text] decreases with increasing temperature. The study explores the response mechanism of O3 with the change of driving variables, which can provide a scientific foundation and methodological support for the targeted management of O3 pollution.

Unintentional emissions of polychlorinated naphthalenes in China: Sources, composition, and historical trends.

Polychlorinated naphthalenes (PCNs) are detrimental to human health and the environment. With the commercial production of PCNs banned, unintentional releases have emerged as a significant environmental source. However, relevant information is still scarce. In this study, provincial emissions for eight PCNs homologues from 37 sources in the Chinese mainland during the period of 1960-2019 were estimated based on a source-specific and time-varying emission factor database. The results showed that the total PCNs emissions in 2019 reached 757.0 kg with Hebei ranked at the top among all the provinces and iron & steel industry as the biggest source. Low-chlorinated PCNs comprised 90% of emissions by mass, while highly chlorinated PCNs dominated in terms of toxicity, highlighting divergent priorities for mitigating emissions and safeguarding human health. The emissions showed an overall upward trend from 1960 to 2019 driven by emission increase from iron & steel industry in terms of source, and from North China and East China in terms of geographic area. Per-capita emissions followed an inverted U-shaped environmental Kuznets curve while emission intensities decreased with increasing per-capita Gross Domestic Product (GDP) following a nearly linear pattern when log-transformed.

Dynamic evaluation of China's atmospheric environmental pressure from 2008 to 2017: Trends and drivers.

Evaluating the pressure of atmospheric pollutant emissions on the atmospheric environment is crucial for effective pollution control and emission reduction policies. This study introduces a novel Atmospheric Environmental Pressure Index (AEPI) and employs a dynamic comprehensive method to evaluate China's Atmospheric Environmental Pressure (AEP) across 31 provinces from 2008 to 2017. The drivers of AEP were analyzed using a spatial panel data model, uncovering the integral role of pollution reduction policies, particularly the Air Pollution Prevention and Control Action Plan, which led to a 25% reduction in AEP during its enforcement. Our findings reveal significant spatial disparities in AEP, with higher levels in the Beijing-Tianjin-Hebei and Yangtze River Delta regions. The regression analysis identifies economic development, industrial structure, energy efficiency, environmental regulations, and urbanization as key influencing factors, though their impacts vary across different regions, suggesting the need for region-specific pollution control policies. Furthermore, the shift in the AEP gravity center from 2008 to 2017 indicated a southeastward movement, suggesting the necessity to focus air pollution control efforts on the southeast provinces. In conclusion, the AEPI developed in this study enables comparative analysis of AEP across different regions and facilitates the monitoring of long-term trends, which is valuable in guiding regional air pollution control in China.