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Background: In 2013, China released the Air Pollution Prevention and Control Action Plan (Action Plan), which set the roadmap for national air pollution control actions for the period of 2013 to 2017. A decrease in the fine particulate matter with aerodynamic diameter ≤ 2.5μ m (PM 2.5 ) concentration may lead to a substantial benefit for human health. Objective: We aimed to quantify the relative contributions four factors: emission reductions, changed meteorology, population growth, and a change in baseline mortality rates to the reducedPM 2.5 -related mortality (PM 2.5 -mortality) during the 2013–2017 period and evaluate the importance of emission controls for human health protection in China. Methods: The integrated exposure–response function was adopted to estimate the chronic health effects ofPM 2.5 . The annualPM 2.5 concentrations were estimated from chemical transport model simulations combined with surface observations for 2013 and 2017. Relative contributions toPM 2.5 -mortality from emission reductions and the three factors were individually quantified through scenario analysis. Results: The estimated totalPM 2.5 -mortality in China was 1.389 million [95% confidence interval (CI): 1.005 million, 1.631 million] in 2013 but was substantially reduced to 1.102 million (95% CI: 0.755 million, 1.337 million) in 2017. Emission controls contributed 88.7% to this reduction inPM 2.5 -mortality, while changed meteorology, the change in baseline mortality rates, and population growth during 2013–2017 contributed 9.6, 3.8, and − 2.2 % , respectively. Conclusions: The implementation of the Action Plan has significantly reduced thePM 2.5 concentration in regions of China where population density is high, dominating the decline inPM 2.5 -mortality during 2013–2017. However, the health burden ofPM 2.5 pollution in China is still extremely high compared with that in other developed countries. An aggressive air pollution control strategy should be implemented in densely populated areas to further reduce the health burden.

A 5-year Clean Air Action Plan was implemented in 2013 to reduce air pollutant emissions and improve ambient air quality in Beijing. Assessment of this action plan is an essential part of the decision-making process to review its efficacy and to develop new policies. Both statistical and chemical transport modelling have been previously applied to assess the efficacy of this action plan. However, inherent uncertainties in these methods mean that new and independent methods are required to support the assessment process. Here, we applied a machine-learning-based random forest technique to quantify the effectiveness of Beijing's action plan by decoupling the impact of meteorology on ambient air quality. Our results demonstrate that meteorological conditions have an important impact on the year-to-year variations in ambient air quality. Further analyses show that the PM2.5 mass concentration would have broken the target of the plan (2017 annual PM2.5<60 µg m−3) were it not for the meteorological conditions in winter 2017 favouring the dispersion of air pollutants. However, over the whole period (2013–2017), the primary emission controls required by the action plan have led to significant reductions in PM2.5, PM10, NO2, SO2, and CO from 2013 to 2017 of approximately 34 %, 24 %, 17 %, 68 %, and 33 %, respectively, after meteorological correction. The marked decrease in PM2.5 and SO2 is largely attributable to a reduction in coal combustion. Our results indicate that the action plan has been highly effective in reducing the primary pollution emissions and improving air quality in Beijing. The action plan offers a successful example for developing air quality policies in other regions of China and other developing countries.

● Major challenges of air pollution control in China are summarized. ● A\"health-oriented\" air pollution control strategy is proposed. ● Directions of air quality standard amendments are discussed. ● \"One-atmosphere\" concept shall be adopted to synergistically address multiple issues. Air pollution is one of the most challenging environmental issues in the world. China has achieved remarkable success in improving air quality in last decade as a result of aggressive air pollution control policies. However, the average fine particulate matter (PM 2.5) concentration in China is still about six times of the World Health Organization (WHO) Global Air Quality Guidelines (AQG) and causing significant human health risks. Extreme emission reductions of multiple air pollutants are required for China to achieve the AQG. Here we identify the major challenges in future air quality improvement and propose corresponding control strategies. The main challenges include the persistently high health risk attributed to PM 2.5 pollution, the excessively loose air quality standards, and coordinated control of air pollution, greenhouse gases (GHGs) emissions and emerging pollutants. To further improve air quality and protect human health, a health-oriented air pollution control strategy shall be implemented by tightening the air quality standards as well as optimizing emission reduction pathways based on the health risks of various sources. In the meantime, an \"one-atmosphere\" concept shall be adopted to strengthen the synergistic control of air pollutants and GHGs and the control of non-combustion sources and emerging pollutants shall be enhanced.

pH is an important property of aerosol particles but is difficult to measure directly. Several studies have estimated the pH values for fine particles in northern China winter haze using thermodynamic models (i.e., E-AIM and ISORROPIA) and ambient measurements. The reported pH values differ widely, ranging from close to 0 (highly acidic) to as high as 7 (neutral). In order to understand the reason for this discrepancy, we calculated pH values using these models with different assumptions with regard to model inputs and particle phase states. We find that the large discrepancy is due primarily to differences in the model assumptions adopted in previous studies. Calculations using only aerosol-phase composition as inputs (i.e., reverse mode) are sensitive to the measurement errors of ionic species, and inferred pH values exhibit a bimodal distribution, with peaks between −2 and 2 and between 7 and 10, depending on whether anions or cations are in excess. Calculations using total (gas plus aerosol phase) measurements as inputs (i.e., forward mode) are affected much less by these measurement errors. In future studies, the reverse mode should be avoided whereas the forward mode should be used. Forward-mode calculations in this and previous studies collectively indicate a moderately acidic condition (pH from about 4 to about 5) for fine particles in northern China winter haze, indicating further that ammonia plays an important role in determining this property. The assumed particle phase state, either stable (solid plus liquid) or metastable (only liquid), does not significantly impact pH predictions. The unrealistic pH values of about 7 in a few previous studies (using the standard ISORROPIA model and stable state assumption) resulted from coding errors in the model, which have been identified and fixed in this study.

China has been experiencing fine particle (i.e., aerodynamic diameters ≤ 2.5 μm; PM2.5) pollution and acid rain in recent decades, which exert adverse impacts on human health and the ecosystem. Recently, ammonia (i.e., NH₃) emission reduction has been proposed as a strategic option to mitigate haze pollution. However, atmospheric NH₃ is also closely bound to nitrogen deposition and acid rain, and comprehensive impacts of NH₃ emission control are still poorly understood in China. In this study, by integrating a chemical transport model with a high-resolution NH₃ emission inventory, we find that NH₃ emission abatement can mitigate PM2.5 pollution and nitrogen deposition but would worsen acid rain in China. Quantitatively, a 50% reduction in NH₃ emissions achievable by improving agricultural management, along with a targeted emission reduction (15%) for sulfur dioxide and nitrogen oxides, can alleviate PM2.5 pollution by 11−17% primarily by suppressing ammonium nitrate formation. Meanwhile, nitrogen deposition is estimated to decrease by 34%, with the area exceeding the critical load shrinking from 17% to 9% of China’s terrestrial land. Nevertheless, this NH₃ reduction would significantly aggravate precipitation acidification, with a decrease of as much as 1.0 unit in rainfall pH and a corresponding substantial increase in areas with heavy acid rain. An economic evaluation demonstrates that the worsened acid rain would partly offset the total economic benefit from improved air quality and less nitrogen deposition. After considering the costs of abatement options, we propose a region-specific strategy for multipollutant controls that will benefit human and ecosystem health.

Mercury is a potent neurotoxin that poses health risks to the global population. Anthropogenic mercury emissions to the atmosphere are projected to decrease in the future due to enhanced policy efforts such as the Minamata Convention, a legally-binding international treaty entered into force in 2017. Here, we report the development of a comprehensive climate-atmosphere-land-ocean-ecosystem and exposure-risk model framework for mercury and its application to project the health effects of future atmospheric emissions. Our results show that the accumulated health effects associated with mercury exposure during 2010–2050 are $19 (95% confidence interval: 4.7–54) trillion (2020 USD) realized to 2050 (3% discount rate) for the current policy scenario. Our results suggest a substantial increase in global human health cost if emission reduction actions are delayed. This comprehensive modeling approach provides a much-needed tool to help parties to evaluate the effectiveness of Hg emission controls as required by the Minamata Convention. Mercury is a neurotoxin and pollutant with enhanced emissions from anthropogenic activities. Here, the authors develop a global emissions, transport, and human risk model and find substantial future losses in revenue and public health if emission reductions proposed by the Minamata Convention are delayed.

We identify sources (fossil fuel combustion versus biomass burning) of black carbon (BC) in the atmosphere and in deposition using a global 3-D chemical transport model GEOS-Chem. We validate the simulated sources against carbon isotope measurements of BC around the globe and find that the model reproduces mean biomass burning contribution (fbb; %) in various regions within a factor of 2 (except in Europe, where fbb is underestimated by 63 %). GEOS-Chem shows that contribution from biomass burning in the Northern Hemisphere (fbb: 35±14 %) is much less than that in the Southern Hemisphere (50±11 %). The largest atmospheric fbb is in Africa (64±20 %). Comparable contributions from biomass burning and fossil fuel combustion are found in southern (S) Asia (53±10 %), southeastern (SE) Asia (53±11 %), S America (47±14 %), the S Pacific (47±7 %), Australia (53±14 %) and the Antarctic (51±2 %). fbb is relatively small in eastern Asia (40±13 %), Siberia (35±8 %), the Arctic (33±6 %), Canada (31±7 %), the US (25±4 %) and Europe (19±7 %). Both observations and model results suggest that atmospheric fbb is higher in summer (59 %–78 %, varying with sub-regions) than in winter (28 %–32 %) in the Arctic, while it is higher in winter (42 %–58 %) and lower in summer (16 %–42 %) over the Himalayan–Tibetan Plateau. The seasonal variations of Atmosphericfbb are relatively flat in North America, Europe and Asia. We conducted four experiments to investigate the uncertainties associated with biofuel emissions, hygroscopicity of BC in fresh emissions, the aging rate and size-resolved wet scavenging. We find that doubling biofuel emissions for domestic heating north of 45∘ N increases fbb values in Europe in winter by ∼30 %, reducing the discrepancy between observed and modeled atmospheric fbb from −63 % to −54 %. The remaining large negative discrepancy between model and observations suggests that the biofuel emissions are probably still underestimated at high latitudes. Increasing the fraction of thickly coated hydrophilic BC from 20 % to 70 % in fresh biomass burning plumes increases the fraction of hydrophilic BC in biomass burning plumes by 0 %–20 % (varying with seasons and regions) and thereby reduces atmospheric fbb by up to 11 %. Faster aging (4 h e-folding time versus 1.15 d e-folding time) of BC in biomass burning plumes reduces atmospheric fbb by 7 % (1 %–14 %, varying with seasons and regions), with the largest reduction in remote regions, such as the Arctic, the Antarctic and the S Pacific. Using size-resolved scavenging accelerates scavenging of BC particles in both fossil fuel and biomass burning plumes, with a faster scavenging of BC in fossil fuel plumes. Thus, atmospheric fbb increases in most regions by 1 %–14 %. Overall, atmospheric fbb is determined mainly by fbb in emissions and, to a lesser extent, by atmospheric processes, such as aging and scavenging. This confirms the assumption that fbb in local emissions determines atmospheric fbb in previous studies, which compared measured atmospheric fbb directly with local fbb in bottom-up emission inventories.

Objective: To explore the functional mechanisms of Suanzaoren decoction (SZRD) for treating insomnia using network pharmacology and molecular docking. Methods: The active ingredients and corresponding targets of SZRD were obtained from the Traditional Chinese Medicine Systems Pharmacology database, and then, the names of the target proteins were standardized using the UniProt database. The insomnia-related targets were obtained from the GeneCards, DisGeNET, and DrugBank databases. Next, a Venn diagram comprising the drug and disease targets was created, and the intersecting targets were used to draw the active ingredient-target network diagram using Cytoscape software. Next, the STRING database was used to build a protein-protein interaction network, followed by cluster analysis using the MCODE plug-in. The Database for Annotation, Visualization, Integrated Discovery (i.e., DAVID), and the Metascape database were used for Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. AutoDock Vina and Pymol software were used for molecular docking. Results: SZRD contained 138 active ingredients, corresponding to 239 targets. We also identified 2,062 insomnia-related targets, among which, 95 drug and disease targets intersected. The GO analysis identified 490, 62, and 114 genes related to biological processes, cellular components, and molecular functions, respectively. Lipid and atherosclerosis, chemical carcinogen-receptor activation, and neuroactive ligand-receptor interaction were the most common pathways in the KEGG analysis. Molecular docking demonstrated that the primary active components of SZRD for insomnia had good binding capabilities with the core proteins in PPI network. Conclusion: Insomnia treatment with SZRD involves multiple targets and signaling pathways, which may improve insomnia by reducing inflammation, regulating neurotransmitters.

The Minamata Convention on Mercury, with its objective to protect human health and the environment from the dangers of mercury (Hg), entered into force in 2017. The Convention outlines a life-cycle approach to the production, use, emissions, releases, handling, and disposal of Hg. As it moves into the implementation phase, scientific work and information are critically needed to support decision-making and management. This paper synthesizes existing knowledge and examines three areas in which researchers across the natural sciences, engineering, and social sciences can mobilize and disseminate knowledge in support of Hg abatement and the realization of the Convention’s objective: (1) uses, emissions, and releases; (2) support, awareness raising, and education; and (3) impacts and effectiveness. The paper ends with a discussion of the future of Hg science and policy.

China has committed to reaching carbon neutrality by 2060, which will require a drastic cut in greenhouse gas (GHG) emissions from all sectors, including those from agricultural activities. A comprehensive, long-term, and spatially-precise profile of agricultural GHG emissions can help to accurately understand drivers of historical emissions and their implications for future mitigation. This study constructs province-level agricultural GHG emissions in China from 1978 to 2016. It considers primary and secondary emissions from a full range of agricultural activities related to crop farming, including crop residue open burning, rice cultivation, cropland change, cropland emissions, machinery use, nitrogen fertilizer production, and pesticide production. Annual or interpolated activity data from official sources and the latest emission factors available for China were adopted in this study. The data can be used in spatial and temporal analysis of emissions from cropping systems as well as the design of mitigation strategy in China. Measurement(s) greenhouse gas Technology Type(s) digital curation • computational modeling technique Factor Type(s) date • province Sample Characteristic - Environment cultivated environment • climate change Sample Characteristic - Location China Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14753940