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The application of low-condensation diesel in cold regions with extremely low ambient temperatures (−14 to −29 °C) has enabled the operation of diesel vehicles. Still, it may contribute to heavy haze pollution in cold regions during winter. Here we examine pollutant emissions from low-condensation diesel in China. We measure the emissions of elemental carbon (EC), organic carbon (OC), and elements, including heavy metals such as arsenic (As). Our results show that low-condensation diesel increased EC and OC emissions by 2.5 and 2.6 times compared to normal diesel fuel, respectively. Indicators of vehicular sources, including EC, As, lead (Pb), cadmium (Cd), chromium (Cr), nickel (Ni), and manganese (Mn), increased by approximately 20.2–162.5% when using low-condensation diesel. Seasonal variation of vehicular source indicators, observed at road site ambient environments revealed the enhancement of PM2.5 pollution by the application of low-condensation diesel in winter. These findings suggest that −35# diesel, a low-cetane index diesel, may enhance air pollution in winter, according to a dynamometer test conducted in laboratory. It raises questions about whether higher emissions are released if −35# diesel is applied to running vehicles in real-world cold ambient environments.

Nitrogen oxides (NOx), significant contributors to air pollution and climate change, form aerosols and ozone in the atmosphere. Accurate, timely, and transparent information on NOx emissions is essential for decision-making to mitigate both haze and ozone pollution. However, a comprehensive understanding of the trends and drivers behind anthropogenic NOx emissions from China—the world's largest emitter—has been lacking since 2020 due to delays in emissions reporting. Here we show a consistent decline in China's NOx emissions from 2020 to 2022, despite increased fossil fuel consumption, utilizing satellite observations as constraints for NOx emission estimates through atmospheric inversion. This reduction is corroborated by data from two independent spaceborne instruments: the TROPOspheric Monitoring Instrument (TROPOMI) and the Ozone Monitoring Instrument (OMI). Notably, a reduction in transport emissions, largely due to the COVID-19 lockdowns, slightly decreased China's NOx emissions in 2020. In subsequent years, 2021 and 2022, reductions in NOx emissions were driven by the industry and transport sectors, influenced by stringent air pollution controls. The satellite-based inversion system developed in this study represents a significant advancement in the real-time monitoring of regional air pollution emissions from space.

Abstract A transition away from coal power always maintains a high level of complexity as there are several overlapping considerations such as technical feasibility, economic costs, and environmental and health impacts. Here, we explore the cost-effectiveness uncertainty brought by policy implementation disturbances of different coal power phaseout and new-built strategies (i.e., the disruption of phaseout priority) in China based on a developed unit-level uncertainty assessment framework. We reveal the opportunity and risk of coal transition decisions by employing preference analysis. We find that, the uncertainty of a policy implementation might lead to potential delays in yielding the initial positive annual net benefits. For example, a delay of six years might occur when implementing the prior phaseout practice. A certain level of risk remains in the implementation of the phaseout policy, as not all strategies can guarantee the cumulative positive net benefits from 2018–2060. Since the unit-level heterogeneities shape diverse orientation of the phaseout, the decision-making preferences would remarkably alter the selection of a coal power transition strategy. More strikingly, the cost-effectiveness uncertainty might lead to missed opportunities in identifying an optimal strategy. Our results highlight the importance of minimizing the policy implementation disturbance, which helps mitigate the risk of negative benefits and strengthen the practicality of phaseout decisions.

Wastewater treatment is an important source of greenhouse gases (GHGs). Yet large uncertainties remain in the quantification of GHG emissions from municipal wastewater treatment plants (MWWTPs) in China. A high-resolution and technology-specific emission inventory is still lacking to support mitigation strategies of MWWTPs. Here we develop a plant-level and technology-based MWWTP emission inventory for China covering 8703 plants and 19 treatment technology categories by compiling and harmonizing the most up-to-date facility-level databases. China's methane (CH4) and nitrous oxide (N2O) emissions from MWWTPs in 2020 are estimated to be 150.6 Gg and 22.0 Gg, respectively, with the uncertainty range of −30% to 37% and −30% to 26% at 95% confidence interval. We find an emission inequality across cities, with the richest cities emitting two times more CH4 and N2O per capita from municipal wastewater treatment than the poorest cities. The emitted CH4 and N2O are dominated by Anaerobic/Anoxic/Oxic-, Sequencing Batch Reactor-, Oxidation Ditch-, and Anoxic/Oxic-based MWWTPs of less than 20 years old. Considering the relatively young age structure of China's MWWTPs, the committed emissions highlight the importance of reducing on-site GHG emissions by optimization of operating conditions and innovation management. The emission differences among our estimates, previous studies, and the Intergovernmental Panel on Climate Change guidelines are largely attributed to the uncertainties in emission factors, implying the urgent need for more plant-integrated measurements to improve the accuracy of emission accounting.

Abstract With the decreasing regional-transported levels, the health risk assessment derived from fine particulate matter (PM2.5) has become insufficient to reflect the contribution of local source heterogeneity to the exposure differences. Here, we combined the both ultra-high-resolution PM2.5 concentration with population distribution to provide the personal daily PM2.5 internal dose considering the indoor/outdoor exposure difference. A 30-m PM2.5 assimilating method was developed fusing multiple auxiliary predictors, achieving higher accuracy (R2 = 0.78–0.82) than the chemical transport model outputs without any post-simulation data-oriented enhancement (R2 = 0.31–0.64). Weekly difference was identified from hourly mobile signaling data in 30-m resolution population distribution. The population-weighted ambient PM2.5 concentrations range among districts but fail to reflect exposure differences. Derived from the indoor/outdoor ratio, the average indoor PM2.5 concentration was 26.5 μg/m3. The internal dose based on the assimilated indoor/outdoor PM2.5 concentration shows high exposure diversity among sub-groups, and the attributed mortality increased by 24.0% than the coarser unassimilated model.

Wind energy has become one of the most important measures for China to achieve its carbon neutrality goal. The spatial and temporal evolvement of economic competitiveness for wind energy becomes an important concern in shaping the decarbonization pathway in China. There has been an urgent need in power system planning to model the future dynamics of cost decline and supply potential for wind power in the context of carbon neutrality until 2060. Existing studies often fail to capture the rapid decline in the cost of wind power generation in recent years, and the prediction of wind power cost decline is more conservative than the reality. This study constructs an integrated model to evaluate the cost-competitiveness and grid parity potential of China's onshore wind electricity at fine spatial resolution with updated parameters. Results indicate that the total onshore wind potential amounts to 54.0 PWh. The average levelized cost of wind power is expected to decline from CNY 0.39 kWh−1 in 2020 to CNY 0.30 and CNY 0.21 kWh−1 in 2030 and 2060. 28.3%, 67.6%, and 97.6% of the technical potentials hold power costs lower than coal power in 2020, 2030, and 2060.

China is now confronting the intertwined challenges of air pollution and climate change. Given the high synergies between air pollution abatement and climate change mitigation, the Chinese government is actively promoting synergetic control of these two issues. The Synergetic Roadmap project was launched in 2021 to track and analyze the progress of synergetic control in China by developing and monitoring key indicators. The Synergetic Roadmap 2022 report is the first annual update, featuring 20 indicators across five aspects: synergetic governance system and practices, progress in structural transition, air pollution and associated weather-climate interactions, sources, sinks, and mitigation pathway of atmospheric composition, and health impacts and benefits of coordinated control. Compared to the comprehensive review presented in the 2021 report, the Synergetic Roadmap 2022 report places particular emphasis on progress in 2021 with highlights on actions in key sectors and the relevant milestones. These milestones include the proportion of non-fossil power generation capacity surpassing coal-fired capacity for the first time, a decline in the production of crude steel and cement after years of growth, and the surging penetration of electric vehicles. Additionally, in 2022, China issued the first national policy that synergizes abatements of pollution and carbon emissions, marking a new era for China's pollution-carbon co-control. These changes highlight China's efforts to reshape its energy, economic, and transportation structures to meet the demand for synergetic control and sustainable development. Consequently, the country has witnessed a slowdown in carbon emission growth, improved air quality, and increased health benefits in recent years.

Abstract The toughest‐ever clean air actions to date in China have helped to reduce national air pollutant emissions significantly in recent years. However, the heterogeneous mitigation paths and their determinated factors among regions were less concerned. To direct regional mitigation strategies more efficiently, we compiled a time‐series emission inventory of Chinese 30 provinces for SO2, NOx, primary PM2.5 and CO2 at detailed socioeconomic sectors, and then used spatial‐temporal index decomposition analysis to evaluate the driving forces for changes in regional pollutant emissions and emission intensities from 2012 to 2017 and from 2017 to 2020, separately. Our results showed that end‐of‐pipe control measures dominated the decreasing trend of China's pollutant emissions (38%–68% for SO2, NOx, and primary PM2.5), but their relative dominance diminished gradually, and the effects from energy policy emerged, even outweighing the former in southern areas during the second phase. Though driven by different factors, the chemistry, nonmetal, metal, energy and residential sectors dominated regional reduction trend and with varying degrees. Clean air action led to the convergence of regional emission intensity, while optimizing and upgrading industrial structure and improving energy efficiency is still necessary for further reduction in northern and western areas at present.

Abstract The global surge in solar photovoltaic (PV) power has featured spatial specialization from manufacturing to installation along its industrial chain. Yet how to improve PV climate benefits are under-investigated. Here we explore the evolution of net greenhouse gas (GHG) mitigation of PV industry from 2009–2060 with a spatialized-dynamic life-cycle-analysis. Results suggest a net GHG mitigation of 1.29 Gt CO2-equivalent from 2009–2019, achieved by 1.97 Gt of mitigation from installation minus 0.68 Gt of emissions from manufacturing. The highest net GHG mitigation among future manufacturing-installation-scenarios to meet 40% global power demand in 2060 is as high as 204.7 Gt from 2020–2060, featuring manufacturing concentrated in Europe and North America and prioritized PV installations in carbon-intensive nations. This represents 97.5 Gt more net mitigation than the worst-case scenario, equivalent to 1.9 times 2020 global GHG emissions. The results call for strategic international coordination of PV industrial chain to increase GHG net mitigation.

It is well recognized that carbon dioxide and air pollutants share similar emission sources so that synergetic policies on climate change mitigation and air pollution control can lead to remarkable co-benefits on greenhouse gas reduction, air quality improvement, and improved health. In the context of carbon peak, carbon neutrality, and clean air policies, this perspective tracks and analyzes the process of the synergetic governance of air pollution and climate change in China by developing and monitoring 18 indicators. The 18 indicators cover the following five aspects: air pollution and associated weather-climate conditions, progress in structural transition, sources, inks, and mitigation pathway of atmospheric composition, health impacts and benefits of coordinated control, and synergetic governance system and practices. By tracking the progress in each indicator, this perspective presents the major accomplishment of coordinated control, identifies the emerging challenges toward the synergetic governance, and provides policy recommendations for designing a synergetic roadmap of Carbon Neutrality and Clean Air for China.

Product trade plays an increasing role in relocating production and the associated air pollution impact among sectors and regions. While a comprehensive depiction of atmospheric pollution redistribution through trade chains is missing, which may hinder targeted clean air cooperation among sectors and regions. Here, we combined five state-of-the-art models from physics, economy, and epidemiology to track the anthropogenic fine particle matters (PM2.5) related premature mortality along the supply chains within China in 2017. Our results highlight the key sectors that affect PM2.5-related mortality from both production and consumption perspectives. The consumption-based effects from food, light industry, equipment, construction, and services sectors, caused 2–22 times higher deaths than those from a production perspective and totally contributed 63% of the national total. From a cross-boundary perspective, 25.7% of China's PM2.5-related deaths were caused by interprovincial trade, with the largest transfer occurring from the central and northern regions to well-developed east coast provinces. Capital investment dominated the cross-boundary effect (56% of the total) by involving substantial equipment and construction products, which greatly rely on product exports from regions with specific resources. This supply chain-based analysis provides a comprehensive quantification and may inform more effective joint-control efforts among associated regions and sectors from a health risk perspective.

The Chishui River Valley is a microscale ecology-preservation area with industrial clusters. The significance of evaluating vehicular emissions has been gradually highlighted with the rapid development of the local transportation and tourism sectors. This study provides the first estimates based on both bottom-up and top-down approaches. The annual total emissions of CO, NOx, hydrocarbons (HC), PM10, and PM2.5 in 2019 were 347.8, 189.6, 46.3, 6.9, and 6.3 Mg, respectively. Trucks contributed the most (55%) to the NOx emissions, followed by heavy-duty passenger vehicles (26%). In contrast, light-duty passenger vehicles and motorcycles generated 75% of the HC emissions. The superior accuracy of highly spatial and temporal bottom-up estimates versus top-down estimates is validated by the similar variation trends of hourly emission intensities and enhanced concentrations relative to background observations for both NOx and CO, with Pearson correlation coefficients between the intensities and concentrations ranging from 0.79 to 0.85. Historical HC emissions peaked in 2013, followed by a sharp decline in 2014 and a continuous rise since then, whereas NOx emissions have kept increasing since 2010. These indicated the necessity and urgency of effective vehicular emission mitigations. Based on scenario analysis, traffic restrictions combined with upgrading the emission standards of admitted vehicles will possess huge emission reduction potentials. Future recommendations about establishing a low emission zone in the valley and supporting policies were introduced.

China’s clean air action stimulated a net accumulative reduction of 2.43 Gt CO2 emission from 2013-2020. Phase-out and upgrades of outdated, polluting, and inefficient combustion facilities have promoted the transition of the country’s energy system.

Abstract Globally consistent measurements of airborne metal concentrations in fine particulate matter (PM2.5) are important for understanding potential health impacts, prioritizing air pollution mitigation strategies, and enabling global chemical transport model development. PM2.5 filter samples (N ~ 800 from 19 locations) collected from a globally distributed surface particulate matter sampling network (SPARTAN) between January 2013 and April 2019 were analyzed for particulate mass and trace metals content. Metal concentrations exhibited pronounced spatial variation, primarily driven by anthropogenic activities. PM2.5 levels of lead, arsenic, chromium, and zinc were significantly enriched at some locations by factors of 100–3000 compared to crustal concentrations. Levels of metals in PM2.5 and PM10 exceeded health guidelines at multiple sites. For example, Dhaka and Kanpur sites exceeded the US National Ambient Air 3-month Quality Standard for lead (150 ng m−3). Kanpur, Hanoi, Beijing and Dhaka sites had annual mean arsenic concentrations that approached or exceeded the World Health Organization’s risk level for arsenic (6.6 ng m−3). The high concentrations of several potentially harmful metals in densely populated cites worldwide motivates expanded measurements and analyses.

The COVID-19 pandemic has stopped many human activities, which has had significant impact on emissions of greenhouse gases. Here, the authors present daily estimates of country-level CO2 emissions for different economic sectors and show that there has been a 8.8% decrease in global CO2 emissions in the first half of 2020.

Air pollution can affect people’s emotional status and well-being. Here, the authors simulate fixed-scene images to show that under the atmospheric conditions in Beijing, negative emotions occur when air quality index of PM2.5 increases to approximately 150.

Considering air pollution-induced health risks from a consumption perspective is important. Here the authors evaluated the premature deaths resulting from household consumption across 30 Chinese provinces and find that rural households can cause a similar number of pollution-induced deaths as urban households despite a larger and wealthier urban population, due to the combustion of solid fuel.

To improve air quality, China has been implementing strict clean air policies since 2013. These policies not only substantially improved air quality but may also modify the spatial distribution of air pollution, since urban emission sources were under stricter control and some were moved to rural regions with lower air quality improvement targets and lacking of monitoring. Here, we predicted satellite-based monthly PM2.5 concentrations during 2000–2018 at a 1-km resolution with complete spatial-temporal coverage to analyze changes in the spatial pattern of PM2.5 pollution in China. We found that the PM2.5 concentration in urban regions was higher than that in rural regions of the same city by an average of 3.3 μg/m3 during 2000–2018. This urban-rural disparity in PM2.5 concentration significantly increased from 2.5 μg/m3 in 2000 and peaked in 2007 of 3.8 μg/m3, then it sharply declined by 49% during 2013–2018 with the implementation of clean air policies. This shrinkage in the urban-rural PM2.5 gap was partly due to the 1.3 μg/m3 greater average decrease in the PM2.5 level in the urban region than in the rural region of the same town during 2013–2018 on average. We also observed that cities that started monitoring earlier experienced greater decreases in the urban-rural PM2.5 difference, and regions surrounding monitor showed significantly greater PM2.5 decrease than regions far away from monitor during 2013–2018. Additionally, clean air policies modified the relationship between PM2.5 concentrations and per capita gross domestic product (GDP), leading to a lower PM2.5 level with the same per capita GDP after 2013. Emissions in rural and suburban regions should be considered to further improve air quality in China.

A second wave of coronavirus disease 2019 (COVID-19) infections emerged in Beijing in summer 2020, which provided an opportunity to explore the response of air pollution to reduced human activity. Proton-transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) coupled with positive matrix factorization (PMF) source apportionment were applied to evaluate the pollution pattern and capture the detailed dynamic emission characteristics of volatile organic compounds (VOCs) during the representative period, with the occurrence of O _3 pollution episodes and the Beijing resurgence of COVID-19. The level of anthropogenic VOC was lower than during the same period in previous years due to the pandemic and emission reduction measures. More than two thirds of the days during the observation period were identified as high-O _3 days and VOCs exhibited higher mixing ratios and faster consumption rates in the daytime on high-O _3 days. The identified VOC emission sources and the corresponding contributions during the whole observation period included: vehicle + fuel (12.41 ± 9.43%), industrial process (9.40 ± 8.65%), solvent usage (19.58 ± 13.46%), biogenic (6.03 ± 5.40%), background + long-lived (5.62 ± 11.37%), and two groups of oxygenated VOC (OVOC) factors (primary emission and secondary formation, 26.14 ± 15.20% and 20.84 ± 14.0%, respectively). Refined dynamic source apportionment results show that the ‘stay at home’ tendency led to decreased emission (−34.47 ± 1.90%) and a weakened morning peak of vehicle + fuel during the Beijing resurgence. However, a growing emission of primary OVOCs (+51.10 ± 8.28%) with similar diurnal variation was observed in the new outbreak and afterwards, which might be related to the enhanced usage of products intended to clean and disinfect. The present study illustrated that more stringent VOC reduction measures towards pandemic products should be carried out to achieve the balanced emission abatement of NO _x and VOC when adhering to regular epidemic prevention and control measures.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20254-5

Fugitive particle emission of enclosed storage yards in iron and steel plant is a complicated and multivariable problem, which will have negative impacts on the environment and economy. Researchers have discussed methodologies of emission estimation in open storage yards, but rarely focused on enclosed ones. However, enclosed storage yards are commonly adopted in most industries in China. This paper links onsite observation and computational fluid dynamics (CFD) to estimate the impact of fugitive PM10 emissions from enclosed storage yards on the open air. By collecting and analyzing PM10 samples at three sites inside the yard and one site outside, The result shows that PM10 concentration is in the range of 7.3 ± 1.5~13.4 ± 4.2 mg/m3, which is extremely high in an enclosed storage yard, and significantly influences workers’ health inside and outside atmospheric aerosols. The CFD model simulation is conducted by considering particle deposition, particle emission sources of shovel loader and road dust emission, as well as different wind direction and wind speed. The result shows that PM10 discharge rate from the enclosed area to open-air is significantly influenced by wind velocity and direction, e.g., the result of northwest wind with wind speed in 12.7 m/s is eight times higher than wind speed in 2.5 m/s with the same wind direction, and are 47 and 62 times higher than the east and west wind direction with the same wind speed in 12.7 m/s, respectively. In this case, the PM10 discharge rate is about 131.7 ton/year, which contains about 38~55 ton/year iron-relating particles. This will directly contribute PM10 to open-air and may produce secondary aerosols, due to heterogeneous catalytic reaction. This work identifies the important contribution of fugitive emissions and provides an approach for fugitive emission estimation of industries to the surrounding air. The results provide a reference for material yard zoning and fugitive emission control from minimizing influence from the meteorological condition and reducing source discharge inside.

Revealing the determinants and associated impacts of the transboundary pollution caused by trade is a critical issue when promoting the joint control among regions. This interdisciplinary study utilizes physical, economic and epidemiological methods to explore the anthropogenic PM _2.5 related mortality driven by interprovincial trade within China and its determinants. The results showed that 68% of the mortality flow in China was from the central and north plain area, with 29% occurring within these regions and 39% flowing to other eastern and western provinces. The high death intensity resulting from higher exports of heavily polluted agricultural and heavy industry products dominated the trade surplus of PM _2.5 mortality for the central and northern plains of China; these bring an imbalanced economic return for these regions, with only 43% of the value added generated in interprovincial trade being retained in these regions. Our study provides a more comprehensive picture of how atmospheric pollution deaths were caused by domestic trade within China, which may facilitate the multilateral pollution mitigation actions from an environmentally economic balanced perspective.

It is increasingly recognized that various chemical components of PM _2.5 might have differential toxicities to human health, although such studies are hindered by the sparse or non-existent coverage of ground PM _2.5 speciation monitors. The Multi-angle Imaging SpectroRadiometer (MISR) onboard the Terra satellite has an innovative design to provide information about aerosol shape, size and extinction that are more related to PM _2.5 speciation concentrations. In this study, we developed random forest models that incorporated ground measurements of PM _2.5 species, MISR fractional AODs, simulated PM _2.5 speciation concentrations from a chemical transport model (CTM), land use variables and meteorological fields, to predict ground-level daily PM _2.5 sulfate, nitrate, organic carbon (OC) and elemental carbon (EC) concentrations in California between 2005 and 2014. Our models had out-of-bag R ^2 of 0.72, 0.70, 0.68 and 0.70 for sulfate, nitrate, OC and EC, respectively. We also conducted sensitivity tests to explore the influence of variable selection on model performance. Results show that if there are sufficient ground measurements and predictor data to support the most sophisticated model structure, fractional AODs and total AOD have similar predicting power in estimating PM _2.5 species. Otherwise, models using fractional AODs outperform those with total AOD. PM _2.5 speciation concentrations are more sensitive to land use variables than other supporting data (e.g., CTM simulations and meteorological information).

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at the surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO2 but relatively poor for surface concentrations of several species such as CO, NO2, SO2, PM2.5, and PM10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.

Daily PM2.5 mass concentrations and chemical compositions together with the aerosol optical properties were measured from 8–28 November 2011 in Beijing. PM2.5 mass concentration varied from 15.6–237.5 μg∙m−3 and showed a mean value of 111.2 ± 73.4 μg∙m−3. Organic matter, NH4NO3 and (NH4)2SO4 were the major constituents of PM2.5, accounting for 39.4%, 15.4%, and 14.9% of the total mass, respectively, while fine soil, chloride salt, and elemental carbon together accounted for 27.7%. Daily scattering and absorption coefficients (σsc and σap) were in the range of 31.1–667 Mm−1 and 8.24–158.0 Mm−1, with mean values of 270 ± 200 Mm−1 and 74.3 ± 43.4 Mm−1. Significant increases in σsc and σap were observed during the pollution accumulation episodes. The revised IMPROVE algorithm was applied to estimate the extinction coefficient (bext). On average, organic matter was the largest contributor, accounting for 44.6% of bext, while (NH4)2SO4, NH4NO3, elemental carbon, and fine soil accounted for 16.3% 18.0%, 18.6%, and 2.34% of bext, respectively. Nevertheless, the contributions of (NH4)2SO4 and NH4NO3 were significantly higher during the heavy pollution periods than those on clean days. Typical pollution episodes were also explored, and it has been characterized that secondary formation of inorganic compounds is more important than carbonaceous pollution for visibility impairment in Beijing.

Measurement of the phosphorus concentration in aerosols in Beijing, which was a representative East Asian mega-city, was carried out. The optimum procedure for analyzing phosphorus in aerosols was found in this study. Recovery of phosphorus in environmental samples through the improved method was almost 100%. The concentration of phosphorus in TSP was 145±47 ng/m3, with a seasonal variation showing high concentrations in winter and low concentrations in summer. The concentrations of phosphorus in PM2.5 accounted for 35±6% of those in TSP, with no seasonal variations. The major source of phosphorus in aerosols in Beijing was soil dust, and additional sources of phosphorus in fine particles could be coal combustion and biomass burning.

Satellite-based remote sensing provides a unique opportunity to monitor air quality from space at global, continental, national and regional scales. Most current research focused on developing empirical models using ground measurements of the ambient particulate. However, the application of satellite-based exposure assessment in environmental health is still limited, especially for acute effects, because the development of satellite PM2.5 model depends on the availability of ground measurements. We tested the hypothesis that MODIS AOD (aerosol optical depth) exposure estimates, obtained from NASA satellites, are directly associated with daily health outcomes. Three independent healthcare databases were used: unscheduled outpatient visits, hospital admissions, and mortality collected in Beijing metropolitan area, China during 2006. We use generalized linear models to compare the short-term effects of air pollution assessed by ground monitoring (PM10) with adjustment of absolute humidity (AH) and AH-calibrated AOD. Across all databases we found that both AH-calibrated AOD and PM10 (adjusted by AH) were consistently associated with elevated daily events on the current day and/or lag days for cardiovascular diseases, ischemic heart diseases, and COPD. The relative risks estimated by AH-calibrated AOD and PM10 (adjusted by AH) were similar. Additionally, compared to ground PM10, we found that AH-calibrated AOD had narrower confidence intervals for all models and was more robust in estimating the current day and lag day effects. Our preliminary findings suggested that, with proper adjustment of meteorological factors, satellite AOD can be used directly to estimate the acute health impacts of ambient particles without prior calibrating to the sparse ground monitoring networks. Keywords: Absolute humidity, Aerosol optical depth, Environmental health, Particulate matter, Satellite remote sensing

As the world’s largest developing country, China currently is undergoing rapid urbanization and motorization, which will result in far-reaching impacts on energy and the environment. According to estimates, energy use and carbon emissions in the transportation sector will comprise roughly 30% of total emissions by 2030. Since the late 1990s, transportation-related issues such as energy, consumption, and carbon emissions have become a policy focus in China. To date, most research and policies have centered on vehicle technologies that promote vehicle efficiency and reduced emissions. Limited research exists on the control of greenhouse gases through mode shifts in urban transportation—in particular, through the promotion of public transit. The purpose of this study is to establish a methodology to analyze carbon emissions from the urban transportation sector at the Chinese city level. By using Jinan, the capital of China’s Shandong Province, as an example, we have developed an analytical model to simulate energy consumption and carbon emissions based on the number of trips, the transportation mode split, and the trip distance. This model has enabled us to assess the impacts of the transportation mode split on energy consumption and carbon emissions. Furthermore, this paper reviews a set of methods for data collection, estimation, and processing for situations where statistical data are scarce in China. This paper also describes the simulation of three transportation system development scenarios. The results of this study illustrate that if no policy intervention is implemented for the transportation mode split (the business-as-usual (BAU) case), then emissions from Chinese urban transportation systems will quadruple by 2030. However, a dense, mixed land-use pattern, as well as transportation policies that encourage public transportation, would result in the elimination of 1.93 million tons of carbon emissions—approximately 50% of the BAU scenario emissions.

Measurements of Pollution in the Troposphere (MOPITT) satellite and ground-based carbon monoxide (CO) measurements both suggest a widespread downward trend in CO concentrations over East Asia during the period 2005–2016. This negative trend is inconsistent with global bottom-up inventories of CO emissions, which show a small increase or stable emissions in this region. We try to reconcile the observed CO trend with emission inventories using an atmospheric inversion of the MOPITT CO data that estimates emissions from primary sources, secondary production, and chemical sinks of CO. The atmospheric inversion indicates a ~ −2% yr ^−1 decrease in emissions from primary sources in East Asia from 2005–2016. The decreasing emissions are mainly caused by source reductions in China. The regional MEIC inventory for China is the only bottom up estimate consistent with the inversion-diagnosed decrease of CO emissions. According to the MEIC data, decreasing CO emissions from four main sectors (iron and steel industries, residential sources, gasoline-powered vehicles, and construction materials industries) in China explain 76% of the inversion-based trend of East Asian CO emissions. This result suggests that global inventories underestimate the recent decrease of CO emission factors in China which occurred despite increasing consumption of carbon-based fuels, and is driven by rapid technological changes with improved combustion efficiency and emission control measures.

Epidemiological studies have associated high levels of airborne particulate matter (PM) with increased respiratory diseases. In order to investigate the mechanisms of air pollution-induced lung toxicity in humans, human bronchial epithelial cells (16HBE) were exposed to various concentrations of particles smaller than 2.5 μm (PM2.5) collected from Beijing, China. After observing that PM2.5 decreased cell viability in a dose-dependent manner, we first used Illumina RNA-seq to identify genes and pathways that may contribute to PM2.5-induced toxicity to 16HBE cells. A total of 539 genes, 283 up-regulated and 256 down-regulated, were identified to be significantly differentially expressed after exposure to 25 μg/cm2 PM2.5. PM2.5 induced a large number of genes involved in responses to xenobtiotic stimuli, metabolic response, and inflammatory and immune response pathways such as MAPK signaling and cytokine-cytokine receptor interaction, which might contribute to PM2.5-related pulmonary diseases. We then confirmed our RNA-seq results by qPCR and by analysis of IL-6, CYP1A1, and IL-8 protein expression. Finally, ELISA assay demonstrated a significant association between exposure to PM2.5 and secretion of IL-6. This research provides a new insight into the mechanisms underlying PM2.5-induced respiratory diseases in Beijing.

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. Through assembling techniques, including linear mixed effect regressions with a spatial-varying coefficient, a maximum likelihood estimator and the spatiotemporal Kriging together, we develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1° over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.0 μg/m3 and R2 = 0.72) and outperforms either AOD-derived PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-derived PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides spatiotemporally complete predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.7 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81 across China during 2014. Fused estimates will be publicly available for future health-related studies.

Aggressive emission control measures were taken by the Chinese government after the promulgation of the ‘Air Pollution Prevention and Control Action Plan’ in 2013. Here we evaluated the air quality and health benefits associated with this stringent policy during 2013–2015 by using surface PM _2.5 concentrations estimated from a three-stage data fusion model and cause-specific integrated exposure–response functions. The population-weighted annual mean PM _2.5 concentrations decreased by 21.5% over China during 2013–2015, reducing from 60.5 in 2013 to 47.5 μg m ^−3 in 2015. Subsequently, the national PM _2.5 -attributable mortality decreased from 1.22 million (95% CI: 1.05, 1.37) in 2013 to 1.10 million (95% CI: 0.95, 1.25) in 2015, which is a 9.1% reduction. The limited health benefits compared to air quality improvements are mainly due to the supralinear responses of mortality to PM _2.5 over the high concentration end of the concentration–response functions. Our study affirms the effectiveness of China’s recent air quality policy; however, due to the nonlinear responses of mortality to PM _2.5 variations, current policies should remain in place and more stringent measures should be implemented to protect public health.

Shipping in China plays a global role, and has led worldwide maritime transportation for the last decade. However, without taking national or local port boundaries into account, it is impossible to determine the responsibility that each local authority has on emission controls, nor compare them with land-based emissions to determine the priority for controlling these emissions. In this study, we provide national- to port-level inventories for China. The results show that in 2013, the total emissions of CO, non-methane volatile organic compounds (NMVOCs), nitrogen oxides (NO _x ), particulate matter (PM), SO _2 and CO _2 were 0.0741 ± 0.0004 Tg∙yr ^−1 , 0.0691 ± 0.0004 Tg∙yr ^−1 , 1.91 ± 0.01 Tg∙yr ^−1 , 0.164 ± 0.001 Tg∙yr ^−1 , 1.30 ± 0.01 Tg∙yr ^−1 and 86.3 ± 0.3 Tg∙yr ^−1 in China, respectively. By providing high-resolution spatial distribution maps of these emissions, we identify three hotspots, centered on the Bohai Rim Area, the Yangtze River Delta and Pearl River Delta. These three hotspots account for 8% of the ocean area evaluated in this study, but contribute around 37% of total shipping emissions. Compared with on-road mobile source emissions, NO _x and PM emissions from ships are equivalent to about 34% and 29% of the total mobile vehicle emissions in China. Moreover, this study provides detailed emission inventories for 24 ports in the country, which also greatly contributes to our understanding of global shipping emissions, given that eight of these ports rank within the top twenty of the port league table. Several ports in China suffer emissions 12–147 times higher than those at Los Angeles port. The ports of Ningbo-Zhou Shan, Shanghai, Hong Kong and Dalian dominate the port-level inventories, with individual emissions accounting for 28%–31%, 10%–14%, 10%–12% and 8%–14% of total emissions, respectively.

Two real-time instruments, NCSA (Nanoparticle Chemical Speciation Analyzer) and ACSA (Aerosol Chemical Speciation Analyzer), were both deployed in Beijing, China to explore the sized-dependent characterization of atmospheric particles. The mass concentrations of PM1, PM2.5, PM10, and sulfate and nitrate in the three size fractions were hourly measured in situ from 13 December 2013 to 7 January 2014. Generally, “sawtooth cycles” are common during winter in Beijing, with the PM concentrations increasing slowly over a few days, then falling to a low level abruptly in only a few hours. The secondary species, sulfate and nitrate, play important roles in haze formation and account for 10.5% and 11.1% of total PM1 mass on average. Based on the variation of PM1 mass concentrations, we classify the study periods into three categories, clean, slightly polluted, and polluted. The oxidation ratios of sulfur and nitrogen both increase from clean to polluted periods, indicating the significant contribution of secondary transformation to haze evolution. While the PM2.5/PM10 ratio shows high dependence on PM pollution level, the ratio of PM1/PM2.5 remains almost stable during the entire study, with an average of 0.90. With respect to the mass-size distribution of chemical components, both sulfate and nitrate show dominant contributions in PM1 size fraction, accounting for 80.7% and 60.3% of total sulfate and nitrate, respectively. Our results also reveal that the elevated sulfate in PM1, and the enhanced nitrate in PM1 and PM2.5–1 size fraction, prompt the formation of haze pollution.

Tropospheric nitrogen dioxide (NO _2 ) column densities detected from space are widely used to infer trends in terrestrial nitrogen oxide (NO _x ) emissions. We study changes in NO _2 column densities using the Ozone Monitoring Instrument (OMI) over China from 2005 to 2015 and compare them with the bottom-up inventory to examine NO _x emission trends and their driving forces. From OMI measurements we detect the peak of NO _2 column densities at a national level in the year 2011, with average NO _2 column densities deceasing by 32% from 2011 to 2015 and corresponding to a simultaneous decline of 21% in bottom-up emission estimates. A significant variation in the peak year of NO _2 column densities over regions is observed. Because of the reasonable agreement between the peak year of NO _2 columns and the start of deployment of denitration devices, we conclude that power plants are the primary contributor to the NO _2 decline, which is further supported by the emission reduction of 56% from the power sector in the bottom-up emission inventory associated with the penetration of selective catalytic reduction (SCR) increasing from 18% to 86% during 2011–2015. Meanwhile, regulations for vehicles also make a significant contribution to NO _x emission reductions, in particular for a few urbanized regions (e.g., Beijing and Shanghai), where they implemented strict regulations for vehicle emissions years before the national schedule for SCR installations and thus reached their NO _2 peak 2–3 years ahead of the deployment of denitration devices for power plants.

Following a series of extreme air pollution events, the Chinese government released the Air Pollution Prevention and Control Action Plan in 2013 (China’s State Council 2013). The Action Plan sets clear goals for key regions (i.e. cities above the prefecture level, Beijing-Tianjin-Hebei Province, the Yangtze River Delta and the Pearl River Delta) and establishes near-term control efforts for the next five years. However, the extent to which the Action Plan can direct local governments’ activities on air pollution control remains unknown. Here we seek to evaluate the air quality improvement and associated health benefits achievable under the Action Plan in the Pearl River Delta (PRD) area from 2012 to 2017. Measure-by-measure quantification results show that the Action Plan would promise effective emissions reductions of 34% of SO _2 , 28% of NO _x , 26% of PM _2.5 (particulate matter less than 2.5 μ m in diameter), and 10% of VOCs (volatile organic compounds). These emissions abatements would lower the PM _2.5 concentration by 17%, surpassing the 15% target established in the Action Plan, thereby avoiding more than 2900 deaths and 4300 hospital admissions annually. We expect the implementation of the Action Plan in the PRD would be productive; the anticipated impacts, however, fall short of the goal of protecting the health of local residents, as there are still more than 33 million people living in places where the annual mean ambient PM _2.5 concentrations are greater than 35 μ g m ^−3 , the interim target-3 of the World Health Organization (WHO). We therefore propose the next steps for air pollution control that are important not only for the PRD but also for all other regions of China as they develop and implement effective air pollution control policies.

To evaluate the real reductions in sulfur dioxide (SO _2 ) emissions from coal-fired power plants in China, Ozone Monitoring Instrument (OMI) remote sensing SO _2 columns were used to inversely model the SO _2 emission burdens surrounding 26 isolated power plants before and after the effective operation of their flue gas desulfurization (FGD) facilities. An improved two-dimensional Gaussian fitting method was developed to estimate SO _2 burdens under complex background conditions, by using the accurate local background columns and the customized fitting domains for each target source. The OMI-derived SO _2 burdens before effective FGD operation were correlated well with the bottom-up emission estimates ( R = 0.92), showing the reliability of the OMI-derived SO _2 burdens as a linear indicator of the associated source strength. OMI observations indicated that the average lag time period between installation and effective operation of FGD facilities at these 26 power plants was around 2 years, and no FGD facilities have actually operated before the year 2008. The OMI estimated average SO _2 removal equivalence (56.0%) was substantially lower than the official report (74.6%) for these 26 power plants. Therefore, it has been concluded that the real reductions of SO _2 emissions in China associated with the FGD facilities at coal-fired power plants were considerably diminished in the context of the current weak supervision measures.

Primary PM _2.5 emissions contributed significantly to poor air quality in China. We present an interdisciplinary study to measure the magnitudes of socioeconomic factors in driving primary PM _2.5 emission changes in China between 1997–2010, by using a regional emission inventory as input into an environmentally extended input–output framework and applying structural decomposition analysis. Our results show that China’s significant efficiency gains fully offset emissions growth triggered by economic growth and other drivers. Capital formation is the largest final demand category in contributing annual PM _2.5 emissions, but the associated emission level is steadily declining. Exports is the only final demand category that drives emission growth between 1997–2010. The production of exports led to emissions of 638 thousand tonnes of PM _2.5 , half of the EU27 annual total, and six times that of Germany. Embodied emissions in Chinese exports are largely driven by consumption in OECD countries.

PM _2.5 (particulate matter with aerodynamic diameters less than 2.5 μm) and PM _10 (particulate matter with aerodynamic diameters less than 10 μm) samples were collected by high-volume air samplers simultaneously at a rural site and an urban site in Beijing, China. Various carbohydrates were quantified by high-performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD), including the sugar alcohols mannitol and arabitol, recently proposed as molecular tracers for fungal aerosol. The annual average concentrations of arabitol in PM _2.5 and PM _10 at the urban site were 7.4 ± 9.4 and 21.0 ± 20.4 ng m ^−3 , and the respective mannitol concentrations were 10.3 ± 9.5 and 31.9 ± 26.9 ng m ^−3 . During summer and autumn, higher arabitol and mannitol levels than during spring and winter were observed in coarse particles, probably due to different dominant sources of fungal spores in different seasons. In the dry season (i.e., winter and spring) in Beijing, probably only the suspension from exposed surfaces (e.g., soil resuspension, transported dust, etc) can be regarded as the main sources for fungal aerosols. On the other hand, in summer and autumn, fungal spores in the atmosphere can be derived from more complex sources, including plants, vegetation decomposition and agricultural activity, such as ploughing; these fungal spore sources may contribute more to coarse PM. Moreover, statistical analysis according to typical seasonal patterns, including a dry season (December 2010 to March 2011) and a wet season (July to September 2011), revealed different variations of fungal spores in different seasons. Although fungal spore levels at rural sites were reported to be consistently higher than those at urban sites in other studies, our findings showed the opposite pattern, indicating a high abundance of fungal spores in the urban area of this Chinese megacity.

Understanding the compositions and evolution of atmospheric organic vapors is crucial for exploring their impact on air quality. However, the molecular and seasonal characteristics of organic vapors in urban areas, with complex anthropogenic emissions and high variability, remain inadequately understood. In this study, we conducted measurements in urban Beijing during 2021-2022 covering four seasons using a Vocus-PTR, an improved Proton Transfer Reaction-Mass Spectrometry (PTR-MS). During the measurement period, a total of 895 peaks are observed, and 543 of them can be assigned to formulas. The contribution of CxHyOz species is most significant, which compose up to 53.7% of the number and 76.0% of the mass of total organics. With enhanced sensitivity and mass resolution, various sub-ppt level species and organics with multiple oxygens (≥3) were discovered. When counting the species number, 42.2% of the organics measured are at sub-ppt level and 37.8% of the species contain 3-8 oxygens. Organic vapors with multiple oxygens mainly consist of intermediate volatility and semi-volatile compounds, and many of them are found to be the multi-generational oxidation products of various volatile organic precursors. In summer, the fast photooxidation process generates organic vapors with multiple oxygens, and leads to an increase in both their concentration and proportion. While in other seasons, the variations of organic vapors with multiple oxygens are closely correlated with those of organic vapors with 1-2 oxygens, which could be heavily influenced by primary emissions. Organic vapors with low oxygen content (≤ 2 oxygens) are comparable to the results obtained by traditional PTR-MS measurements in both urban Beijing and neighboring regions. [ABSTRACT FROM AUTHOR]