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Carcinogenic nitrosamines have been widely studied due to their risk to human health. However, the universality and evolutionary processes of their generation, particularly concerning their secondary sources, remain unclear at present. We demonstrated through laboratory flow tube experiments that corresponding nitrosamines were generated from heterogeneous reactions of nitrous acid (HONO) with five structurally diverse amines commonly found indoors, including diphenylamine (DPhA), dibenzylamine (DBzA), dioctylamine (DOtA), N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine (6PPD), and N-phenyl-1-naphthylamine (PANA). The heterogeneous reaction rate constants of DBzA and DOtA with HONO (∼70 ppb) were 1.21 × 10–3and 2.13 × 10–3min–1at 30% relative humidity (RH), resulting in a lifetime of 13.8 and 7.8 h. As compared to higher RH (∼80%), more nitrosamines were produced from the reaction of HONO with surface-sorbed DBzA, DOtA, 6PPD, and PANA at lower RH (30%), with product yields ranging from <0.1% to 0.5%. Furthermore, we observed the formation of nitroso-6PPDs and nitro-6PPDs during room air exposure of 6PPD in a genuine indoor environment, in addition to various other transformation products indicative of reactions of 6PPD with HONO, NOx, and ozone indoors. This study confirmed the universality of the heterogeneous reaction of surface-sorbed amine with HONO as a source of nitrosamines indoors.

Ultrafine particles (UFPs) dominate the atmospheric particles in number concentration, impacting human health and climate change. However, existing studies primarily rely on mass-based approaches, leading to a restricted understanding of the number-based and chemically resolved health effects of atmospheric UFPs. In this study, we utilized a high-mass-resolution single-particle aerosol mass spectrometer to investigate the online chemical composition and number size distribution of ultrafine, fine, and coarse particles during the summertime in urban Shenzhen, China. Human respiratory deposition dose assessments of particles with varying chemical compositions were further conducted by a respiratory deposition model. The results showed that during our observation, particles containing elemental carbon (EC) were the dominant components in UFPs (0.05–0.1 μm). Compared to fine and coarse particles, UFPs can deposit more deeply into the respiratory tract with a daily dose of ∼2.08 ± 0.67 billion particles. Among the deposited UFPs, EC-cluster particles constituted ∼85.7% in number fraction, accounting for a daily number dose of ∼1.78 billion particles, which poses a greater impact on human health. Simultaneously, we found discrepancies in the chemically resolved particle depositions among number-, surface area-, and mass-based approaches, emphasizing the importance of an appropriate metric for particle health-risk evaluation.

Ozone pollution is profoundly modulated by meteorological features such as temperature, air pressure, wind, and humidity. While many studies have developed empirical models to elucidate the effects of meteorology on ozone variability, they predominantly focus on local weather conditions, overlooking the influences from high-altitude and broader regional meteorological patterns. Here, we employ convolutional neural networks (CNNs), a technique typically applied to image recognition, to investigate the influence of three-dimensional spatial variations in meteorological fields on the daily, seasonal, and interannual dynamics of ozone in Shenzhen, a major coastal urban center in China. Our optimized CNNs model, covering a 13° × 13° spatial domain, effectively explains over 70% of daily ozone variability, outperforming alternative empirical approaches by 7 to 62%. Model interpretations reveal the crucial roles of 2-m temperature and humidity as primary drivers, contributing 16% and 15% to daily ozone fluctuations, respectively. Regional wind fields account for up to 40% of ozone changes during the episodes. CNNs successfully replicate observed ozone temporal patterns, attributing −5–6 μg·m–3of interannual ozone variability to weather anomalies. Our interpretable CNNs framework enables quantitative attribution of historical ozone fluctuations to nonlinear meteorological effects across spatiotemporal scales, offering vital process-based insights for managing megacity air quality amidst changing climate regimes.

Crop production is a large source of atmospheric ammonia (NH3), which poses risks to air quality, human health and ecosystems1–5. However, estimating global NH3emissions from croplands is subject to uncertainties because of data limitations, thereby limiting the accurate identification of mitigation options and efficacy4,5. Here we develop a machine learning model for generating crop-specific and spatially explicit NH3emission factors globally (5-arcmin resolution) based on a compiled dataset of field observations. We show that global NH3emissions from rice, wheat and maize fields in 2018 were 4.3 ± 1.0 Tg N yr−1, lower than previous estimates that did not fully consider fertilizer management practices6–9. Furthermore, spatially optimizing fertilizer management, as guided by the machine learning model, has the potential to reduce the NH3emissions by about 38% (1.6 ± 0.4 Tg N yr−1) without altering total fertilizer nitrogen inputs. Specifically, we estimate potential NH3emissions reductions of 47% (44–56%) for rice, 27% (24–28%) for maize and 26% (20–28%) for wheat cultivation, respectively. Under future climate change scenarios, we estimate that NH3emissions could increase by 4.0 ± 2.7% under SSP1–2.6 and 5.5 ± 5.7% under SSP5–8.5 by 2030–2060. However, targeted fertilizer management has the potential to mitigate these increases.

Foreign investments in overseas coal-fired power plants (OCPs) largely impede decarbonization efforts, yet their global carbon dioxide (CO2) emissions have not been sufficiently quantified. Here we analyse investment data from 908 OCPs worldwide, and then reveal current annual emissions of 0.53 GtCO2yr−1and a historical cumulative total of 26 GtCO2. Developed nations account for 78% of these cumulative emissions on the basis of investments, while emissions from developing nations have surged from 8% in 1960 to 39% in 2022. Assuming unchanged policies and technologies, OCPs are projected to contribute an additional 15–30 GtCO2in cumulative emissions by 2060 directly. Furthermore, they could stimulate local coal power growth in emerging economies, potentially adding 6.3–45.0 GtCO2emissions indirectly. Our study underscores the critical importance of low-carbon policy interventions in emerging countries to curb the power-sector carbon emissions increasingly influenced by international capital.

The iron and steel industry (ISI) is important for socio-economic progress but emits greenhouse gases and air pollutants detrimental to climate and human health. Understanding its historical emission trends and drivers is crucial for future warming and pollution interventions. Here, we offer an exhaustive analysis of global ISI emissions over the past 60 years, forecasting up to 2050. We evaluate emissions of carbon dioxide and conventional and unconventional air pollutants, including heavy metals and polychlorinated dibenzodioxins and dibenzofurans. Based on this newly established inventory, we dissect the determinants of past emission trends and future trajectories. Results show varied trends for different pollutants. Specifically, PM2.5emissions decreased consistently during the period 1970 to 2000, attributed to adoption of advanced production technologies. Conversely, NOxand SO2began declining recently due to stringent controls in major contributors such as China, a trend expected to persist. Currently, end-of-pipe abatement technologies are key to PM2.5reduction, whereas process modifications are central to CO2mitigation. Projections suggest that by 2050, developing nations (excluding China) will contribute 52–54% of global ISI PM2.5emissions, a rise from 29% in 2019. Long-term emission curtailment will necessitate the innovation and widespread adoption of new production and abatement technologies in emerging economies worldwide.

As the main anthropogenic source in open seas and coastal areas, ship emissions impact the climate, air quality, and human health. The latest marine fuel regulation with a sulfur content limit of 0.5% went into effect globally on January 1, 2020. Investigations of ship emissions after fuel switching are necessary. In this study, online field measurements at an urban coastal site and modeling simulations were conducted to detect the impact of ship emissions on air quality in the Greater Bay Area (GBA) in China under new fuel regulation. By utilizing a high mass-resolution single particle mass spectrometer, the vanadium(V) signal was critically identified and was taken as a robust indicator for ship-emitted particles (with relative peak area > 0.1). The considerable number fractions of high-V particles (up to 30–40% during ship plumes) indicated that heavy fuel oils via simple desulfurization or blending processes with low-sulfur fuels were extensively used in the GBA to meet the global 0.5% sulfur cap. Our results showed that ship-emitted particulate matter and NOxcontributed up to 21.4% and 39.5% to the ambient, respectively, in the summertime, significantly affecting the air quality in the GBA. The sea-land breeze circulation also played an important role in the transport pattern of ship-emitted pollutants in the GBA.

Black carbon (BC) is a crucial air pollutant that contributes to short-lived climate forcing and adverse health impacts. BC emissions have rapidly declined over the past three decades and it is important to uncover the major factors behind this decline. Herein, the temporal trends in BC emissions were compiled from 146 detailed sources from 1960 to 2019. Results revealed that the major emission sources were residential solid fuel usage, coke production and brick production. Furthermore, 96.9% of the emission reduction from 3.03 Tg in 1995 to 1.02 Tg in 2019 was attributed to these three sources. It was determined that the transition in residential energy/stove usage, phasing-out of beehive coke ovens and brick kiln upgrading were the most important drivers leading to this reduction and will continue to play a key role in future emission mitigation. In addition, this study identified the need to address emissions from coal used in vegetable greenhouses and the commercial sector, and diesel consumption in on/off-road vehicles.Black carbon emission inventory for China was fully updated with major drivers affecting the changes quantified.

Gaseous and particulate chlorine species play an important role in modulating tropospheric oxidation capacity, aerosol water uptake, visibility degradation, and human health. The lack of recent global continental chlorine emissions has hindered modeling studies of the role of chlorine in the atmosphere. Here, we develop a comprehensive global emission inventory of gaseous HCl and particulate Cl–(pCl), including 35 sources categorized in six source sectors based on published up-to-date activity data and emission factors. These emissions are gridded at a spatial resolution of 0.1° × 0.1° for the years 1960 to 2014. The estimated emissions of HCl and pCl in 2014 are 2354 (1661–3201) and 2321 (930–3264) Gg Cl a–1, respectively. Emissions of HCl are mostly from open waste burning (38%), open biomass burning (19%), energy (19%), and residential (13%) sectors, and the major sources classified by fuel type are combustion of waste (43%), biomass (32%), and coal (25%). Emissions of pCl are mostly from biofuel (29%) and open biomass burning processes (44%). The sectoral and spatial distributions of HCl and pCl emissions are very heterogeneous along the study period, and the temporal trends are mainly driven by the changes in emission factors, energy intensity, economy, and population.

Ozone (O3) isopleths describe the nonlinear responses of O3concentrations to changes in nitrogen oxides (NOX) and volatile organic compounds (VOCs) and thus are pivotal to the determination of O3control requirements. In this study, we innovatively use the Community Multiscale Air Quality model with the high-order decoupled direct method (CMAQ-HDDM) to simulate O3pollution of China in 2017 and derive O3isopleths for individual cities. Our simulation covering the entire China Mainland suggests severe O3pollution as 97% of the residents experienced at least 1 day, in 2017, in excess of Chinese Level-II Ambient Air Quality Standards for O3as 160 μg·m–3(81.5 ppbV equally). The O3responses to emissions of precursors vary widely across individual cities. Densely populated metropolitan areas such as Jing-Jin-Ji, Yangtze River Delta, and Pearl River Delta are following NOX-saturated regimes, where a small amount of NOXreduction increases O3. Ambient O3pollution in the eastern region generally is limited by VOCs, while in the west by NOX. The city-specific O3isopleths generated in this study are instrumental in forming hybrid and differentiated strategies for O3abatement in China.

Exposure to air pollution by burning solid fuels (such as coal) for residential cooking and heating in China has caused significant health impacts in the past. The government has implemented measures to replace coal with relatively clean energy sources (e.g., natural gas). However, the scale and scope of health benefits associated with such energy switching in an urban context, when considering both ambient and indoor air quality, remain unclear. Here we used an atmospheric chemical transport model showing that relatively clean energy use increased from 2% to 71% from 1980 to 2014, and although annual premature deaths attributed to particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) from urban residential sources increased from 136,000 (87,000–194,000) to 202,000 (117,000–302,000) during the same period, this was primarily due to population growth, urbanization, aging, and background mortality rate changes. In the absence of energy switching, there would have been 2.2 million additional premature deaths. The results provide solid evidence on health benefits of energy switching, suggesting further switching to cleaner energy for expanded health-climate co-benefits.

Coal abatement actions for pollution reduction often target total coal consumption. The health impacts of coal uses, however, vary extensively among sectors. Here, we modeled the sectorial contributions of coal uses to emissions, outdoor and indoor PM2.5(particulate matter with an aerodynamic diameter of less than 2.5 mm) concentrations, exposures, and health outcomes in China from 1970 to 2014. We show that in 2014, residential coal accounted for 2.9% of total energy use but 34% of premature deaths associated with PM2.5exposure, showing that effects were magnified substantially along the causal path. The number of premature deaths attributed to unit coal consumption in the residential sector was 40 times higher than that in the power and industrial sectors. Emissions of primary PM2.5were more important than secondary aerosol precursors in terms of health consequences, and indoor exposure accounted for 97% and 91% of total premature deaths attributable to PM2.5from coal combustion in 1974 and 2014, respectively. Our assessment raises a critical challenge in the switching of residential coal uses to effectively mitigate PM2.5exposure in the Chinese population.

Air pollution is a major environmental issue in China and imposes severe health burdens on Chinese citizens. Consequently, China has deployed a series of control measures to mitigate fine particulate matter (PM2.5). However, the extent to which these measures have been effective is obscured by the existence of confounding meteorological effects. Here, we use a newly developed reduced-form model that can address emission-driven PM2.5trends and control for meteorological effects to examine the level of PM2.5reduction across 367 cities since the introduction of the Air Pollution Prevention and Control Action Plan (the Plan) in 2013. Our findings show that, on average, the national annual mean level of PM2.5decreased by 34% from 2013 to 2019 after the removal of meteorological effects, about 10% less than the reduction level officially observed. Despite this difference, assuming that current control efforts continue through 2035, the long-term air-quality target of 35 μg/m3as determined by the recently updated Plan will be met.

On-road emissions sources degrade air quality, and these sources have been highly regulated. Epidemiological and environmental justice studies often use road proximity as a proxy for traffic-related air pollution (TRAP) exposure, and other studies employ air quality models or satellite observations. To assess these metrics’ abilities to reproduce observed near-road concentration gradients and changes over time, we apply a hierarchical linear regression to ground-based observations, long-term air quality model simulations using Community Multiscale Air Quality (CMAQ), and satellite products. Across 1980–2019, observed TRAP concentrations decreased, and road proximity was positively correlated with TRAP. For all pollutants, concentrations decreased fastest at locations with higher road proximity, resulting in “flatter” concentration fields in recent years. This flattening unfolded at a relatively constant rate for NOx, whereas the flattening of CO concentration fields has slowed. CMAQ largely captures observed spatial–temporal NO2trends across 2002–2010 but overstates the relationships between CO and elemental carbon fine particulate matter (EC) road proximity. Satellite NOxmeasures overstate concentration reductions near roads. We show how this perspective provides evidence that California’s on-road vehicle regulations led to substantial decreases in NO2, NOx, and EC in California, with other states that adopted California’s light-duty automobile standards showing mixed benefits over states that did not adopt these standards.

Residential heating using solid fuels contributes significantly to air pollution and has subsequent health impacts in China. To mitigate emissions, a clean heating campaign (CHC-1) covering 28 municipalities has been implemented. Although only a single penetration rate was initially planned by CHC-1 for all municipalities, outcomes in the different municipalities varied considerably. Recently, a second phase (CHC-2) has been launched for the remaining 128 municipalities in northern China with once again a fixed penetration rate set. Here, we quantified factors that affected the penetration rates of CHC-1, developed an intervention scheme with differentiated targets for CHC-2, and compared the environmental and health benefits of the fixed- and differentiated-rate strategies. We found that the penetration rates of CHC-1 depended on per capita income, terrain slope, and population density and that such relationships could be quantified using a piecewise regression model. This model was applied to develop a differentiated-rate strategy for CHC-2. It clearly evidenced that a differentiated scheme would be more environmentally beneficial. Although the same number of rural households can achieve clean heating under both intervention scenarios, the proposed differentiated strategy can prevent 30 000 (23 000–34 000) premature deaths associated with residential heating annually compared to the 26 000 (21 000–31 000) premature deaths prevented under the fixed-rate scheme. Differences among gender and age groups and the effects of urbanization and aging are also discussed.

Cropland ammonia volatilization (VNH3,AG) is a major pathway of agricultural nitrogen loss. It remains unclear, however, how climate warming and human intervention (e.g., agricultural management) will affect VNH3,AG. Here, we use a fully coupled agroecosystem/chemical transport model and multiple climate projections to quantify the changes in climate-induced VNH3,AGover the US. We show that climate change under an intensely warming scenario will increase VNH3,AGby 81% (95% confidence interval, 69%–92%) from 2010 to 2100. The increase in VNH3,AGwill cause a 10% loss of nitrogen applied, decrease crop yields by 540 Gg-N year−1, increase atmospheric burden of ammonia/ammonium by 18%, and increase ammonia/ammonium deposition to sensitive ecosystems by 14%. We have found that combining climate-adaptive agricultural practices with feasible mitigation measures can fully offset the warming-induced increase in VNH3,AG, saving 13% of applied nitrogen, increasing yields by 735 Gg-N year−1, and providing net benefits for air quality and ecosystem health.

The presence of sulfur dioxide (SO2) in the air is a global concern because of its severe environmental and public health impacts. Recent evidence from satellite observations shows rapid changes in the spatial distribution of global SO2emissions, but such features are generally missing in global emission inventories that use a bottom-up method due to the lack of up-to-date information, especially in developing countries. Here, we rely on the latest data available on emission activities, control measures, and emission factors to estimate global SO2emissions for the period 1960–2014 on a 0.1° × 0.1° spatial resolution. We design two counterfactual scenarios to isolate the contributions of emission activity growth and control measure deployment on historical SO2emission changes. We find that activity growth has been the major factor driving global SO2emission changes overall, but control measure deployment is playing an increasingly important role. With effective control measures deployed in developed countries, the predominant emission contributor has shifted from developed countries in the early 1960s (61%) to developing countries at present (83%). Developing countries show divergency in mitigation strategies and thus in SO2emission trends. Stringent controls in China are driving the recent decline in global emissions. A further reduction in SO2emissions would come from a large number of developing nations that currently lack effective SO2emission controls.

The nocturnal boundary layer (NBL) significantly influences the dispersion and fate of atmospheric species at night. Subtropical forests are crucial in carbon and water exchange between the biosphere and the atmosphere. However, the NBL characteristics and their impact on atmospheric species over these forests remain unknown. This study conducted vertical measurements of atmospheric species such as O3and volatile organic compounds (VOCs), along with meteorological variables, over a national forest reserve in Southern China. Results reveal that the NBL height ranged from 180 to 300 m in the summer and from 80 to 160 m in the winter. The vertical distribution of chemical species varied by time and season, with greater concentration gradients observed in the summer. Over 90% of VOCs above the NBL were anthropogenic, while biogenic VOCs were mainly found within the NBL. Higher O3concentration and VOC product-to-reactant ratios were observed in the residual layer, suggesting enhanced oxidation levels. This unique vertical distribution of atmospheric species at night is driven by factors, such as emission, deposition, turbulence, and atmospheric chemistry, potentially affecting ecosystem functions. Results from this study highlight the importance of incorporating NBL dynamics into atmospheric models to better understand the evolution of chemical species and their ecological effects over forests.

Environmental pollution is escalating due to rapid global development that often prioritizes human needs over planetary health. Despite global efforts to mitigate legacy pollutants, the continuous introduction of new substances remains a major threat to both people and the planet. In response, global initiatives are focusing on risk assessment and regulation of emerging contaminants, as demonstrated by the ongoing efforts to establish the UN’s Intergovernmental Science-Policy Panel on Chemicals, Waste, and Pollution Prevention. This review identifies the sources and impacts of emerging contaminants on planetary health, emphasizing the importance of adopting a One Health approach. Strategies for monitoring and addressing these pollutants are discussed, underscoring the need for robust and socially equitable environmental policies at both regional and international levels. Urgent actions are needed to transition toward sustainable pollution management practices to safeguard our planet for future generations.

China, especially the densely populated North China region, experienced severe haze events in the past decade that concerned the public. Although the most extreme cases have been largely eliminated through recent mitigation measures, severe outdoor air pollution persists and its environmental impact needs to be understood. Severe indoor pollution draws less public attention due to the short visible distance indoors, but its public health impacts cannot be ignored. Herein, we assess the trends and impacts of severe outdoor and indoor air pollution in North China from 2014 to 2021. Our results demonstrate the uneven contribution of severe hazy days to ambient and exposure concentrations of particulate matter with an aerodynamic diameter <2.5 (PM2.5). Although severe indoor pollution contributes to indoor PM2.5concentrations (23%) to a similar extent as severe haze contributes to ambient PM2.5concentrations (21%), the former’s contribution to premature deaths was significantly higher. Furthermore, residential emissions contributed more in the higher PM2.5concentration range both indoors and outdoors. Notably, severe haze had greater health impacts on urban residents, while severe indoor pollution was more impactful in rural areas. Our findings suggest that, besides reducing severe haze, mitigating severe indoor pollution is an important aspect of combating air pollution, especially toward improving public health.

The evaporative emissions of anthropogenic volatile organic compounds (AVOCs) are sensitive to ambient temperature. This sensitivity forms an air pollution-meteorology connection that has not been assessed on a regional scale. We parametrized the temperature dependence of evaporative AVOC fluxes in a regional air quality model and evaluated the impacts on surface ozone in the Beijing–Tianjin–Hebei (BTH) area of China during the summer of 2017. The temperature dependency of AVOC emissions drove an enhanced simulated ozone-temperature sensitivity of 1.0 to 1.8 μg m–3K–1, comparable to the simulated ozone-temperature sensitivity driven by the temperature dependency of biogenic VOC emissions (1.7 to 2.4 μg m–3K–1). Ozone enhancements driven by temperature-induced AVOC increases were localized to their point of emission and were relatively more important in urban areas than in rural regions. The inclusion of the temperature-dependent AVOC emissions in our model improved the simulated ozone-temperature sensitivities on days of ozone exceedance. Our results demonstrated the importance of temperature-dependent AVOC emissions on surface ozone pollution and its heretofore unrepresented role in air pollution–meteorology interactions.

Brown carbon (BrC) absorption impacts radiative forcing and climate change. Quantifying radiative forcing of BrC requires understanding its molecular composition and absorption characteristics. While organic molecules surrounding BrC may impact its absorption, their effects have not yet been investigated. This research determined matrix effect on BrC absorption by comparing individual BrC molecules and BrC within an organic matrix. Over 20,000 water‐soluble organic molecules constituted the water‐soluble BrC and associated organic matrix. The matrix enhanced aliphatic BrC absorption but suppressed aromatic BrC, especially with higher matrix O/C ratios indicating greater polarity and acidity. By directly measuring and modeling organic matrix effect on BrC, we can improve climate prediction precision and aerosol‐radiation interaction comprehension. In the atmosphere, organic carbon that absorb light are called brown carbon. Brown carbon can impact climate change. It is critical to understand potential factors affecting brown carbon's absorption of light. Our study proposed another potential influencing light absorbing of brown carbon, effect from organic matrix formed by co‐existing organic molecules. The matrix effect on brown carbon absorption was simulated by the absorption properties of individual molecules and the absorption contributions from the same molecules embedded within organic matrix. We found over 20,000 molecules in all samples, separating them into major contributing brown carbon molecules and co‐existing organic molecules. We found CHO and CHON formed the majority of these molecules. The organic matrix showed the different behavior to effect light absorption to different portion for organic molecules, namely aliphatic and aromatic brown carbon molecules. The brown carbon absorption was suppressed during the nighttime, with the high O/C ratio co‐existing organics. Through the direct measurement and modeling of organic matrix effect on brown carbon, the finding could improve the precision of climate predictions and enhance our comprehension of aerosol‐radiation interactions. Organic molecules co‐existing around brown carbon constituted the organic matrixThe organic matrix enhanced aliphatic but suppressed aromatic brown carbon absorptionHigher matrix O/C ratios indicating greater polarity and acidity especially suppressed aromatic brown carbon absorption Organic molecules co‐existing around brown carbon constituted the organic matrix The organic matrix enhanced aliphatic but suppressed aromatic brown carbon absorption Higher matrix O/C ratios indicating greater polarity and acidity especially suppressed aromatic brown carbon absorption

Non‐methane volatile organic compounds (NMVOCs) have a significant impact on air quality in urban areas. Detecting NMVOCs emission with its proxy HCHO on urban scales from space, however, has been limited by the lack of discernible enhancement. Here we show clear urban HCHO plumes from 16 cities over the globe by rotating TROPOspheric Monitoring Instrument HCHO pixels according to wind directions. We fit the downwind structure of the plumes with the exponentially modified Gaussian approach to quantify urban HCHO effective production rates between 7.0 and 88.5 mol s−1. Our results are in line with total NMVOC emissions from the EDGAR inventory (r= 0.76). Our work offers a new measure of total NMVOC emissions from urban areas and highlights the potential of satellite HCHO data to provide new information for monitoring urban air quality. Non‐methane volatile organic compounds (NMVOCs) play an important role in urban air quality. Formaldehyde (HCHO) satellite observations have been shown to be able to reliably track and quantify NMVOC emissions at global and regional scales. Here, we use state‐of‐the‐art satellite sensors to quantify effective HCHO production rates in 16 global cities and further constrain total NMVOC emissions. Our results are broadly consistent with current emissions inventories, implying that satellites may be able to provide new information for urban air studies. We show clear urban HCHO plumes from 16 cities over the globe by relating satellite pixels with wind fieldsWe obtain urban effective HCHO production rates by fitting the downwind structure of HCHO plumesSatellite‐based effective HCHO production rates provide potential measures of total non‐methane volatile organic compound emissions We show clear urban HCHO plumes from 16 cities over the globe by relating satellite pixels with wind fields We obtain urban effective HCHO production rates by fitting the downwind structure of HCHO plumes Satellite‐based effective HCHO production rates provide potential measures of total non‐methane volatile organic compound emissions

Historically, beehive coke ovens (BCOs) were extensively operated in China and emitted large quantities of pollutants, including primary PM2.5and secondary PM2.5precursors, and other climate forcers. Although these ovens were legally banned in 1996 by the Coal Law, the process of phasing them out took over a decade to accomplish. Based on historical operation data derived from remote sensing images, temporal trends and the spatial distribution of the emissions of various pollutants from BCOs were compiled and used to model the resulting perturbation in ambient PM2.5, population exposure, and PM2.5-associated adverse health impacts. Historically, PM2.5originating from BCOs affected a vast region across China, which peaked in approximately 1996 and decreased afterward until the ovens’ final elimination in 2011. According to the results of a supply–demand model, emissions from the BCOs would have continued to increase after 1996 if they had not been banned. As a result, national average PM2.5attributable to BCOs in 2014 would have been more than three times as high as that in 1996. It was estimated that the cumulative number of premature deaths associated with BCO-originating PM2.5from 1982 to 2014 was as high as 365 000 (95% confidence interval 259 000–402 000). The number would have nearly tripled if BCOs had not been banned and halved if the ban had been implemented immediately after the regulation was in force, suggesting the importance of legislation implementation.

Aerosol pH can affect gas-particle partitioning of semivolatile species, secondary aerosol formation, aerosol water uptake and growth, acid deposition, and, potentially, aerosol toxicity. Despite its importance, aerosol pH projected in the near future has not been addressed explicitly while investigating the response of aerosol concentrations to emission regulations. In this study, we apply CMAQ to simulate aerosol pH in 2011 and 2050 across the continental U.S. We also assess the influence of two major emission trends, declining SO2emissions and rising NH3emissions, with a set of sensitivity simulations. Our results show that the aerosols will remain acidic with average pH typically ranging from 0.5 to 3.5 in 2050. Further reducing domestic SO2emissions does not significantly decrease aerosol acidity, even if SO2emissions were reduced to preindustrial levels because of the nonlinear response of SO42–concentration to SO2emissions, and the semivolatile NH3–NH4+buffering effect. Aerosol pH response to NH3emission increase will remain minor. Consequently, future fine particulate matter control efficiency will not be undercut by additional nitrate aerosol formation even if SO2emissions from industry and electricity generation are aggressively controlled, although areas will see some substitution leading to nitrate increases if NOxemissions are not reduced.

Fire forecasts that predict dry‐season fire activities several months in advance are beneficial for fire management. On a global scale, however, the predictability of fires is limited because fires depend on multiple factors and lack a single dominant predictor to describe diverse fire characteristics across regions. Here, based on 33 local meteorological parameters (MPs) and 37 large‐scale climate indices (CIs), we establish four empirical model clusters to predict global interannual fire variability. We show that across various geographic locations, the models provide reliable fire forecasts at least three months prior to the peak fire months. Compared to MPs, CIs such as the Oceanic Niño Index are comparable or even superior predictors. Globally, as well as in most continents, the El Niño–Southern Oscillation is the major driving force, explaining 17% of interannual fire variability, with strong implications for fire carbon emissions and the global carbon cycle. Other important predictors include the Northern Atlantic sea surface temperature (9%), the Southern Atlantic sea surface temperature (5%), and the Pacific/North American Pattern (3%). The predictive models reveal a strong interaction between MPs and CIs, indicating potential climate‐induced modification of fire responses to meteorological conditions. We show that the newly developed predictive models can benefit future fire management in response to climate change. Integration of climate indices and meteorological parameters enables more accurate fire forecasts globally with a longer forecast length. We developed empirical models to provide global fire forecasts 3 months prior to the peak fire monthsCombining meteorological and climate variables enhances fire predictabilityThe El Niño–Southern Oscillation is a driving factor that affects global interannual fire variability

Survey data from a comprehensive national survey of ∼34 000 households were analyzed for the mix status and transition trajectory of energy for boiling water in rural Chinese households from 1992 to 2012. In 1992, ∼6% of households reported using electricity, biogas, or liquefied petroleum gas (LPG) to boil drinking water; in 2012, the proportion was ∼60%. Income per capita appeared most strongly associated with this transition toward electricity and other clean fuels. Median annual incomes for households using biomass fuels, electric kettles, and LPG were RMB 15 000, 28 000, and 30 000, respectively. Overall, the transition was most pronounced in eastern China, a region which experienced relatively higher rates of economic growth over the same 20-year period. Energy type preferences appear to be highly dependent on fuel accessibility such that coal and straw usage was higher in provinces with higher coal and grain production. These trends suggest that electric kettle use would likely increase from ∼29% (2012) to ∼60% by 2030, at which point <5% of rural households would be expected to boil with solid fuels. Recent evidence suggests that this transition could contribute to reductions in water-related gastrointestinal illness as well as reductions in air pollutant emissions in rural China.

Although PM2.5(particulate matter with aerodynamic diameters less than 2.5 μm) in the air originates from emissions, its concentrations are often affected by confounding meteorological effects. Therefore, direct comparisons of PM2.5concentrations made across two periods, which are commonly used by environmental protection administrations to measure the effectiveness of mitigation efforts, can be misleading. Here, we developed a two-step method to distinguish the significance of emissions and meteorological factors and assess the effectiveness of emission mitigation efforts. We modeled ambient PM2.5concentrations from 1980 to 2014 based on three conditional scenarios: realistic conditions, fixed emissions, and fixed meteorology. The differences found between the model outputs were analyzed to quantify the relative contributions of emissions and meteorological factors. Emission-related gridded PM2.5concentrations excluding the meteorological effects were predicted using multivariate regression models, whereas meteorological confounding effects on PM2.5fluctuations were characterized by probabilistic functions. When the regression models and probabilistic functions were combined, fluctuations in the PM2.5concentrations induced by emissions and meteorological factors were quantified for all model grid cells and regions. The method was then applied to assess the historical and future trends of PM2.5concentrations and potential fluctuations on global, national, and city scales. The proposed method may thus be used to assess the effectiveness of mitigation actions.