Yilin Chen

Urbanization-driven, large-scale rural-to-urban migration in China has substantially modernized household energy use and reshaped air pollution exposure pathways. However, the magnitude, underlying drivers, and temporal evolution of the resulting health outcomes from combined indoor and outdoor air pollution remain insufficiently resolved. Here, by coupling a reconstruction of seven decades of migration (1949–2021) with nationwide household energy surveys, we quantify migration-attributable changes in integrated (indoor + outdoor) PM_2.5 exposure and mortality. Relative to a no-migration counterfactual from 1949 onward, migration reduced integrated PM_2.5 exposure by 27.6 μg·m^–3 (15.7−39.4 as the 95% confidence interval) in 2019 and cumulatively avoided 2.3 (1.9–2.6) million deaths since 1949, with reductions in indoor exposure providing the dominant contribution. Arising from rural–urban disparities in household energy use, these health gains were pronounced even during intermediate stages of societal development and are likely to occur in other transitioning economies worldwide. Our study thus challenges the conventional view that rapid urbanization in developing economies is strictly detrimental to environmental health.

Stir-fry cooking (SFC) is a common food preparation method in Chinese cities, but its contribution to indoor air pollution and related health effects on a national scale remains unclear. Here, we evaluate SFC emissions and health impacts on urban indoor air quality and population health in Chinese cities using PM_2.5 measurements in 94 households across 15 Chinese cities over one year. By decomposing the observed time series data of indoor PM_2.5 into contributions from SFC, outdoor-to-indoor infiltration, and other indoor sources, our results show that SFC raises indoor PM_2.5 levels in kitchens and living rooms by 21% and 7%, respectively. Taking both indoor and outdoor exposure into consideration, the disability-adjusted life years (DALYs) attributable to PM_2.5 with SFC or without SFC were 15.1 (95% CI: 10.2–20.1) million years or 13.7 (95% CI: 9.0–18.6) million years, respectively. Females and the elderly are more affected. Proper use of ventilation reduces these impacts, but many households still face elevated risks. Our findings highlight the health challenges posed by indoor air pollution from SFC and suggest that improved ventilation, less frequent stir-frying, and use of air purifiers or face masks can help lower these risks.

Persistent discrepancies exist between bottom-up inventories and satellite-based ammonia (NH3) emission estimates, with satellites typically reporting values one-third higher. These discrepancies prevent accurate targeting of NH3 control policies for reducing air pollution and ecosystem nitrogen deposition. Here we demonstrate that systematic biases in satellite vertical profile assumptions substantially explain these long-standing discrepancies. By replacing default vertical profile in satellite retrievals with spatially and temporally resolved atmospheric profiles, we reduced satellite-model discrepancies from 71% to 18%. Our hybrid inversion analysis across China reveals that baseline satellite retrievals overestimated growing season emissions by up to 44% due to systematic overestimation of near-surface NH3 concentrations, while our corrected estimates show close agreement with bottom-up inventories (7.9% difference). Critically, our analysis reveals that China’s NH3 emissions are more spatially concentrated than the a priori inventory indicates, with the top 10% of high-emitting areas contributing 54-56% of national emissions. This concentration reflects agricultural intensification patterns inadequately captured by bottom-up inventories. Independent validation confirms improved accuracy with 1-27% error reductions across all months. These findings provide essential insights for targeted emission control policies in the most concentrated agricultural regions while resolving methodological uncertainties that have long complicated NH3 management strategies.

The co-mitigation of carbon emissions and air pollutants offers substantial benefits but is complicated by divergent sectoral emission profiles and spatial disparities. By integrating input-output analysis with health impact source attribution, we examine how interprovincial trade redistributes CO₂ emissions and PM_2.5-related mortality across China's supply chains. We find that demand from economically advanced provinces induces two distinct burden-shifting patterns between carbon emissions and health burdens. Carbon emissions are outsourced to sparsely populated northwestern regions through power generation, while health burdens concentrate in the densely populated industrial manufacturing belt of central and northern China. Despite production-side divergences, we identify a notable alignment at the final production level, offering opportunities to narrow the energy intensity gap through supply chain coordination. We simulate three convergence scenarios in which upstream producers in the nonmetal, metal, and power sectors adopt energy intensities of their downstream partners. These include full convergence (100% adoption) and two partial convergence scenarios (75% and 50% adoption), with the latter constrained by national benchmark performance. Full convergence reduces trade-related CO₂ emissions by 17% (491 Mt) and averts 19% of associated mortality (3.8 × 10⁴ deaths). Partial convergence scenarios still deliver meaningful co-benefits. This demonstrates that supply chain coordination offers pathways to reconciling production-side disparities and more balanced climate-health co-benefits in China.

Persistent discrepancies exist between bottom-up inventories and satellite-based ammonia (NH₃) emission estimates, with satellites typically reporting values one-third higher. These discrepancies prevent accurate targeting of NH₃ control policies for reducing air pollution and ecosystem nitrogen deposition. Here, we demonstrate that systematic biases in satellite vertical profile assumptions substantially explain these long-standing discrepancies. By replacing default vertical profile in satellite retrievals with spatially and temporally resolved atmospheric profiles, we reduced satellite-model discrepancies from 71 to 18%. Our hybrid inversion analysis across China reveals that baseline satellite retrievals overestimated growing season emissions by up to 44% due to systematic overestimation of near-surface NH₃ concentrations, while our corrected estimates show close agreement with bottom-up inventories (7.9% difference). Critically, our analysis reveals that China's NH₃ emissions are more spatially concentrated than what the a priori inventory indicates, with the top 10% of high-emitting areas contributing 54-56% of national emissions. This concentration reflects agricultural intensification patterns inadequately captured by bottom-up inventories. Independent validation confirms improved accuracy with 1-27% error reductions across all months. These findings provide essential insights for targeted emission control policies in the most concentrated agricultural regions while resolving methodological uncertainties that have long complicated NH₃ management strategies.

Ammonia (NH3) emissions significantly contribute to atmospheric pollution, yet discrepancies exist between bottom-up inventories and satellite-constrained top-down estimates, with the latter typically one-third higher. This study quantifies how assumptions about NH3 vertical distribution in satellite retrievals contribute to this gap. By implementing spatially and temporally resolved vertical profiles from the Community Multiscale Air Quality model to replace steep gradients in Infrared Atmospheric Sounding Interferometer (IASI) retrievals, we reduced satellite-model column discrepancies from 71% to 18%. We subsequently constrained NH3 emissions across China using a hybrid inversion framework combining iterative mass balance and four-dimensional variational methods. Our posterior emissions showed agreement with the a priori inventory (7.9% lower), suggesting that discrepancies between inventory approaches were amplified by overestimation of near-surface NH3 in baseline satellite retrievals, potentially causing a 43% overestimation of growing season emissions. Evaluation against ground-based measurements confirmed improved model performance, with normalized root-mean-square error reductions of 1-27% across six months. These findings demonstrate that accurate representation of vertical profiles in satellite retrievals is critical for robust NH3 emission estimates and can reconcile the long-standing discrepancy between bottom-up and top-down approaches. Our hybrid inversion methodology, leveraging profile-corrected satellite data, reveals that China's NH3 emissions exhibit greater spatial concentration than previously recognized, reflecting agricultural intensification. This advancement enables timely and accurate characterization of rapidly changing agricultural emission patterns, critical for implementing effective nitrogen pollution control measures.

China's dual strategy to mitigate climate change and air pollution is constrained by insufficient data on the distinct sources of carbon emissions and associated health damages. This study utilizes adjoint emission sensitivity modeling with the CMAQ Adjoint model, alongside an exposure-response model and a multiregional input-output model, to perform high-resolution source attribution across 53 production sectors and fuel/process combinations, as well as 42 consumption economic sectors. Our analysis uncovers significant discrepancies between sources of CO2 emissions and PM2.5-related premature mortality, with monetized health damages surpassing climate impacts in over half of the subsectors examined. Additionally, more than one third of the CO2 emissions and health damages are outsourced from well-developed coastal provinces to less-developed inland provinces, though the regions absorbing these burdens differ geographically. CO2 emissions are primarily shifted to the northwestern region, which relies heavily on coal as an energy source, while PM2.5-related deaths are concentrated in the central region, the heavy industrial hub of China with high population densities. These findings demonstrate that high population densities and lower adoption of control technologies exacerbate health damages, particularly in downstream provinces that bear the majority of emission leakages. The CMAQ Adjoint model’s capability to evaluate the marginal benefits of emission reductions at a granular level enabled precise source attribution by incorporating emission profiles, population density, and atmospheric conditions. This research underscores the critical advantage of adjoint modeling in integrating health and climate impacts, advocating for tailored mitigation strategies that address emissions from both production and consumption sides to achieve balanced decarbonization and effective health risk mitigation in China.

Port cities, as crucial nodes in global supply chains, face challenges from both intense traffic emissions and vulnerability to climate-related extremes due to pollution density. Effective and near-term mitigation strategies for greener road freight are imperative to reverse the increasing trend of emissions. This study utilizes a high-resolution emission inventory from 1.2 billion global positioning system trajectories of heavy-duty trucks in Shenzhen, a global port city, to evaluate the combined effects of road network development and fleet electrification on emissions from 2016 to 2035, providing a basis for policy interventions applicable to various urban contexts. Our findings reveal that an integrated strategy decreases road freight emissions, cutting peak carbon dioxide and nitrogen oxide emissions by 34% and 43%, respectively, compared to electrification-only scenarios. While fleet electrification supported by net-zero emission grids is necessary, it is insufficient without addressing congestion and enhancing connectivity through expanded road networks. Spatial projections also assist targeted policymaking by showing how emission distributions shift with regional road network expansion.