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Air pollution exerts crucial influence on crop yields and impacts regional and global food supplies. Here we employ a statistical model using satellite-based observations and flexible functional forms to analyse the synergistic effects of reductions in ozone and aerosols on China's food security. The model consistently shows that ozone is detrimental to crops, whereas aerosol has variable effects. China's maize, rice and wheat yields are projected to increase by 7.84%, 4.10% and 3.43%, respectively, upon reaching two air quality targets (60 μg m -3 for peak-season ozone and 35 μg m -3 for annual fine particulate matter). Average calories produced from these crops would surge by 4.51%, potentially allowing China to attain grain self-sufficiency 2 years earlier than previously estimated. These results show that ozone pollution control should be a high priority to increase staple crop edible calories, and future stringent air pollution regulations would enhance China's food security., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Recent evidence shows that carbon emissions in China are likely to peak ahead of 2030. However, the social and economic impacts of such an early carbon peak have rarely been assessed. Here we focus on the economic costs and health benefits of different carbon mitigation pathways, considering both possible socio-economic futures and varying ambitions of climate policies. We find that an early peak before 2030 in line with the 1.5 °C target could avoid ~118,000 and ~614,000 PM 2.5 attributable deaths under the Shared Socioeconomic Pathway 1, in 2030 and 2050, respectively. Under the 2 °C target, carbon mitigation costs could be more than offset by health co-benefits in 2050, bringing a net benefit of $393-$3,017 billion (in 2017 USD value). This study not only provides insight into potential health benefits of an early peak in China, but also suggests that similar benefits may result from more ambitious climate targets in other countries., (© 2022. The Author(s).)

China started to implement comprehensive measures to mitigate traffic pollution at the end of 1990s, but the comprehensive effects, especially on ambient air quality and public health, have not yet been systematically evaluated. In this study, we analyze the effects of vehicle emission control measures on ambient air pollution and associated deaths attributable to long-term exposures of fine particulate matter (PM 2.5 ) and O 3 based on an integrated research framework that combines scenario analysis, air quality modeling, and population health risk assessment. We find that the total impact of these control measures was substantial. Vehicular emissions during 1998-2015 would have been 2-3 times as large as they actually were, had those measures not been implemented. The national population-weighted annual average concentrations of PM 2.5 and O 3 in 2015 would have been higher by 11.7 μg/m 3 and 8.3 parts per billion, respectively, and the number of deaths attributable to 2015 air pollution would have been higher by 510 thousand (95% confidence interval: 360 thousand to 730 thousand) without these controls. Our analysis shows a concentration of mortality impacts in densely populated urban areas, motivating local policymakers to design stringent vehicle emission control policies. The results imply that vehicle emission control will require policy designs that are more multifaceted than traditional controls, primarily represented by the strict emission standards, with careful consideration of the challenges in coordinated mitigation of both PM 2.5 and O 3 in different regions, to sustain improvement in air quality and public health given continuing swift growth in China's vehicle population., Competing Interests: The authors declare no competing interest.

Holding the largest recoverable reserves over the world, China makes an ambitious plan to increase shale gas production. Here we use an integrated approach to quantify its impact on indoor and outdoor air quality and greenhouse gas emissions. This approach includes emission estimation, three-dimensional atmospheric chemistry modeling, and human health assessment. Although the production of shale gas generates PM 2.5 , this risk is outweighed by the benefits of the decreased PM 2.5 resulted from coal combustion when shale gas replaces coal as a fuel source. The total avoided premature deaths are 14,000 (10,650-17,160 as 95% confidence interval) and 13,400 (10,350-17,100) in 2017, resulted from the outdoor and indoor pathways, respectively. Future scenario analysis suggests deploying shale gas in the residential sector, but the greenhouse gas emission reductions are minimal if replacing biomass fuel. In production regions, a net deterioration of air quality is predicted if deploying shale gas in the power and industrial sectors, but a net benefit is calculated if deploying in the residential sector. Our study calls for more stringent emission control during upstream processes, and comprehensive consideration of the cost and benefits in both the production and consumption regions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Large-scale population migration accompanied by rapid urbanization is expected to cause the spatial relocation of air pollution because of heterogeneous energy use and consumption preferences of rural versus urban areas in China. In this study, we adopted an integrated approach by combining a population migration model and environmentally extended input-output analysis to quantify impacts of rural-to-urban (RU) and urban-to-urban (UU) migrations on emissions of NO x , SO 2 , and primary PM 2.5 in China. Results indicate that population migration increases NO x (1.42 Mt), SO 2 (1.30 Mt), and primary PM 2.5 (0.05 Mt) emissions, accounting respectively for 5.4, 4.8, and 0.4% of China's total in 2012. RU migration, involving 54% of the migrating population, significantly increases NO x and SO 2 emissions because of high urban indirect per-capita emissions from consumption and investment. RU migration influences negligibly primary PM 2.5 emissions reflecting the small rural-urban difference in per-capita emissions. Interestingly, UU migration, mostly from inland to coastal provinces, leads to a slight emission decrease for the three pollutants, attributable to the greener development in coastal cities. A significant emission growth can be traced back to heavy and utility industries, suggesting that future emission control of these sectors should reduce the exposure to air pollution of the growing urban population.

With frequent severe haze and smog episodes in Chinese cities, an increasing number of studies have focused on estimating the impact of fine particulate matter (PM 2.5 ) on public health. However, the current use of national and provincial demographic data might mask regional differences and lead to inaccurate estimations of pollution-related health impacts across cities. We applied the Global Burden of Disease methodology to develop a dataset of premature deaths attributed to ambient PM 2.5 in 129 Chinese cities in 2006, 2010 and 2015, based on the information of baseline mortality rates and population densities at the city level. Our results suggested that ambient PM 2.5 pollution led to 631,230 (95% confidence interval: 281,460-873,800) premature deaths in those cities in 2015, which was similar to that in 2010, but 42.8% higher than that in 2006. The reduction of premature deaths was not as obvious as the improvement in air quality in recent years, primarily owing to the aging Chinese population. For large and medium/small cities, the effects of PM 2.5 abatement on alleviating public health burdens were lower than those for megalopolises and metropolises; however, such large and medium/small cities are at risk of increasing future PM 2.5 pollution levels due to rapid development. Significant differences in PM 2.5 -induced premature deaths indicated the need for specific policies to mitigate the health burden of air pollution in different types of Chinese cities., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Serious air pollution has caused about one million premature deaths per year in China recently. Besides cross-border atmospheric transport of air pollution, trade also relocates pollution and related health impacts across China as a result of the spatial separation between consumption and production. This study proposes an approach for calculating the health impacts of emissions due to a region's consumption based on a multidisciplinary methodology coupling economic, atmospheric, and epidemiological models. These analyses were performed for China's Beijing and Hebei provinces. It was found that these provinces' consumption-based premature deaths attributable to ambient PM 2.5 were respectively 22,500 and 49,700, which were 23% higher and 37% lower than the numbers solely within their boundaries in 2007. The difference between the effects of trade and trade-related emissions on premature deaths attributable to air pollution in a region has also been clarified. The results illustrate the large and broad impact of domestic trade on regional air quality and the need for comprehensive consideration of supply chains in designing policy to mitigate the negative health impacts of air pollution across China., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Recent studies show that international trade affects global distributions of air pollution and public health. Domestic interprovincial trade has similar effects within countries, but has not been comprehensively investigated previously. Here we link four models to evaluate the effects of both international exports and interprovincial trade on PM 2.5 pollution and public health across China. We show that 50-60% of China's air pollutant emissions in 2007 were associated with goods and services consumed outside of the provinces where they were produced. Of an estimated 1.10 million premature deaths caused by PM 2.5 pollution throughout China, nearly 19% (208,500 deaths) are attributable to international exports. In contrast, interprovincial trade leads to improved air quality in developed coastal provinces with a net effect of 78,500 avoided deaths nationwide. However, both international export and interprovincial trade exacerbate the health burdens of air pollution in China's less developed interior provinces. Our results reveal trade to be a critical but largely overlooked consideration in effective regional air quality planning for China.International and domestic interprovincial trade of China are entangled, but their health impacts have been treated separately in earlier studies. Here Wang. quantify the complex impacts of trade on public health across China within an integrative framework.

While recent assessments have quantified the burden of air pollution at the national scale in China, air quality managers would benefit from assessments that disaggregate health impacts over regions and over time. We took advantage of a new 10×10km satellite-based PM 2.5 dataset to analyze spatial and temporal trends of air pollution health impacts in China, from 2004 to 2012. Results showed that national PM 2.5 related deaths from stroke, ischemic heart disease and lung cancer increased from approximately 800,000 cases in 2004 to over 1.2 million cases in 2012. The health burden exhibited strong spatial variations, with high attributable deaths concentrated in regions including the Beijing-Tianjin Metropolitan Region, Yangtze River Delta, Pearl River Delta, Sichuan Basin, Shandong, Wuhan Metropolitan Region, Changsha-Zhuzhou-Xiangtan, Henan, and Anhui, which have heavy air pollution, high population density, or both. Increasing trends were found in most provinces, but with varied growth rates. While there was some evidence for improving air quality in recent years, this was offset somewhat by the countervailing influences of in-migration together with population growth. We recommend that priority areas for future national air pollution control policies be adjusted to better reflect the spatial hotspots of health burdens. Satellite-based exposure and health impact assessments can be a useful tool for tracking progress on both air quality and population health burden reductions., (Copyright © 2016. Published by Elsevier Ltd.)

This study explored the factors that influence respondents' willingness to pay (WTP) for CO2 mitigation under climate change. A questionnaire survey combined with contingent valuation and psychometric paradigm methods were conducted in the city of Suzhou, Jiangsu Province in China. Respondents' traditional demographic attributes, risk perception of greenhouse gas (GHG), and attitude toward the government's risk management practices were established using a Tobit model to analyze the determinants. The results showed that about 55% of the respondents refused to pay for CO2 mitigation, respondent's WTP increased with increasing CO2 mitigation percentage. Important factors influencing WTP include people's feeling of dread of GHGs, confidence in policy, the timeliness of governmental information disclosure, age, education and income level., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

A grid-based, bottom-up method has been proposed by combining a vehicle emission model and a travel demand model to develop a high-resolution vehicular emission inventory for Chinese cities. Beijing is used as a case study in which the focus is on fuel consumption and emissions from hot-stabilized activities of light-duty gasoline vehicles (LGVs) in 2005. The total quantity of emissions, emission intensity, and spatial distribution of emissions at 1- by 1-km resolution are presented and compared with results from other inventory methods commonly used in China. The results show that the total daily fuel consumption and vehicular emissions of carbon dioxide, carbon monoxide, hydrocarbons, and oxides of nitrogen from LGVs in the Beijing urban area in 2005 were 1.95 x 10(7) L, 4.28 x 10(4) t, 1.97 x 10(3) t, 0.28 x 10(3) t, and 0.14 x 10(3) t, respectively. Vehicular fuel consumption and emissions show spatial variations that are consistent with the traffic characteristics. The grid-based inventory developed in this study reflects the influence of traffic conditions on vehicle emissions at the microscale and may be applied to evaluate the effectiveness of traffic-related measures on emission control in China.

To improve the accuracy and applicability of vehicular emission models, this study proposes a speed and vehicle-specific power (VSP) modeling method to estimate vehicular emissions and fuel consumption using data gathered by a portable emissions monitoring system (PEMS). The PEMS data were categorized into discrete speed-VSP bins on the basis of the characteristics of vehicle driving conditions and emissions in Chinese cities. Speed-VSP modal average rates of emissions (or fuel consumption) and the time spent in the corresponding speed-VSP bins were then used to calculate the total trip emissions (or fuel consumption) and emission factors (or fuel economy) under specific average link speeds. The model approach was validated by comparing it against measured data with prediction errors within 20% for trip emissions and link-speed-based emission factors. This analysis is based on the data of light-duty gasoline vehicles in China; however, this research approach could be generalized to other vehicle fleets in other countries. This modeling method could also be coupled with traffic demand models to establish high-resolution emissions inventories and evaluate the impacts of traffic-related emission control measures.

Vehicle exhaust emissions have posed a serious threat in recent years to the urban air quality of Beijing. It is necessary to accurately estimate the magnitude and distribution of these emissions in order to reduce the uncertainty of local scale air quality modeling assessment. This paper provides a bottom-up approach by combining vehicle emission factors and vehicle activity data from a travel demand model estimated at the grid level to generate vehicle emissions data for the Beijing urban area in 2005. In that year, vehicular emissions of HC, CO and NOx were respectively 13.33x10(4), 100.02x10(4) and 7.55x10(4) tons. The grid-based emissions were also compared with the vehicular emission inventory developed by macro-scale approach. It shows this bottom-up approach can result in better estimates of the levels and spatial distribution of vehicle emissions than the macro-scale method that relies on more average and aggregated information.

Surface ozone is damaging to human health and crop yields. When evaluating global air pollution risk, gridded datasets with high accuracy are desired to reflect the local variations in air pollution concentrations. Here, a cluster‐enhanced ensemble machine learning method was used to develop a new 0.5‐degree monthly surface ozone data set during 2003–2019 by combining numerous informative variables. The overall accuracy of our data set is 91.5% (90.8% for space and 92.3% for time). Historically, populations in South Asia, North Africa and Middle‐East, and High‐income North America are exposed to the highest ozone concentrations. Globally, the population weighted ozone concentration in the peak season is 47.07 ppbv. Our results highlight that ozone pollution is intensifying in some regions, and implicate air quality management is crucial to secure human health from air pollution. Plain Language Summary: Surface ozone is one of the most hazardous air pollutants to human health and plants. However, estimation of global surface ozone is still limited. Here, by using state‐of‐the‐art machine learning techniques, we fuse satellite, chemical transport model outputs, atmospheric reanalyses, and emission data with surface observations to construct a full coverage and long‐time period surface ozone data set. We demonstrate that surface population weighted ozone concentration in North America and Europe has decreased from 2003 to 2019, while ozone pollution in East Asia has intensified during 2016–2019. We also show at least 37% of the world's population is exposed to ozone greater than the World Health Organization's interim target one of 50 ppbv (MDA8) in the peak season. Our results could help identify the key regions for improving global air quality and offers an insightful data set for human health assessments and air quality management. Key Points: A cluster‐enhanced ensemble machine learning method can predict global surface ozone with high accuracyPopulations in South Asia, North Africa and Middle‐East, and High‐income North America are exposed to the highest MDA8 during 2003–2019At least 37% of world's population is exposed to greater than 50 ppbv MDA8 in peak seasons [ABSTRACT FROM AUTHOR]

Urban air pollution has tremendous spatial variability at scales ranging from kilometers to meters due to unevenly distributed emission sources, complex flow patterns, and photochemical reactions. However, high-resolution air quality information is not available through traditional approaches such as ground-based measurements and regional air quality models (with typical resolution > 1 km). Here we develop a 10 m resolution air quality model for traffic-related CO pollution based on the Parallelized Large-Eddy Simulation Model (PALM). The model performance is evaluated with measurements obtained from sensors deployed on a taxi platform, which collects data with a comparable spatial resolution to our model. The very high resolution of the model reveals a detailed geographical dispersion pattern of air pollution in and out of the road network. The model results (0.92 ± 0.40 mg m -3) agree well with the measurements (0.90 ± 0.58 mg m -3 , n=114502). The model has similar spatial patterns to those of the measurements, and the r2 value of a linear regression between model and measurement data is 0.50 ± 0.07 during non-rush hours with middle and low wind speeds. A non-linear relationship is found between average modeled concentrations and wind speed with higher concentrations under calm wind speeds. The modeled concentrations are also 20 %–30 % higher in streets that align with the wind direction within ∼ 20 ∘. We find that streets with higher buildings downwind have lower modeled concentrations at the pedestrian level, and similar effects are found for the variability in building heights (including gaps between buildings). The modeled concentrations also decay fast in the first ∼ 50 m from the nearest highway and arterial road but change slower further away. This study demonstrates the potential of large-eddy simulation in urban air quality modeling, which is a vigorous part of the smart city system and could inform urban planning and air quality management. [ABSTRACT FROM AUTHOR]

China has implemented active clean air policies in recent years, and the spatiotemporal patterns of major pollutant emissions have changed substantially. In this study, we construct a regional air pollution data assimilation system based on the WRF/CMAQ model and ensemble Kalman filter algorithm to quantitatively optimize gridded CO emissions using hourly surface CO measurements over China. The Multi‐resolution Emission Inventory of China CO emission inventories in December 2012 and 2016 are treated as prior emissions, and the CO emissions in December 2013 and 2017 are optimized using the CO observations of December of 2013 and 2017, respectively. The results show that in both periods, assimilation of CO observations significantly improves the CO simulations and emission estimates. Assimilation increases the CO emissions in most areas of mainland China, especially in northern China, and the spatial patterns of the increases in the two periods are similar. Overall, the posterior CO emissions in December 2017 are 17% lower than those in December 2013. Large emission decreases are mainly found in most key urban areas and developed regions, and emission increases are mainly located in their surrounding areas and certain central and western regions, which might reflect the emission migration from developed regions or urban areas to developing regions or surrounding areas. These changes are not found in the prior emissions but are basically consistent with the emission control strategies and industrial transformation and upgrade phenomena in recent years, indicating that our CO assimilation system could successfully capture the temporal and spatial variations. Plain Language Summary: CO emissions over China in December 2013 and 2017 were optimized using surface hourly CO observations, and the emission changes between these two periods were presented. We found that there were large emission decreases in key urbans and developed regions, and increases in their surrounding areas and some central and western regions, which were basically consistent with the emission control strategies and industrial transformation in recent years, might reflect the emission migration. Key Points: A regional air pollution data assimilation system based on WRF/CMAQ and EnKF is constructedOverall, the CO emissions are reduced by 17% between December 2013 and 2017 over the whole mainland of ChinaThe emissions migration is found in the posterior emissions but not shown in the prior emissions [ABSTRACT FROM AUTHOR]

Multiyear inventories of vehicular emissions in Beijing, Shanghai and Guangzhou from 1995 through 2005 have been developed in this paper to study the vehicle emissions trends in China''s mega cities during the past decade. The results show that the vehicular emissions of CO, HC, NO x and PM10 have begun to slow their growth rates and perhaps even to decline in recent years due to the implementation of measures to control vehicular emissions in these cities. However, vehicular CO2 emissions have substantially increased and still continue to grow due to little fuel economy improvement. Passenger cars and large vehicles (including heavy duty trucks and buses) are the major sources of vehicular CO2 and CO emissions while large vehicles were responsible for nearly 70% and 80% of the vehicular NO x and PM10 emissions in these mega cities. Motorcycles are also important contributors to vehicular emissions in Guangzhou and Shanghai. [Copyright &y& Elsevier]

As vehicle population and activity increase, vehicle emissions are becoming the most predominant source of air pollution in Shanghai, China. It has become important to accurately estimate the traffic emissions in this city. This paper presents a bottom–up approach based on the International Vehicle Emission (IVE) model to develop the vehicle emission inventory for Shanghai. The results show that the total emissions of CO, VOC, NO X and PM from vehicles in Shanghai in 2004 were 57.06×104 t, 7.75×104 t, 9.20×104 t and 0.26×104 t, respectively. About 20% of the total emissions were emitted during the cold start period. Heavy-duty vehicles such as trucks and buses contributed over half of NO X and PM. Motorcycles and mopeds provided 45.0% of VOC and 36.3% of PM. Light-duty vehicles are the main source of CO emissions. An assessment of vehicle emissions by time of day and road type was also discussed. The three peak emission periods accounted for 54% to 56% of the total emissions during the day and more than 50% of the total emissions were emitted on the arterial roads. Finally, the study focused on the uncertainty analysis of two critical factors: emission factors and the estimate of the total Vehicle Kilometers Traveled (VKT). The analysis indicates that the emission factors calculated in this paper are close to those factors measured during on-road testing, and the difference between the VKT used in this paper and other calculations is less than 10%. [Copyright &y& Elsevier]

Abstract Emissions from power plants in China and India contain a myriad of fine particulate matter (PM 2.5 , PM ≤ 2.5 μm in diameter) precursors, posing significant health risks among large, densely settled populations. Studies isolating the contributions of various source classes and geographic regions are limited in China and India, but such information could be helpful for policy makers attempting to identify efficient mitigation strategies. We quantified the impact of power generation emissions on annual mean PM 2.5 concentrations using the state-of-the-art atmospheric chemistry model WRF-Chem (Weather Research Forecasting model coupled with Chemistry) in China and India. Evaluations using nationwide surface measurements show the model performs reasonably well. We calculated province-specific annual changes in mortality and life expectancy due to power generation emissions generated PM 2.5 using the Integrated Exposure Response (IER) model, recently updated IER parameters from Global Burden of Disease (GBD) 2015, population data, and the World Health Organization (WHO) life tables for China and India. We estimate that 15 million (95% Confidence Interval (CI): 10 to 21 million) years of life lost can be avoided in China each year and 11 million (95% CI: 7 to 15 million) in India by eliminating power generation emissions. Priorities in upgrading existing power generating technologies should be given to Shandong, Henan, and Sichuan provinces in China, and Uttar Pradesh state in India due to their dominant contributions to the current health risks. Highlights • Health risks of emissions from power plants in China and India are estimated using the state-of-the-science framework. • Both mortality burdens and years of life lost (YLL) are calculated for each province/state in China and India. [ABSTRACT FROM AUTHOR]

[Display omitted] • Vehicle population is projected to peak around 2045 in China's Yangtze River Delta. • Environmental impacts of fleet electrification largely depend on local energy structure. • Health impacts of fleet electrification on reducing NO 2 exposure might surpass PM 2.5 and O 3. • Rapid fleet electrification in densely populated cities could lead to substantial health benefits. Fleet electrification is one of the most promising strategies to mitigate carbon emissions and improve air quality. This study provides a comprehensive analysis of the currently unclear CO 2 mitigation and human health benefits from electric vehicle (EV) adoption and energy decarbonization in the Yangtze River Delta (YRD) region by integrating fleet modeling, emission projection, air quality modeling and health risk assessment. Based on future socioeconomic trajectories, we project that the total vehicle stock in the YRD region will peak at 107 – 117 million around 2045 – 2050. The transition to EVs combined with largely renewable energy in the YRD region can potentially reduce CO 2 emissions by 870 Tg in 2060 and brings along substantial health co-benefits with ∼360 avoided premature deaths per million from reduced PM 2.5 and O 3 concentrations. This study further explores the NO 2 -attributable burden from road transportation and reveals that fleet electrification could yield greater NO 2 -attributable health benefits than those from reduced PM 2.5 and O 3 , especially in traffic-dense urban areas. Those findings indicate that China's near-term energy development plans (35% renewable energy) have created the conditions for large-scale EV adoption. Our results imply that the benefits of EVs exhibit substantial spatial heterogeneity, underscoring the importance of region-specific EV incentive policies, and hint that policymakers should prioritize densely populated megacities to maximize the potential for public health gains. [ABSTRACT FROM AUTHOR]

With rapid economic growth, China has witnessed increasingly frequent and severe haze and smog episodes over the past decade, posing serious health impacts to the Chinese population, especially those in densely populated city clusters. Quantification of the spatial and temporal variation of health impacts attributable to ambient fine particulate matter (PM 2.5 ) has important implications for China's policies on air pollution control. In this study, we evaluated the spatial distribution of premature deaths in China between 2000 and 2010 attributable to ambient PM 2.5 in accord with the Global Burden of Disease based on a high resolution population density map of China, satellite retrieved PM 2.5 concentrations, and provincial health data. Our results suggest that China's anthropogenic ambient PM 2.5 led to 1,255,400 premature deaths in 2010, 42% higher than the level in 2000. Besides increased PM 2.5 concentration, rapid urbanization has attracted large population migration into the more developed eastern coastal urban areas, intensifying the overall health impact. In addition, our analysis implies that health burdens were exacerbated in some developing inner provinces with high population density (e.g. Henan, Anhui, Sichuan) because of the relocation of more polluting and resource-intensive industries into these regions. In order to avoid such national level environmental inequities, China's regulations on PM 2.5 should not be loosened in inner provinces. Furthermore policies should create incentive mechanisms that can promote transfer of advanced production and emissions control technologies from the coastal regions to the interior regions. [ABSTRACT FROM AUTHOR]