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China put forward that it would strive to achieve the carbon peaking in 2030 and carbon neutrality goals in 2060, which needed realizing the synergistic effect of pollution reduction and CO 2 reduction. CO 2 and PM 2.5 from coal consumption were "homogenous and synchronous" and they had significant synergistic effect. The synergistic reduction of PM 2.5 from coal consumption could have impacts on public health. The Logarithmic Mean Divisia Index (LMDI) was adopted to decompose the PM 2.5 from coal consumption in China from 2012 to 2017 based on data availability and quantified the synergy. PM 2.5 emissions from coal consumption were forecasted in 2030, 2035, 2050 and 2060, and its health effects of PM 2.5 were estimated. The main conclusions were: (1) the synergy of CO 2 and PM 2.5 was the largest contribution factor of PM 2.5 from coal consumption. (2) PM 2.5 from coal consumption in 2060 would achieve the WHO air quality guidelines. (3) The most health effects economic loss from PM 2.5 generated by coal consumption in China was in 2014. The health effects economic loss would have been decreased to negative by 2050. We should reinforce the synergistic effect of CO 2 and PM 2.5 , improve energy efficiency and optimize energy structure to achieve PM 2.5 pollution control and reduce health effects economic loss., 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 © 2022 Elsevier Ltd. All rights reserved.)

The emissions reduction of CO 2 and air pollutants are the main task in China. The two have the same roots and they interact with each other. However, CO 2 and air pollutants are quite different in space, so it is of great practical significance to explore the spatial differences of their synergy. As PM 2.5 and O 3 are more concerned at present, thus, this paper examined the decoupling of CO 2 , PM 2.5 and O 3 from GDP in China's 296 cities using the latest available data from 2015 to 2016. And the spatial differences of synergy among CO 2 , PM 2.5 and O 3 were quantitatively analyzed by using spatial autocorrelation analysis and geographically weighted regression model. The results showed that: (1) The cities achieving the three synergy emissions reduction were mainly in the southeast of China. (2) Only 26 cities had achieved the strong decoupling of CO 2 , PM 2.5 and O 3 from GDP. (3) The synergy characteristics between CO 2 and PM 2.5 , CO 2 and O 3 were different. This paper put forward the policies according to the conclusions., 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 © 2022 Elsevier B.V. All rights reserved.)

Due to the fast growth of China's economy, urban atmospheric pollution has become a serious problem affecting the public's physical and mental health. The '2 + 26' cities, as the Jing-Jin-Ji atmospheric pollution transmission channel, has attracted widespread concern. There were several previous studies on the economic loss of public health caused by PM 2.5 pollution in '2 + 26' cities. To assess the economic loss caused by PM 2.5 on human health in '2 + 26' cities, this paper used the exposure-response model, the health effect loss model and willingness to pay method to obtain the economic loss from PM 2.5 pollution with the latest available data in 2020. It was concluded that, in 2020, the economic loss of '2 + 26' cities from PM 2.5 was spatially distributed low in the east and high in the west. In addition, it was larger in the southern and northern part, which was smaller in the middle of the region. Based on the conclusions, policy recommendations were put forward.

At present, the concentration of PM 2.5 in the Fenwei Plain has become the second highest in China, ranking second to the Beijing-Tianjin-Hebei region. At the same time, China began to monitor and control the PM 2.5 concentration in the Fenwei Plain, but the data indicated that the concentration of PM 2.5 in the Fenwei Plain rose instead of falling. PM 2.5 concentrations in 6 cities from the Fenwei Plain ranked highest among the 20 cities in 2018 in China, and PM 2.5 pollution can cause some health economic loss. Based on this background, the exposure-response model is used to estimate the impact of PM 2.5 pollution on the health economic loss in the Fenwei Plain, and PM 2.5 concentration in 2020, 2025, and 2030 is also predicted based on the setting of three scenarios: baseline scenario, emission reduction scenario, and enhanced emission reduction scenario. Then, according to the estimated results, the paper provides suggestions for reducing public health loss in the Fenwei Plain in the future.

The Central Plains Urban Agglomeration is an important growth pole of China's economy, but the rapid economic growth is accompanied by serious air pollution problems. In this paper, the latest available PM 2.5 monitoring data in 2015-2017 and exposure-response relationship model are used to quantitatively analyze the health effect damages due to PM 2.5 pollution. The way of disease cost, adjusted human capital, and willingness to pay were adopted to estimate the economic loss of health effect damages. The results show that health effect damages of PM 2.5 pollution in 2015-2017 were 11.9251 million, 11.4292 million, and 11.1012 million, respectively, accounting for 7.41%, 7.05%, and 6.94% of the total population of this area. The health effect economic loss was 97.398 billion RMB, 93.516 billion RMB, and 94.485 billion RMB, accounting for 1.73%, 1.53%, and 1.41% of the GDP. Chronic bronchitis and premature death due to PM 2.5 are the main sources of health effect economic loss. Elderly people and infants are vulnerable groups of PM 2.5 pollution. Affected by economic growth level, population density, and economic structure, Heze, Zhengzhou, Handan, and Liaocheng were greatly affected by PM 2.5 pollution, and their health effect damages was larger. The health effect damages and health effect economic loss due to PM 2.5 pollution in this area show a downward trend, indicating that air pollution reduction measures have played a positive role. However, the whole effect is still large. According to the results, this paper puts forward the policies.

Jing-Jin-Ji is the largest and most dynamic economic region in northern China, and its air pollution has attracted much public attention. Scientific evaluation of health losses caused by air pollution can provide decision-making basis for formulation and improvement of pollution reduction policies in the Jing-Jin-Ji region. This paper estimated the adverse effects of particulate matter pollution on health in the Jing-Jin-Ji region in 2016 by using logarithmic linear exposure-response function, and monetized the health effects by adjusting human capital method and disease cost method. The results show non-ignorable health hazards and economic impacts caused by atmospheric particulate pollution. The economic losses relevant to health hazards by PM2.5 in the Jing-Jin-Ji region are 122.40 billion yuan, and those relevant to PM10 are 118.34 billion yuan, accounting for 1.62% and 1.56% of the region's GDP, respectively. Similar evaluations previously conducted in other countries yielded figures within the same order of magnitude. Considering the difference in economic losses per unit among disease types, the economic losses caused by air pollution in the Jing-Jin-Ji region mainly come from premature deaths. Infants and elderly people are the main victims of particulate matter. Affected by population, pollutant concentration, industrial structure, and other factors, the economic losses of particulate matter pollution in Beijing, Tianjin, Shijiazhuang, Tangshan, and Baoding are large. In order to reduce health hazards and economic impacts caused by particulate matter pollution, this paper put forward to guide the urban population diversion, reduce the outgoing frequency of susceptible groups such as infants and the elderly in haze weather, adopt high-efficiency particulate matter air purifier indoors, and develop public transportation to reduce motor vehicle exhaust emissions. In Tianjin and Hebei, promoting cleaner production in industries such as steel and cement and reducing coal use in the power industry are also suggested.

Based on the China's 1997, 2002, 2007, and 2012 multiregional input-output model, this study calculates China's provincial CO 2 emissions from investment demand and interprovincial transfer of CO 2 emissions caused by investment demand. The findings of this study are as follows: (1) From 1997 to 2012, the CO 2 emissions from China's investment demand have seen rapid growth-the CO 2 emissions from investment demand has increased by 4.52 times, and the per capita CO 2 emissions caused by investment demand has increased by 4.13 times. Investment demand is an important driver of growth of China's CO 2 emissions. The proportion of CO 2 emissions from investment demand in CO 2 emissions from China's three final demands rose from 37.72% in 1997 to 50.68% in 2012. (2) The CO 2 emissions from investment demand are relatively large in provinces which have large-scale industries. Affected by investment-driven economic growth, CO 2 emissions from investment demand in central, western, and northeastern provinces have increased more rapidly. (3) Large amounts of CO 2 are emitted in the less-developed central and western provinces to meet the investment demand of the developed eastern provinces. As China's economy enters the "new normal," economic growth is shifting from investment-driven to consumption-driven, and the growth of CO 2 emissions from investment demand will slow down.

Jing-Jin-Ji region (i.e., Beijing, Tianjin, and Hebei) is China's key development region, but it is also the leading and most serious air pollution region in China. High fossil fuel consumption is the major source of both carbon dioxide (CO 2 ) emissions and air pollutants. Therefore, it is important to reveal the source of CO 2 emissions to control the air pollution in the Jing-Jin-Ji region. In this study, an interregional input-output model was applied to quantitatively estimate the embodied CO 2 transfer between Jing-Jin-Ji region and other region in China using China's interregional input-output data in 2010. The results indicated that there was a significant difference in the production-based CO 2 emissions in China, and furthermore, the Jing-Jin-Ji region and its surrounding regions were the main regions of the production-based CO 2 emissions in China. Hebei Province exported a large amount of embodied CO 2 to meet the investment, consumption, and export demands of Beijing and Tianjin. The Jing-Jin-Ji regions exported a great deal of embodied CO 2 to the coastal provinces of southeast China and imported it from neighboring provinces.

China's climate and environmental problems remained prominent. Energy transition was the key to improve climate and pollution, and it was at a critical period. Previous studies mostly focused on the impact of climate policies on the reduction of air pollutants and the environmental health impacts of individual sector or pathway policies. Thus, focusing on the synergistic abatement of CO 2 and air pollutants and health effects of energy transition in carbon neutrality was significant for building beautiful and healthy China. LEAP-HEA model was constructed to project energy demand, CO 2 and air pollutants, and assess energy transition's environmental health effects from 2020 to 2060. LMDI model was adopted to decompose the abatement contribution. Synergistic assessment index was used to estimate the coordinated abatement effects. Cost-effectiveness of energy transition and regional heterogeneity of PM 2.5 toxicity were not considered. The results indicated: (1) energy demand would decrease and structure would be optimized significantly under deep energy transition scenario. (2) Deep energy transition could promote earlier realization of carbon neutrality. It would contribute significantly to CO 2 and air pollutants abatement with strong synergistic effects. (3) Energy transition would reduce health risks with large economic benefits. Recommendations were proposed based on the conclusions. The framework of LEAP-HEA model. [Display omitted] • The synergistic abatement and health effect of energy transition were explored. • The models of LEAP, LMDI, exposure-response and the data of 2020 were used. • Energy transition would have significant synergistic abatement and health effect. • The paper has significance for promoting carbon neutrality and healthy China. [ABSTRACT FROM AUTHOR]

China's economic growth is accompanied by air pollution, which has harmed public health. Former scholars have explored the influencing factors of public health from different perspectives with different methods, among which family income and environmental pollution are two important factors. The paper explored the combined effects of economic level and air pollution on public health at the micro and macro level using the multivariate ordered Logit model and panel data regression model. A comparative analysis was also explored between China's eastern and western regions. The results demonstrated that: (1) Both at the micro and macro level, economic level was positively correlated with public health, while air pollution was negatively correlated with it. (2) The improvement of the economic level made public health more susceptible to air pollution at the micro level and at the macro level. (3) The higher the economic level, the lower the effect of economic growth in reducing the adverse effects of air pollution on public health. This paper proposed that sustainable economic growth should be pursued, the emissions of air pollutants should be reduced, regional development should be balanced and the development gap between China's eastern and western regions should be narrowed. [ABSTRACT FROM AUTHOR]