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Wang SW, Tang KQ, Zhang HR, Liu WW, Bai L, Li N. [Effect of Carbon Dioxide Emission Reduction Policy on Air Quality Improvement in Jiangsu Province]. Huan Jing Ke Xue 2023; 44:5443-5455. [PMID: 37827762 DOI: 10.13227/j.hjkx.202210203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/14/2023]
Abstract
Carbon emission peaking and air quality improvement is an urgent issue in the research of the atmospheric environment. Here, the emission factor method was used to compile the city-level greenhouse gas emission inventory of Jiangsu Province from 2010 to 2019, which was then combined with greenhouse gas-air pollutant synergy analysis and WRF-Chem air quality model simulation to analyze the synergistic gain of air quality improvement under different carbon emission reduction scenarios. The results revealed that the annual mean CO2 emission in Jiangsu Province from 2010 to 2019 was 701.74-897.47 Mt. Suzhou, Xuzhou, and Nanjing had the highest emissions (91.19-182.12 Mt·a-1); Yangzhou, Suqian, and Lianyungang had the lowest emissions (13.19-32.54 Mt·a-1); and majority of the cities had a continuous upward trend in the CO2 emissions. Energy activities were the main source of CO2 emissions, accounting for nearly 90%, whereas industrial production processes contributed to the remaining 10%. This study designed three types of CO2 emission reduction conditions according to different emission reduction priorities, namely, sector-wide collaborative, energy priority, and industrial priority. Each type of emission reduction condition included a different intensity of CO2 emission reduction (10%, 20%, and 40%). The condition-based simulation results demonstrated that, taking 2017 as the base year, the average annual decrease in PM2.5 concentration in sector-wide collaborative, energy priority, and industrial priority emission reduction was 6.7-21.1, 3.1-12.0, and 3.4-14.3 μg·m-3, respectively. Sector-wide collaborative emission reduction had the most notable improvement in PM2.5 pollution. Under the condition of the sector-wide collaborative emission reduction of 40%, the average annual PM2.5 concentration of all cities, excluding Xuzhou and Suqian, met the national Ⅱ standard (35 μg·m-3). The change responses of PM10, SO2, NO2, and CO were similar to that of PM2.5, but O3 pollution increased under the conditions of energy and industrial priorities.
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Affiliation(s)
- Song-Wei Wang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring & Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Ke-Qin Tang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring & Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Hao-Ran Zhang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring & Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Wan-Wan Liu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring & Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Lu Bai
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring & Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Nan Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring & Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
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Le D, Li Y, Ren F. Does air quality improvement promote enterprise productivity increase? Based on the spatial spillover effect of 242 cities in China. Front Public Health 2022; 10:1050971. [PMID: 36504993 PMCID: PMC9732380 DOI: 10.3389/fpubh.2022.1050971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 11/10/2022] [Indexed: 11/27/2022] Open
Abstract
Introduction Air pollution not only harms people's health, but also impedes urban economic development. This study aims to analyze how air quality improvement affects enterprise productivity. And then from regional and time heterogeneities' aspects to investigate if the air quality improvement increase enterprise productivity. Methods The data were obtained from China Industrial Enterprise Database and China Patent Database,and this study used Spatial Durbin Model to analyze how air quality improvement affects enterprise productivity. Results The results show that: (1) air quality improvement and its spatial spillover effect can significantly increase enterprise productivity in adjacent areas. (2) After 2010, the government implemented more stringent measures to prevent and control air pollution, which made the air quality improvement promote enterprise productivity increase more obviously. The air quality improvement in eastern and central regions was less obvious than in western regions. (3) Air quality improvement can increase enterprise productivity by improving enterprise innovation quality, ensuring the health of urban residents, and increasing the stock of urban human capital. Conclusion Air quality improvement and its spatial spillover effect can significantly increase enterprise productivity in adjacent areas. So this study puts forward some policy enlightenment, such as establishing an air pollution detection system, using an intelligent network supervision platform, and implementing a coordinated defense and governance system.
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Wang H, Shi H. Particle Retention Capacity, Efficiency, and Mechanism of Selected Plant Species: Implications for Urban Planting for Improving Urban Air Quality. Plants (Basel) 2021; 10:2109. [PMID: 34685918 DOI: 10.3390/plants10102109] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 09/18/2021] [Accepted: 09/28/2021] [Indexed: 11/17/2022]
Abstract
Atmospheric particulate matter (PM) has been of concern owing to its negative effects on human health and its role in environmental degradation. For mitigation purposes, it is important to select the most efficient plant species in urban greening. Here, a fast, cost-saving methodology was first added to the conventional method to investigate the size-resolved PM retention capacity and efficiency of twenty plant species. Surface PM (SPM), which can be removed by water and brushing, accounted for 44.9–66.9% of total PM, in which the water-soluble PM (DPM) accounted for 12.9–22.1% of total PM. A large mass proportion of in-wax PM (14.1–31.7%) was also observed. Platycladus orientalis, Eriobotrya japonica, Viburnum odoratissimum, Magnolia grandiflora had the highest AEleaf (retention efficiency on per unit leaf area) to retain SPM within different diameter classes (DPM, PM0.1–2.5, PM2.5–10, PM>10). AEplant (retention efficiency of individual tree) varied greatly among different plant species, mainly due to the dependence on the total area of a tree. AEland (retention efficiency on per unit green area) is a suitable index for PM retention ability and efficiency. In general, P. orientalis, V. odoratissimum, Pittosporum tobira, Photinia serrulate, M. grandiflora, E. japonica were the efficient species in retaining PM at different scales (i.e., leaf, individual tree, green area). The species like Trifolium repens, Phyllostachys viridis, were the least efficient plant species. The investigated species are all evergreen species, which will remove PM throughout the whole year, even in winter. So, we recommended that the plant species with the highest PM retention efficiency can be used in urban greening. Meanwhile, horticulture practices should also be considered to improve the leaf area index to improve their PM retention and air purification abilities.
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Bo Y, Chang LY, Guo C, Lin C, Lau AKH, Tam T, Yeoh EK, Lao XQ. Associations of Reduced Ambient PM2.5 Level With Lower Plasma Glucose Concentration and Decreased Risk of Type 2 Diabetes in Adults: A Longitudinal Cohort Study. Am J Epidemiol 2021; 190:2148-2157. [PMID: 34038953 DOI: 10.1093/aje/kwab159] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 05/20/2021] [Accepted: 05/20/2021] [Indexed: 01/09/2023] Open
Abstract
It remains unknown whether reduced air pollution levels can prevent type 2 diabetes mellitus. In this study, we investigated the associations between dynamic changes in long-term exposure to ambient fine particulate matter, defined as particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5), and changes in fasting plasma glucose (FPG) levels and incidence of type 2 diabetes. A total of 151,398 adults (ages ≥18 years) were recruited in Taiwan between 2001 and 2014. All participants were followed up for a mean duration of 5.0 years. Change in PM2.5 (ΔPM2.5) was defined as the value at a follow-up visit minus the corresponding value at the immediately preceding visit. The PM2.5 concentration in Taiwan increased during 2002-2004 and began to decrease in 2005. Compared with participants with little or no change in PM2.5 exposure, those with the largest decrease in PM2.5 had a decreased FPG level (β = -0.39, 95% confidence interval: -0.47, -0.32) and lower risk of type 2 diabetes (hazard ratio = 0.86, 95% confidence interval: 0.80, 0.93). The sensitivity analysis and analyses stratified by sex, age, body mass index, smoking, alcohol drinking, and hypertension generally yielded similar results. Improved PM2.5 air quality is associated with a better FPG level and a decreased risk of type 2 diabetes development.
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Bo Y, Brook JR, Lin C, Chang LY, Guo C, Zeng Y, Yu Z, Tam T, Lau AKH, Lao XQ. Reduced Ambient PM 2.5 Was Associated with a Decreased Risk of Chronic Kidney Disease: A Longitudinal Cohort Study. Environ Sci Technol 2021; 55:6876-6883. [PMID: 33904723 DOI: 10.1021/acs.est.1c00552] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Many countries have dedicated to the mitigation of air pollution in the past several decades. However, evidence of beneficial effects of air quality improvement on chronic kidney disease (CKD) remains limited. We thus investigated the effects of dynamic changes (including deterioration and improvement) in air quality on the incidence of CKD in a longitudinal study in Taiwan. During 2001-2016, this study recruited a total of 163,197 Taiwanese residents who received at least two standard physical examinations. The level of fine particle matter (PM2.5) was estimated using a high-resolution (1 km2) satellite-based spatio-temporal model. We defined changes of PM2.5 concentrations (ΔPM2.5) as the difference between the two-year average measurements during follow-up and during the immediately preceding visit. The time-dependent Cox regression model was adopted to evaluate the relationships between ΔPM2.5 and the incidence of CKD after adjusting for a series of covariates. The concentrations of PM2.5 in Taiwan peaked around 2004 and began to decrease since 2005. We observed an approximate linear concentration-response relationship of ΔPM2.5 with CKD incidence. Every 5 μg/m3 decrease in the ambient concentration of PM2.5 was associated with a 25% reduced risk of CKD development [hazard ratio (HR): 0.75; 95% CI: 0.73, 0.78]. In conclusion, this study demonstrated that the improvement of PM2.5 air quality might be associated with a lower risk of CKD development. Our findings indicate that reducing air pollution may effectively prevent the development of CKD.
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Affiliation(s)
- Yacong Bo
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Kowloon 999077, Hong Kong, China
| | | | - Changqing Lin
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Kowloon 999077, Hong Kong, China
- Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Kowloon 999077, Hong Kong, China
| | - Ly-Yun Chang
- Gratia Christian College, Kowloon 999077, Hong Kong, China
- Institute of Sociology, Academia Sinica, Taipei 11529, Taiwan
| | - Cui Guo
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Kowloon 999077, Hong Kong, China
| | - Yiqian Zeng
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Kowloon 999077, Hong Kong, China
| | - Zengli Yu
- Department of Nutrition and Food Hygiene, School of Public Health, Zhengzhou University, Zhengzhou 450000, China
| | - Tony Tam
- Department of Sociology, The Chinese University of Hong Kong, Kowloon 999077, Hong Kong, China
| | - Alexis K H Lau
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Kowloon 999077, Hong Kong, China
- Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Kowloon 999077, Hong Kong, China
| | - Xiang Qian Lao
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Kowloon 999077, Hong Kong, China
- Shenzhen Research Institute of The Chinese University of Hong Kong, Shenzhen 518000, China
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Abstract
Fine particulate matter has been a major concern in China as it is closely linked to issues such as haze, health and climate impacts. Since China released its new national air quality standard for fine particulate matter (PM2.5) in 2012, great efforts have been put into reducing its concentration and meeting the standard. Significant improvement has been seen in recent years, especially in Beijing, the capital city of China. This paper reviews how China understands its sources of fine particulate matter, the major contributor to haze, and the most recent findings by researchers. It covers the characteristics of PM2.5 in China, the major methods to understand its sources such as emission inventory and measurement networks, the major research programmes in air quality research, and the major measures that lead to successful control of fine particulate matter pollution. A great example of linking scientific findings to policy is the control of coal combustion from the residential sector in northern China. This review not only provides an overview of the fine particulate matter pollution problem in China, but also its experience of air quality management, which may benefit other countries facing similar issues. This article is part of a discussion meeting issue 'Air quality, past present and future'.
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Affiliation(s)
- Mei Zheng
- SKL-ESPC and BIC-ESAT, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, People's Republic of China
| | - Caiqing Yan
- Environment Research Institute, Shandong University, Qingdao 266237, People's Republic of China
| | - Tong Zhu
- SKL-ESPC and BIC-ESAT, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, People's Republic of China
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