Is collaborative governance effective for air pollution prevention? A case study on the Yangtze river delta region of China

Wang, Yu; Zhao, Yihang

doi:10.1016/j.jenvman.2021.112709

Cited by 49 publications

(22 citation statements)

References 35 publications

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“…To better identify the governance effect of JPCAP, some scholars have conducted studies using causal inference methods. Song et al ( 2020 ) and Wang and Zhao ( 2021 ) used the regression discontinuity design (RDD) to investigate the governance effect of JPCAP in the YRD and BTH, respectively. Yang et al ( 2016 ) and Wang et al, ( 2022a , b ) used the DID model to investigate the governance effect of JPCAP in the capital city group of Shandong Province and the key treatment area of APPCAP, respectively.…”

Section: Literature Reviewmentioning

confidence: 99%

The effect of joint prevention and control plan on atmospheric pollution governance and residents’ willingness to pay

Zeng

Chen

2022

Environ Dev Sustain

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This study investigates the governance effect of China’s joint prevention and control of atmospheric pollution (JPCAP) plan and residents’ willingness to pay for clean air. First, this study delves into the JPCAP plan’s atmospheric pollution governance effect using the difference-in-difference and spatial difference-in-difference models. The results showed that the atmospheric pollution in Beijing–Tianjin–Hebei (BTH) and surrounding cities have significant spatial autocorrelation characteristics. From the autumn and winter of 2017 to 2019, the JPCAP plan implemented by BTH atmospheric pollution transmission channel cities significantly reduced atmospheric pollution. However, the atmospheric pollution governance effect of the JPCAP plan is weaker in 2018–2019 than in 2017–2018. Second, this study introduced the air quality index and three atmospheric pollutants—PM 2.5 , NO 2 , and SO 2 —into the hedonic price model and investigated the residents’ willingness to pay by employing the spatial error model and spatial lag model. Finally, subsample and quantile regression were used to discuss the heterogeneity of residents’ willingness to pay. The results show that the reduction in atmospheric pollution increases residents’ willingness to pay for clean air. Residents have different willingness to pay for reducing different atmospheric pollutants, and there is heterogeneity in willingness to pay across regions and consumption levels. Residents in areas with the JPCAP plan have a higher willingness to pay than those without the JPCAP plan, and there is no spatial autocorrelation characteristic of the willingness to pay of residents in BTH and surrounding cities.

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Section: Literature Reviewmentioning

confidence: 99%

The effect of joint prevention and control plan on atmospheric pollution governance and residents’ willingness to pay

Zeng

Chen

2022

Environ Dev Sustain

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“…First, the collaborative governance of air pollution prevention and control in the YRD should be seen as an impetus to strengthen the cooperative effects of inter-regional air pollution prevention and control. Although the collaborative governance of regional air pollution has obvious advantages in reducing the cost of emission reduction (Xiao Liu et al, 2022), the long-term effectiveness of the YRD's regional air pollution policy is obviously insufficient (Wang and Zhao, 2021). Moreover, the collaborative governance of air pollutants (such as NOx-VOC) has benefits for human health and crop production (Ding et al, 2022).…”

Section: Spatial Associations and Policy Implications Of Air Pollutantsmentioning

confidence: 99%

Break point identification and spatiotemporal dynamic evolution of air pollutants: An empirical study from Anhui province, east China

Wang

Gui²,

Wang³

et al. 2022

Front. Environ. Sci.

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The new modality of inter-regional joint prevention and control is increasingly important to the integrated process of collaborative governance of air pollutants. Therefore, it has become necessary to analyze the degree of interaction among air pollutants within and between cities, master the dynamics of their spatiotemporal distribution and its influencing factors, and diagnose the primary obstacle factors. Long-term data on the concentrations of six air pollutants among 16 cities of Anhui province from 2015 to 2020 were analyzed using harmonic regression, the coupling coordination degree model, the obstacle degree model, the logarithmic mean Divisia index (LMDI), and exploratory spatial data analysis (ESDA). Over all, the annual mean concentrations of five of these pollutants (NO2, SO2, CO, PM10, and PM2.5) decreased to a certain extent over time, whereas O3 concentrations increased. The biggest decrease was observed in BZ city, where SO2 decreased by 80.60% (halving time: −2.03 ± 0.02 years), and the biggest increase was observed in CZ city, where O3 increased by 113.85% (doubling time: 1.74 ± 0.01 years). The O3 concentrations in most cities reached their break points starting in 2018, but the break points of other air pollutants appeared earlier than that of O3, mostly before 2018. With the exception of NO2 and O3, the halving times of other air pollutants were basically shorter than the doubling times. The high degree of interaction among air pollutants within and between cities contrasted sharply with the low degree of coordination. An analysis of hotspot evolution revealed that particulate matter (PM10 and PM2.5) migrated to northern Anhui, NO2 and O3 agglomerated to central Anhui, and CO eventually gathered in the Wanjiang City Belt. The primary obstacle factors of air pollutants in Anhui were particulate matter, SO2 and NO2. The seasonal differences in primary obstacle factors were most evident in 2020: NO2 dominated in winter (in 10 cities), SO2 dominated in southern Anhui, and particulate matter dominated in northern and central Anhui in spring. Other seasons were almost entirely dominated by particulate matter. Industrial structure was found to be more effective in reducing industrial carbon emissions, and technological improvement was found to be more advantageous in reducing industrial particulate matter, NOx and SO2. Finally, the policy implications of these results and suggestions for strengthening the inter-city joint prevention and control of air pollutants are discussed.

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“…This virus, which is a human-to-human transmitted virus (Wang et al 2020 ; Wang and Su 2020 ), causes an acute respiratory infection that can progress to pneumonia if the symptoms are not treated (Jiang et al 2020a , b ; Coccia 2021 ). The findings indicate that old age is one of its risk factors (Luo et al 2020 ; Wang and Zhao 2021 ) with an approximate 2–3% fatality rate (total infected people who died) (Rodriguez-Morales et al 2020 ; Bonilla-Aldana et al 2020 ). On February 19, 2020, the Iranian Ministry of Health officially reported that two patients with pneumonia were associated with COVID-19 in the city of Qom.…”

Section: Introductionmentioning

confidence: 99%

Analysis of changes in air pollution quality and impact of COVID-19 on environmental health in Iran: application of interpolation models and spatial autocorrelation

Keshtkar

heidari

Moazzeni

et al. 2022

Environ Sci Pollut Res

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In the global COVID-19 epidemic, humans are faced with a new challenge. The concept of quarantine as a preventive measure has changed human activities in all aspects of life. This challenge has led to changes in the environment as well. The air quality index is one of the immediate concrete parameters. In this study, the actual potential of quarantine effects on the air quality index and related variables in Tehran, the capital of Iran, is assessed, where, first, the data on the pollutant reference concentration for all measuring stations in Tehran, from February 19 to April 19, from 2017 to 2020, are monitored and evaluated. This study investigated the hourly concentrations of six particulate matters (PM), including PM2.5, PM10, and air contaminants such as nitrogen dioxide (NO 2 ), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO). Changes in pollution rate during the study period can be due to reduced urban traffic, small industrial activities, and dust mites of urban and industrial origins. Although pollution has declined in most regions during the COVID-19 quarantine period, the PM2.5 rate has not decreased significantly, which might be of natural origins such as dust. Next, the air quality index for the stations is calculated, and then, the interpolation is made by evaluating the root mean square (RMS) of different models. The local and global Moran index indicates that the changes and the air quality index in the study area are clustered and have a high spatial autocorrelation. The results indicate that although the bad air quality is reduced due to quarantine, major changes are needed in urban management to provide favorable conditions. Contaminants can play a role in transmitting COVID-19 as a carrier of the virus. It is suggested that due to the rise in COVID-19 and temperature in Iran, in future studies, the effect of increased temperature on COVID-19 can be assessed.

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Is collaborative governance effective for air pollution prevention? A case study on the Yangtze river delta region of China

Cited by 49 publications

References 35 publications

The effect of joint prevention and control plan on atmospheric pollution governance and residents’ willingness to pay

The effect of joint prevention and control plan on atmospheric pollution governance and residents’ willingness to pay

Break point identification and spatiotemporal dynamic evolution of air pollutants: An empirical study from Anhui province, east China

Analysis of changes in air pollution quality and impact of COVID-19 on environmental health in Iran: application of interpolation models and spatial autocorrelation

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