Clean air for some: Unintended spillover effects of regional air pollution policies

Fang, Delin; Chen, Bin; Hubacek, Klaus; Ni, Ruijing; Chen, Lulu; Feng, Kuishuang; Lin, Jian

doi:10.1126/sciadv.aav4707

Cited by 140 publications

(71 citation statements)

References 72 publications

(67 reference statements)

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“…Based on a panel covering 285 cities, Feng et al [34] utilized the spatial Durbin model to examine the spatial spillover effect of air pollution control on urban development quality in China, providing evidence of heterogeneity within different spatial regions in China. Fang et al [35] later discovered the unintended spillover effects of regional air pollution policies on mitigating air pollution in urban areas. Previous research has also explored the spatial spillover effect of air pollution on public health and healthcare expenditure in China [36,37].…”

Section: Spatial Spillover Effects Of Air Pollution In Chinamentioning

confidence: 99%

The Impact of Air Pollution on Domestic Tourism in China: A Spatial Econometric Analysis

Dong

et al. 2019

Sustainability

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This study utilizes a spatial econometric model to analyze the impact of air pollution on domestic tourism in China. Based on a panel dataset covering 337 cities from 2004–2013, this study derives the following findings. (1) Air pollution significantly reduces domestic tourist arrivals in the local city. On average, if the concentration of PM 2.5 (particulate matter equal to or less than 2.5 micrometers in width) in one city increases by 1 μ g/m 3 , the number of domestic tourists to the city declines by 0.7%. (2) Air pollution demonstrates significant spatial spillover effects. If the PM 2.5 in other cities simultaneously increases by 1 μ g/m 3 , the number of domestic tourists traveling to the local city rises by 4.1%. (3) The magnitude of the spillover effects of air pollution is larger than the negative direct effects on local cities. This study suggests that enhancing air quality in the local area will effectively promote the domestic tourism industry in the local city. In addition, it is implied that a simultaneous improvement in the air quality in all cities might not lead to an increase in the number of domestic tourist arrivals. Thus, in order to deal with the spillover effects of air pollution on the domestic tourism industry, local governments should make efforts to develop cross-city or cross-region tourism.

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Section: Spatial Spillover Effects Of Air Pollution In Chinamentioning

confidence: 99%

The Impact of Air Pollution on Domestic Tourism in China: A Spatial Econometric Analysis

Dong

et al. 2019

Sustainability

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“…However, there may be poor representativeness for 360 these areas over western China with few ground monitoring stations. In general, we have to say that the PM2.5 pollution has been significantly reduced in 2018 across China due to the effective emission control measures implemented by the Chinese government (Fang et al, 2019;Ma et al, 2019).…”

Section: Predicted Pm25 Maps Across Chinamentioning

confidence: 99%

Improved 1-km-resolution PM2.5 estimates across China using the space-time extremely randomized trees

Wei¹,

Li²,

Huang³

et al. 2019

Preprint

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Abstract. Fine particulate matter with aerodynamic diameters &#8804;&#8201;2.5&#8201;&#956;m (PM2.5) shows adverse effects on human health and atmospheric environment. Satellite-derived aerosol products have been intensively adopted in estimating surface PM2.5 concentrations, but most previous studies failed to monitor air pollution over small-scale areas limited by coarse spatial-resolution (3&#8211;50&#8201;km) and low data-quality aerosol optical depth (AOD) products. Therefore, a new space-time extremely randomized trees (STET) model is developed that integrates spatiotemporal information to improve PM2.5 estimates at both spatial resolution and overall accuracy across China. To this end, the newly released MODIS MAIAC AOD product, meteorological and other auxiliary data are inputs to the STET model. Daily 1-km PM2.5 maps in 2018 across mainland China are produced. The STET model performs well with a high out-of-sample (out-of-station) cross-validation coefficient of 0.89 (0.88), a low root-mean-square error of 10.35 (10.97)&#8201;&#956;g/m3, a small mean absolute error of 6.71 (7.17)&#8201;&#956;g/m3, and a small mean relative error of 21.37&#8201;% (23.77&#8201;%), respectively. Particularly, it can well capture the PM2.5 concentrations at both regional and individual site scales. In addition, it posed a strong predictive power (e.g., monthly-R2&#8201;=&#8201;0.80) and can be used to predict the historical PM2.5 records. The North China Plain, the Sichuan Basin, and Xinjiang Province always are featured with high PM2.5 pollution, especially in winter. The STET model outperforms most models presented in previous related studies. More importantly, our study provides a new approach to obtain high-quality PM2.5 estimates, which is important for air pollution studies over urban areas.

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“…It also suffers from noises added by various spatial interpolation techniques and issues from selective choices of monitoring sites. The next step of our research is to use the GEOS-Chem atmospheric transport model with emission data as key inputs to derive high-resolution pollutant concentration indicators [23,27]. We then will examine the relationships between urban expansion and pollution concentration with the Bayesian spatio-temporal statistical models.…”

Section: Discussionmentioning

confidence: 99%

“…Pollutant emissions data were made publicly available by the School of Environmental Sciences at Peking University (http://inventory.pku.edu.cn). Second, high space-time resolution emissions data can serve as an important input into the GEOS-Chem atmospheric transport model to derive high-resolution and spatio-temporally consistent pollutant concentrations [26,27]. Finally, official air pollution monitoring data did not have the necessary temporal coverage required by the present study.…”

Section: Pollutant Emissions Datamentioning

confidence: 96%

A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province

Zhao

Dong

2020

IJERPH

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Urbanization processes at both global and regional scales are taking place at an unprecedent pace, leading to more than half of the global population living in urbanized areas. This process could exert grand challenges on the human living environment. With the proliferation of remote sensing and satellite data being used in social and environmental studies, fine spatial- and temporal-resolution measures of urban expansion and environmental quality are increasingly available. This, in turn, offers great opportunities to uncover the potential environmental impacts of fast urban expansion. This paper investigated the relationship between urban expansion and pollutant emissions in the Fujian province of China by building a Bayesian spatio-temporal autoregressive model. It drew upon recently compiled pollutant emission data with fine spatio-temporal resolution, long temporal coverage, and multiple sources of remote sensing data. Our results suggest that there was a significant relationship between urban expansion and pollution emission intensity—urban expansion significantly elevated the PM2.5 and NOx emissions intensity in Fujian province during 1995–2015. This finding was robust to different measures of urban expansion and retained after controlling for potential confounding effects. The temporal evolution of pollutant emissions, net of covariate effects, presented a fluctuation pattern rather than a consistent trend of increasing or decreasing. Spatial variability of the pollutant emissions intensity among counties was, however, decreasing steadily with time.

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Clean air for some: Unintended spillover effects of regional air pollution policies

Cited by 140 publications

References 72 publications

The Impact of Air Pollution on Domestic Tourism in China: A Spatial Econometric Analysis

The Impact of Air Pollution on Domestic Tourism in China: A Spatial Econometric Analysis

Improved 1-km-resolution PM<sub>2.5</sub> estimates across China using the space-time extremely randomized trees

A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province

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Clean air for some: Unintended spillover effects of regional air pollution policies

Cited by 140 publications

References 72 publications

The Impact of Air Pollution on Domestic Tourism in China: A Spatial Econometric Analysis

The Impact of Air Pollution on Domestic Tourism in China: A Spatial Econometric Analysis

Improved 1-km-resolution PM&lt;sub&gt;2.5&lt;/sub&gt; estimates across China using the space-time extremely randomized trees

A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province

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Product

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Improved 1-km-resolution PM<sub>2.5</sub> estimates across China using the space-time extremely randomized trees