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The effect of forest on PM2.5 concentrations: A spatial panel approach

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  • Lin, Ying
  • Yang, Xiuyun
  • Li, Yanan
  • Yao, Shunbo

Abstract

Spatial relationships between forest and PM2.5 concentrations are of great policy implications in regional afforestation layout and air pollution control. This paper investigates the transboundary externality of a city’s forest on the concentrations of PM2.5 in different city segments. Employing a mixed-regressive spatial panel model with data for 255 Chinese cities over 2000 to 2015, we find that the concentrations of PM2.5 tend to be substantially lower in cities with larger forest area and the depositing effect of forest spills over significantly to neighboring cities. A one percentage increase in forest area reduces the average annual concentrations of PM2.5 by 2.53%, of which 76% is contributed to the spillover effect. Moreover, the average marginal effect of forest on PM2.5 concentrations exhibits an inverted-U relationship with wind speed and the depositing effect minimizes (in magnitude) as the average annual speed of wind approaches to 23 kilometers per hour. These findings suggest that severe hazing cities with mild wind speed are priority afforestation areas for transboundary air pollution control.

Suggested Citation

  • Lin, Ying & Yang, Xiuyun & Li, Yanan & Yao, Shunbo, 2020. "The effect of forest on PM2.5 concentrations: A spatial panel approach," Forest Policy and Economics, Elsevier, vol. 118(C).
  • Handle: RePEc:eee:forpol:v:118:y:2020:i:c:s1389934120300010
    DOI: 10.1016/j.forpol.2020.102261
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    1. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    2. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    3. Robert Buitenwerf & Laura Rose & Steven I. Higgins, 2015. "Three decades of multi-dimensional change in global leaf phenology," Nature Climate Change, Nature, vol. 5(4), pages 364-368, April.
    4. John C. Driscoll & Aart C. Kraay, 1998. "Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 549-560, November.
    5. Jörg Balsiger & Stacy D. VanDeveer, 2012. "Navigating Regional Environmental Governance," Global Environmental Politics, MIT Press, vol. 12(3), pages 1-17, August.
    6. Rasa Zalakeviciute & Jesús López-Villada & Yves Rybarczyk, 2018. "Contrasted Effects of Relative Humidity and Precipitation on Urban PM 2.5 Pollution in High Elevation Urban Areas," Sustainability, MDPI, vol. 10(6), pages 1-21, June.
    7. Daniel Hoechle, 2007. "Robust standard errors for panel regressions with cross-sectional dependence," Stata Journal, StataCorp LP, vol. 7(3), pages 281-312, September.
    8. Jones, Benjamin A. & McDermott, Shana M., 2018. "The economics of urban afforestation: Insights from an integrated bioeconomic-health model," Journal of Environmental Economics and Management, Elsevier, vol. 89(C), pages 116-135.
    9. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012. "Measuring Economic Growth from Outer Space," American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
    10. Hong Sok Kim & Eungcheol Kim, 2004. "Effects Of Public Transit On Automobile Ownership And Use In Households Of The Usa," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 16(3), pages 245-262, November.
    11. Schomers, Sarah & Matzdorf, Bettina, 2013. "Payments for ecosystem services: A review and comparison of developing and industrialized countries," Ecosystem Services, Elsevier, vol. 6(C), pages 16-30.
    12. Kroeger, Timm, 2013. "The quest for the “optimal” payment for environmental services program: Ambition meets reality, with useful lessons," Forest Policy and Economics, Elsevier, vol. 37(C), pages 65-74.
    13. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
    14. Paudyal, Kiran & Baral, Himlal & Burkhard, Benjamin & Bhandari, Santosh P. & Keenan, Rodney J., 2015. "Participatory assessment and mapping of ecosystem services in a data-poor region: Case study of community-managed forests in central Nepal," Ecosystem Services, Elsevier, vol. 13(C), pages 81-92.
    15. Ji, Xi & Yao, Yixin & Long, Xianling, 2018. "What causes PM2.5 pollution? Cross-economy empirical analysis from socioeconomic perspective," Energy Policy, Elsevier, vol. 119(C), pages 458-472.
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    Cited by:

    1. Zhang, Yingjie & Zhang, Tianzheng & Zeng, Yingxiang & Cheng, Baodong & Li, Hongxun, 2021. "Designating National Forest Cities in China: Does the policy improve the urban living environment?," Forest Policy and Economics, Elsevier, vol. 125(C).
    2. Dongyang Yang & Fei Meng & Yong Liu & Guanpeng Dong & Debin Lu, 2022. "Scale Effects and Regional Disparities of Land Use in Influencing PM 2.5 Concentrations: A Case Study in the Zhengzhou Metropolitan Area, China," Land, MDPI, vol. 11(9), pages 1-12, September.

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