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Linking urban air pollution with residents’ willingness to pay for greenspace: A choice experiment study in Beijing

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  • Liu, Zhaoyang
  • Hanley, Nick
  • Campbell, Danny

Abstract

This study investigates the nexus between urban air pollution and residents’ preferences for greenspace. The two environmental issues could be linked through people’s general tastes for environmental amenities helping to determine residential location choice, implying that residents of heavily-polluted neighbourhoods may care less about environmental amenities in general, including greenspace. Alternatively, high pollution levels could force people to reduce their local outdoor activities and thereby devalue urban greenspace as local recreational resources. Finally, residents of severely-polluted areas may derive additional benefits from greenspace as trees can enhance air quality. To examine these issues, we undertook choice experiment surveys in Beijing to elicit willingness to pay (WTP) for three types of greenspace: a neighbourhood park near respondents’ homes, a city park in central Beijing and a national park outside the city. We then used air pollution data to help explain the spatial heterogeneity in WTP. Neighbourhood parks provide direct air purification services for communities nearby, and our results indeed suggest that respondents exposed to higher pollution levels have higher WTP for a new neighbourhood park. However, we failed to find evidence of a significant effect of pollution on WTP for a new city park or a new national park.

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  • Liu, Zhaoyang & Hanley, Nick & Campbell, Danny, 2020. "Linking urban air pollution with residents’ willingness to pay for greenspace: A choice experiment study in Beijing," Journal of Environmental Economics and Management, Elsevier, vol. 104(C).
    • Handle: RePEc:eee:jeeman:v:104:y:2020:i:c:s0095069620301066
    DOI: 10.1016/j.jeem.2020.102383
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    2. Yuta Kuroda & Takeru Sugasawa, 2023. "The Value of Scattered Greenery in Urban Areas: A Hedonic Analysis in Japan," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 85(2), pages 523-586, June.
    3. Julia Bronnmann & Veronika Liebelt & Fabian Marder & Jasper Meya & Martin Quaas, 2023. "The Value of Naturalness of Urban Green Spaces: Evidence from a Discrete Choice Experiment," Land Economics, University of Wisconsin Press, vol. 99(4), pages 528-542.
    4. Van Oijstaeijen, Wito & Van Passel, Steven & Back, Phil & Cools, Jan, 2022. "The politics of green infrastructure: A discrete choice experiment with Flemish local decision-makers," Ecological Economics, Elsevier, vol. 199(C).
    5. Xin Dong & Shili Yang & Chunxiao Zhang, 2022. "Air Pollution Increased the Demand for Gym Sports under COVID-19: Evidence from Beijing, China," IJERPH, MDPI, vol. 19(19), pages 1-16, October.
    6. Waranan Tantiwat & Christopher Gan & Wei Yang, 2021. "The Estimation of the Willingness to Pay for Air-Quality Improvement in Thailand," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    7. Piaggio, Matías, 2021. "The value of public urban green spaces: Measuring the effects of proximity to and size of urban green spaces on housing market values in San José, Costa Rica," Land Use Policy, Elsevier, vol. 109(C).
    8. Weixiang Zhao & Yankun Xu, 2022. "Public Expenditure and Green Total Factor Productivity: Evidence from Chinese Prefecture-Level Cities," IJERPH, MDPI, vol. 19(9), pages 1-27, May.
    9. Valeria M. Toledo‐Gallegos & Jed Long & Danny Campbell & Tobias Börger & Nick Hanley, 2021. "Spatial clustering of willingness to pay for ecosystem services," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 673-697, September.
    10. Reeko Watanabe & Tsunemi Watanabe, 2020. "Does Haze Drive Pro-Environmental and Energy Conservation Behaviors? Evidence from the Beijing-Tianjin-Hebei Area in China," Sustainability, MDPI, vol. 12(23), pages 1, November.

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    More about this item

    Keywords

    Greenspace; Urban air pollution; Spatial heterogeneity of preferences; Choice experiment; Willingness to pay; Mixed logit model; Instrumental variable;
    All these keywords.

    JEL classification:

    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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