Simulating PM2.5 removal in an urban ecosystem based on the social-ecological model framework

Xiangyu Luo, Peng Jiang, Jingyi Yang, Jing Jin and Jun Yang

Ecosystem Services, 2021, vol. 47, issue C

Abstract: To incorporate the concept of ecosystem services into the planning and management practices has been proposed as a way to improve the management of urban ecosystems. Nevertheless, the uptake of the idea is slow due to the many political and technical barriers. One of the technical barriers is the lack of tools for cities to predict the impacts of proposed policies and actions on urban ecosystem services. To address this gap, we have developed an urban ecosystem service model based on the social-ecological model framework. Using the PM2.5 removal service in Beijing, China as an example, we showed how this model could be used to simulate the impacts of different policy scenarios on the specified ecosystem service. Our simulation results show that he PM2.5 removal service contributed by the city’s ecosystem can help to lower PM2.5 emissions from its social system, which formed a positive feedback. The PM2.5 removal service provided by urban green spaces from 2016 to 2035 in Beijing vary significantly among the three policy scenarios, including business as usual, restricting urban growth, and adjusting the energy structure. Based on the projections of the PM2.5 removal service, we concluded that Beijing should give priority to the policy of restricting the urban growth through urban planning. Our study showed that the feedback effects of ecosystem services are significant in a long term. Also, the model developed in this study provides a useful tool to simulate the impact of urban planning and management on urban ecosystem services.

Keywords: Urban ecosystem service; Social-ecological model; Feedback; PM2.5 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecoser:v:47:y:2021:i:c:s2212041620301765

DOI: 10.1016/j.ecoser.2020.101234

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