Ecological Indicators (Apr 2023)

Quantitative structure and spatial pattern optimization of urban green space from the perspective of carbon balance: A case study in Beijing, China

  • Yang Liu,
  • Chuyu Xia,
  • Xiaoyang Ou,
  • Yingshuo Lv,
  • Xin Ai,
  • Ruiqi Pan,
  • Yaru Zhang,
  • Mengyu Shi,
  • Xi Zheng

Journal volume & issue
Vol. 148
p. 110034

Abstract

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Cities experience the most intensive level of human activity. As a result, more than 60 % of global CO2 emissions come from urban areas. Urban green space has the dual ecological benefits of increasing carbon sinks and reducing carbon emissions. Creating green space is essential to promoting the development of a low-carbon cycle in a city. Therefore, exploring the quantitative structure and spatial pattern optimization of urban green space from the perspective of carbon balance can effectively improve the total carbon sink of a city. Based on the carbon balance theory, this paper first evaluates the carbon offsetting capability (COC) of urban green space in Beijing in 2020. Then, CO2 emissions is predicted, COC improvement targets are established, and the quantity of standard green space is calculated under these targets in 2035. A multi-objective programming model (MOP) is constructed to derive the optimal solution to determine the amount of standard green space needed to meet the constraints of urban development planning and maximize the carbon sink. A circuit model is used to identify the priority distribution area of green space in 2035, and the Patch-generating Land Use Simulation (PLUS) model is used to simulate the spatial pattern optimization results. The results show that: (1) CO2 emissions in Beijing caused by human activities in 2020 totaled about 240.12 million tons, the net absorption of CO2 of green space was about 8.99 million tons, and the COC was about 3.74 %; (2) in 2035, Beijing’s CO2 emissions will be about 265.40 million tons. Under 5 %, 10 %, 15 %, 20 %, and 25 % COC improvement gradients, the demand for standard green space will be 12,204.80 km2, 12,763.80 km2, 13,353.85 km2, 13,943.90 km2, and 14,533.96 km2, respectively; (3) the results of the Multi-Objective Programming (MOP) model show that the optimal COC in 2035 is 4.19 %, and the standard green space quantity is 13,012.24 km2; (4) In 2035, Beijing’s urban green space will be characterized by a network structure of circular radiation. The optimized COC is 4.37 %, and the standard green space quantity is 13,577.86 km2, which is largely consistent with the MOP model’s predicted result. This study can provide theoretical and methodological support for urban green space planning, and expand nature-based solutions for the low-carbon development in cities.

Keywords