Ecological Indicators (Feb 2024)
Spatiotemporal changes in urban forest carbon sequestration capacity and its potential drivers in an urban agglomeration: Implications for urban CO2 emission mitigation under China’s rapid urbanization
Abstract
Urban forests can absorb carbon dioxide for urban CO2 emission mitigation. However, the potential capacity of urban forest carbon sequestration (CS) and its drivers remain unclear in urban agglomerations under rapid urbanization. In our study, the net primary productivity (NPP) of built-up areas was reconstructed in the Harbin-Changchun urban agglomeration (HCUA) from 2000 to 2020 to reflect urban forest CS, and the drivers of spatial urban forest CS patterns were further explored using the Geodetector model. Our results showed that the HCUA has experienced rapid urbanization over the past 20 years. Across the urbanization gradient, the CS capacity was higher in new developing built-up areas than in the old developed built-up areas for all years. The CS capacity of urban forests increased gradually from 2000 to 2020, especially in large built-up areas. The urban forest CS was skewed toward low (300 g·m−2) show an overall increasing trend from 2000 to 2020, especially in small, low-altitude and old developed built-up areas. The total CS of built-up areas increased from 0.35 Mt·C·yr−1 in 2000 to 2.06 Mt·C·yr−1 in 2020, and the urban forests in the HCUA could offset approximately 2.23 % of urban carbon emissions in 2000, increasing to 5.08 % in 2020. Natural factors, such as temperature, mainly determined changes of the spatial urban forest CS distribution. In addition, we found that urban morphology factors, such as urban build-up area, construction height, population density, and gross national product, can significantly influence urban forest CS. We further found there may exist the threshold of urban built-up area and gross national product significantly affecting urban forest CS variation. The interaction between natural and anthropogenic factors had stronger explanatory power for the spatial variation of CS. Our study can help city managers formulate low-carbon development strategies to address the negative impacts of climate change and realize the low-carbon development of cities.
