Spatiotemporal Patterns and Drivers of the Carbon Budget in the Yangtze River Delta Region, China

Abstract

Improving our understanding of the patterns and drivers of regional carbon budgets is critical to mitigating climate change regionally and globally. Different from previous research, our study attempts to reveal the comprehensive impact of climate change and human activities factors on the carbon budget. Based on the Carnegie–Ames–Stanford approach (CASA) model, the IPCC inventory method, the ordinary least squares (OLS) regression model, the Geodetector model, and the geographically weighted regression (GWR) method, we investigated the spatiotemporal patterns of the carbon budget in the Yangtze River Delta (YRD) region from 2000 to 2015 and analyzed the effects of climate change and human activities on the carbon budget. The results showed that the carbon budget in the YRD region changed from 271.33 million tons in 2000 to −1193.76 million tons in 2015. During this period, the changes in the carbon budget per unit area in the four provinces all showed a decreasing trend, among which Shanghai decreased the most, followed by Jiangsu, Zhejiang and Anhui. In terms of spatial pattern, the carbon budget of the YRD region has a “core-edge” structural feature. The closer it is to Shanghai, the core area, the more severe the carbon budget deficit; the farther from it, the greater the carbon budget surplus. Overall, we found that human activities have a greater impact on the carbon budget than climate change. The top three drivers were, in order, changes in population density, GDP per capita, and unused land, with q values of 0.3317, 0.1202, and 0.0998, respectively. Locally, the impact of the drivers on the carbon budget shows obvious spatial heterogeneity. In particular, the population density was negatively correlated with carbon budget changes in the entire study area, and the coefficients of GDP per capita and unused land were negative in most counties. Based on the results, we put forward suggestions for restricting population flow among the core area and the peripheral area, promoting industrial innovation in the core area and ecological protection in the peripheral area, as well as implementing three-dimensional space development in the core area and controlling the expansion of construction land in the peripheral area. Our study can provide a scientific basis for low-carbon development in the YRD region. The methodology and findings of this study can provide references for similar studies in other urbanized regions around the world.

Health-Oriented Emission Control Strategy of Energy Utilization and Its Co-CO2 Benefits: A Case Study of the Yangtze River Delta, China

“…Consequently, about 11.2 μg/m 3 of PM 2.5 can be attributed to the direct use of fuels, accounting for 44% of the PM 2.5 concentrations associated with anthropogenic emissions from the YRD region. Previous study 53 suggests that, to achieve carbon neutrality in the YRD region, the CO 2 emissions from energy use has to be reduced by at least 61% with a carbon sequestration limit of 1020 Mt CO 2 for the YRD. Therefore, reducing energy-related emissions is the key to achieve clean air and carbon naturality in the YRD region.…”

Effects of climate change and land use/cover changes on carbon sequestration in forest ecosystems in the coastal area of China

“…Terrestrial carbon storages or sinks can be assessed by field surveys, ecosystem process modeling, remote-sensing techniques, inventories, and atmospheric inversion methods (Wang et al, 2012;Fu et al, 2022;Piao et al, 2022). Each method has its own advantages and limitations (Piao et al, 2022;Shi et al, 2023).…”

“…For example, process-modeling methods are often used since this method can simulate carbon cycles under different climate condition scenarios, when examining the influences of climate change on carbon sinks of terrestrial ecosystems (Yang et al, 2016;Lu et al, 2019). Inventories are often used when detecting the influences of LUCC on carbon storages or sinks in terrestrial ecosystems (Liu et al, 2019;Fu et al, 2022). However, the fixed levels of carbon fluxes for each land use type in the inventory method often result in large uncertainties on a regional scale.…”