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Achieving the peak of carbon emissions before 2030 is a top priority for the Chinese government to achieve the goal of carbon neutrality. The slowdown in the pandemic and CI decline cannot be ignored. Based on new and extensive datasets of carbon emissions at the provincial, city, and county levels in China, we develop multiple methods to analyze the timing, magnitude, driving patterns, emission networks, and policy implications of China's carbon peak. For the first time, this study assigned the peak areas to the county level, which provided an important reference for formulating priority peak policies. Given the national carbon peaking and carbon neutrality goals, the study highlights the importance of close inter-provincial cooperation on carbon emissions in a complex network.
This study shows that China will reach a CO2 peak of 11.7-13.1 Gt in 2021-2026 with an 80% probability. However, CO2 peaking by 2030 remains uncertain due to the COVID-19 pandemic and a slowdown in CI reduction. Under the BAU and advanced emission reduction technology scenarios, the gap in China's carbon dioxide emissions is 8.4 Gt in 2030 and 13.4 Gt in 2035. In addition, a comprehensive analysis of the Divisia index shows that CI emission reduction is more important for post-Kyoto era China's CO2 emission reduction in provinces and cities divided by population size and economic structure. Therefore, it is necessary to strengthen the implementation of CI emission reduction through emission reduction technology innovation, support the peak of CO2 in 2030, guide the steady decline of emissions, and achieve the goal of carbon neutrality in 2060. Since most provinces, cities and counties in China have not yet reached the CO2 peak in 2019, the necessary condition for achieving the above-mentioned national goals is to develop a close inter-provincial CO2 emission reduction cooperation mechanism. However, the SNA suggests that there is a "trade-off" between applying technology to reduce carbon emissions and economic recovery in the post-pandemic era.
Karbon is a data platform that lets you scale data collection and analysis
Second, the Chinese government can establish a regional carbon peak rapid response system and implement regional priority policies. Real-time monitoring is difficult when CO2 levels in an area are peaking. Therefore, it is crucial to adopt a unified carbon inventory accounting system based on top-down and bottom-up approaches to improve the timeliness of updating CO2 emission data. Furthermore, given the important role of drivers in changing CO2 emissions, policymakers may consider using different methodologies (such as the Generalized Divisia Index method, GDIM) to determine regional CO2 emission trends as well as CO2 tracking and forecast peaks. In addition, policymakers should fully consider the differences in the vertical management structure of vegetation-based carbon sinks and regional carbon peaking plans when formulating regional peaking strategies. For example, policy makers can formulate relevant CO2 peaking guidelines based on the differences in key industries and the urbanization process of various provinces, cities and counties.
Based on the equation. (12) Construct the inter-provincial carbon emission gravity matrix to obtain the above-mentioned complex inter-provincial carbon emission network. We then further analyzed network properties, focusing on overall network properties and individual network properties. We describe overall network properties using network attachment, network density, network hierarchy, and network efficiency, and analyze individual network properties using degree centrality, betweenness centrality, and proximity centrality (Supplementary Method S1).
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