Serving as the backbone of economic development, industrial parks have strong implications for reducing carbon emissions in China under the “carbon peak and carbon neutrality” background. This study explores the carbon emission reduction effects of three different types of national-level industrial parks on prefectural-level cities in China, including economic and technological development zones (ETDZs), eco-industrial demonstration parks (EIDPs), and low-carbon industrial parks (LCIPs). Data on 204 prefectural-level cities over the period of 1999 to 2019 were examined by using the difference-in-differences method and the mediating effect model. The study revealed that (1) the three types of industrial parks significantly reduced the intensity of city carbon emissions by 1,155, 395, and 450 tons per million CNY, respectively; (2) There existed lag effects of 7 years for the ETDZ and 3 years for the EIDP; (3) Industrial structure exhibited significant mediating effects, with ETDZ and EIDP reducing city carbon emission intensity by 58 and 56 tons per million CNY, respectively; (4) Strong heterogeneity in the effects was found, arising from the differences in geographical location, resources endowment, and amount of industrial parks; and (5) ETDZ and EIDP reduced the carbon emission intensity of neighboring cities by 174 and 144 tons per million CNY, respectively, while LCIP increased that by 686 tons per million CNY. The major contribution of this study is analyzing the city-level impacts of ETDZ, EIDP, and LCIP, three different types of national industrial park policies with different implementation periods, regional distributions, and policy focuses. This not only fills a gap in the analyses of ETDZ and LCIP policies in this area of research, but also draws analogies and contrasts between the effects of the three different policies. This study suggests that the stability and long-term nature of industrial park policies be maintained and further transformation and upgrading of industrial structure be attained. Additionally, intercity coordination could be introduced or enhanced.

China is the world’s largest carbon emitter. Reducing greenhouse gas emissions from agriculture, one of the main sources, is a channel for achieving China’s carbon peaking and carbon neutrality targets on schedule. To clarify the status and prospects of greenhouse gas (GHG) emissions reduction in Chinese agriculture, this paper focuses on macro-level factors such as policies, economy, society, and technology, meso-level factors such as agricultural digital transformation and carbon trading market construction, and micro-level factors such as individual farmers and household influences on agricultural emissions reduction. Therefore, this article examines the strengths, weaknesses, opportunities, and threats in China’s agricultural greenhouse emission reductions by SWOT. It is concluded that optimized industrial structure and technological progress are strengths, while weak low-carbon awareness among farmers and the limitations of traditional small-scale production methods are weaknesses. Aligning with national development direction, absorbing foreign experiences, and integrating with digitization are opportunities. The imbalance between the economy and emission reduction and the significant regional differences are the threats. Overall, China’s efforts are on the right track, but urgent action is needed to improve the quality of farmers and transform the agricultural economy, which requires fundamental changes. Based on this, suggestions are proposed for farmers, businesses, and government from four aspects: promoting and expanding pilot demonstration areas for agricultural carbon sequestration trading, building regionally superior agricultural products and specialty industries, synergistic cooperation for technology development and promotion, improving farmer educational level in the form of agricultural cooperatives, so as to help balance economic and environmental benefits in reducing agricultural GHG emissions.

In the current global economic downturn and energy transition period, how to better coordinate the differences in carbon emission footprints among sub-regions has become an emerging issue. With the Gini decomposition method, social network analysis, and difference-in-differences estimation, this study explores the spatial differentiation of China’s province-level carbon emission footprint from 2000 to 2021. The findings of this study indicate that: (1) The Gini-based carbon emission footprint index shows an overall upward trend, revealing the constantly expanding differences among provinces. By comparison, the crude oil difference between the low-carbon pilot and non-pilot provinces is evident, reaching more than 0.15; (2) The carbon emission footprint spatial correlation network structure shows strong spillover characteristics. Provinces with higher network centrality have better structural holes, maintaining closer relationships with surrounding provinces. Those pilot provinces have a comparative advantage regarding social network position, as they have more effective mutual node connections; and (3) China’s low-carbon pilot policy can effectively reduce carbon emissions, with a certain reduction effect of -17.433 in comparison. Industrial rational transformation and green innovation performance are essential in this emission reduction process. At the crossroads of sustainable development, it will be incredibly beneficial to speed up the green transformation by enhancing the coordinated development of regional characteristics.

Multi-cropping systems play a crucial role in global agricultural production. Accurately estimating the soil carbon sequestration capacity of multi-cropping systems is of significant importance for enhancing agricultural productivity, mitigating greenhouse gas emissions, and reducing carbon footprint. However, soil carbon cycling is more complex in multi-cropping systems compared with single-cropping systems, and existing assessment methods cannot accurately estimate soil carbon sequestration in multi-cropping systems with high operability. Here, we reviewed the accuracy and efficiency of the three primary global soil carbon assessment methods, including statistical models, process-based models, and the Intergovernmental Panel on Climate Change (IPCC) steady-state method. Our study concludes that it is difficult to simulate the dynamic evolution of soil organic carbon (SOC) using the statistical models, while the well simulation through process-based models demands a large amount of data. Additionally, the IPCC Tier 2 method cannot be directly applied to estimate SOC in multi-cropping systems due to mismatches in parameters and time steps. We suggest modifying the structures and parameters of the IPCC Tier 2 method by revising the inventory unit and redetermining the parameter values, which should efficiently address its bottleneck in estimating SOC for multi-cropping systems. Moreover, long-term experimental observations and multi-model ensemble simulations are beneficial for determining the parameter values to address the data deficiencies in IPCC Tier 2. This study aims to explore pathways for improving the accuracy of SOC estimation in multi-cropping systems and, thus, carbon footprint calculation worldwide.

Using Shanghai as a case study, this article discusses the practices and methods of carbon footprint measurement in megacities, analyzing its evolution and significance in supporting densely populated megacities worldwide to achieve carbon neutrality. The study emphasizes thorough greenhouse gas emission accounting in high-density urban areas characterized by intensive economic activity and population concentration. Globally, nations, including China, are enhancing carbon management strategies by introducing new standards under the regulatory guidance of organizations such as the National Development and Reform Commission. However, notable obstacles remain, including the lack of a centralized database, insufficient product-specific approaches to managing emissions, and the absence of standardized certification systems for labeling products based on their environmental impact. To address these challenges, Shanghai is promoting a low-carbon transition across industries and encouraging the city's green development by fostering a collaborative industrial framework. This includes the CN100 program, which mobilizes leading companies to reduce the carbon footprint of supply chains and industrial processes.