As the world’s second largest economy, China ranks among the world’s top nations when it comes to carbon emission. Accordingly, its attitude towards climate change is closely followed by all parties concerned. There have been few studies on the role of environmental governance in the transformation process to low-carbon, especially Chinese ones. This study analyzes the impact of government environmental regulation on the low-carbon city transformation process by adopting Shenzhen as the research object. One of the world’s youngest super cities, Shenzhen also happens to be the city with the lowest carbon emission intensity in China. The multi-level governance framework is a useful mechanism with which to gauge divisions of responsibility and resources. This paper uses multilevel environmental governance to explain the policy for dealing with the climate in the city of Shenzhen. Striving to explore green low-carbon development path for the whole country, Shenzhen provides practical experience for countries to cope with global climate change.

Megacities are the main sources of carbon emissions and are pillars of socioeconomic development due to economic prosperity, industrial development, and population agglomeration. Taking the megacity of Shenzhen, China, as an example, this research explored the advantages of low-carbon transformation in both climate change mitigation and socioeconomic progress. Soft linking of the Low Emissions Analysis Platform (LEAP) model with input–output analysis demonstrates that adopting feasible low-carbon transformation strategies has the potential to reverse the ongoing trend of carbon emission growth in Shenzhen, resulting in a peak before 2025. The peaks in carbon intensity and carbon emissions per capita occurred earlier than those in total carbon emissions. Furthermore, a total low-carbon investment of 462.04 billion CNY could yield approximately 799.49 billion CNY in output, 311.42 billion CNY in value-added, and 156.10 billion CNY in resident remuneration and create 1.79 million job opportunities during policy implementation. Taking into account both the reduction in carbon emissions and the socioeconomic benefits of low-carbon transformation, this research elucidates a potential pathway for Shenzhen to achieve synergy between mitigating climate change and promoting socioeconomic development, thus offering a valuable model for cities facing similar challenges.

Effectively reducing manufacturing carbon dioxide (CO₂) emissions is a vital strategy for China to curb its rapidly rising carbon footprint. Features of such a reduction in manufacturing include an increase in the share of high-tech manufacturing and optimization of the energy consumption structure. This study aims to analyze the case of Shenzhen, a unique post-industrial innovative manufacturing megacity, for its leading experience in China’s manufacturing transition. Disaggregated manufacturing emissions data of Shenzhen, including 27 sub-sectors in four categories, were collected, and driving factors were identified by the logarithmic mean Divisia index (LMDI) method. The results suggest that: (1) CO₂ emissions from Shenzhen’s manufacturing show a phased difference between 2008–2012 and 2012–2020. CO₂ emissions embodied in electricity consumption have increased by over 30% in the former period and have remained stable at a high level of over 90%. (2) Significant heterogeneity of CO₂ emissions in various manufacturing sectors is revealed, with the largest emissions sources being factories that make communication equipment, computers, and other electronic equipment. (3) Lower carbon intensity is the primary factor in reducing CO₂ emissions, while the economic activity effect of manufacturing possesses a stimulating impact. (4) The marginal impact of restructuring on CO₂ emissions is insignificant since the manufacturing and energy structures of Shenzhen have been upgraded to a low carbon level. Therefore, strengthening the power saving management and improving the energy efficiency of the manufacturing, rather than optimizing the manufacturing and final energy structures, will be a necessary potential solution to the problem of how to reduce CO₂ emissions in Shenzhen’s manufacturing.

As the world’s second largest economy, China ranks amount the world’s top nations when it comes to carbon emission, and therefore its attitude towards climate change is closely followed by all parties concerned. There have been few researches on the role of environmental governance in low-carbon city transformation process, especially the Chinese one. This paper analyses the role of government environmental regulation played in the low-carbon city transformation process by taking Shenzhen as the research object. One of the world's youngest super cities, it also happens to be the lowest carbon emission intensity city in China. Striving to explore green low-carbon development path for the whole country, Shenzhen provides practical experience for countries to cope with global climate change. However, its efforts to reduce the total carbon emissions failed, but it emphasized the carbon emission intensity, which is consistent with the international commitments made by the central government. China’s policy towards handling climate change relies on hierarchical governance arrangement. The strength of the NGOs in the country is weak and incomparable with the government’s, which has mastered most of the resources and is just a reality in China.

With severe haze pollution continuing to frequently occur in many regions of China in recent years, increasing research effort has been made to study the source and control of haze pollution using socio-economic factors. Based on the urban panel data of 21 cities in Guangdong Province, South China, from 2005 to 2016, this paper analyzes the spatial and temporal evolution trend, spatial autocorrelation and influencing factors of Guangdong’s haze pollution through spatial econometric methods with inverse distance weight. First, the results show that the haze pollution of 21 cities in Guangdong Province has strong spatial autocorrelation and spatial clustering phenomenon. Aggregation areas of heavy air pollution are located in the Pearl River Delta region centered on Guangzhou, Foshan, Zhongshan and Dongguan. Those cities should be targeted as priority haze-pollution-reduction areas. Secondly, significant spatial dependence and spatial spillover effects of haze pollution in Guangdong are demonstrated by the spatial econometric models. Joint prevention and control of haze pollution between cities are therefore important and necessary. Thirdly, the direct and indirect effects of energy consumption on haze pollution are positive and significant at the 1% level. Meanwhile, population, foreign direct investments (FDI) and the ratio of the secondary industry (e.g., manufacturing and construction industries) relative to the service industry also play important roles in haze pollution, and all of them have positive effects on air pollution. However, the environmental Kuznets curve (EKC) hypothesis is not supported by the economy-emission data of Guangdong. Economic growth and car density are not significant factors in deciding the level of haze pollution. To effectively improve the local air quality, the government is recommending the introduction of policies for adjusting the structures of energy, economy and FDI, promoting the research, development and application of clean technologies, and enhancing the awareness of energy conservation among residents and enterprises.

High-precision CO₂ emission data by sector are of great significance for formulating CO₂ emission reduction plans. This study decomposes low-precision energy consumption data from China into 149 sectors according to the high-precision input–output (I–O) table for 2017. An economic I–O life cycle assessment model, incorporating sensitivity analysis, is constructed to analyze the distribution characteristics of CO₂ emissions among sectors. Considering production, the electricity/heat production and supply sector contributed the most (51.20%) to the total direct CO₂ emissions. The top 10 sectors with the highest direct CO₂ emissions accounted for >80% of the total CO₂ emissions. From a demand-based perspective, the top 13 sectors with the highest CO₂ emissions emitted 5171.14 Mt CO₂ (59.78% of the total), primarily as indirect emissions; in particular, the housing construction sector contributed 23.97% of the total. Based on these results, promoting decarbonization of the power industry and improving energy and raw material utilization efficiencies of other production sectors are the primary emission reduction measures. Compared with low-precision models, our model can improve the precision and accuracy of analysis results and more effectively guide the formulation of emission reduction policies.