Junping Ji

There is still a huge gap between the emissions pathways of megacities and the pathways to meeting the targets set by the Paris agreement. Compared with technological emission reductions, structural emission reduction can provide cities with more stable and sustainable carbon-peaking solutions. This study constructs a scenario-based input–output optimization model, adopting a novel carbon emission accounting method for purchased electricity that considers shared responsibility, and systematically evaluates the decarbonization paths of megacities and their impacts on economic growth, energy consumption, and carbon emissions. The results show that (a) through industry substitution and manufacturing restructuring, Shenzhen is projected to peak at 57.68 MtCO₂ emissions in 2026, with a 10.57% energy and a 19.55% carbon reduction by 2030. (b) Shenzhen can achieve its carbon emission peak target through the energy transition while accepting a loss of 0.97%–3.23% of GDP, requiring the maximum economic concession of 16.45% from the transportation sector (S10) in the early stage of transformation, while 12.24% from the extractive industry (S2) in the later stage. (c) The comprehensive structure adjustment proved to be more effective than other mitigation approaches, capable of achieving high-quality economic growth of 6.4% during the study period while reaching a peak target of 53.55 million tons of CO₂ by 2026. (d) The emission reduction effect of the power sector was the most significant among all the scenarios, with emission reduction rates between 6.26% and 35.63%, and the cumulative emission reduction potential reached 38.1–110.6 MtCO₂. The priority for emission reduction in the power sector is the coal phase-out plan, which is essential for achieving these significant reductions. This study provides an important reference for megacities facing similar challenges, especially those in developing countries, to achieve a stable and sustainable carbon peak pathway through structural adjustment.

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.

The close production and consumption relationship between industries leads to the embodied CO₂ transfer among industrial sectors along with the exchange of products. Thus, grasping the situation of embodied carbon transfers from the demand side is of great significance for better reducing a country or region’s CO₂ emissions. This study investigates the embodied carbon transfers in Guangdong Province from 2002 to 2017 from the industrial dimension by applying a hypothetical extraction method. An enhanced generalized RAS method was utilized to predict the intersectoral carbon transfers in 2025 and 2030. The results show that, from 2002 to 2017, the average proportion of carbon emission output of 72.11% made the production and supply of electricity and heat sector the main CO₂ emission transfer exporter, while the other service and construction sectors were the leading importers. Moreover, the embodied carbon transfers between these three sectors are the main carbon transfer paths. By 2025, the other service sectors will become the largest embodied carbon importers, surpassing the construction sector. Therefore, it is necessary to control the consumption demand of other service and construction sectors on the demand side to reduce carbon emissions driven by demand.

With the growing cost of carbon emissions reduction, the application of industrial restructuring to suppress carbon emissions is becoming more attractive. By constructing an input-output optimization model, this study explored how industrial restructuring helps megacities synergistically achieve carbon peak and high-quality development. The results showed that through contributing 164.4% of the reduction in emissions from 2020 to 2025, industrial structure optimization significantly inhibited the growth of carbon emissions; From 2020 to 2025, the manufacturing structure continued to be high-end, which resulted in a reduction in industrial carbon emissions by 10.3%; through vigorous development of the low-carbon service industry, the carbon emission of the service industry would continue to slow down at an average annual rate of 2.4%. Industrial premiumization and the low-carbonization of the modern service sector are the key driving forces for Shenzhen to achieve low-carbon transformation. The results also showed that the power and retail sectors are the most important for emissions reduction. This study can provide a roadmap for megacities on how to explore potential emission reduction via optimizing their economic structure to help them achieve their carbon emissions peak.

China has implemented strict policies for the installation of desulfurization facilities in coal power plants in order to mitigate their negative environmental and human health impacts. However, it is rarely acknowledged that desulfurization processes lead to increased water consumption and carbon emissions from the coal power sector. By using a bottom-up approach, we quantified that the desulfurization facilities in all of China’s coal power plants together avoided emissions of 29.52 Mt of SO₂ in 2014, with expenses of 550.26 million m³ of increased water consumption, and 53.28 Mt of additional CO₂ emissions. Such conflicts were especially pronounced in the North China Grid, where 9.77 Mt of SO₂ emission reductions were realized at expenses of 132.15 million m³ of water consumption, and 14.25 Mt of CO₂ emissions. The provinces in the North China Grid were already facing extreme water scarcity. Furthermore, while more than 90% of China’s coal power plants have installed desulfurization facilities, the application of full desulfurization would further reduce the greatest amount of SO₂ emissions with the smallest amounts of additional water consumption and carbon emissions in the Northwest Grid. Replacing all wet desulfurization facilities with dry ones saves 498.38 million m³ of water consumption in total, and reduces 26.65 Mt of CO₂ emissions; however, this is at an expense of 14.33 Mt of SO₂ emissions. These conflicts are most pronounced in Shanxi Province in the North Grid, and in Guangdong Province in the South Grid.

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.