China-UK Low Carbon College, Shanghai Jiao Tong University, Shanghai, 201306, China; Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Fukuoka, Japan.
School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; SJTU-UNIDO Joint Institute of Inclusive and Sustainable Industrial Development, Shanghai Jiao Tong University, Shanghai, 200030, China.
J Environ Manage. 2022 Apr 15;308:114645. doi: 10.1016/j.jenvman.2022.114645. Epub 2022 Feb 4.
Overcapacity is regarded as an inevitable problem for rapid economic developing countries like China, which also causes serious adverse impacts on the environment and public health. However, few studies have quantified the overcapacity feature and corresponding co-benefit from de-capacity policy. To fill such research gaps, this study constructed a comprehensive assessment model by combining the Data Envelopment Analysis (DEA) model, the GAINS-China (Greenhouse gas - Air pollution Interactions and Synergies) model, and a meta-analysis and health impact assessment module, to measure the capacity utilization rate of 41 industrial sectors in 31 Chinese provinces and forecast the environmental and health co-benefits from de-capacity policy in 2050. Results showed that the capacity utilization rate of China's industry is 64.13% in 2018, which is much lower than the threshold value of 75%, indicating serious overcapacity in China's industry. Capacity utilization rates of light industries are higher (around 70%) than heavy industries (50%-60%), and the capacity utilization rate in East and South-Central China is higher (70%-96%) than West China (below 40%). Under a de-capacity scenario in 2050, China's CO and PM emissions are reduced by 1.05 billion tons (9.6%) and 57.8 kilotons (5.8%), respectively. This reduction in PM emissions results in a substantial health co-benefit, reducing national premature mortality cases by approximately 792,100 (1.6%). Finally, it is recommended that de-capacity priority be given to industries with low capacity utilization rate, as well as regions with intensive heavy industry or high levels of greenhouse gas emissions, severe air pollution, and dense population.
产能过剩被认为是中国等快速发展经济体所面临的一个必然问题，它也对环境和公共健康造成了严重的负面影响。然而，很少有研究量化过产能过剩的特征及其去产能政策的相应协同效益。为了填补这一研究空白，本研究构建了一个综合评估模型，该模型结合了数据包络分析（DEA）模型、GAINS-China（温室气体-空气污染物相互作用和协同）模型以及荟萃分析和健康影响评估模块，以衡量中国 31 个省份 41 个工业部门的产能利用率，并预测 2050 年去产能政策的环境和健康协同效益。结果表明，2018 年中国工业的产能利用率为 64.13%，远低于 75%的阈值，表明中国工业存在严重的产能过剩。轻工业的产能利用率较高（约 70%），重工业较低（50%-60%），中国中东部地区的产能利用率较高（70%-96%），而西部地区较低（低于 40%）。在 2050 年去产能情景下，中国的 CO 和 PM 排放量分别减少了 10.5 亿吨（9.6%）和 57.8 千吨（5.8%）。PM 排放量的减少带来了显著的健康协同效益，使全国过早死亡人数减少了约 792100 人（1.6%）。最后，建议优先对产能利用率较低的行业以及重工业密集、温室气体排放强度高、空气污染严重、人口密集的地区进行去产能。
