STRUCTURAL OPTIMIZATION OF JIANGSU’S
CHEMICAL INDUSTRY CONSTRAINED BY CARBON REDUCTION AND WATER ECOLOGICAL
CARRYING CAPACITY

doi:10.13776/j.cnki.resourcesindustries.20240305.002

Abstract

Abstract:

Yangtze River economic zone, as China’s key strategic zone, is closely related to national development by its ecological restoration and resources use. Jiangsu’s chemical industry, an intensive polluting and resources-depleting industry, needs to properly handle industrial development and resources & environmental protection, which is of significance to protect Yangtze River and realize carbon reduction. This paper establishes a multiple-objective optimization model of chemical industry under dual constraints of carbon reduction and water ecological carrying capacity, and applies NSGA-II-VIKOR algorithm to discuss the way to adjust Jiangsu’s chemical industrial structure. Balanced development scenario, compared with low-carbon, water-saving and economic development scenarios, can save water of 998.48×10⁴ m3 , reduce carbon emission intensity by 4.27%, and make GDP rising rate up to 4.73% on the basis of benchmark year 2017. Water resources are used efficiently and carbon emission is largely reduced, while economy gains high-quality development. Chemical industrial structure needs to be adjusted through developing rubber and plastics, limiting petroleum processing, coking coal and nuclear fuel processing, using water-saving and carbon-reducing measures in chemical fiber manufacturing. Optimization of chemical industry needs to promote clean energy and reform energy consuming structure, with coal use down by 5.54% and gas & electricity use up by 5.45%. Water resources allocation should be consistent with industrial structural adjustment, which can save water by 9.8% in petroleum processing, coking coal and nuclear fuel processing, and 5.14% in chemical fiber manufacturing, which can be transferred to rubber and plastics sector. This paper presents suggestions on increasing regional ecological carrying capacity to realize high-quality development, establishing clean energy consuming system to raise energy efficiency, developing water-saving industries to materialize a coordinated sustainability in industrial development and water ecology.

Key words: carbon reduction, water ecological carrying capacity, chemical industry, multiple objective optimization, industrial structure

摘要： 长江经济带作为重大国家战略发展区域，其生态修护和资源合理高效利用关系国家发展全局。江苏化工产业为污染密集型和资源消耗型产业，妥善处理产业发展和资源环境保护的矛盾，对推动长江大保护以及实现协同减排目标具有重要意义。以江苏省化工产业为研究对象，2017年为基准年，构建碳减排和水生态承载双重约束下化工产业结构多目标优化模型，运用NSGA-Ⅱ-VIKOR算法，探讨不同情景下江苏化工产业结构调整的路径。结果表明：1）相比低碳发展型、节水发展型和经济发展型情景，均衡发展型情景下江苏化工产业节约用水998.48万m³，碳排放强度年下降率为4.27%，产值年增长率达到4.73%，在实现水资源高效利用、碳排放强度显著降低的同时，兼顾经济高质量发展。2）化工产业结构仍需调整，具体为支持发展橡胶和塑料制品业，限制发展石油加工、炼焦及核燃料加工业，重点针对化学纤维制造业采取节水降碳措施。3）优化结果的实现需要能源消费结构向清洁能源方向优化调整，煤炭消费比重下降5.54%，天然气及电力等清洁能源上涨5.45%。4）水资源配置转移方向基本和产业结构调整方向一致，通过水资源分配优化可使石油加工、炼焦及核燃料加工业和化学纤维制造业分别节约9.8%和5.14%的用水量，并通过水交易市场转移配置到橡胶和塑料制品业。据此，建议提升区域生态承载能力，实现区域高质量发展；构建清洁高效能源消费体系，提升能源利用率；建设节水型产业发展体系，实现产业与水生态全面协调、可持续发展。

关键词: 碳减排, 水生态承载力, 化工产业, 多目标优化, 产业结构

CLC Number:

F205

CHEN Junfei, CHE Yajing, GU Yan, et al.

STRUCTURAL OPTIMIZATION OF JIANGSU’S CHEMICAL INDUSTRY CONSTRAINED BY CARBON REDUCTION AND WATER ECOLOGICAL CARRYING CAPACITY [J]. Resources & Industries, 2024, 26(2): 111-123.

陈军飞, 车雅静, 顾岩, 等.

碳减排和水生态承载双重约束下的江苏化工产业结构优化研究 [J]. 资源与产业, 2024, 26(2): 111-123.

References

崔晨韵, 朱永华, 吕海深, 等, 2020. 长兴县与水相关的生态环境承载力评价[J].河海大学学报(自然科学版), 48（5）: 406-412.〔CUI C Y, ZHU Y H, LÜ H S, et al., 2020.Water-related eco-environmental carrying capacity evaluation index system in Changxing County[J].Journal of Hohai University（Natural Sciences）, 48（5）: 406-412.〕

崔江龙, 2020.空气质量视角下的京津冀产业结构调整研究[D].北京: 首都经济贸易大学.〔CUI J L, 2020. Research on the adjustment of Beijing-Tianjin-Hebei industrial structure from the perspective of air quality[D].Beijing: Capital University of Economics and Business.〕

戴宝华, 2021.“双碳”目标约束下炼化产业转型发展思考[J].石油炼制与化工, 52（10）: 25-30. 〔DAI B H, 2021.Countermeasures of refining and petrochemical industry transformation development under the targets of carbon emission peak and carbon neutrality[J]. Petroleum Processing and Petrochemicals, 52（10）: 25-30.〕

戴厚良, 陈建峰, 袁晴棠, 等, 2021.石化工业高质量发展战略研究[J].中国工程科学, 23（5）: 122-129.〔DAI H L, CHEN J F, YUAN Q T, et al., 2021. High-quality development of the petrochemical industry in China[J]. Strategic Study of CAE, 23（5）: 122-129.〕

冯浩源, 石培基, 周文霞, 等, 2018. 水资源管理“三条红线”约束下的城镇化水平阈值分析: 以张掖市为例[J]. 自然资源学报, 33（2）: 287-301.〔FENG H Y, SHI P J, ZHOU W X, et al., 2018. Threshold analysis of urbanization with the constraint of “Three Red Lines”on water resources management: a case study of Zhangye City[J].Journal of Natural Resources, 33（2）: 287-301.〕

高向龙, 石辉, 党小虎, 2022.基于投入产出模型的黄河“几字弯”城市群用水特征与节水关键区域[J]. 生态学报, 42（24）: 10150-10163.〔GAO X L, SHI H, DANG X H, 2022．Characteristics of water use in the “Jiziwan”urban agglomeration of the Yellow River Watershed and key areas of water-saving based on input and output model[J]. Acta Ecologica Sinica, 42（24）: 10150-10163.〕

焦士兴, 李青云, 王安周, 等, 2021. 基于生态位的安阳市用水结构与产业结构动态演化分析[J].水资源保护, 37（1）: 79-85, 109.〔JIAO S X, LI Q Y, WANG A Z, et al., 2021. Dynamic evolution analysis of water consumption structure and industrial structure based on niche in Anyang City[J]. Water Resources Protection, 37（1）: 79-85, 109.〕

刘春梅, 李能, 赵强, 2017.新常态下基于混合投入产出的多目标产业结构优化研究[J].软科学, 31（9）: 5-10.〔LIU C M, LI N, ZHAO Q, 2017. Research on multi-objective optimization of industrial structure based on a hybrid input-output under new normal of Chinese economy[J].Soft Science, 31（9）: 5-10.〕

李一阳, 王红瑞, 杨默远, 等, 2023.基于多重检验EKC的中国用水与产业发展关系分析[J].水资源保护, 39（2）: 190-198.〔LI Y Y, WANG H R, YANG M Y, et al., 2023. Analysis of relationship between water consumption and industrial development in China based on multiple testing Kuznets curve[J]. Water Resources Protection, 39（2）: 190-198.〕

马志远, 段学军, 王磊, 等, 2022.长江经济带区域发展与资源环境承载力空间耦合特征及高质量发展路径[J].长江流域资源与环境, 31（9）: 1873-1883.〔MA Z Y, DUAN X J, WANG L, et al., 2022.Study on spatial coupling characteristics of regional development and resource-environment carrying capacity and path of high-quality development in Yangtze River Economic Belt[J]. Resources and Environment in the Yangtze Basin, 31（9）: 1873-1883.〕

潘崇超, 王博文, 侯孝旺, 等, 2023. 基于LMDI-STIRPAT模型的中国钢铁行业碳达峰路径研究[J].工程科学学报, 45（6）: 1034-1044.〔PAN C C, WANG B W, HOU X W, et al., 2023.Carbon peak path of the Chinese iron and steel industry based on the LMDI-STIRPAT model[J]. Chinese Journal of Engineering, 45（6）: 1034-1044.〕

孙振清, 李欢欢, 刘保留, 2020. 碳交易政策下区域减排潜力研究: 产业结构调整与技术创新双重视角[J].科技进步与对策, 37（15）: 28-35.〔SUN Z Q, LI H H, LIU B L, 2020. Research on regional emission reduction potential under carbon trading policies: the perspectives of industrial restructuring and technological innovation[J]. Science & Technology Progress and Policy, 37（15）: 28-35.〕

苏伟洲, 王成璋, 杜念霜, 2015. 水资源与产业结构关系及产业结构调整倒逼机制研究[J]. 科技进步与对策, 32（6）: 80-84.

唐晓华, 张欣钰, 李阳, 2018.中国制造业产业结构优化调整研究: 基于低碳、就业、经济增长多重约束视角[J].经济问题探索（1）: 147-154.

王成军, 韩延菲, 2023.节能减排约束下的行业经济增长路径研究[J]. 资源与产业, 25（4）: 1-11.〔WANG C J, HAN Y F, 2023. Approaches to industry economic growth path constrained by energy-saving-emission-reducing[J]. Resources & Industries, 25（4）: 1-11.〕

王小军, 廖传华, 李永亮, 等, 2020.我国石化产业基地布局及其水安全保障研究[J].环境保护, 48(17): 41-44.〔WANG X J, LIAO C H, LI Y L, et al., 2020. Study on the layout and water security for China’s petrochemical industry base[J]. Environmental Protection, 48(17): 41-44.〕

王西琴, 高伟, 张家瑞, 2015.区域水生态承载力多目标优化方法与例证[J].环境科学研究, 28（9）: 1487-1494.〔WANG X Q, GAO W, ZHANG J R, 2015. Multi-objective optimization for regional water ecological carrying capacity and case study[J]. Research of Environmental Sciences, 28（9）: 1487-1494.〕

魏楚, 2015.中国二氧化碳排放特征与减排战略研究: 基于产业结构视角[M]. 北京: 人民出版社.〔WEI C, 2015. Emission characteristics and abatement strategy of China’s CO₂ : an industry structure perspective[M]. Beijing: People’s Publishing House.〕

吴传清, 叶云岭, 2020. 破解“化工围江”难题的“湖北样本”和“江苏样本”[J]. 西部论坛, 30（6）: 71-83.〔WU C Q, YE Y L, 2020.“Hubei example”and “Jiangsu example”for solving the problem of “chemical industry encircling Yangtze River Economic Belt”[J]. West Forum, 30（6）: 71-83.〕

吴丹, 向筱茜, 2022.基于双层诊断准则的京津冀水资源与产业结构优化适配方法[J].中国人口·资源与环境, 32（4）: 154-163.〔WU D, XIANG X Q, 2022.Optimal adaptation method of water resources and industrial structure in the Beijing-Tianjin-Hebei region based on bilevel diagnosis criteria[J].China population, resources and environment, 32（4）: 154-163.〕

谢剑, 苗湃林, 2023.中国能源消费结构多目标优化研究[J].科学决策（7）: 159-167.〔XIE J, MIAO P L, 2023. Multi objective optimization of China’s energy consumption structure in the context of carbon neutrality[J]. Scientific Decision Making（7）: 159-167.〕

习近平, 2022. 坚定信心勇毅前行共创后疫情时代美好世界[N].人民日报. 2022-01-18(002).

尹杰杰, 崔远来, 刘博, 等, 2017. 基于多目标优化的灌区水资源承载力研究[J].中国农村水利水电（8）: 5-8.〔YIN J J, CUI Y L, LIU B, et al., 2017. Research on water resources carrying capacity in irrigation districts based on multi-objective optimization[J]. China Rural Water and Hydropower（8）: 5-8.〕

曾晨, 刘艳芳, 张万顺, 等, 2011.流域水生态承载力研究的起源和发展[J].长江流域资源与环境, 20（2）: 203-210.〔ZENG C, LIU Y F, ZHANG W S, et al., 2011. Origination and development of the concept of aquatic ecological carrying capacity in the basin[J]. Resources and Environment in the Yangtze Basin, 20（2）: 203-210.〕

朱智洺, 桂梦婷, 李红艳, 2023.“双碳”目标下江苏省碳平衡潜力预测研究[J]. 资源与产业, 25（1）: 1-13.〔ZHU Z M, GUI M T, LI H Y, 2023. Forecast of Jiangsu’s carbon balance potential under “dual carbon” objectives[J]. Resources & Industries, 25（1）: 1-13.〕

ARNAUDO M, TOPEL M, PUERTO P, et al., 2019. Heat demand peak shaving in urban integrated energy systems by demand side management: a techno-economic and environmental approach[J].Energy, 186: 115887.

DAI L X, WANG M Y, 2020. Study on the influence of carbon emission constraints on the performance of thermal power enterprises[J]. Environmental Science and Pollution Research, 27: 30875-30884.

DEB K, PRATAP A, AGARWAL S, et al., 2002.A fast and elitist multi-objective genetic algorithm: NSGA-Ⅱ[J].IEEE Transactions on Evolutionary Computation, 6（2）: 182-197.

DIETZ T, ROSA E A, 1994. Rethinking the environmental impacts of population, affluence and technology[J]. Human Ecology Review, 1（2）: 277-300.

KAYA Y, 1990．Impact of carbon dioxide emission control on GNP growth: interpretation of proposed scenarios[R]． Paris: IPCC．

LI Y J, ZHANG Z Y, SHI M J, 2019. What should be the future industrial structure of the Beijing-Tianjin-Hebei city region under water resource constraint? an inter-city input-output analysis[J].Journal of Cleaner Production, 239: 118117.

WU Q, 2019.Intelligent transformation and upgrading of oil refining & petrochemical industries in China: investigation & application[J]. China Petroleum Processing & Petrochemical Technology, 21（2）: 1-9 .

WANG X Q, GAO W, ZENG Y, 2014. Methods and case study on water ecological carrying capacity using SD model[J].

System Engineering Theory ＆ Practice, 34（5）: 1352-1360．

YANG Y, HE F, JI J P, et al., 2022.Peaking carbon emissions in a megacity through economic restructuring: a case study of Shenzhen, China[J]. Energies, 15: 6932.

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STRUCTURAL OPTIMIZATION OF JIANGSU’S CHEMICAL INDUSTRY CONSTRAINED BY CARBON REDUCTION AND WATER ECOLOGICAL CARRYING CAPACITY

碳减排和水生态承载双重约束下的江苏化工产业结构优化研究

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