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| 黄河流域煤炭富集区煤炭水足迹演变及驱动效应研究 | |
| 引用本文： | 刘秀丽,王昕,郭丕斌,熊睿,聂雷,申俊,张静. 黄河流域煤炭富集区煤炭水足迹演变及驱动效应研究[J]. 地理科学, 2022, 42(2): 293-302. DOI: 10.13249/j.cnki.sgs.2022.02.011 |
| 作者姓名： | 刘秀丽 王昕 郭丕斌 熊睿 聂雷 申俊 张静 |
| 作者单位： | 1.山西财经大学资源型经济转型发展研究院， 山西 太原 030006 2.太原学院管理系， 山西 太原 030006 |
| 基金项目： | 国家自然科学基金项目（42001257,71874119）；;山西省高等学校哲学社会科学研究项目（20210115）； |
| 摘 要： | 煤炭与水资源相互影响和制约，如何评价煤炭耗水的演变趋势及其影响机制对煤炭和水资源进行协同管理具有重要意义。基于国际标准的煤炭水足迹测算模型，分析2000—2017年黄河流域煤炭富集区——晋陕蒙煤炭水足迹的时空演变趋势，构建煤炭水足迹压力指数评价区域煤炭和水资源的匹配关系，并运用LMDI模型定量分析煤炭水足迹的驱动效应。结论如下：① 煤炭水足迹总量在研究期内呈增长趋势，主要以原煤和火力发电水足迹为主，山西和内蒙古煤炭水足迹最高，陕西最低。② 研究区整体煤炭水足迹压力指数逐渐增大，由煤–水关系缓和型逐渐演变为煤–水关系制约型，从空间分异来看，山西最大，研究期内均属于煤–水紧张型，陕西次之，内蒙古最小，均由煤–水关系缓和型演变为煤–水关系制约型。③ 影响煤炭水足迹的主要驱动因素是经济效应和技术效应，前者对煤炭水足迹的影响逐渐增强，后者对煤炭水足迹压力的影响先增强后减弱，各驱动效应空间分异明显。研究结果可为煤炭富集区煤炭和水资源可持续利用提供决策参考，为黄河流域生态保护和高质量发展的资源管理提供决策支持。 |
| 关 键 词： | 煤炭水足迹 LMDI模型 煤–水关系 黄河流域 |
| 收稿时间： | 2021-01-03 |
| 修稿时间： | 2021-03-18 |
Evolution and Driving Effect of Coal-Water Footprint in Coal Rich Areas of the Yellow River Basin |
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| Liu Xiuli,Wang Xin,Guo Pibin,Xiong Rui,Nie Lei,Shen Jun,Zhang Jing. Evolution and Driving Effect of Coal-Water Footprint in Coal Rich Areas of the Yellow River Basin[J]. Scientia Geographica Sinica, 2022, 42(2): 293-302. DOI: 10.13249/j.cnki.sgs.2022.02.011 | |
| Authors: | Liu Xiuli Wang Xin Guo Pibin Xiong Rui Nie Lei Shen Jun Zhang Jing |
| Affiliation: | 1. Research Institute of Resource-based Economics, Shanxi University of Finance & Economics, Taiyuan 030006, Shanxi, China 2. Department of Management, Taiyuan University, Taiyuan 030006, Shanxi, China |
| Abstract: | Coal and water resources are important strategic natural resources in China. How to evaluate the evolution of coal and water consumption and its influence mechanism is great significantly for the coordinated management of coal and water consumption. The coal-water footprint is calculated based on ISO standard method to measure the space-time evolution trend of coal-water footprint in Yellow River basin in 2000-2017, using coal- water footprint pressure index evaluation to analysis the matching relation between coal and water, and using Kaya identities and LMDI model to analyze the driving effect of coal-water footprint. The conclusions are as follows: 1) The total coal-water footprint showed an increasing trend during the study period, and the coal-water footprint was mainly dominated by raw coal and thermal power generation. The coal-water footprint in Shanxi and Inner Mongolia was the highest, while that in Shaanxi was the lowest. 2) The coal-water footprint pressure index gradually increased, and gradually changed from the moderating type of coal-water relationship to the moderating type of coal-water relationship. From the perspective of spatial variation, Shanxi was the largest, with the intense type of coal-water relationship. Shaanxi followed closely, and Inner Mongolia was the smallest, both of which changed from the moderating type to the moderating type of coal-water relationship. 3) The main factors influencing the coal-water footprint pressure were economic effect and technological effect. The former had a gradually enhanced influence on the coal-water footprint pressure, while the latter had a gradually weakened influence on the coal-water footprint pressure. The spatial differentiation of each driving factor was obvious. The research results can provide reference for the sustainable utilization of coal and water resources in the coal-rich areas, and provide decision support for the resource management of ecological protection and high-quality development in the Yellow River Basin. |
| Keywords: | coal-water footprint LMDI model coal-water relationship the Yellow River Basin |
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