Liu Yesen, Huang Yaohuan, Liu Yuanyuan
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; Key Laboratory of River Basin Digital Twinning of Ministry of Water Resources, Beijing 100038, China.
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resource and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
Sci Total Environ. 2024 Nov 1;949:175146. doi: 10.1016/j.scitotenv.2024.175146. Epub 2024 Jul 30.
Rivers play a crucial role in the development of human civilization, and river pollution is a significant environmental issue that accompanies with intensified human activity. However, the evaluation of river pollution at a global scale is difficult because of the limitations of long-term pollution-related datasets. As human activities are the main factor causing river pollution, nighttime light (NTL) remote sensing data can be used as an alternative indicator of the risk of river pollution stress(RPS), which is closely related to human activities and refers to the amount of pollutants within the confluence range of river reaches. In this study, we propose a river pollution pressure index (PI) to indicate risk of RPS by considering the accumulation effect of water flow. Then we calculated PI of over 0.67 million reaches global with annual total flow >100 million m/s from 2000 to 2022, which was validated using water quality data of >2000 river sections in China. The results show that, from 2000 to 2022, the spatial variations of the risk of RPS are uneven, with a migration trend from west to east. The risk of RPS continues to increase globally, especially rapidly after 2010. Central Asia, Southeast Asia, East Asia, and eastern China are the regions with the fastest growth rates. In most developed countries, developing countries, and underdeveloped countries, the risk of RPS is high and increasing slowly, moderate and increasing rapidly, and low and increasing slowly, respectively. However, in some special cases, such as Japan, the risk of RPS continues to decrease. These spatiotemporal variations of the risk of RPS correlate with global events, such as quantitative easing of global economy after 2008, China's "Belt and Road Initiative", and COVID-19. This study demonstrates that NTL data can be applied to evaluate the global risk of RPS.
河流在人类文明发展中发挥着至关重要的作用,而河流污染是伴随人类活动加剧而产生的一个重大环境问题。然而,由于长期污染相关数据集的局限性,在全球范围内评估河流污染具有一定难度。由于人类活动是造成河流污染的主要因素,夜间灯光(NTL)遥感数据可作为河流污染压力风险(RPS)的替代指标,RPS与人类活动密切相关,指的是河流汇流范围内的污染物量。在本研究中,我们提出了一个河流污染压力指数(PI),通过考虑水流的累积效应来指示RPS风险。然后,我们计算了2000年至2022年全球超过67万个年总流量>1亿立方米/秒的河段的PI,并使用中国2000多个河段的水质数据进行了验证。结果表明,2000年至2022年,RPS风险的空间变化不均衡,呈现出从西向东的迁移趋势。全球范围内RPS风险持续上升,尤其是2010年之后上升迅速。中亚、东南亚、东亚和中国东部是增长率最快的地区。在大多数发达国家、发展中国家和欠发达国家,RPS风险分别为高且增长缓慢、中等且增长迅速、低且增长缓慢。然而,在一些特殊情况下,如日本,RPS风险持续下降。RPS风险的这些时空变化与全球事件相关,如2008年后全球经济的量化宽松、中国的“一带一路”倡议以及新冠疫情。本研究表明,NTL数据可用于评估全球RPS风险。