CAS Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen, 361021, China.
University of Chinese Academy of Sciences, Beijing, China.
Environ Sci Pollut Res Int. 2019 Feb;26(6):5680-5692. doi: 10.1007/s11356-018-3875-0. Epub 2019 Jan 5.
Worldwide socioeconomic development has resulted in huge irretrievable environmental problems in various ecosystems. This study employed seven coastal watersheds in two provinces, Zhejiang and Fujian, China forming a gradient to testify the environmental Kuznets curve (EKC) interactions between socioeconomic development and environmental impact at a watershed scale. Annual socioeconomic indicators, including gross domestic product (GDP) and its components, registered population (agricultural and non-agricultural population), and electricity consumption, and annual discharges of chemical oxygen demand (COD) and ammonium were collected at a county level, and land use pattern to generate watershed level dataset in the period of 2011-2016. Results indicated that non-agricultural GDP per capita of the non-agricultural population and discharge of COD or ammonium per unit of total GDP were top-ranked pair-indicators significantly fitting the EKC model instead of the classic GDP per capita and pollutants. The development of seven selected watersheds have passed the turning point of the EKC and entered impact-reducing development stages along the EKC, i.e., the three Zhejiang watersheds are at the low-impact development stage, the Huotong Stream watershed from Fujian province was at impact-declining development stage right, and other three Fujian watersheds were at medium-impact development stage. In term of the environmental impact indicator, pollutant discharge per unit of total GDP serves as a development impact indictor per se. These findings might provide an EKC-based approach to support and strategize the watershed management for sustainable development in the world.
全球社会经济发展导致了各种生态系统中不可挽回的巨大环境问题。本研究采用中国浙江和福建两省的七个沿海流域，形成一个梯度，在流域尺度上验证社会经济发展与环境影响之间的环境库兹涅茨曲线（EKC）关系。在 2011-2016 年期间，以县级水平收集了年度社会经济指标，包括国内生产总值（GDP）及其组成部分、登记人口（农业和非农业人口）和用电量，以及每年的化学需氧量（COD）和氨排放量。土地利用格局生成流域水平数据集。结果表明，非农业人口人均非农 GDP 和单位总 GDP 的 COD 或氨排放量是排名最高的配对指标，与 EKC 模型显著拟合，而不是经典的人均 GDP 和污染物。所选七个流域的发展已经通过了 EKC 的转折点，并沿着 EKC 进入了减少影响的发展阶段，即三个浙江流域处于低影响发展阶段，福建霍童溪流域处于影响下降发展阶段，其他三个福建流域处于中等影响发展阶段。就环境影响指标而言，单位总 GDP 的污染物排放量本身就是一个发展影响指标。这些发现可能为基于 EKC 的方法提供支持，并为世界范围内的流域可持续发展管理制定战略。
