Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China; Geography, School of Environment, Education and Development, The University of Manchester, Manchester, M13 9PL, UK.
Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China.
J Environ Manage. 2018 May 1;213:247-254. doi: 10.1016/j.jenvman.2017.08.007.
Discharge of urban domestic pollution has risen sharply during China's extensive urbanization. Together with understanding the complexity of influencing factors underpinning this rise, it has become a pressing issue to estimate total discharge and illustrate its driving mechanism scientifically. This paper reports on the monitoring of discharge from 36 sampling sites in selected residential districts in the heavily polluted Taihu Basin, China. The data were used to estimate the total amount of discharge, to develop corresponding urban domestic pollutant discharge coefficients and to analyse associated spatial patterns. Data from a questionnaire survey of over 1000 households in downtown, suburb and market town areas were then used to apply an econometric model in order to distinguish driving mechanisms. The urban domestic pollutant discharge coefficients developed in this paper are generally smaller than those reported nationally for China, based on more generalised data, decaying from city centres to the urban periphery. This study quantifies the amount of discharge and also demonstrates that urban domestic pollutant discharge is driven by multiple factors. For example, urban domestic pollution discharge rates were positively correlated with income and female-dominated households also tend to discharge more wastewater. Other factors were found to have negative correlations, such as sewage treatment rates, awareness of environmental protection, age and degree of education. As well as providing new and refined data on urban pollution discharge characteristics, the research in this paper also demonstrates the utility of combining household questionnaire and sample monitoring data in order to yield greater insights into the causes of typical polluting behaviour in Chinese neighbourhoods.
随着中国广泛的城市化进程，城市生活污水排放量急剧增加。在这种情况下，了解导致排放量增加的复杂影响因素，并科学地估计总排放量及其驱动机制已成为当务之急。本文报告了对中国太湖流域重度污染地区选定居民区 36 个采样点污水排放情况的监测结果。利用这些数据来估算排放量，制定相应的城市生活污染物排放系数，并分析相关的空间分布模式。然后，利用市中心、郊区和城镇地区 1000 多户家庭的问卷调查数据，应用计量经济学模型来区分驱动机制。本文开发的城市生活污染物排放系数普遍小于基于更广泛数据的全国平均水平，从城市中心向城市边缘逐渐降低。本研究量化了排放量，并证明城市生活污染物排放是由多种因素驱动的。例如，城市生活污水排放量与收入呈正相关，女性主导的家庭往往排放更多的废水。其他因素则呈负相关，如污水处理率、环保意识、年龄和受教育程度。本研究不仅提供了有关城市污染排放特征的新的、详细的数据，还展示了将家庭问卷调查和样本监测数据相结合以深入了解中国社区典型污染行为的原因的有效性。
