Black-odorous water bodies annual dynamics in the context of climate change adaptation in Guangzhou City, China

被引:4
|
作者
Liu, Bing [1 ,2 ]
Xi, Haojun [1 ,2 ]
Li, Tianhong [1 ,2 ,5 ]
Borthwick, Alistair G. L. [3 ,4 ]
机构
[1] Peking Univ, Coll Environm Sci & Engn, Beijing, Peoples R China
[2] State Environm Protect Key Lab All Mat Fluxes Rive, Beijing, Peoples R China
[3] Univ Edinburgh, Inst Infrastruct & Environm, Sch Engn, Kings Bldg, Edinburgh EH9 3JL, Scotland
[4] Univ Plymouth, Sch Engn Math & Comp, Plymouth PL4 8AA, England
[5] Peking Univ, Room 311,Bldg Environm, Beijing 100871, Peoples R China
关键词
Black-odorous water; Detection model; GF images; Climate change adaptation; Spatiotemporal trends; Guangzhou; LAND-USE; QUALITY CHANGES; PEARL RIVER; PATTERNS; DRIVERS; CLARITY; TRENDS; BLOOMS; LAKE;
D O I
10.1016/j.jclepro.2023.137781
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Black-odorous water (BOW) in urban areas has brought detrimental ecological effects and posed a threat to the health of surrounding residents. Identifying BOWs in urban areas is difficult because they are usually small in area, and discontinuous in spatial distribution. The efforts to adapt to climate change in cities have a direct connection to urban environment and may affect the dynamics of BOWs, but their relationship has seldom been addressed in previous research. This research builds a new urban BOW detection model using Gaofen (GF) images and ground-level in-situ water quality data to detect the spatiotemporal dynamics of BOWs in Guangzhou City's main urban area from 2016 to 2020, when comprehensive climate adaptation strategy has been implemented as a pilot metropolitan area in China. Spatial analysis in the study area with a total of 97 focused rivers revealed a decreasing trend in BOW occurrence (from 85.57% in 2016 to 21.65% in 2020) in the context of climate change adaptation efforts. Redundancy analysis between BOWs occurrence and environmental factors showed that across the entire study area, the contributions of anthropogenic factors (highest proportion at 14.3% for the area percentage of built-ups) to BOW, such as population density, agricultural water use, domestic water use, and so on, distinctly stronger than climatic drivers (largest contribution of 4.4% for temperature). The results suggested that climate change adaptation efforts help to decrease BOW occurrence in the study area, while exploring the response mechanism between climate change adaptation measures and the changes of BOWs is necessary in the future research. The findings were conducive to the development of targeted measures to decrease the occurrence of urban BOWs while improving adaptability of the city to climate change.
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页数:11
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