Temporal and Spatial Characteristics of Thermal Discharge of Xiangshan Harbor (China) Power Plant Derived from Landsat Remote Sensing Data

The thermal discharge from coastal power plants exchanges heat with the surrounding marine environment, potentially affecting the aquatic ecosystem. This study utilizes Landsat-series satellite data from 2008 to 2023 to extract the spatiotemporal distribution characteristics of thermal discharges from the Xiangshan Harbor Guohua Power Plant (GPP) and the Wushashan Power Plant (WPP). Additionally, the study investigates the impact of thermal discharge on local aquatic life by examining the spatiotemporal distribution of chlorophyll-a (Chl-a). The results indicate that (1) the overall area of thermal rise in GPP and WPP shows a decreasing trend. The interannual variation in low thermal rise zones (+1 °C, +2 °C) is substantial, with significant seasonal differences mainly influenced by seasonal sea–air temperature differences, the flow velocity of seawater at the discharge outlet, and water depth. (2) The diffusion of thermal discharge is significantly affected by tides. The area of thermal rise is larger during ebb tide compared to flood tide, and during neap tide compared to mid-tide and spring tide. During the ebb tide of the neap tide period, the total area of thermal rise in WPP is approximately three times that of GPP. (3) There is a significant positive correlation between thermal discharge and concentrations of Chl-a. Thermal discharge has complex impacts on aquatic life, primarily positive. The findings of this study provide important references for analyzing the ecological impacts of thermal discharge from coastal power plants.

Authors

Institutions

Publication Details

Journal
Remote Sensing
Published
2025-08-22
DOI
https://doi.org/10.3390/rs17172926
Primary Topic
Remote Sensing and Land Use
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Temporal and Spatial Characteristics of Thermal Discharge of Xiangshan Harbor (China) Power Plant Derived from Landsat Remote Sensing Data

Zhongfeng Qiu, Rong Tang, Chaofan Duan, Dongzhi Zhao et al.
Remote Sensing
Remote Sensing and Land Use
article

Temporal and Spatial Characteristics of Thermal Discharge of Xiangshan Harbor (China) Power Plant Derived from Landsat Remote Sensing Data

Zhongfeng Qiu, Rong Tang, Chaofan Duan, Dongzhi Zhao, Lina Cai
article en

Abstract

The thermal discharge from coastal power plants exchanges heat with the surrounding marine environment, potentially affecting the aquatic ecosystem. This study utilizes Landsat-series satellite data from 2008 to 2023 to extract the spatiotemporal distribution characteristics of thermal discharges from the Xiangshan Harbor Guohua Power Plant (GPP) and the Wushashan Power Plant (WPP). Additionally, the study investigates the impact of thermal discharge on local aquatic life by examining the spatiotemporal distribution of chlorophyll-a (Chl-a). The results indicate that (1) the overall area of thermal rise in GPP and WPP shows a decreasing trend. The interannual variation in low thermal rise zones (+1 °C, +2 °C) is substantial, with significant seasonal differences mainly influenced by seasonal sea–air temperature differences, the flow velocity of seawater at the discharge outlet, and water depth. (2) The diffusion of thermal discharge is significantly affected by tides. The area of thermal rise is larger during ebb tide compared to flood tide, and during neap tide compared to mid-tide and spring tide. During the ebb tide of the neap tide period, the total area of thermal rise in WPP is approximately three times that of GPP. (3) There is a significant positive correlation between thermal discharge and concentrations of Chl-a. Thermal discharge has complex impacts on aquatic life, primarily positive. The findings of this study provide important references for analyzing the ecological impacts of thermal discharge from coastal power plants.

Remote SensingVol. 17(17)
National University of Defense Technology (CN), Nanjing University of Information Science and Technology (CN), Zhejiang Ocean University (CN), Sanya University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 73%
Remote Sensing and Land Use
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.