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Integrated monitoring and prediction of thermal discharge from nuclear power plants using satellite, UAV, and numerical simulation.
Wang, Luyan; Li, Guoqing; Shi, Hongyuan; Zhu, Jun; Zhan, Chao; Zhang, Xuri; Wang, Qing.
Afiliação
  • Wang L; School of Resources and Environmental Engineering, Ludong University, Yantai, 264025, China.
  • Li G; School of Resources and Environmental Engineering, Ludong University, Yantai, 264025, China. ligqing@foxmail.com.
  • Shi H; Institute of Coastal Research, Ludong University, Yantai, 264025, China.
  • Zhu J; School of Hydraulic Engineering, Ludong University, Yantai, 264025, China.
  • Zhan C; Institute of Coastal Research, Ludong University, Yantai, 264025, China.
  • Zhang X; School of Hydraulic Engineering, Ludong University, Yantai, 264025, China.
  • Wang Q; Institute of Coastal Research, Ludong University, Yantai, 264025, China.
Environ Monit Assess ; 196(8): 736, 2024 Jul 15.
Article em En | MEDLINE | ID: mdl-39009747
ABSTRACT
Global nuclear power is surging ahead in its quest for global carbon neutrality, eyeing an anticipated installed capacity of 436 GW for coastal nuclear power plants by 2040. As these plants operate, they emit substantial amounts of warm water into the ocean, known as thermal discharge, to regulate the temperature of their nuclear reactors. This discharge has the potential to elevate the temperature of the surrounding seawater, potentially influencing the marine ecosystem in the discharge vicinity. Therefore, our study area is on the Qinshan and Jinqimen Nuclear Power Plants in China, employing a blend of Landsat 8/9, and unmanned aerial vehicle (UAV) imagery to gather sea surface temperature (SST) data. In situ measurements validate the temperature data procured through remote sensing. Leveraging these SST observations alongside hydrodynamic and meteorological data from field measurements, we input them into the MIKE 3 model to prognosticate the three-dimensional (3D) spatial distribution and temperature elevation resulting from thermal discharge. The findings reveal that (1) satellite remote sensing can instantly acquire the horizontal distribution of thermal discharge, but with a spatial resolution much lower than that of UAV. The spatial resolution of UAV is higher, but the imaging efficiency of UAV is only 1/40,000 of that of satellite remote sensing. (2) Numerical simulation models can predict the 3D spatial distribution of thermal discharge. Although UAV and satellite remote sensing cannot directly obtain the 3D spatial distribution of thermal discharge, using remotely sensed SST as the temperature field input for the MIKE 3 model can reduce the quantity of measured temperature data and lower the cost of numerical simulation. (3) In the process of monitoring and predicting the thermal discharge of nuclear power plants, achieving an effective balance between monitoring accuracy and cost can be realized by comprehensively considering the advantages and costs of satellite, UAV, and numerical simulation technologies.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Centrais Nucleares / Tecnologia de Sensoriamento Remoto País/Região como assunto: Asia Idioma: En Revista: Environ Monit Assess Assunto da revista: SAUDE AMBIENTAL Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Centrais Nucleares / Tecnologia de Sensoriamento Remoto País/Região como assunto: Asia Idioma: En Revista: Environ Monit Assess Assunto da revista: SAUDE AMBIENTAL Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Holanda