Detection of thermal pollution from power plants on China’s eastern coast using remote sensing data

The acceleration of the industrialization process in China has increased the demand for electricity and triggered a power-plant building boom, especially along China’s eastern coast, where the economy gets off early and enjoys a fast development. The thermal plumes, residual chlorine, nuclides and other pollutions produced by the thermal and nuclear power plants have exerted an impact on the coastal eco-environment. To monitor the thermal pollution from the power plants at Yueqing Bay on the eastern coast, in this research, the distribution of sea surface temperature (SST) surrounding the power plants is obtained by using the SST retrieval methods developed for Landsat Enhanced Thematic Mapper Plus (ETM+), HJ-1B infrared sensor (IRS) and Terra moderate resolution imaging spectroradiometer (MODIS) data. The comparison of the SST retrieval results before and after the operation of power plants indicates that the total area of sea waters that is impacted by the thermal discharge from the two power plants at Yueqing Bay is approximately 17.95 km2, with the highest SST rise of 4.5 °C appearing over the waters around the outlet of the Huaneng Yuhuan power plant on the eastern shore, whereas the highest SST rise around the Zheneng Yueqing power plant on the western shore reaches 3.8 °C. The intensity and scope of influence of the thermal discharge mainly depend on the installed capacity of power plants, coastal terrain, and tide. Although the area where the SST rise is more than 3 °C is not large, thermal discharge still has an impact on bay ecosystems due to the relatively closed nature of the bay environment. Due to the influence of rising water temperatures on the reproduction and individual evolution of fish, shrimp, crabs, shellfish and other aquatic creatures, in the long term, the thermal pollution from coastal power plants will affect the volume of natural fishery and biological resources throughout the waters. The quantitative retrieval results also suggest that relative to MODIS data, Landsat ETM+ and HJ-1B IRS data with a high spatial resolution are more applicable to the estimation of small-scale SST, and IRS data with a high temporal resolution are more helpful in the study of spatio-temporal variability of thermal plumes from coastal power plants.