PlanetData ENERGY FOUNDATION 能源基金会 Understanding the Effects of Thermal PowerPlantsonRegionalWaterQuality BasedonSatellite-derivedDatainYunnan Planet Data Inc. 2020.12.30
PlanetData IBackground With the rapid growth of economy the demand of electricity consumption for daily still the main mode in China. In 2017 The total power generation reaches 6.5 trillion kwh. Among them thermal power plants account for more than 71% of power generation. In addition to air water is usually chosen as the cooling medium. In 2015 the Standing Committee of the Political Bureau of the Central Committee deliberates and approves the Action Plan for the Prevention and Control of Water Pollution (Water 10) aiming to strengthen efforts to prevent and control water pollution and ensure national water security. The plan calls for more than 70 percent of seven river basins including the Yangtze River and Zhuhai to have water that reaches or exceeds quality category III by 2020. Yunnan province is located at the confluence of the Yangtze River basin and the Pearl River Basin. Although the basin area of nine plateau lakes represented by Yangzonghai and Dianchi lakes only accounts for 2.1% in the area of Yunnan Province they play an important role in the economic and social development of Yunnan province and account for more than one-third of the provincial GDP annually. In recent years as the industry and tourism develop Yangzonghai and Dianchi witness a rapid degradation in water quality. Yunnan provincial government and Provincial Environmental Protection Bureau attach great attention to the prehensive control of water pollution in Yangzonghai and Dianchi and treat it as a major implement of sustainable development. However due to the influence of environmental factors water exchange periods of two lakes are long and the ecosystems are fragile. The high-density population brought by the developed economy aggravates the load of polution in lakes. The multifarious types of pollutants interact with each other which increases the difficulty of implementing water quality management and leads to long-term accumulation of pollutants. Due to the intense urbanization the buffer zone is underdeveloped which leads to fragile plant munities and the decline of self-purification capacity of lakes. Therefore discharge control is critical in improving the water quality of Yangzonghai and Dianchi and passing the window period of ecological restoration.
PlanetData To identify illegal discharges from enterprises and individuals monitor the discharge of major pollution source and provide theoretical and data support for further development of pollution control policies a detailed evaluation of the temporal and spatial changes in water temperature chlorophyll concentration and water transparency is required. However due to the cost and difficulty of implementing field trips the data obtained have limited coverage in time and space which will lead to a failure in carrying out long-term spatial and temporal analysis of Yangzonghai and Dianchi. With the development of remote sensing technology methods of using empirical formula to evaluate water quality has been optimized and popularized by researchers. Compared to the traditional sampling methods environmental remote sensing technology has higher spatial and temporal resolution. To investigate the relationship among water temperature transparency and chlorophyll concentration and their temporal ad spatial variations we develop three models to respectively represent historical situations. Taking advantage of the satellite-based models we analyze the long-term trend and whole scale variations. Hypotheses are proposed that discharged warm water could deteriorate aquatic ecosystem by providing a warm and nutrient-rich environment for plankton and plants. Previous studies have pointed out that the discharged warm water from thermal power plants may cause multiple kinds of damage to water quality including increasing the water temperature (thermal pollution) increasing the concentration of suspended particulate matter and However the remote sensing technology mainly works for revealing correlations rather than casual relationships the intermediate processes are not discussed in this report. Analyses are merely based on satellite-derived observations. We ignore the principles of the intermediate reactions among pollutants and aquatic organisms. For instance the way that discharged warm water impacts the vigor of plankton and plant 2
PlanetData II Method 1.Study Area 1)Yangzonghai Yangzonghai located in the southeast of Kunming covers an area of 31.9 square kilometers with an average water depth of 20 meters. It stores 604 million cubic meters of water which is about half of the water volume of Dianchi Lake. According to the 2015 Environmental status Bulletin of Yunnan Province the water quality of Yangzonghai in 2015 is classified as Class IV. Arsenic concentration is classified as Class IV which is 0.05 times above the standard. Phosphorus and chemical oxygen are 0.36 times and 0.17 times above the standard respectively. The average nutritional status index of the whole lake is 41.2 which is classified as mesoeutrophic. 2) Dianchi Dianchi is the largest lake in southwest China belonging to the Yangtze River Basin. It is in the south-central part of Kunming Basin. The lake covers an area of 300 square kilometers and the shoreline is about 150 kilometers long. In the north of the lake there is an embankment stretching from east to west which is 3.5 kilometers long and 300 meters wide. It divides Dianchi into two parts. South of the embankment known as the outer sea is the main part of the Dianchi covering an area of 289.065 square kilometers accounting for 97.2% of the total area. North of the embankment is called inner sea which is also known as grass sea occupying an area of about 10 square kilometers. The average depth of Dianchi is about 5 meters. 2. Data acquirement and pre-processing In order to btain sufficient data for time series analysis we expand the time period to 2006 to 2018. For the data pre-processing we firstly conduct radiometric calibration for Landsat5TM and Landsat8OLI images and the calibration type is radiometric brightness. Secondly we calibrate the images based on sensor types the parameters acquired by each image (season aerosol model atmospheric model visibility etc.) the altitude and regional type of the study area. Thirdly we use the object-oriented image segmentation technology to extract the vector boundary of Yangzonghai and Dianchi Lake. Then we utilize the vector boundary as a mask
PlanetData to extract areas of Yangzonghai and Dianchi Lake. Finally for areas covered by clouds we remove the noise based on spectrum signature. 3.Modeling 1)Water surface temperature model The inversion of water surface temperature is based on atmospheric correction method. The expression for the infrared thermal luminance value La received by the satellite sensor: Lx=[εB(Ts)(1e)Ld]Lu (1) Where c is the surface emissivity T's is the true temperature (K) B(Ts)为 is the luminance of the blackbody at temperature T t is the atmospheric transmittance in thermal infrared band Lu is upward atmospheric luminance and Ld is downward atmospheric luminance. The luminance of the blackbody at temperature T B(T's) is expressed as following: B(T's)=[Lx-Lu-T(1-E)La]/te (2) T's is calculated by Planck formula: Ts=K2/ln(K/B(Ts)1) (3) 2)Water transparency model The change of water transparency (SD) is mainly affected by the optical ponents (algae non-algal particles yellow substances). Transparency is also an important index to evaluate eutrophication which directly reflects the clarity and turbidity degree of the lake. The reflectance of red and near-infrared bands is easily affected by suspended matters. Suspended matters have a strong negative correlation with transparency. However it is rarely used due to the strong absorption of near-infrared bands in water. Based on the reflectance characteristics of each band we select the ratio of red and green bands to construct a water transparency model: Ln(SD)= a * ( BGreen/BRed) - b (4) 3) Chlorophyll concentrationmodel Based on the empirical models for the same water area the ratio of near-infrared band to visible red band is used as a sub-factor which can effectively minimize the influence of the atmospheric effect. The model established is the relationship between the natural logarithm of 4
基于卫星数据分析云南火电厂对地区水质的影响.pdf
