The data set records the monitoring report of the key industrial enterprises in Qinghai Province (2015-2020). The data is collected from the Department of ecological environment of Qinghai Province. The data set contains 115 data files, including the supervision monitoring of Qinghai Huadian Datong Power Generation Co., Ltd. in the first quarter of 2015, the supervision monitoring of Qinghai Huadian Datong Power Generation Co., Ltd. in the second quarter of 2015, the supervision monitoring of Qinghai Huadian Datong Power Generation Co., Ltd. in the third quarter of 2015, and the supervision monitoring of Qinghai Huadian Datong Power Generation Co., Ltd. in the fourth quarter of 2015 Supervision monitoring of Huadian Datong Power Generation Co., Ltd. The key polluting enterprises involved are: Qinghai Huadian Datong Power Generation Co., Ltd., Qinghai Products Industry Investment Co., Ltd., Qilian mountain cement, Qinghai ningbei Power Generation Co., Ltd., Qinghai Qiaotou Aluminum Power Co., Ltd., Qinghai new building materials industry and Trade Co., Ltd., Qinghai Products Industry Investment Co., Ltd., Qinghai Yihua Chemical Co., Ltd., and Chalco Qinghai Branch Company, Qinghai cement, Baihe aluminum, Huaneng Xining Thermal Power Co., Ltd., Huanghe Xinye, Jihua Jiangyuan, Qinghai Huanghe Jianiang Beer Co., Ltd., Qinghai Jiangcang Energy Development Co., Ltd., Qinghai ningbei Power Generation Co., Ltd., Qinghai Tianlu Dairy Co., Ltd., Qinghai xiaoxiniu Dairy Co., Ltd., Western zinc and Xining Special Steel Co., Ltd Company, Asia silicon (Qinghai) Co., Ltd., Salt Lake Haina, yuntianhuazhong, State Power Investment Group Xi'an solar power generation Co., Ltd., upper Yellow River Hydropower Development Co., Ltd., Qinghai Electronic Materials Industry Development Co., Ltd., Qinghai Yellow River Jianiang Beer Co., Ltd., Qinghai Pharmaceutical Factory Co., Ltd., Qinghai Western Indium Industry Co., Ltd., Qinghai Hongyang Cement Co., Ltd Ltd., Qinghai Jieshen Environmental Energy Industry Co., Ltd., etc. among Monitoring point: flue gas outlet of rotary kiln. Monitoring items: particulate matter, sulfur dioxide, nitrogen oxides, flue gas flow. Monitoring frequency: three samples per production cycle under normal operation condition Contents of daily monitoring: cod, pH, COD, cod
Department of Ecology and Environment of Qinghai Province
The data set records the monitoring results of sewage treatment plants in Qinghai Province from 2014 to 2015. Data statistics from the Qinghai Provincial Department of ecological environment data set contains six documents, which are: the monitoring results of Qinghai sewage treatment plant in the first quarter of 2014, the monitoring results of Qinghai sewage treatment plant in the second quarter of 2014, the monitoring results of Qinghai sewage treatment plant in the third quarter of 2014, the monitoring results of Qinghai sewage treatment plant in the fourth quarter of 2014, and the monitoring results of Qinghai sewage treatment plant in the first quarter of 2015 The monitoring results of the treatment plant and the supervision monitoring of the sewage treatment plant in Qinghai Province in the third quarter of 2015. The structure of the data table is the same, and the monitoring area covers Xining city and its three counties, Ping'an County, Ledu County, Gonghe County and Delingha city. The number of supervisory monitoring of sewage treatment plant, including 15 fields Field 1: Administrative Region Field 2: name of sewage treatment plant Field 3: receiving water body Field 4: monitoring date Field 5: name of executive standard Field 6: name of execution standard condition Field 7: Design daily capacity (T / D) Field 8: import flow (T / D) Field 9: export flow (T / D) Field 10: monitoring items Field 11: inlet concentration (mg / L) Field 12: outlet concentration (mg / L) Field 13: standard limit (mg / L) Field 14: emission unit Field 15: is it up to standard
Department of Ecology and Environment of Qinghai Province
The data set records the supervisory monitoring of key pollution sources controlled by the state in Huangnan Prefecture in 2016. The data set is compiled from the Department of ecological environment of Qinghai Province. The data set contains four data tables, which are respectively the statistics of the first, second, third and fourth quarter of 2016 national control key pollution sources supervision monitoring in Huangnan Prefecture. The data table structure is the same. There are 17 fields in each data table (only the top 6 fields are listed), for example, the monitoring situation of national key pollution sources in the first quarter of 2016: Field 1: Administrative Region Field 2: name of sewage treatment plant Field 3: receiving water body Field 4: monitoring date Field 5: name of executive standard Field 6: name of execution standard condition
Department of Ecology and Environment of Qinghai Province
The data set records the monitoring report of key pollution sources controlled by the state in Hainan Province from 2013 to 2014. Data statistics from the Qinghai Provincial Department of ecological environment data set, including four data files, respectively: the first quarter of 2014 national control monitoring report of Hainan prefecture, Qinghai Province, national control key pollution source supervision and monitoring report - 2013, Hainan state, Qinghai Province, national control key pollution source supervision and monitoring report - 2014 (1), Hainan state, Qinghai Province, national control key pollution source supervision and monitoring report - 2014 （2）。 The monitoring report is entrusted by the Environmental Protection Bureau of Hainan Tibetan Autonomous Prefecture. The monitoring sites include Gonghe County sewage treatment plant, guide county sewage treatment plant, Qinghai Saishitang Copper Co., Ltd. and Gonghe County Jinhe Cement Co., Ltd. the monitoring items include pH, chemical oxygen demand, five-day biochemical oxygen demand, chromaticity, ammonia nitrogen, total phosphorus, total nitrogen, total chromium, arsenic, mercury, cadmium and chromium（ The monitoring frequency was 2 times / day, one day;
Department of Ecology and Environment of Qinghai Province
The data set records the reasons why the state key monitoring enterprises in Qinghai province did not carry out the monitoring of pollution sources in 2014. The data is collected from the Department of ecological environment of Qinghai Province, and the data set contains four documents, which are: the reasons why the national key monitoring enterprises of Qinghai province did not carry out the supervision monitoring of pollution sources in the first, second, third and fourth quarters of 2014. According to Huangzhong County, Huzhu County, Minhe County, Gonghe County, Xinghai County, Tianjun County, Delingha County, Dachaidan County, Datong County, Ledu County and Golmud City of Qinghai Province, the specific reasons for the failure of export monitoring in "unmonitored wastewater", "unmonitored waste gas" and "unmonitored heavy metal wastewater" are given in the data set. The data table has the same structure and contains five fields Field 1: monitoring category Field 2: location city Field 3: enterprise name Field 4: reason not monitored Field 5: remarks
Department of Ecology and Environment of Qinghai Province
The data set records the monitoring reports of key pollution sources in Hainan Province from 2013 to 2014. The data is collected from the Department of ecological environment of Qinghai Province, and the data set contains two data files, which are: Supervision Monitoring Report of key pollution sources controlled by Hainan Province in Qinghai Province - 2013, and supervision monitoring report of key pollution sources controlled by Hainan Province in Qinghai Province - 2014. The monitoring sites cover six enterprises including Qinghai Xuefeng yak Dairy Co., Ltd. and Hainan Sifang Thermal Power Co., Ltd. the monitoring items are: smoke and dust, sulfur dioxide, nitrogen oxide export emission concentration and emission, pH, ammonia nitrogen, BOD5, total phosphorus, total nitrogen, nitrate nitrogen, suspended solids, chemical oxygen demand; the monitoring frequency is one day, four times in a row; the monitoring frequency is one day, four times in a row;
Ecological Environment Bureau of Hainan Prefecture
The data set records the monitoring report of the key industrial enterprises in Qinghai Province (2015-2020). The data is collected from the Department of ecological environment of Qinghai Province. The data set contains 115 data files, including the supervision monitoring of Qinghai Huadian Datong Power Generation Co., Ltd. in the first quarter of 2015, the supervision monitoring of Qinghai Huadian Datong Power Generation Co., Ltd. in the second quarter of 2015, the supervision monitoring of Qinghai Huadian Datong Power Generation Co., Ltd. in the third quarter of 2015, and the supervision monitoring of Qinghai Huadian Datong Power Generation Co., Ltd. in the fourth quarter of 2015 Supervision monitoring of Huadian Datong Power Generation Co., Ltd. The key polluting enterprises involved are: Qinghai Huadian Datong Power Generation Co., Ltd., Qinghai Products Industry Investment Co., Ltd., Qilian mountain cement, Qinghai ningbei Power Generation Co., Ltd., Qinghai Qiaotou Aluminum Power Co., Ltd., Qinghai new building materials industry and Trade Co., Ltd., Qinghai Products Industry Investment Co., Ltd., Qinghai Yihua Chemical Co., Ltd., and Chalco Qinghai Branch Company, Qinghai cement, Baihe aluminum, Huaneng Xining Thermal Power Co., Ltd., Huanghe Xinye, Jihua Jiangyuan, Qinghai Huanghe Jianiang Beer Co., Ltd., Qinghai Jiangcang Energy Development Co., Ltd., Qinghai ningbei Power Generation Co., Ltd., Qinghai Tianlu Dairy Co., Ltd., Qinghai xiaoxiniu Dairy Co., Ltd., Western zinc and Xining Special Steel Co., Ltd Company, Asia silicon (Qinghai) Co., Ltd., Salt Lake Haina, yuntianhuazhong, State Power Investment Group Xi'an solar power generation Co., Ltd., upper Yellow River Hydropower Development Co., Ltd., Qinghai Electronic Materials Industry Development Co., Ltd., Qinghai Yellow River Jianiang Beer Co., Ltd., Qinghai Pharmaceutical Factory Co., Ltd., Qinghai Western Indium Industry Co., Ltd., Qinghai Hongyang Cement Co., Ltd Ltd., Qinghai Jieshen Environmental Energy Industry Co., Ltd., etc. among Monitoring point: flue gas outlet of rotary kiln. Monitoring items: particulate matter, sulfur dioxide, nitrogen oxides, flue gas flow. Monitoring frequency: three samples per production cycle under normal operation condition Contents of daily monitoring: cod, pH, COD, cod
Department of Ecology and Environment of Qinghai Province
The data set records the monitoring report of the key industrial enterprises in Qinghai Province (2015-2020). The data is collected from the Department of ecological environment of Qinghai Province. The data set contains 115 data files, including the supervision monitoring of Qinghai Huadian Datong Power Generation Co., Ltd. in the first quarter of 2015, the supervision monitoring of Qinghai Huadian Datong Power Generation Co., Ltd. in the second quarter of 2015, the supervision monitoring of Qinghai Huadian Datong Power Generation Co., Ltd. in the third quarter of 2015, and the supervision monitoring of Qinghai Huadian Datong Power Generation Co., Ltd. in the fourth quarter of 2015 Supervision monitoring of Huadian Datong Power Generation Co., Ltd. The key polluting enterprises involved are: Qinghai Huadian Datong Power Generation Co., Ltd., Qinghai Products Industry Investment Co., Ltd., Qilian mountain cement, Qinghai ningbei Power Generation Co., Ltd., Qinghai Qiaotou Aluminum Power Co., Ltd., Qinghai new building materials industry and Trade Co., Ltd., Qinghai Products Industry Investment Co., Ltd., Qinghai Yihua Chemical Co., Ltd., and Chalco Qinghai Branch Company, Qinghai cement, Baihe aluminum, Huaneng Xining Thermal Power Co., Ltd., Huanghe Xinye, Jihua Jiangyuan, Qinghai Huanghe Jianiang Beer Co., Ltd., Qinghai Jiangcang Energy Development Co., Ltd., Qinghai ningbei Power Generation Co., Ltd., Qinghai Tianlu Dairy Co., Ltd., Qinghai xiaoxiniu Dairy Co., Ltd., Western zinc and Xining Special Steel Co., Ltd Company, Asia silicon (Qinghai) Co., Ltd., Salt Lake Haina, yuntianhuazhong, State Power Investment Group Xi'an solar power generation Co., Ltd., upper Yellow River Hydropower Development Co., Ltd., Qinghai Electronic Materials Industry Development Co., Ltd., Qinghai Yellow River Jianiang Beer Co., Ltd., Qinghai Pharmaceutical Factory Co., Ltd., Qinghai Western Indium Industry Co., Ltd., Qinghai Hongyang Cement Co., Ltd Ltd., Qinghai Jieshen Environmental Energy Industry Co., Ltd., etc. among Monitoring point: flue gas outlet of rotary kiln. Monitoring items: particulate matter, sulfur dioxide, nitrogen oxides, flue gas flow. Monitoring frequency: three samples per production cycle under normal operation condition Contents of daily monitoring: cod, pH, COD, cod
Department of Ecology and Environment of Qinghai Province
Based on the ecological environmental risk data of the development of agriculture and animal husbandry in 2030, 2050 and 2070 in the Qinghai Tibet Plateau, the risk values of agriculture and animal husbandry in the six typical years of 198519901995200002010 and 2015 are calculated, and the predicted value of ecological environmental risk in 203020502070 is calculated by using the fuzzy weighted Markov chain model. The grid map of meteorological factors extracted from ArcGIS and the future climate model (rcp4.5) was superimposed to obtain the data of agricultural and animal husbandry ecological environment risk in the Tibetan Plateau in 203020502070.
LU Hongwei
The data set of socio-economic vulnerability parameters in the agricultural and pastoral areas of the Qinghai Tibet Plateau mainly contains the socio-economic vulnerability parameter data at county level. The data time range is from 2000 to 2015, involving 112 counties and districts in Qinghai Province and Tibet Autonomous Region. The main parameters include population density, the proportion of unit employees in the total population, the proportion of rural employees in the total population, the proportion of agricultural, forestry, animal husbandry and fishery employees in rural employees, per capita GDP, per capita savings balance of residents, per capita cultivated land area, per capita grain output, and people Average oil production, livestock stock per unit area, per capita meat production, the proportion of primary and secondary school students in the total population, and the number of hospital beds per 10000 people. The entropy weight method is used to calculate the weight of each index, and ArcGIS is used to spatialize, and finally the county scale socio-economic vulnerability parameter data is obtained. The original data is from the statistical yearbook of Qinghai Province and Tibet Autonomous Region. The data are expressed by shape file and excel file. This data set will provide reference for socio-economic vulnerability assessment and selection of typical agricultural and pastoral areas.
ZHAN Jinyan, TENG Yanmin, LIU Shiliang
1) The data include the emission information of various pollutants (CO2, Co, CH4, NOx, SO2, PM2.5, PM10) from Pan third pole solid civil sources. The data are sorted according to China and other pan third polar regions. 2) This data is based on the pan third pole emission inventory of solid civil sources, and the population data of 1km * 1km (2017) provided by landscan is used for grid distribution. 3) The data format is shpfile format, which is grid emission data with high spatial resolution. 4) The data can provide data support for the study of pollutant emission in the pan third polar region.
WANG Shuxiao
This data contains part of the economic indicators of Qinghai province and Tibet Autonomous Region. The data statistics based on provinces can be used to construct the evaluation index system for the coupling coordination relationship between urbanization and eco-environment on the Tibetan Plateau. The data of the Tibet Autonomous Region contains seven indicators, including the gross domestic product (GDP), the primary, secondary and tertiary industries, industry, construction industry, and the per capita GDP, the time span is 1951-2016. The time span of the data set of Qinghai province is from 1952 to 2015, besides the above seven indicators, there is one more indicator of Qinghai province called agriculture forwdtry animal husbandry and fishery. All data are derived from the statistical yearbook, which is calculated at current prices. The gross domestic product (GDP) for 2005-2008 has been revised based on data from the second economic census.
DU Yunyan
1) The data includes the soil erosion modulus of 11 watersheds with a resolution of 5 m in the year of 2017 in Tibet. 2）Based on the surface layer of rainfall erosivity R, soil erodibility K, slope length factor LS, vegetation coverage FVC, and rotation sampling survey unit, the Chinese soil erosion model (CSLE) was used to calculate soil erosin modulus in 11 watersheds respectively. Through spatial data processing (including chart linking and transformation, vector-grid conversion, and resampling), R, K, LS factors were calculated from the regional thematic map of rainfall erosivity, soil erodibility, and DEM. By half-month FVC, NPV, half-month rainfall erosivity data, we calculated the value of B factors in each sampling watershed. The value of E factor was calculated based on the remote sensing interpretation results and engineering measure factor table. The value of tillage factor T was obtained from tillage zoning map and tillage measure table. And then the soil erosion modulus in each sampling watershed was calculated by the equation: A=R•K•LS•B•E•T. The selection of 11 watersheds was based on the layout of sampling survey in pan-third polar region. 3) Compared with the data of soil erosion intensity in the same region in the same year, there is no significant difference and the data quality is good.4) the data of soil erosion modulus is of great significance for studying the present situation of soil erosion in Pan third polar region, and it is also crucial for the implementation of the development policy of the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
1) The data includes the soil erosion modulus of 11 watersheds with a resolution of 30 m in the year of 2017 in Qinhai. 2）Based on the surface layer of rainfall erosivity R, soil erodibility K, slope length factor LS, vegetation coverage FVC, and rotation sampling survey unit, the Chinese soil erosion model (CSLE) was used to calculate soil erosin modulus in 11 watersheds respectively. Through spatial data processing (including chart linking and transformation, vector-grid conversion, and resampling), R, K, LS factors were calculated from the regional thematic map of rainfall erosivity, soil erodibility, and DEM. By half-month FVC, NPV, half-month rainfall erosivity data, we calculated the value of B factors in each sampling watershed. The value of E factor was calculated based on the remote sensing interpretation result and engineering measure factor table. The value of tillage factor T was obtained from tillage zoning map and tillage measure table. And then the soil erosion modulus in each sampling watershed was calculated by the equation: A=R•K•LS•B•E•T. The selection of 11 watersheds was based on the layout of sampling survey in pan-third polar region. 3) Compared with the data of soil erosion intensity in the same region in the same year, there is no significant difference and the data quality is good.4) the data of soil erosion modulus is of great significance for studying the present situation of soil erosion in Pan third polar region, and it is also crucial for the implementation of the development policy of the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
ZHANG Wenbo
1) The data includes the soil erosion modulus of 18 watersheds with a resolution of 5 m in the year of 2017 in Thailand. 2) Based on the surface layer of rainfall erosivity R, soil erodibility K, slope length factor LS, vegetation coverage FVC, and rotation sampling survey unit, the Chinese soil erosion model (CSLE) was used to calculate soil erosin modulus in 18 watersheds of Thailand respectively. Through spatial data processing (including chart linking and transformation, vector-grid conversion, and resampling), R, K, LS factors were calculated from the regional thematic map of rainfall erosivity, soil erodibility, and DEM. By half-month FVC, NPV, half-month rainfall erosivity data, we calculated the value of B factors in each sampling watershed. The value of E factor was calculated based on the remote sensing interpretation result and engineering measure factor table. The value of tillage factor T was obtained from tillage zoning map and tillage measure table. And then the soil erosion modulus in each sampling watershed was calculated by the equation: A=R•K•LS•B•E•T. The selection of 18 watersheds was based on the layout of sampling survey in pan-third polar region. 3) Compared with the data of soil erosion intensity in the same region in the same year, there is no significant difference and the data quality is good.4) the data of soil erosion intensity is of great significance for studying the present situation of soil erosion in Pan third polar region and better implementation of the development policy of the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
YANG Qinke
1) The data is the layout of sample survey units in 65 countries of Pan-Third Polar region and western China. 2)Sample survey units were set in the pan-third pole region (70 °N-10 °S, 180 °E-180 ° W) . No samplings points were selected in the region with latitude >70 °. In the region wiht latitude of 60 ° -70 ° , sample survey units were selected in cells of 0.5 ° latitude ×1 ° Longitude (about 55km×55km-55km×38km). In the area with latitude of 40°-60°, sample survey units were selected in cells of 0.5 ° latitude×0.75 ° longitude (about 55km×63km-55km×42km). In the area with latitude <40°, sample survey units were selected in cells of 0.5 ° latitude × 0.5 ° longitude. In the Qinghai-Tibet Plateau, sample survey units were selected in cells of 0.25 ° latitude × 0.25 ° longitude. Thesample survey units deployed in the first national water conservancy survey for soil and water conservation were used in current project in five provinces including Xinjiang, Qinghai, Gansu, Sichuan and Yunnan in western China. The total number of sample survey units is 29,651, of which, 4052 are in the Qinghai-Tibet Plateau, 8771 in the western China, and 16,828 in countries outside of China. 3) The selected sample survey units is well distributed and the data quality is good.4) the layout map of sample survey units is of great significance for the study of soil erosion in Pan third polar region, and it is also crucial for the implementation of the development policy of the area along the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
WEI Xin
1) The dataset includes the raster data of soil erosion intensity in Pan-Third Pole 65 countries.2) The data of soil erosion intensity are obtained by using the Chinese soil loss equation (CSLE). The formula of soil erosion prediction model includes rainfall erosivity factor, soil erodibility factor, slope length factor, slope factor, vegetation cover and biological measure factor, engineering measure factor and tillage measure factor. Rainfall erodibility factors are calculated from the daily rainfall data by the US Climate Prdiction Center (CPC); soil erodibility factors are calculated by 250 m soil grid data; engineering measure factors are calculated based on vegetation cover, land use and rainfall erosivity ratio; tillage measure factors haven't been considered yet, and the default value is 1; slope length factors and slope factors are obtained by resampling after calculating 30 m elevation data; vegetation coverage and biological measures factors are obtained by combining fractional vegetation cover with land use data and rainfall erodibility proportionometer. The fractional vegetation cover is calculated by MODIS vegetation index products through pixel dichotomy. 3) Compared with the data of soil erosion intensity in the same region in the same year, there is no significant difference and the data quality is good.4) the data of soil erosion intensity is of great significance for studying the present situation of soil erosion in Pan third polar 65 countries and better implementation of the development policy of the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
ZHANG Wenbo
The interaction mechanism project between major road projects and the environment in western mountainous areas belongs to the major research plan of "Environment and Ecological Science in Western China" of the National Natural Science Foundation. The person in charge is Cui Peng researcher of Chengdu Mountain Disaster and Environment Research Institute, Ministry of Water Resources, Chinese Academy of Sciences. The project runs from January 2003 to December 2005. Data collected for this project: Engineering and Environmental Centrifugal Model Test Data (word Document): Consists of six groups of centrifugal model test data, namely: Test 1. Centrifugal Model Test of Soil Cutting High Slope (6 Groups) Test 2. Centrifugal Model Experiment of Backpressure for Slope Cutting and Filling (4 Groups) Test 3. Centrifugal Model Experimental Study on Anti-slide Piles and Pile-slab Walls (10 Groups) Test 4. Centrifugal Model Tests for Different Construction Timing of Slope (5 Groups) Test 5. Migration Effect Centrifugal Model Test (11 Groups) Test 6. Centrifugal Model Test of Water Effect on Temporary Slope (8 Groups) The purpose, theoretical basis, test design, test results and other information of each test are introduced in detail.
CUI Peng
The data set recorded one belt, one road, 2002-2016 years' fertilizer and pesticide consumption data in 65 countries. Fertilizer and pesticide consumption refers to the amount of plant nutrients and pesticides consumed per unit of cultivated land. Fertilizer products include nitrogen, potassium and phosphate (including phosphate rock powder), and traditional nutrients animal and plant fertilizers are not included. Data source: Food and Agriculture Organization, electronic files and web site. Fertilizer and pesticide are the main sources of agricultural chemical pollution, which pose a serious threat to the agricultural ecological environment and the sustainable development of agricultural economy. The data set reflects one belt, one road, along the line of fertilizer and pesticide use, and can provide data support for the research on agricultural ecological environment and other related research. The data set contains two data tables: fertilizer consumption (kg / ha of cultivated land) and pesticide consumption (kg / ha of cultivated land).
XU Xinliang
Geographical distribution of major ecological protection and construction projects on the Tibetan plateau. There are four main projects, i.e. forest protection and construction project, grassland protection and construction project, desertification control project, soil erosion comprehensive control project. Processing method: classified summary, and the county as a unit of the regional distribution.
Da Wei
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