Based on the MODIS satellite remote sensing data, the overall vegetation coverage (VC) of the China-Mongolia-Russia Economic Corridor was calculated. The traditional VC formula selects the normalized difference vegetation index (NDVI) as a variable. For the reduction of deviation caused by soil background and the impacts of the atmosphere, the enhanced vegetation index (EVI) instead of NDVI is adopted in the calculation process of VC data set. The original data is the enhanced vegetation index data in the Terra MODIS Vegetation Index Data Version 6 (MOD13A3) with the resolution of 1 km. The MOD13A3 dataset is of higher quality than the source data because it filters the outliers or missing measurements of the MODIS satellite data. The China-Mongolia-Russia Economic Corridor is an area with high risk of desertification. At present, the development of desertification in the corridor extends along the main road between China and Mongolia, and the desertification is the most serious in densely populated urban areas. The regional desertification information can be extracted effectively from the vegetation coverage data, which will provide ecological and environmental data support for the disaster risk prevention and safe operation of transportation and pipelines.
ZHANG Xueqin
The China-Mongolia-Russia Economic Corridor is confronted with security problems related with global warming, mostly including the increasingly serious of degradation of permafrost and land desertification. On one hand, frozen soil degradation has caused frequent disasters such as debris flow, flood, ice and snow damage along the China-Mongolia-Russia transportation and pipeline, which will cause water and soil erosion followed by exposed pipes in frozen soil, in particular in summer. On the other hand, desertification will drive the ecological environment more vulnerable with the compound hazards of soil erosion and sandstorms occurring frequently. Therefore, this dataset will hopefully provide basic climate data for the research on the climate change and its impacts on permafrost and desertification for the China-Mongolia-Russia Economic Corridor. The original data is extracted from ERA5- Land surface climate reanalysis data (ERA5 – Land) (source: https://cds.climate.copernicus.eu). We adopted the inverse distance weight (IDW) method to interpolate the original data with the spatial resolution of 10 km. Based on this dataset, the spatial and temporal distribution pattern of climatic factors are outlined over the past 40 years for the corridor.
ZHANG Xueqin
Main railway lines of China-Mongolia-Russia Economic Corridor: Manzhouli-Chita; Hohhot-Erlian-Ulaanbaatar; Suifenhe-Vladivostok/Khabarovsk; Erlian-Zamen Uud; Dalian-Harbin; Harbin-Manzhouli; Jining-Erlian; Changchun-Huichun; Zamen Udda-Ulaanbaatar-Sukhbaatar; Zabaikalsk-Chita; Novosibirsk-Ulan-Ude; Ulan-Ude-Chaktu-Darhan-Bayan Gol-Ulaanbaatar-Bayantar-Gobi Sumber-Joy Er-Sinshanda-Zamyn-Uud-Erenhot-Jining-Yanggao-Zhangjiakou-Langfang-Tianjin Port; Inner Mongolia-Erenhot-Zamyn-Uud-Joyel-Ulaanbaatar-Dalkhan-A Letan Bragg-Chaktu-Ulan-Ude; Naushki-Ulan-Ude; Changchun-Hunchun; Sino-Russian oil pipeline: The first and second lines of the Sino-Russian crude oil pipeline (Linyuan-Daqing-Lindian-Nehe-Nenjiang-Dayangshu-Uerqi-Jagedaqi-Mohe-Songling-Jingsong-Xinlin-Tahe-Walagan- 22nd Station-Xing'an Town-Skovorodino (Siberia-Pacific Crude Oil Pipeline System) East Siberia-Pacific Pipeline ((Daqing-Taishe 1, 2) Taishet-Skovorodino-Magdagazi-Khabarovsk-Perevoznaya-Kozimino) Sino-Russian crude oil pipeline (Taishet-Lensk-Olyekminsk-Ardan-Tenda-Skovorodino-Mohe-Qiqihar-Daqing) Sino-Russian Far East pipeline (Tashet-Lensk-Olyekminsk-Ardan-Tenda-Khabarovsk-Vladivostok)
BU Xiaoyan
The data set records the monitoring situation of waste water and waste gas pollution of key enterprises under provincial control in Qinghai Province from 2013 to 2015. The monitoring results of waste water of Qinghai Province in the first quarter of 2013 and Qinghai provincial control enterprises in the fourth quarter of 2013 are included in the PDF file 。 Waste gas monitoring data audit table, a total of 16 fields Field 1: Administrative Region Field 2: enterprise name Field 3: industry name Field 4: monitoring point name Field 5: name of executive standard Field 6: monitoring date Field 7: operating load (%) Field 8: flow (m3 / h) Field 9: flue gas temperature (℃) Oxygen content: 10% Field 11: monitoring item name Field 12: measured concentration (mg / m3) Field 13: standard limit (mg / m3) Field 14: emission unit Field 15: is it up to standard Field 16: excess multiple The number of wastewater supervision monitoring, including 16 fields Field 1: Administrative Region Field 2: industry name Field 3: receiving water body Field 4: monitoring point name Field 5: name of executive standard Field 6: name of execution standard condition Field 7: monitoring date Field 8: production load (%) Field 9: monitoring point flow (T / D) Field 10: monitoring item name Field 11: pollutant concentration Field 12: standard limits Field 13: Unit Field 14: is it up to standard Field 15: excess multiple Field 16: enterprise name
Department of Ecology and Environment of Qinghai Province
By applying Supply-demand Balance Analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, on which basis the vulnerability of the water resources system of the basin was evaluated. The IPAT equation was used to set a future water resource demand scenario, setting variables such as future population growth rate, economic growth rate, and unit GDP water consumption to establish the scenario. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were predicted. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydrometeorological Institute, a model of the variation tendency of the basin under climate change was designed. The glacial melting scenario was used as the model input to construct the runoff scenario under climate change. According to the national regulations for the water resources allocation of the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the (grain production) land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources under the climate change, glacial melt and population growth scenarios was analyzed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities for the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.
YANG Linsheng ZHONG Fanglei
By applying Supply-demand Balance Analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, based on which the vulnerability of the water resources system of the basin was evaluated. The IPAT equation was used to set a future water resource demand scenario, which was to establish the scenario by setting variables such as future population growth rate, economic growth rate, and unit GDP water consumption. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were predicted. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydrometeorological Institute, a model of the variation tendency of the basin under climate change was designed. The glacial melting scenario was used as the model input to construct the runoff scenario under climate change. According to the national regulations of the water resources allocation of the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the (grain production) land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources under the climate change, glacial melt and population growth scenarios was analyzed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities for the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.
YANG Linsheng
The data set records the statistical table of groundwater level dynamic changes in various monitoring areas of Qinghai Province from 2015 to 2018. The data are recorded from the Department of natural resources of Qinghai Province, and the data set contains four data tables, which are: the statistical table of groundwater level dynamic change in each monitoring area of Qinghai Province in 2015, the statistical table of groundwater level dynamic change in each monitoring area of Qinghai Province in 2016, the statistical table of groundwater level dynamic change in each monitoring area of Qinghai Province in 2017, and the statistical table of groundwater level dynamic change in each monitoring area of Qinghai Province in 2018 The data table has the same structure and contains 7 fields Field 1: "geographic location" Field 2: "basic balance area (km2)" Field 3: "percentage of monitoring area (%)" Field 4: "weak descent area (km2)" Field 5: "percentage (%) of monitored area" Field 6: "strong uplift area (km2)" Field 7: "percentage (%) of monitored area"
Department of Natural Resources of Qinghai Province
The data set records the monitoring data statistics of Huangnan wastewater treatment plant in Qinghai Province from 2017 to 2018. The data is from the Department of ecological environment of Qinghai Province. The data set contains 11 data tables, which are: the audit table of monitoring data of Huangnan sewage treatment plant in the second quarter of 2017, the audit of monitoring data of Huangnan sewage treatment plant in the third quarter of 2017, the audit of waste water monitoring data of Huangnan state-controlled enterprises in the fourth quarter of 2017, the audit of waste gas monitoring data of Huangnan state-controlled enterprises in the first quarter of 2017, and the audit of Huangnan sewage treatment plant in the first quarter of 2017 Audit of monitoring data of plant management, audit of monitoring data of sewage treatment plant in November 2017, audit of monitoring data of waste water from pollution sources of provincial controlled enterprises in the third quarter of 2017, audit of monitoring data of waste water in the first quarter of 2018, audit of monitoring data of waste gas in the second quarter of 2018, audit of monitoring data of sewage treatment plant in the second quarter of 2018 and audit of monitoring data of waste water in the third quarter of 2018 Water treatment plant monitoring data audit, Huangnan state-controlled enterprise waste gas monitoring data audit in the fourth quarter of 2018, Huangnan sewage treatment plant monitoring data audit in the fourth quarter of 2018. The data table structure is different. Sewage treatment plant monitoring data audit table: a total of 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 Waste gas monitoring data audit table, a total of 16 fields Field 1: Administrative Region Field 2: enterprise name Field 3: industry name Field 4: monitoring point name Field 5: name of executive standard Field 6: monitoring date Field 7: operating load (%) Field 8: flow (m3 / h) Field 9: flue gas temperature (℃) Oxygen content: 10% Field 11: monitoring item name Field 12: measured concentration (mg / m3) Field 13: standard limit (mg / m3) Field 14: emission unit Field 15: is it up to standard Field 16: excess multiple
Department of Ecology and Environment of Qinghai Province
The data set records the supervisory monitoring results of sewage treatment plants in Zeku County, Gangcha County, Haiyan County, Qilian County, Henan County, Jianzha county and Tongren County (2020.1-2020.6). The data is collected from the Department of ecological environment of Qinghai Province. The data set contains seven documents, namely: supervisory monitoring of Gangcha sewage treatment plant in 2020.pdf, In 2020, Haiyan County sewage treatment plant of Haibei Prefecture was monitored.pdf; in 2020, Qilian sewage treatment plant was monitored.pdf; in the first half of 2020, Jianzha county sewage treatment plant was monitored; in the first half of 2020, Tongren County sewage treatment plant was monitored; in the first half of 2020, Zeku County sewage treatment plant was monitored; in the first half of 2020, Henan county sewage treatment plant was monitored The results of supervision monitoring. The data monitoring entrusted units are Zeku County, Gangcha County, Haiyan County, Qilian County, Henan County, Jianzha county and Tongren County Environmental Bureau; Detection point: inlet and outlet of sewage treatment plant Detection items: water temperature, flow rate, pH value, chromaticity, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, lead, cadmium, chromium, sclera, arsenic, suspended solids, hexavalent chromium, petroleum, animal and vegetable oil, anionic surfactant, fecal coliform, alkyl mercury, free chlorine (free residual chlorine), a total of 22 items Detection frequency: 1. Water temperature, pH value and flow rate are sampled in 24h, measured on site, and measured once every 2h (the average value of data is measured); 2. Chemical oxygen demand powder, suspended solids, five-day biochemical oxygen demand, petroleum, animal and vegetable oil, fecal coliform group are sampled by 24h, once every 2h, and all items are collected and packed separately (the average value of data is determined) 3. The other 13 items were sampled every 2 hours and mixed samples were taken for 24 hours
Department of Ecology and Environment of Qinghai Province
The data set records the monthly air quality report of Xining from 2018 to 2020 in Qinghai Province. The dataset contains 146 files, which are: Qinghai environmental protection - Xining air quality monthly report - January 2012, Qinghai environmental protection - Xining air quality monthly report - March 2012, Qinghai environmental protection - Xining air quality monthly report - April 2012, Qinghai environmental protection - Xining air quality monthly report - may 2012, Qinghai environmental protection - Xining air quality monthly report - June 2012, Qinghai environmental protection - Xining air quality monthly report - June 2012 Quality monthly report - July 2012, Qinghai environmental protection - Xining air quality monthly report - August 2012, Qinghai environmental protection - Xining air quality monthly report - September 2012, Qinghai environmental protection - Xining air quality monthly report - October 2012 Qinghai environmental protection - Xining air quality monthly report - June 2020, etc. The data provides the proportion of excellent days and the change of excellent days.
Department of Ecology and Environment of Qinghai Province
The data set records the information disclosure form of surface water quality monitoring in Haixi Prefecture of Qinghai Province from January 2019 to June 2020. The data were collected from the ecological environment bureau of Haixi Prefecture. The data set contains 18 data tables, which are respectively the information disclosure table of surface water quality monitoring in January, February, 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12 of 2019, and the information disclosure table of surface water quality monitoring in January, February, 3, 4, 5 and 6 of 2020. Each data table has 11 fields, such as the information disclosure table of surface water quality monitoring in January 2019 Field 1: serial number Field 2: Region Field 3: water body Field 4: section name Field 5: section level Field 6: monitoring unit Field 7: monitoring frequency Field 8: water quality objectives Field 9: is it up to standard Field 10: over standard factor Field 11: remarks
Ecological Environment Bureau of Haixi Prefecture Qinghai Province
The data set records the ambient air quality of Xining, and the data statistics are from the Department of ecological environment of Qinghai Province. The data set includes one data table, which is the ambient air quality of Xining from 2007 to 2008, and the data table structure is the same. There are three fields in each data table Field 1: level Field 2: days Field 3: proportion of test days The classification of ambient air functional areas, standard classification, pollutant items, average time and concentration limits, monitoring methods, effectiveness provisions of data statistics, implementation and supervision in the data sheet are in line with the relevant provisions of the ambient air quality standard (gb3095-2012).
Department of Ecology and Environment of Qinghai Province
The data set records the monitoring results of Haixi sewage treatment plant in Qinghai Province from 2013 to 2016. The data is collected from the Department of ecological environment of Qinghai Province. The data set includes 8 data tables, 3 PDF files and 5 compressed documents, which are respectively the supervision monitoring results of Haixi sewage treatment plant in Qinghai Province in the second quarter of 2015, the supervision monitoring results of Haixi sewage treatment plant in Qinghai Province in the third quarter of 2015 and the supervision monitoring results of Haixi sewage treatment plant in Qinghai Province in the fourth quarter of 2015 In the fourth quarter of 2016, the supervision monitoring results of Haixi sewage treatment plant in Qinghai Province, the supervision monitoring results of Haixi sewage treatment plant in the first quarter of 2016, the supervision monitoring data of Dulan sewage treatment plant in the second quarter of 2017, the supervision monitoring results of Golmud sewage treatment plant in the second quarter of 2017, and the supervision monitoring results of Wulan sewage treatment plant in the second quarter of 2017 The monitoring results of Haixi sewage treatment plant in Qinghai Province in the fourth quarter of 2013, the second quarter of 2014 and the third quarter of 2014. The data table contains 10 fields: Field 1: Administrative Region Field 2: name of sewage treatment plant Field 3: monitoring date Field 4: name of executive standard Field 5: monitoring items Field 6: outlet concentration (mg / L) Field 7: standard limit (mg / L) Field 8: emission unit Field 9: evaluation conclusion Field 10: excess multiple
Department of Ecology and Environment of Qinghai Province
The data set records the monitoring status of centralized drinking water quality in Haixi Prefecture of Qinghai Province from January 2019 to June 2020. The data were collected from the ecological environment bureau of Haixi Prefecture. The data set includes six data tables, which are: information disclosure data of centralized drinking water quality monitoring in Haixi Prefecture in the first quarter of 2019, information disclosure data of centralized drinking water quality monitoring in Haixi Prefecture in the second quarter of 2019, information disclosure data of centralized drinking water quality monitoring in Haixi Prefecture in the third quarter of 2019, and information disclosure data of centralized drinking water quality monitoring in Haixi Prefecture in the second quarter of 2019 The structure of information disclosure data and data table is the same for the fourth quarter of 2020, the first quarter of 2020 and the second quarter of 2020. Each data table has a total of 11 fields, such as the information disclosure table of prefecture level centralized drinking water quality monitoring in the second quarter of 2020 in Haixi prefecture (only 6 fields are listed) Field 1: serial number Field 2: name of water source Field 3: water level Field 4: water source type Field 5: water quality category requirements Field 6: testing unit Field 7: monitoring items Field 8: monitoring frequency Field 9: exceedance factor Field 10: is it up to standard Field 11: remarks
Ecological Environment Bureau of Haixi Prefecture Qinghai Province
This data set records the statistical bulletin of national economic and social development of Haidong city in Qinghai Province in 2019. The data is collected from the Statistics Bureau of Qinghai Province. The data set contains a word file, which is the statistical bulletin of national economic and social development of Haidong in Qinghai Province in 2019. The Gazette covers the annual gross domestic product of the whole city, the completion of the regional public budget revenue, the household registration population and its changes throughout the year, the annual total consumption price index of the whole city, the planting and animal husbandry, the industrial and construction industries, the annual fixed assets investment of the whole City, the total retail sales of social consumer goods, and the total value of the total import and export of the whole city in the whole year. Information statistics and comparative data on the added value of wholesale and retail industry, cultural tourism, health and sports, residents' income, consumption and social security, environment and emergency management, etc.
Qinghai Provincial Bureau of Statistics
The data set records the monthly air quality report of Yushu prefecture (2017.7-2019.12). The data is collected from Yushu Ecological Environment Bureau, and the data set contains six files, which are: monitoring data report form of Yushu environmental monitoring station from January to December in 2019, monthly air quality report of Yushu, monthly air quality report of Yushu (July 2017), monthly air quality report of Yushu (August 2017), monthly air quality report of Yushu (September 2017) Yushu Monthly air quality report (October 2017). The data table contains 10 fields: Field 1: City Field 2: site name Field 3: time Field 4: sulfur dioxide μ g / m3 Field 5: PM10 μ g / m3 Field 6: nitrogen dioxide μ g / m3 Field 7: NOx μ g / m3 Field 8: PM2.5 μ g / m3 Field 9: carbon monoxide mg / m3 Field 10: ozone 8h μ g / m3
Ecological Environment Bureau of Yushu Prefecture
The monitoring data set of surface water quality in Xining city of Qinghai Province was collected from July, 2015 to July, 2015. The data is collected from the Department of ecological environment of Qinghai Province. The data set contains 15 data tables, which are: surface water quality of Xining City in July 2015, surface water quality of Xining City in November 2015, surface water quality of Xining City in January 2016, and surface water quality of Xining City in February 2016. The data table structure is the same. There are six fields in each data table, such as the monitoring section water quality table of Xining surface water in July 2015 Field 1: serial number Field 2: section name Field 3: executive standard level Field 4: actual water quality grade Field 5: over standard items
Department of Ecology and Environment of Qinghai Province
The data set records the typical geological disasters in Qinghai Province from 1999 to 2017. The data are collected from the Department of ecological environment of Qinghai Province, and the data set includes seven tables: the content of hexavalent chromium in spring 1 of Xinghuo village, Haiyan County, 1999-2011, the content of hexavalent chromium in spring 1 of Xinghuo village, Haiyan County, Qinghai Province, 1999-2012, the content of hexavalent chromium in spring 1 of Xinghuo village, Haiyan County, Qinghai Province, 2002-2013, the content of hexavalent chromium in spring 1 of Xinghuo village, Haiyan County, Qinghai Province, 2002-2014, and 2006-2015 The structure of the data sheet is the same as the table of hexavalent chromium content in spring 1, Xinghuo village, Haiyan County, Qinghai Province in 2006-2016, and the table of hexavalent chromium content in spring 1, Xinghuo village, Haiyan County, Qinghai Province in 2006-2017. Each data table has two fields, Field 1: year Field 2: content
Department of Ecology and Environment of Qinghai Province
The data set records the comparison of direct economic losses caused by geological disasters in Qinghai Province from 2011 to 2018. The data is collected from the Department of ecological environment of Qinghai Province, and the data set contains 8 data tables, which are: direct economic losses caused by sudden geological disasters in 2011, direct economic losses caused by sudden geological disasters in 2012, comparison chart of direct economic losses caused by sudden geological disasters in 2013 and comparison chart of direct economic losses caused by geological disasters in 2014 The statistical table of direct economic losses caused by sudden geological disasters in Qinghai Province in 2015, the statistical table of direct economic losses caused by sudden geological disasters in Qinghai Province in 2016, the comparison of direct economic losses caused by sudden geological disasters in Qinghai Province in 2017, and the comparison chart of direct economic losses caused by sudden geological disasters in Qinghai Province in 2018 have the same data table structure. Each data table has two fields, such as the comparison chart of direct economic losses caused by sudden geological disasters in Qinghai Province in 2013 Field 1: disaster type Field 2: direct economic loss
Department of Ecology and Environment of Qinghai Province
The data set records the information disclosure data (2018) of centralized drinking water quality monitoring and safety status in cities and towns at or above the county level in Xining city. The data statistics are from the Department of ecological environment of Qinghai Province, and the data set contains three documents, which are respectively: information disclosure form of centralized drinking water quality monitoring and safety status in cities and towns at or above the county level of Xining City in the first quarter of 2018, information disclosure form of centralized drinking water quality monitoring and safety status in cities and towns at or above the county level of Xining City in the second quarter of 2018, information disclosure form of centralized drinking water quality monitoring and safety status in cities and towns at or above the county level of Xining City in the second quarter of 2018 In the second half of 2018, the structure of the data sheet is the same. There are 10 fields in each data table Field 1: serial number Field 2: name of water source Field 3: water level Field 4: water source type Field 5: monitoring unit Field 6: number of monitoring indicators Field 7: monitoring frequency Field 8: evaluation criteria Field 9: pass rate Field 10: public period
Department of Ecology and Environment of Qinghai Province
