This data set includes the concentration and distribution data of main persistent organic pollutants in environmental media of Qilian Mountains. Samples were collected from the Qilian Mountains and its surrounding areas in May 2018. The samples were prepared by Soxhlet extraction purification concentration and determined by gas chromatography ion trap mass spectrometry. The target compounds include organochlorine pesticides, polychlorinated biphenyls, polycyclic aromatic hydrocarbons, etc. Mirex and pcb-30 were added as recovery markers during sample pretreatment. PCNB and PCB-209 are the internal standards for sample testing. The recoveries of the samples are generally between 60% and 101%.
GONG Ping, WANG Xiaoping
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
This data set records the bulletin of environmental status of Qinghai Province from 1998 to 2019. The data set contains 22 files, which are: Qinghai Province environmental situation bulletin in 1998, Qinghai Province environmental situation bulletin in 1999 Qinghai Province environmental situation communique in 2019, etc. The contents of the communique include water quality monitoring of 61 sections in the main stream of the Yangtze River, the main stream of the Yellow River, the main stream of the Lancang River, the main stream of the Heihe River, the Qinghai Lake Basin, the Huangshui River Basin and the Qaidam inland river basin, the proportion of days for reaching the standard of ambient air quality in the whole province, the year-on-year comparison of ambient air monitoring factors in cities (towns), the overall situation of acoustic environment quality and ecological environment quality in urban areas, as well as relevant guarantee measures And supporting measures.
Department of Ecology and Environment of Qinghai Province
Based on the vulnerability assessment framework of "exposure sensitivity adaptability", the vulnerability assessment index system of agricultural and pastoral areas in Qinghai Tibet Plateau was constructed. The index system data includes meteorological data, soil data, vegetation data, terrain data and socio-economic data, with a total of 12 data indicators, mainly from the national Qinghai Tibet Plateau scientific data center and the resource and environmental science data center of the Chinese Academy of Sciences. Based on the questionnaire survey of six experts in related fields, the weight of the indicators is determined by using the analytic hierarchy process (AHP). Finally, four 1km grid data are formed involving ecological exposure, sensitivity, adaptability and ecological vulnerability in the agricultural and pastoral areas of the Qinghai Tibet Plateau. The data can provide a reference for the identification of ecological vulnerable areas in the Qinghai Tibet Plateau.
ZHAN Jinyan, TENG Yanmin, LIU Shiliang
This data set records the statistical data of environmental pollution control in Qinghai Province from 1990 to 2013, which is divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 13 tables Environmental pollution control of enterprises and institutions in Main Years 1990-2004.xls Environmental pollution control of enterprises and institutions in Main Years 1990-2005.xls Environmental pollution control 2003.xls Environmental pollution control, 2004.xls Environmental pollution control 2006.xls Investment in environmental pollution control 2005-2006.xls Investment in environmental pollution control 2005-2007.xls Investment in environmental pollution control 2005-2008.xls Investment in environmental pollution control 2006-2009.xls Investment in environmental pollution control 2007-2010.xls Environmental pollution control investment 2008-2011.xls Investment in environmental pollution control, 2008-2012.xls Environmental pollution control investment 2010-2013.xls The data table structure is the same. For example, there are two fields in the data table of environmental pollution control in 2003 Field 1: Indicators Field 2: 2003
Qinghai Provincial Bureau of Statistics
By archaeological investigation and excavation in Tibetan Plateau, we discovered 8 Paleolithic sites, including 151, Jiangxigou 1, Jiangxigou 2, Heimahe 1, Xiadawu, Yezere, Niamudi and Lingjiong. In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified animal remains, plant macrofossil, selected some samples for radiocarbon dating and stable carbon and nitrogen isotopes. This dataset provide important basic data for understanding when and how prehistoric human lived in the Tibetan Plateau during the Paleolithic.
ZHANG Dongju , ZHANG Xiaoling, LIU Xiangjun
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
This data set records some monitoring data of guide sewage treatment plant in Hainan Province from 2013 to 2018. The data is collected from the Department of ecological environment of Qinghai Province. The data set contains six data files, which are: the monitoring results of guide sewage treatment plant in Hainan prefecture of Qinghai Province in the fourth quarter of 2014, the monitoring data audit of guide sewage treatment plant in Hainan prefecture of Qinghai Province in the fourth quarter of 2015, the monitoring data audit of guide sewage treatment plant in Hainan prefecture of Qinghai Province in the first quarter of 2016, and the monitoring data audit of guide sewage treatment plant in Hainan prefecture of Qinghai Province in the first quarter of 2016 Sewage treatment plant in the first half of 2019, guide county sewage treatment plant in Hainan Province in the second half of 2019, guide county sewage treatment plant in Hainan Province in 2013. The monitoring result table of sewage treatment plant contains 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 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
1) Data content: species list and distribution data of Phrynocephalus and Eremais in Tarim Basin, including class, order, family, genus, species, and detailed distribution information including country, province, city and county; 2) Data source and processing method: Based on the field survey of amphibians and reptiles in Tarim Basin from 2008 to 2020, and recording the species composition and distribution range of Phrynocephalus and Eremias in this area; 3) Data quality description: the investigation, collection and identification of samples are all conducted by professionals, and the collection of samples information are checked to ensure the quality of distribution data; 4) Data application results and prospects: Through comprehensive analysis of the dataset, the list of species diversity and distribution can provide important data for biodiversity cataloguing in arid central Asia, and provide scientific basis for assessing biodiversity pattern and formulating conservation strategies.
GUO Xianguang
This dataset includes the concentrations and spatial pattern of mercury (Hg) in the foliage of the local tree species over the easteran and the southern Tibetan Plateau. Fifty-three leaf samples were collected, and cold vapor atomic fluorescence spectrophotometry (CVAFS) was used to analyse the Hg contents. The limit of detection (LOD) for this method is 1.8 ng/g. The standard reference material, foliage GB GSW-11, which is supplied by National Institute of Metrology P.R.China, was also analyzed for assessing the accuracy of this method, and the recoveries of this method were 94.6%±9.7%. This dataset will provide the informations of foliage absoprtion to Hg over the Tibetan Plateau.
WANG Xiaoping
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 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
The data set records the monitoring data of waste gas from state-controlled enterprises and thermal power enterprises in Xining city of Qinghai Province from 2013 to 2017. The data set includes 11 data tables and 3 PDF data files, which are respectively: monitoring results of Qinghai provincial waste gas control enterprises in the first quarter of 2013, supervisory monitoring data of Qinghai Huadian Datong Power Generation Co., Ltd. in the second half of 2017, pollution source monitoring data of Qinghai Huadian Datong Power Generation Co., Ltd. in the first quarter of 2017, waste gas monitoring data audit of thermal power plants in the fourth quarter of 2013, and fourth quarter of 2014 Waste gas monitoring data audit of thermal power plant. There are 16 fields in the waste gas monitoring data audit table 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 ecological data of Zhangye City from 2001 to 2012 include: the reuse rate of industrial water, the comprehensive utilization rate of industrial solid, the ratio of environmental protection investment to GDP, the per capita water consumption, the share of ecological water, the use intensity of chemical fertilizer, the use intensity of pesticide, the use intensity of agricultural plastic film, and the energy consumption per unit GDP
ZHANG Dawei
Taking 2005 as the base year, the future population scenario was predicted by adopting the Logistic model of population. It not only can better describe the change pattern of population and biomass but is also widely applied in the economic field. The urbanization rate was predicted by using the urbanization Logistic model. Based on the existing urbanization horizontal sequence value, the prediction model was established by acquiring the parameters in the parametric equation by nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. The data adopted the non-agricultural population. The Logistic model was used to predict the future gross national product of each county (or city), and then, according to the economic development level of each county (or city) in each period (in terms of GDP per capita),the corresponding industrial structure scenarios in each period were set, and the output value of each industry was predicted. The trend of changes in industrial structure in China and the research area lagged behind the growth of GDP and was therefore adjusted according to the need of the future industrial structure scenarios of the research area.
ZHONG Fanglei
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 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 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
The data set records the monitoring results of Huangnan medical waste disposal center in the first half of 2020. The data is collected from the Department of ecological environment of Qinghai Province. The data set contains a PDF file: the monitoring results of Huangnan medical waste disposal center in the first half of 2020. The monitoring was entrusted by Huangnan environmental monitoring station and implemented by Qinghai Hongjing Environmental Protection Industry Development Co., Ltd. The test items include: (1) Wastewater: water temperature, pH value, ammonia nitrogen, total chlorine (total residual chlorine), chemical oxygen demand, five-day biochemical oxygen demand, suspended solids, fecal coliform group, a total of 8 items. (2) Organized waste gas: ammonia, hydrogen sulfide, odor concentration, non methane hydrocarbon, a total of 4. (3) Monitoring frequency: wastewater: 1 day, once a day. Organized waste gas: 1 day, 3 times a day.
Department of Ecology and Environment of Qinghai Province
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