The Grassland Degradation Assessment Dataset in agricultural and pastoral areas of the Qinghai-Tibet Plateau (QTP) is a data set based on the 500m Global Land Degradation Assessment Data (2015), which is evaluated according to the degree of grassland degradation or improvement. In this dataset, the grassland degradation of the QTP was divided into two evaluation systems. At the first level, the grassland degradation assessment was divided into 3 types, including no change type, improvement type and degradation type. At the second level, the grassland degradation assessment on the QTP was divided into 9 types, among which the type with no change was class 1, represented by 0. There were 4 types of improvement: slight improvement (3), relatively significant improvement (6), significant improvement (9) and extremely significant improvement (12). The degradation types can be divided into 4 categories: slight degradation (-3), relatively obvious degradation (-6), obvious degradation (-9) and extremely obvious degradation (-12). This dataset covers all grassland areas on the QTP with a spatial resolution of 500m and a time of 2015. The projection coordinate system is D_Krasovsky_1940_Albers. The data are stored in TIFF format, named “grassdegrad”, and the data volume is 94.76 MB. The data were saved in compressed file format, named “500 m grid data of grassland degradation assessment in agricultural and pastoral areas of the Qinghai-Tibet Plateau in 2015”. The file volume is 2.54 MB. The data can be opened by ArcGIS, QGIS, ENVI, and ERDAS software, which can provide reference for grassland ecosystem management and restoration on the QTP.
LIU Shiliang, SUN Yongxiu, LIU Yixuan
This data set contains data on the concentrations of persistent organic pollutants (POPs) and total suspended particulate (TSP) in the atmosphere at a station in southeastern Tibet (Lulang). The samples were collected using an atmospheric active sampler equipped with a tandem fibreglass membrane-polyurethane foam sampling head. The gaseous POPs and TSPs were collected. The sampling period for each sample was 2 weeks. The types of observed POPs include organochlorine pesticides (OCPs), polychorinated biphenyls (PCBs), and polycyclic aromatic hydrocarbons (PAHs). Only gaseous concentrations were detected for OCPs and PCBs, while both gaseous concentrations and particulate concentrations were detected for PAHs. All of the data contained in the data set are measurement data. The samples were collected in the field at the Integrated Observation and Research Station of the Alpine Environment in Southeast Tibet. The sampler was an atmospheric flow active sampler equipped with a tandem fibreglass membrane-polyurethane foam sampling head, in which the fibreglass membrane was used to collect TSPs and the polyurethane foam was used to adsorb gaseous pollutants in the atmosphere. During the sampling period, the sampler was run every other day for approximately 24 hours each time, and each sample was collected for 2 weeks. The atmospheric volume collected for each sample was 500-700 cubic metres. Both gaseous and particulate POP samples were prepared and analysed in the Key Laboratory of Tibetan Environment Changes and Land Surface Processes, CAS. The sample preparation steps included Soxhlet extraction, silica-alumina column purification, removal of macromolecular impurities by a GPC column, concentration to a defined volume, etc. The analytical test instrument was a gas chromatography/ion trap mass spectrometer (Finnigan-TRACE GC/PolarisQ) produced by Thermo Fisher Scientific. The column used to separate OCPs and PCBs was a CP-Sil 8CB capillary column (50 m × 0.25 mm × 0.25 μm), and the column used to separate PAHs was a DB-5MS capillary column (60 m x 0.25 mm x 0.25 μm). The total suspended particulate concentration in the atmosphere was determined by the gravimetric method, and the accuracy of the weighing balance was 1/100,000 g. The field samples were subjected to strict quality control with laboratory blanks and field blanks. The detection limit of a given compound was 3 times the standard deviation of the concentration of the corresponding compound in the field blank; if the compound was not detected in the field blank, the detection limit of the method was determined by the lowest concentration of the working curve. For a sample, concentrations above the detection limit of the method are corrected by subtracting the detection limit; concentrations below the detection limit of the method but higher than 1/2 times the detection limit are corrected by subtracting half the method detection limit; and concentrations below 1/2 times the detection limit are considered undetected. The recovery rate of PAH laboratory samples was between 65-120%, and that of OCPs was between 70-130%; the sample concentrations were not corrected by the recovery rate. In the table, undetected data are marked as BDL; data marked in black italics are data corrected by subtracting 1/2 the method detection limit.
WANG Xiaoping
The data set recorded the content of hexavalent chromium in Xiejia village downstream of Tianjiazhai Township, Huangzhong County, Qinghai Province from 2005 to 2017. The data is from the official website of the Department of ecological environment of Qinghai Province. The data set contains five Excel data tables, which are: the hexavalent chromium content table of downstream riverside spring of Xiejia village, Tianjiazhai Township, Huangzhong County from 2005 to 2011, the hexavalent chromium content table of downstream riverside spring of Xiejia village, Tianjiazhai Township, Huangzhong County from 2005 to 2014, the hexavalent chromium content table of downstream riverside spring of Xiejia village, Tianjiazhai Township, Huangzhong County from 2005 to 2015, the hexavalent chromium content table of downstream riverside spring of Xiejia village, Tianjiazhai Township, Huangzhong County from 2006 to 2016, and 2 006-2017 hexavalent chromium content table of riverside spring downstream of Xiejia village, Tianjiazhai Township, Huangzhong County. The data table structure is the same. Each data table has two fields: Field 1: year Field 2: content (mg / L)
Department of Ecology and Environment of Qinghai Province
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
The waste gas monitoring data of provincial and municipal wastewater treatment units from 2020 to 2013 were collected. The data is collected from the Department of ecological environment of Qinghai Province, and the data set contains 106 data tables, which are respectively: the results of supervisory monitoring data of waste water, waste gas and sewage treatment plant of provincial controlled enterprises in Haidong city from 2013 to 2020, the results of supervisory monitoring data of waste water, waste gas and sewage treatment plant of municipal controlled enterprises in Haidong city from 2013 to 2020, and the results of supervisory monitoring data of waste water, waste gas and sewage treatment plant of state controlled enterprises in Haidong city from 2013 to 2020 The results of supervisory monitoring data of management plant, and the results of supervisory monitoring data of waste water, waste gas and sewage treatment plant of provincial enterprises in Haidong county from 2013 to 2020. The data table structure is different. 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 Waste gas monitoring data audit table, a total of 16 fields Administrative Region: 1 field Field 2: enterprise name Field 3: industry name Field 4: monitoring point name Executive standard field name: 5 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 Xining sewage treatment plant (2013-2020). The data is collected from the Department of ecological environment of Qinghai Province. The data set contains 39 documents, including the monitoring results of the sewage treatment plant in the second quarter of 2013, the supervision monitoring report of the wastewater from the key pollution sources of Huangyuan sewage treatment plant in the second quarter of 2019, and the audit of the monitoring data of the sewage treatment plant in the second quarter of 2014. 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
This data set records the statistical data of Qinghai Province environmental situation bulletin from 1998 to 2005, which is published by Qinghai Provincial Environmental Protection Bureau, and the bulletin data is compiled from the statistical yearbook of Qinghai Province issued by Qinghai Provincial Bureau of statistics. The data set consists of six files, which are: Bulletin of environmental situation of Qinghai Province, 1998.doc Bulletin of environmental situation of Qinghai Province, 2002.docx Qinghai environmental bulletin 2003.docx Bulletin of environmental situation of Qinghai Province, 2004.docx Bulletin of environmental situation of Qinghai Province 2005.docx Bulletin of environmental situation of Qinghai Province 2006.docx The contents of the communique include "water environment assessment", "proportion of industrial wastewater discharge in various regions", "pollution control measures and actions", "atmospheric environment", "industrial solid waste", "acoustic environment", "radiation environment" and "ecological environment".
Qinghai Provincial Bureau of Statistics
Temperature-humidity index (THI) was adopted to evalulate the climate suitability for the Green Silk Road. The relative humidity isone of the basic parameters to calculate THI. Refering to theTHI model of Tanget al. (2008), the multi-year average of relative humidity is calculted based on the observation data (1981-2017) of weather stations provided by National Meteorological Information Center. The multi-year average values were interpolated into the raster dataset at the resolution of 11km×1km by Kriging method based on GIS software. The climate suitability evaluation results calculated based on this dataset could highlight regional differences.
The data set records the basic situation of environmental sanitation in Xining city of Qinghai Province from 1978 to 2013, and the data is divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 16 data tables with the same structure. For example, there are 12 fields in the data table from 1985 to 1998 Field 1: Category Field 2: Unit Field 3: 1985 Field 4: 1990 Field 5: 1991 Field 6: 1992 Field 7: 1993 Field 8: 1994 Field 9: 1995 Field 10: 1996 Field 11: 1997 Field 12: 1998
Qinghai Provincial Bureau of Statistics
Temperature-humidity index (THI) was adopted to evalulate the climate suitability for the Green Silk Road. Temperature is one of the basic parameters to calculate THI. Refering to theTHI model of Tanget al. (2008), the multi-year average of temperature is calculted based on the observation data (1981-2017) of weather stations provided by National Meteorological Information Center. The multi-year average values were interpolated into the raster dataset at the resolution of 11km×1km by Kriging method based on GIS software. The climate suitability evaluation results calculated based on this dataset could highlight regional differences.
LIN Yumei
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
Taking 2000 as the base year, the future population scenario prediction adopted the Logistic model of population, and it not only can better describe the change pattern of population and biomass but also is widely applied in the economic field. The urbanization rate was predicted 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 applying nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. 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 real 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 industrial structure changing in China and the research area lagged behind the growth of GDP, so it was adjusted according to the need of the future industrial structure scenarios of the research area.
ZHONG Fanglei
According to the method of dendrology, tree cores of Schrenk spruce (Picea schrenkiana) in central (Houxia, Urumqi) and western Tianshan Mountains (kuruning, Yili) were collected. Through the traditional method of dendrology, the sample was processed and dated according prescriptive process. We established the width chronology of Schrenk spruce (Picea schrenkiana) in central and western Tianshan Mountains. As the method of tree ring isotope, four tree cores were selected. After cleaning and air-dried, tree rings were separated five-year increments suing a scalpel under a microscope. Hg concentrations were analyzed in duplicate following the established procedures on a Leeman Hydra IIC Direct Hg Analyzer (Teledyne Leeman Labs, Hudson, NH, USA). The principle of the analytical method is cold vapor atomic absorption spectrometer after thermal decomposition and amalgamation of a gold trap following the US EPA method 7473 (USEPA 1998). The enhanced Hg pollution, especially at low-frequency, was revealed, which was consistent with the changes of global Hg deposition. In central Tianshan Mountains, Hg values showed strong anthropogenic impacts and reflected the local Hg emission loading. Compared to the ice-core Hg records on the Tibet Plateau, our outcomes presented the dramatic increasing trend after the World War Ⅱ. We suggested that tree rings in remote area can be employed to reflect the low-frequency and large-scale Hg deposition and can benefit to accurate the Hg emission inventory in China.
LIU Xiaohong
The data set records the urban living and other pollution in Qinghai Province, and the data are divided by region. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 10 data tables with the same structure. For example, the data table in 2013 has two fields: Field 1: Indicators Field 2: year
Qinghai Provincial Bureau of Statistics
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 monitoring situation of provincial key pollutant discharge units in Huangnan Prefecture of Qinghai Province in 2019. The data set is compiled from the Department of ecological environment of Qinghai Province. The data set contains two PDF files, including the supervision monitoring of provincial key pollutant discharge units in Huangnan Prefecture in the first half of 2019 and the supervision monitoring of provincial key pollutant discharge units in Huangnan Prefecture in the second half of 2019. The monitoring report was commissioned by the environment and Forestry Bureau of Tongren County and implemented by Qinghai Jinyun Environmental Technology Co., Ltd. the monitoring report includes the water temperature, flow rate, pH value, chroma, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, ammonia nitrogen at the inlet and outlet of the sewage treatment plant Total phosphorus, total nitrogen, lead, cadmium, total chromium, mercury, arsenic, suspended solids, hexavalent chromium, petroleum, animal and vegetable oils, anionic surfactants, fecal coliform, alkyl mercury and so on, a total of 64 samples were tested.
Department of Ecology and Environment of Qinghai Province
Based on the calculated ecological environmental risk of agriculture and animal husbandry in 1985, 1990, 1995, 2000, 2010 and 2015 on the Tibetan Plateau, the fuzzy weighted Markov chain model was used to predict the ecological environmental risk without the meteorological factors.The meteorological factors data extracted from future climate model (rcp4.5) was superimposed with ecological environmental risk of agriculture and animal husbandry without the meteorological factors. The resulting risk of agriculture and animal husbandry development in 2030, 2050 and 2070 can provide scientific basis for the future development planning of agricultural and animal husbandry on the Tibetan Plateau.
LU Hongwei
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
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