The GHG emission reduction resilience of the countries along the Belt and Road reflects the level of GHG emission reduction resilience of the countries along the Belt and Road, and the higher the value of the data, the stronger the GHG emission reduction resilience of the countries along the Belt and Road. The Emissions Database for Global Atmospheric Research (EDGAR) for 2000-2020 was used to prepare the GHG resilience data. The product was prepared based on a sensitivity and adaptation analysis, using year-by-year data of total GHG emissions of countries along the Belt and Road from 2000 to 2020, and a comprehensive diagnosis based on year-by-year changes. The GHG emission reduction resilience dataset for countries along the Belt and Road is an important reference for analyzing and comparing the current GHG emission reduction resilience of each country.
XU Xinliang
The CO2 emission reduction resilience per unit GDP of countries along the Belt and Road reflects the level of CO2 emission reduction resilience per unit GDP of the countries along the Belt and Road, and the higher the value of the data, the stronger the CO2 emission reduction resilience per unit GDP of the countries along the Belt and Road. The CO2 emission reduction resilience per unit of GDP was prepared by referring to the Emissions Database for Global Atmospheric Research (EDGAR) for 2000-2020, using the 2000-2020 data for the period 2000-2020. The CO2 emission reduction resilience products per unit GDP of countries along the "Belt and Road" were prepared based on sensitivity and adaptation analyses, taking into account the year-to-year changes, and through comprehensive diagnosis. The CO2 emission reduction resilience per unit GDP of countries along the "Belt and Road" is an important reference for analyzing and comparing the current CO2 emission reduction resilience per unit GDP of each country.
XU Xinliang
The CO2 emission reduction resilience of the countries along the "Belt and Road" reflects the level of CO2 emission reduction resilience of the countries along the Belt and Road, and the higher the value of the data, the stronger the CO2 emission reduction resilience of the countries along the Belt and Road. The Emissions Database for Global Atmospheric Research (EDGAR) was used to prepare data on the total CO2 emissions of the countries along the "Belt and Road" from 2000 to 2020, taking into account the year-on-year changes. Based on the sensitivity and adaptation analysis, a comprehensive diagnosis was made based on the annual data of the total CO2 emissions of the countries along the "Belt and Road" from 2000 to 2020, and a resilience product for CO2 emission reduction was prepared. "The data set of CO2 emission reduction resilience of countries along the Belt and Road is an important reference for the analysis and comparison of the current CO2 emission reduction resilience of countries.
XU Xinliang
The southwest Alpine Canyon Region is one of the biodiversity hot spots in the world. The establishment of bio climate geographic database is the premise to study the distribution pattern and formation causes of biodiversity in this region. Based on the distribution information of more than 7000 species of plants in the region provided by the project team, combined with climate data (from NCEP # reanalysis # products, https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.surface.html , average value from 1950 to 2020), and establish a comprehensive database of biodiversity and ecological environment in southwest Alpine canyon area. Biological data includes names of animal and plant families, genera and species, longitude and latitude information of the collection place, etc., geographic data includes altitude and slope, and climate data includes 24 indicators including rainfall and temperature. This database provides support for studying the distribution law, current situation, formation mechanism and conservation network planning of biodiversity in this region.
HE Hongming , ZHAO Hongfei , HUANG Xianhan
To investigate the paternal genetic structure of Tibetans, 447 male samples were collected from Ngari (n=211), Chamdo (n=119), and Nyingchi (n=117). Firstly, SNP genotyping was performed to allocate samples into haplogroups. To further evaluate the genetic diversity of the major Y-chromosomal haplogroup in Tibetan populations from Lhasa, eight commonly used Y-chromosomal STR (short tandem repeat) loci (DYS19, DYS388, DYS389I, DYS389II, DYS390, DYS391, DYS392, and DYS393) were genotyped using fluorescence-labeled primers with an ABI 3130XL Genetic Analyzer (Applied Biosystems, USA). The results indicated that haplogroup D displayed highest frequency in these three Tibetan populations (Ngari 54.50%, Nyingchi 64.10%, Chamdo 67.23%). Among haplogroup D, D-P47 showed the highest frequency (Ngari 29.39%, Nyingchi 51.28%, Chamdo 55.46%). Differently, D-N1 showed the highest frequency in Ngari (21.33%), followed by Nyingchi (11.97%) and Chamdo (10.92%). Haplogroup O-M117 is the second frequent haplogroup in these three populations, with the highest frequency in Ngari (29.86%), followed by Nyingchi (26.50%) and Chamdo (15.97%). Compared with the other two populations, Ngari Tibetans have higher frequencies of western Eurasian haplogroups, including R-M17 (1.42%), R-M343 (1.42%), and J, probably reflecting more genetic contribution from the west into Ngari. In combination with the data from Lhasa that deposited in 2019 and 2020, our Y chromosome data of Tibetans from different locations on the Tibetan Plateau will be very helpful to understanding the paternal genetic structure of Tibetans. Moreover, the genetic history of Tibetans can also be dissected by phylogeographic and coalescent analyses.
KONG Qingpeng
The temperature humidity index (THI) was proposed by J.E. Oliver in 1973. Its physical meaning is the temperature after humidity correction. It considers the comprehensive impact of temperature and relative humidity on human comfort. It is an important index to measure regional climate comfort. On the basis of referring to the existing classification standards of physiological and climatic evaluation indexes, combined with the natural and geographical characteristics of the Qinghai Tibet Plateau and facing the needs of human settlements suitability evaluation in the Qinghai Tibet Plateau, the temperature and humidity index and its suitability zoning results of the Qinghai Tibet Plateau (more than 3000 meters) are developed (including unsuitable, critical suitable, general suitable, relatively suitable and highly suitable).
LI Peng, LIN Yumei
This vegetation water content data set is derived from the ground synchronous observation in the Luanhe River Basin soil moisture remote sensing experiment, including 55 sampled plots.The vegetation types involved in these sampled plots include grass, corn, potatoes, naked oats and carrots. The data measurement time is from September 13, 2018 to September 26, 2018.
ZHENG Xingming, JIANG Tao
The data set records the monthly report of ambient air quality of national rural air monitoring from May 2011 to February 2013 at Huzhu County observation station in Qinghai Province, and the data is collected from the official website of Qinghai Provincial Department of ecological environment. The dataset contains 7 word documents, 6 txt files and 9 PDF documents. Data contents include: total monitoring days of air quality, air quality status, percentage of air quality in total monitoring days, comparison of air quality with that of last month. Monitoring factors mainly include: SO2, NOx, NO2, no, PM10, data unit: percentage (%), grade (I, II, III, IV, V, etc.)
Department of Ecology and Environment of Qinghai Province
The natural resources dataset of the Qinghai-Tibetan Plateau covers 215 counties in this area. The observation intervals are 5 years from 2000-2015. The indicators are rainfall, temperature, humidity, population, and land area. The data sources are meteorological station data, regional statistical yearbook, etc., which are expressed by Excel. This data provides a reference for understanding the natural background conditions on the county scale in the Qinghai Tibet Plateau.
FENG Xiaoming
The natural resources dataset of the Qinghai-Tibetan Plateau covers 215 counties in this area. The observation intervals are 5 years from 2000-2015. The indicators are rainfall, temperature, humidity, population, and land area. The data sources are meteorological station data, regional statistical yearbook, etc., which are expressed by Excel. This data provides a reference for understanding the natural background conditions on the county scale in the Qinghai Tibet Plateau.
FENG Xiaoming
Coupled Model Intercomparison Project Phase 5 (CMIP5) provides a multiple climate model environment, which can be used to predict the future climate change in the key nodes in the Belts and Road to deal with the environmental and climate problems. Key nodes in the Belt and Road are taken as the study regions of this dataset. The ability of 43 climate models in CMIP5 to predict the future climate change in the study regions was assessed and the optimal models under different scenarios were selected according to the RMSE between the prediction results and real observations. This dataset is composed of the prediciton results of precipitation and near-surface air temperature between 2006 and 2065 using the optimal models in monthly temporal frequncy. The spatial resolution of the dataset has been downscaled to 10 km using statistical downscaling method. Data of each period has three bands, namely maximum near-surface air temperature, minimum near-surface air temperature and precipitation. In this data set, the unit of precipitation is kg / (m ^ 2 * s), and the unit of near-surface air temperature is K. This dataset provides data basis for solving environmental and climate problems of the key nodes in the Belts and Road.
LI Xinyan, LING Feng
Referring to the temperature-humidity index formula proposed by J.E. Oliver in 1973, the temperature-humidity index of thethe Green Silk Road Countries(GSRCs) is calculated based on the annual average temperature and relative humidity. The climate suitability assessment of human settlements of the GSRCs is carried out on the basis of the temperature-humidity index. the climate suitability of human settlements in different areas of GSRCs can be divided into five categories: Non-suitable area,Critically suitable area, Low suitable area, Moderately suitable area and High suitable area, based on the distribution characteristics of temperature-humidity index and its correlation with population distribution, according to the regional characteristics and differences of temperature and relative humidity, and referring to the physiological climate evaluation standard of temperature-humidity index.
LIN Yumei
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.
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 covers 599 meteorological stations in five Central Asian countries, including the following elements: * daily maximum temperature, * daily minimum temperature, * observed temperature, * Precipitation (i.e. rain, melting snow), covering the following dates: 1980-1986; 1996-2005; 2010; 2014; 2015 The data comes from ghcn-d, a data set containing global land area daily observation data, which integrates climate records. The data is a direct measurement of surface temperature, without interpolation or model assumptions, and contains many long-term site records. The disadvantage is uneven space coverage. Due to changes in observation time, site location, and the type of thermometer used, the records contain many heterogeneity. For more information about this dataset, see https://www.ncdc.noaa.gov/ghcnd-data-access
Shule River Basin is one of the three inland river basins in Hexi corridor. In recent years, with the obvious change of climate and the aggravation of human activities, the shortage of water resources and the problem of ecological environment in Shule River Basin have become increasingly prominent. It is of great significance to study the runoff change of Shule River Basin in the future climate situation for making rational water resources planning and ecological environment protection. The Shule River basin boundary is cut from "China's 1:100000 desert sand data set". Taking the 2000 TM image as the data source, it interprets, extracts, revises, and uses remote sensing and geographic information system technology to combine with the 1:100000 scale mapping requirements to carry out thematic mapping of desert, sand and gravel gobi. Data attribute table: Area (area), perimeter (perimeter), ash_ (sequence code), class (desert code), ash_id (desert code). The desert code is as follows: mobile sand 2341010, semi mobile sand 2341020, semi fixed sand 2341030, Gobi 2342000, salt alkali land 2343000. Collect and sort out the basic, meteorological, topographical and geomorphic data of Shule River Basin, and provide data support for the management of Shule River Basin.
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