Current Browsing: 2012-2014


Dataset of Gansu urban air quality daily (2012-2014)

This data is from the central station of environmental monitoring in gansu province. The data includes three observation elements, namely sulfur dioxide, nitrogen dioxide and inhalable particles, which are published on the network. The data format is a text file. The first column is the city name, the second column is sulfur dioxide, the third column is nitrogen dioxide, the fourth column is pm10, and the fifth column is the observation date. The data included lanzhou, jiayuguan, jinchang, baiyin, tianshui, qingyang, pingliang, dingxi, longnan, wuwei, zhangye, jiuquan and linxia. This data will be updated automatically and continuously according to the data source.

2020-06-08

Monitoring dataset of Gansu water quality automatic station (2012-2014)

This data is from the central station of environmental monitoring in gansu province. The data includes three observation elements that are disclosed on the network, namely PH, permanganate index and ammonia nitrogen. The data format is a text file. The first column is the city name, the second column is PH, the third column is permanganate index, the fourth column is ammonia nitrogen, and the fifth column is the observation date. The data include 6 sections of gushuizi, niubei village, wufo temple, shichuan bridge, xincheng bridge and bikou. Gansu section of the Yellow River: xincheng bridge (lanzhou upstream section), shichuan bridge (lanzhou - baiyin junction section), wufo temple (gansu-ningxia junction section), niubei village (gansu-shaanxi junction section).Bailong river wudu section :(section of gushuizi village). Lanzhou city bridge automatic water quality monitoring station is located in xigu district, lanzhou city, gansu province.Point coordinates 103 degrees 35 minutes 02 seconds east longitude, 36 degrees 07 minutes 20 seconds north latitude.Yellow River system (Yellow River main stream), state - controlled provincial boundary section.By lanzhou city environmental monitoring station custody.It's 35 kilometers away.Built in March 2001. PH: the index that characterizes the acidity and alkalinity of water. When the pH value is 7, it is neutral, less than 7 is acidic, and greater than 7 is alkaline.The pH value of natural surface water is generally between 6 and 9. When algae grow in the water, they absorb carbon dioxide due to photosynthesis, resulting in an increase in surface pH value. Permanganate index (CODMn) : the amount consumed when treating surface water samples with potassium permanganate as the oxidant, expressed as mg/L of oxygen.Under these conditions, reductive inorganic substances (ferrous salts, sulphides, etc.) and organic pollutants in water can consume potassium permanganate, which is often used as a comprehensive indicator of the degree of surface water pollution by organic pollutants.Also known as the chemical oxygen demand potassium permanganate method, as distinct from the chemical oxygen demand (COD) of the potassium dichromate method, which is often used to monitor wastewater discharge. Ammonia nitrogen (nh3-n) : ammonia nitrogen exists in water in the form of dissolved ammonia (also known as free ammonia, NH3) and ammonium salt (NH4+). The ratio of the two depends on the pH value and water temperature of the water, and the content of ammonia nitrogen is expressed by the amount of N element.The main sources of ammonia nitrogen in the water are domestic sewage and some industrial wastewater (such as coking and ammonia synthesis industry) and surface runoff (mainly refers to the fertilizer used in farmland entering rivers, lakes, etc.). This data will be updated automatically and continuously according to the data source.

2020-04-01

Digital soil mapping dataset of soil texture (soil particle-size fractions)in the Tianlaochi basin (2012-2014)

Select the soil mechanical composition data with a depth of 0-20cm on the surface of the soil, select the optimal spatial prediction mapping method for soil composition data, and make the spatial distribution data product of soil texture (particle size composition). The classification standard of soil particle size is American classification. The source data of this data set are from the data center of cold and drought regions, soil physical properties-soil bulk density and mechanical composition data set soil sampling profile data of Tianlaochi watershed in Qilian mountain.

2020-03-28

Digital soil mapping dataset of soil bulk density in the Heihe river basin (2012-2014)

The source data of this data set comes from the soil profile data integrated by the major research plan integration project of Heihe River Basin (soil data integration and soil information product generation of Heihe River Basin, 91325301). Scope: Heihe River Basin; Projection: WGS · 1984 · Albers; Spatial resolution: 100M; Data format: TIFF;

2020-03-27

Digital soil mapping dataset of soil pH in the Heihe river basin (2012-2014)

Using digital soil mapping method to produce soil surface pH spatial distribution data products. The source data of this data set comes from the soil profile data integrated by the major research plan integration project of Heihe River Basin (soil data integration and soil information product generation of Heihe River Basin, 91325301).

2020-03-27

Digital soil mapping dataset of soil depth in the Heihe River Basin (2012-2014)

The data of this data set comes from the soil profile data integrated by the major research plan integration project of Heihe River Basin (soil data integration and soil information product generation of Heihe River Basin, 91325301). The prediction method is mainly based on the soil landscape model. The basic theory of the model is the classic soil genesis theory. The model regards the soil as the product of the comprehensive effects of climate, topography, parent material, biology and time. Scope: Heihe River Basin; Projection: Albers ﹣ conic ﹣ equal ﹣ area; Spatial resolution: 90m; Data format: ArcGIS grid; Data content: spatial distribution of soil thickness Prediction method: enhanced regression tree Environmental variables: main soil forming factors

2020-03-27

Digital soil mapping dataset of soil texture in the Heihe river basin (2012-2014)

The American system classification is used as the standard of soil particle classification. The source data of this data set comes from the soil profile data integrated by the major research plan integration project of Heihe River Basin (soil data integration and soil information product generation of Heihe River Basin, 91325301). The prediction method is mainly based on the soil landscape model. The basic theory of the model is the classic soil genesis theory. The model regards the soil as the product of the comprehensive effects of climate, topography, parent material, biology and time. Scope: Heihe River Basin; Projection: WGS · 1984 · Albers; Spatial resolution: 100M; Data format: TIFF; Data content: spatial distribution of soil clay, silt and sand content Prediction method: enhanced regression tree Environmental variables: main soil forming factors

2020-03-27