Assessment and analysis of agricultural non-point source pollution loads in China: 1978-2017.

Hydrogeochemical characterization and quality assessment of groundwater based on integrated-weight water quality index in a concentrated urban area

Exploring the regional differences of ecosystem health and its driving factors in China

As one of the most important ecological functional area in China, the Hengduan Mountain region has experienced dramatic land use/land cover changes (LUCC) over the past 20 years, but the effects of these changes on ecosystem services remain unknown. We revised a proxy-based method to analyze LUCC and ecosystem service value (ESVs) dynamics over three decades, and evaluated the sensitivity of ESVs to LUCC by using an elasticity indicator. Forest land converted to grassland during 1990–2000 was due to deforestation, but a reverse trend was found in 2000–2010 as a result of the implementation of ecological projects. The ESVs of the entire region decreased slightly (0.01% per year) in 1990–2000, and sharply increased (0.14% per year) in 2000–2010. The elasticity reached 0.07 for 1990–2000 and 0.29 for 2000–2010, which were moderate levels for China. For the whole region, forest land is a key land use type and should be maintained. Along the elevation gradient, different developmental strategies should be adopted. Lower areas should focus on the coordinated development of economy and ecology, and higher areas on ecological protection. On the county level, it is necessary to adjust the forest-grassland proportion in each county.

Land use/land cover change and the effects on ecosystem services in the Hengduan Mountain region, China

In this work, we propose a method that is not limited in the identification of the type of pollution source but it also suggests the land covers that emit heavy metals into the surrounding soils by introducing a three-stage procedure, as follows: (a) the Principal Component Analysis/Absolute Principal Component Scores technique is applied to the spatial distribution of soil heavy metal accumulations to identify the type of source that is responsible for soil heavy metal accumulation, (b) based on the spatial distribution of the principal component scores and on four selected driving factors (land cover, distance to mine or smelter, distance to road, and topographic elevation), the Geographical Detector model was used to identify the effect intensity of the driving factors on soil heavy metal accumulation and obtain the landscape type of pollutant sources, and (c) GIS analysis (buffer and overlap analysis) was performed on the principal component scores around the suspected land covers linked to the landscape type of pollutant sources to determine the land covers that, in fact, emit heavy metals into the surrounding soils. Based on the proposed approach, four mining and metallurgy land or land groups were determined to be the actual sources of soil heavy metal pollution in Daye city, Hubei Province, China. Lastly, a Multiple Linear Regression model with decay function was proposed to quantify the contributions of previously identified pollution sources to soil heavy metals accumulation. It was found that the HuangJin mountain quarry, the Tonglu mountain cooper mine (together with some related mineral processing and smelting enterprises), the Lion mountain mining and mineral processing base, and the large Oujia mountain mine are the four sources that contributed 3.2%, 34.3%, 8.3%, and 44% of the total soil heavy metal accumulations in the study area.

Beyond mere pollution source identification: Determination of land covers emitting soil heavy metals by combining PCA/APCS, GeoDetector and GIS analysis

Land use changes and socio-economic development strongly deteriorate river ecosystem health in one of the largest basins in China

Identification of regional water resource stress based on water quantity and quality: a case study in a rapid urbanization region of China.

To control non-point source (NPS) pollution, it is important to estimate NPS pollution exports and identify sources of pollution. Precipitation and terrain have large impacts on the export and transport of NPS pollutants. We established an improved export coefficient model (IECM) to estimate the amount of agricultural and rural NPS total phosphorus (TP) exported from the Luanhe River Basin (LRB) in northern China. The TP concentrations of rivers from 35 selected catchments in the LRB were used to test the model's explanation capacity and accuracy. The simulation results showed that, in 2013, the average TP export was 57.20 t at the catchment scale. The mean TP export intensity in the LRB was 289.40 kg/km2, which was much higher than those of other basins in China. In the LRB topographic regions, the TP export intensity was the highest in the south Yanshan Mountains and was followed by the plain area, the north Yanshan Mountains, and the Bashang Plateau. Among the three pollution categories, the contribution ratios to TP export were, from high to low, the rural population (59.44%), livestock husbandry (22.24%), and land-use types (18.32%). Among all ten pollution sources, the contribution ratios from the rural population (59.44%), pigs (14.40%), and arable land (10.52%) ranked as the top three sources. This study provides information that decision makers and planners can use to develop sustainable measures for the prevention and control of NPS pollution in semi-arid regions.

An improved export coefficient model to estimate non-point source phosphorus pollution risks under complex precipitation and terrain conditions

Traditional models of nutrient simulation usually focus on the pollutant sources and precipitation, lacking the quantification of landscape structure. We developed a new prediction model of pollution risks by combing pollutant sources, precipitation, and landscape structure, which was defined as the source-precipitation-landscape model (SPLM). The SPLM was applied to simulate the non-point source (NPS) total nitrogen (TN) exports in one of the largest river basins in China (the Haihe River Basin, HRB). TN concentrations of 35 sampling catchments in 2013 were used to test the accuracy of the SPLM. Simulated results showed that (1) the SPLM had a relative high accuracy in the simulation of NPS TN export and intensity, especially for TN intensity. (2) The mean TN export and intensity of all the 1578 catchments in the HRB were 441.97 t and 2.08 t/km2, respectively. (3) The TN export intensities differed greatly among the sub-basins in the HRB, ranging from 0.64 to 6.81 t/km2. On the whole, the TN export intensities of the plain sub-basins (e.g., the Tuhaimajia River, the Heilonggang River, and the Beisihe River) were much higher than those of mountainous sub-basins (e.g., the Yongding River, the Beisanhe River, and the Luanhe River). (4) The contributions to TN exports, from high to low, were land use (38.82%), livestock husbandry (33.57%), and rural population (27.61%). Among all the ten pollution sources, arable land (30.87%), rural population (27.61%), and large livestock (17.73%) had the top three contributions to TN exports. This study provides a feasible tool for policymakers and administrators to develop workable management measures for the mitigation of NPS pollution. This SPLM can be extended to other regions in a rapid urbanization context.

Modeling the non-point source pollution risks by combing pollutant sources, precipitation, and landscape structure.

Aquatic environmental deterioration is becoming a serious problem due to rapid urbanization and economic development, particularly in developing countries. As two important components of the aquatic environment, water quality and sediment pollution are widely considered to be concerns; however, they are considered separately in most cases. The relationship between water quality and sediment pollution with heavy metals has been little addressed. In this study, the Haihe River Basin (HRB), one of the most polluted areas in China, was used as a case study, and the eutrophication index (EI) and the potential ecological risk index (RI) were employed to evaluate water quality and sediment pollution of heavy metals, respectively. The results showed that generally in the HRB, the water quality was poor, while the risk of heavy metal pollution was relatively low. Surface water quality was mainly influenced by sewage discharges from human daily life, and heavy metal pollution was affected by industry structure, in that the areas with resource/energy consumption industries and high-pollution industries often have high risks of heavy metal pollution Synergic pollution from water eutrophication and sediment pollution with heavy metals was found, especially in the central areas of the HRB, and it was largely dependent on the type of human activities. In the places with intensive human activities, such as secondary industry, eutrophication occurred simultaneously with heavy metal pollution, other than in less human-affected areas. These findings are useful for planning aquatic environment protections and river ecosystem management.

https://www.mdpi.com/2073-4441/10/1/73/pdf

Xian Cheng

Papers

Land use changes and socio-economic development strongly deteriorate river ecosystem health in one of the largest basins in China

Identification of regional water resource stress based on water quantity and quality: a case study in a rapid urbanization region of China.

An improved export coefficient model to estimate non-point source phosphorus pollution risks under complex precipitation and terrain conditions

Modeling the non-point source pollution risks by combing pollutant sources, precipitation, and landscape structure.

The Synergic Characteristics of Surface Water Pollution and Sediment Pollution with Heavy Metals in the Haihe River Basin, Northern China