During the last decade numerous monitoring programs have been conducted in order to assess pesticide pollution in catchments. This effort has led to the production of large, complex data sets of environmental results making the task of evaluation of the aquatic chemical status more difficult. Furthermore, the evaluation of the chemical status of the water ecosystems is one of the main aspects which should be considered in a River Basin Management Plan. In this study, two indices were developed in order to assess the combined pesticide ecotoxicity to aquatic non-target organisms, the Aquatic Quality Index of Short term Toxicity of Pesticides (AQI ShToxP) and the Aquatic Quality Index of Long term Toxicity of Pesticides (AQI LToxP). These indices were applied to the environmental results obtained from an intensive monitoring study of 302 pesticides in 102 stationary sampling stations located on the surface aquatic network of the Pinios River Basin, in Greece, in 2011 and 2012. The evaluation of the surface water quality was achieved by taking into consideration the frequency and the intensity of exposure of the aquatic organisms to pesticides above the respective ecotoxicological quality objectives such as the acute or chronic term predicted no-effect concentrations derived from risk assessment. Seventy-five pesticides, that have been previously identified as the River Basin Specific Pollutants of Pinios by an environmental and human risk hierarchy exercise, were assessed. It appears, from the implementation of the two indices, that the detected pesticides in the surface aquatic ecosystem of the Pinios River Basin exert significant pressure on the aquatic non-target organisms especially at the chronic effect level. The developed AQI ShToxP and AQI LToxP indices, as well as the proposed quality classification system could be valuable communication and interpretation tools for River Basin Management Plans that can contribute in the restoration of environmental health.
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http://dx.doi.org/10.1016/j.scitotenv.2018.08.240 | DOI Listing |
Mitochondrial DNA B Resour
December 2024
Ningxia Technical College of Wine and Desertification Prevention, Yinchuan, Ningxia, China.
var. (2010), is a new variety of in Solanaceae. Here, we sequenced, assembled, and annotated the complete chloroplast (cp) genome of var.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
Department of Geography, University of Gour Banga, Malda, West Bengal, 732103, India.
This study assesses land degradation vulnerability in the Jainti River basin, Jharkhand, Eastern India, incorporating environmental, socio-economic, and soil health parameters. Using the fuzzy-analytical hierarchical process (AHP), fuzzy transformations and membership functions were applied to target land degradation. AHP determined the relative weight of each parameter based on parameter's relevance to land degradation.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Buildings and Construction Techniques Engineering, College of Engineering, Al-Mustaqbal University, Hillah, Babylon, 51001, Iraq.
The land use transition plays an important role for terrestrial environmental services, which had a mixed impact of positive and negative on the groundwater and terrestrial water resource. The health of ecological systems and groundwater depends on the mapping and management of land use. The Ganga basin is one of the most densely populated and agriculture-intensive river systems in the South Asia and the world.
View Article and Find Full Text PDFSci Rep
January 2025
State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, 830011, China.
Litterfall load is crucial in maintaining ecosystem health, controlling wildfires, and estimating carbon stock in arid regions. However, there is a lack of spatiotemporal analysis of litterfall in arid riparian forests. This study aims to estimate Litterfall load using a BP neural network based on vegetation indices from Landsat 5 and 8 satellite images, litterfall inventory data, slope, and distance to major river tributaries.
View Article and Find Full Text PDFZhongguo Yi Xue Ke Xue Yuan Xue Bao
December 2024
Institute of Basic Medical Sciences,Chinese Academy of Medical Sciences,Department of Epidemiology and Biostatistics, School of Basic Medicine, Peking Union Medical College,Beijing 100005,China.
Objective To reveal the spatial distribution patterns of key pollutants in the Huaihe River Basin and quantify the risks and burdens of non-gastrointestinal cancers by the grade of pollution,providing targets and data support for enhanced management of water pollution in the Huaihe River Basin. Methods Surface water quality data of the Huaihe River Basin were obtained from the National Surface Water Environmental Quality Monitoring Network(2021).Incidence data of seven cancers were extracted from the 2019 Annual Report of the China Cancer Registry.
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