Water quality assessment of deep learning-improved comprehensive pollution index: a case study of Dagu River, Jiaozhou Bay, China

Yang, Haitao; Jia, Chao; Yang, Fan; Yang, Xiao; Wei, Ruchun

doi:10.1007/s11356-023-27174-z

Cited by 10 publications

(1 citation statement)

References 24 publications

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“…The geo-accumulation index is subsequently categorized into seven tiers based on the Igeo values, as delineated in Table 2. The pollution index (PIi) and comprehensive pollution index (IPI N ) of each soil heavy metal are employed to assess the degree of soil contamination [42,43]. The calculation formula is delineated as follows:…”

Section: Geo-accumulation Indexmentioning

confidence: 99%

Characteristics of Soil Heavy Metal Pollution and Health Risks in Chenzhou City

Kuang,

Chen,

Zhu

2024

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The objective of this inquiry is to illuminate the attributes of heavy metal contamination and evaluate the potential ecological hazards inherent in the surface soil of Chenzhou City. A comprehensive analysis was conducted on 600 systematically collected soil samples within the study area, utilizing enrichment factors, geo-accumulation indices, comprehensive pollution indices, potential ecological hazard indices, and health risk assessment models to evaluate the degree of heavy metal contamination in the soil, potential ecological risks, and associated health hazards. The findings reveal that the average enrichment factor (EF) for each heavy metal is below 2, with the hierarchy from highest to lowest being Hg > Cd > Cu > Pb > Ni > Zn > Cr > As. Approximately 78.67% of soil samples exhibit no pollution to weak pollution levels based on heavy metal enrichment factors. Moreover, the comprehensive pollution index (IPIN) indicates that 95.17% of soil samples are within safe and pollution-free levels, indicating an overall environmentally secure setting. However, 2.67% of samples display heightened potential ecological risk levels, primarily concentrated in the southwestern region of the study area, influenced by nearby industrial activities. Additionally, it is noteworthy that both the non-carcinogenic and carcinogenic health hazards emanating from soil heavy metals to adult individuals lie within tolerable thresholds. Among these, arsenic (As), chromium (Cr), and lead (Pb) have been discerned as the principal non-carcinogenic agents. It is of particular significance that only a solitary soil specimen, located in the southwestern quadrant of the investigative region, manifests detectable health perils for children.

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Section: Geo-accumulation Indexmentioning

confidence: 99%

Characteristics of Soil Heavy Metal Pollution and Health Risks in Chenzhou City

Kuang,

Chen,

Zhu

2024

Processes

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Future Climatic Projections and Hydrological Responses with a Data Driven Method: A Regional Climate Model Perspective

Yang,

Sun,

Jia

et al. 2024

Water Resour Manage

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Quantitative Assessment and Validation of Groundwater Pollution Risk in Southwest Karst Area

Liu,

Huan,

et al. 2024

Expo Health

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Groundwater pollution risk assessment is a useful tool for groundwater pollution prevention and control. However, it is difficult to accurately quantify groundwater flow and contaminant fluxes in karst areas and different types of karst areas have different hydrogeological characteristics. Therefore, the assessment of groundwater pollution risk in karst areas must use different assessment indicator systems. This study developed a new methodology that modified the vulnerability assessment model PLEIK, determined pollutant fluxes considering hydrogeological conditions, and revised parameter weights using the random forest method. The resulting PLEIKD-RF model was used to assess the risk of groundwater contamination in the southwestern karst region and its validity was verified. The results showed that the groundwater pollution risk in the region was low, with 65.64% of the low and relatively low risk areas located in the middle and high mountainous regions. 11.81% of the high and relatively high risk areas were sporadically located in the western and central regions, which were mainly controlled by the distribution of the pollution sources and the karst development. The accuracy of the results of groundwater pollution risk assessment in the study area was 71.87% as verified by the horizontal difference method. The results of the sensitivity analysis indicated that accurate, detailed, and representative data on the protective layer, surface water-groundwater interactions, and pollution source loads would improve the accuracy of groundwater pollution risk zoning. This assessment method provided a reference for similar assessments and the results provide a basis for the protection and management of groundwater resources in the region.

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Water quality assessment of deep learning-improved comprehensive pollution index: a case study of Dagu River, Jiaozhou Bay, China

Cited by 10 publications

References 24 publications

Characteristics of Soil Heavy Metal Pollution and Health Risks in Chenzhou City

Characteristics of Soil Heavy Metal Pollution and Health Risks in Chenzhou City

Future Climatic Projections and Hydrological Responses with a Data Driven Method: A Regional Climate Model Perspective

Quantitative Assessment and Validation of Groundwater Pollution Risk in Southwest Karst Area

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