Water quality characteristics, sources, and assessment of surface water in an industrial mining city, southwest of China

Fan, Chuanjie; Liu, Yongbing; Liu, Chenghai; Zhao, Wenbo; Hao, Naixuan; Guo, Wei; Yuan, Jihai; Zhao, Jiujiang

doi:10.1007/s10661-022-09908-7

Cited by 15 publications

(6 citation statements)

References 39 publications

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“…Anthropogenic activities that may also affect water quality are associated with the mining industry. Worldwide, anthropogenic sources such as exploited iron ore and other mineral deposits and environmental liabilities such as mine tailings generate acid mine drainage and/or acid rock drainage (Abarca et al, 2017 ; Alexakis et al, 2021 ; Carrillo-González et al, 2022 ; Fan et al, 2022 ; Guerra et al, 2016 ). Although most of the Chilean mining activities are concentrated to the west, outside of the AP (Tapia et al, 2021 ), there are some copper mining operations in the area that exploit sulfide minerals (for example, in the 021 basin, Fig.…”

Section: Resultsmentioning

confidence: 99%

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Evaluation of surface water quality in basins of the Chilean Altiplano-Puna and implications for water treatment and monitoring

Lizama-Allende

Rámila²,

Leiva

et al. 2022

Environ Monit Assess

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Water quality characterization and assessment are key to protecting human health and ecosystems, especially in arid areas such as northern Chile, where water resources are scarce and rich in pollutants. The objective of this study was to review and assess available official water quality data in the Chilean Altiplano-Puna basins for a 10-year period (2008–2018), including water treatment systems. Within the 43,600 km 2 of Chilean Altiplano-Puna territory, only 16 official water quality monitoring stations had up-to-date data, and the sampling frequency was less than 3 per year. Most of the water samples collected at the evaluated stations exceeded the drinking and irrigation water Chilean standards for arsenic, boron, and electrical conductivity. Moreover, the characteristics of the Altiplano-Puna affect water quality inside and beyond the area, limiting water usage throughout the Altiplano-Puna basins. Drinking water treatment plants exist in urban and rural settlements; however, the drinking water supply in rural locations is limited due to the lack of adequate treatment and continuity of service. Wastewater treatment plants operate in some urban locations but rarely exist in rural locations. Limited data impede the proper assessment of water quality and thus the evaluation of the need for treatment systems. As such, the implementation of public policies that prioritize water with appropriate quantity and quality for local communities and ecosystems is imperative. Supplementary Information The online version contains supplementary material available at 10.1007/s10661-022-10628-1.

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Section: Resultsmentioning

confidence: 99%

“…Mining activities significantly pollute rivers (Fan et al, 2022 ; Kumkrong et al, 2022 ). This is the case for the Río Lluta basin.…”

Section: Resultsmentioning

confidence: 99%

Evaluation of surface water quality in basins of the Chilean Altiplano-Puna and implications for water treatment and monitoring

Lizama-Allende

Rámila²,

Leiva

et al. 2022

Environ Monit Assess

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“…The method is simple and can help determine main pollutants and the relationship between the water quality status and assessment standards 33 , 34 . The calculation of the single factor index method can be expressed as 35 : where SI is the single-factor pollution index of the pollutants; C i is actual concentration of pollutants i; S i is the evaluation standard value of pollutant i; and (SI i )max is the maximum classification for the pollutant parameters (the most polluted parameter).…”

Section: Methodsmentioning

confidence: 99%

Impact on urban river water quality and pollution control of water environmental management projects based on SMS-Mike21 coupled simulation

Wei,

Rao,

Liu

et al. 2024

Sci Rep

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To explore the impact of expanding Nanyang Sewage Purification Center (NSPC) on the main sewage discharge area of Bai River, we constructed a 2D hydrodynamic-water quality model based on surface water modeling system (SMS) and Mike21. Simulating three sewage discharge conditions in wet, normal, and dry season, we evaluated three indicators (COD, NH3-N, and BOD5) by the single-factor pollution index and provided recommendations for water environment management. The results showed that, maximum absolute error of water level was 0.08 m, percentage bias coefficient of COD, NH3-N and BOD5 were 19.3%, 16.2% and 23.1%, indicating the SMS and Mike21 coupling model was applicable; water quality of the assessment section were upgraded from the original class IV, V, V (Condition 1) to class IV, III, II (Condition 2) and class IV, III, III (Condition 3) in the wet, normal and dry season, indicating that NSPC's expansion had improved the water quality of the assessment section; as the primary pollutant, BOD5 concentration in the downstream was lower than the upstream, which was due to the dilution effect of river. Therefore, on the basis of expanding NSPC, we recommend to remediation of BOD5 by physical, chemical, and biological methods. This study broadens new ideas for the application of Mike21, and provide a reference for the prevention and improvement of river water pollution in urban areas.

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“…The assessment of HM pollution status and the comprehensive pollution degree of soil and water resources in the study area utilized screening values from GB 15618-2018 China's "Soil Environmental Quality Construction Land Soil Pollution Risk Control Standard" [39], in conjunction with the single-factor pollution index (P i ) [40][41][42] and Nemerow pollution index (P N ) [43][44][45][46]. Specific values are detailed in Tables S2 and S3.…”

Section: Evaluation Of Pollution Degree Of Sitementioning

confidence: 99%

Assessment of Heavy Metal(loid) Pollution and Human Health Risks Associated with a Mineral (Zn, Cu, and Sn Ores) Processing Plant in Yunnan, Southwest China

Luo,

Zhang,

Wei

et al. 2024

Minerals

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Understanding the contamination and sources of heavy metal(loid)s (HMs) at historical sites is vital for safeguarding human health and the ecological environment. This study focused on As, Hg, Cd, Cu, Pb, Ni, and Cr concentrations in the residual soil, groundwater, and surface water around a mineral processing plant. The sources of these elements and the human health risks posed by them were evaluated using various indexes. Soil HM concentrations exceeded background values for Yunnan Province, ranked as As > Pb > Cd > Cu > Hg > Ni. The river water met China's Class II waterbody standard; however, Cd, Cu, Pb, and pH exceeded the maximum permissible sewage discharge concentrations in the accumulated water. The groundwater showed severe HM pollution, meeting China's Class III water quality standard. The average value of the Nemerow pollution index was consistent with that of the single-factor pollution index in the following order: As > Pb > Cd > Ni > Cu > Hg. Children face heightened risk through the oral ingestion of As, Cd, and Pb, particularly in high-value sampling points in the residue deposit area. The main sources of these pollutants are anthropogenic activities and the soil formation matrix.

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Water quality characteristics, sources, and assessment of surface water in an industrial mining city, southwest of China

Cited by 15 publications

References 39 publications

Evaluation of surface water quality in basins of the Chilean Altiplano-Puna and implications for water treatment and monitoring

Evaluation of surface water quality in basins of the Chilean Altiplano-Puna and implications for water treatment and monitoring

Impact on urban river water quality and pollution control of water environmental management projects based on SMS-Mike21 coupled simulation

Assessment of Heavy Metal(loid) Pollution and Human Health Risks Associated with a Mineral (Zn, Cu, and Sn Ores) Processing Plant in Yunnan, Southwest China

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