Assessment and source analysis of heavy metal contamination in water and surface sediment in Dongping Lake, China

Spatial-temporal variation and source analysis of heavy metals in different land use types in Beilun District (2015 and 2022)

The soil environment plays an important role in urban ecosystems. To study the heavy metal contamination of soil in Beilun District, Ningbo, we collected soil samples from 60 points in urban and peri-urban areas of Beilun District and analyzed the spatiotemporal variation and sources of heavy metal pollution in various land-use types. The results shown that the heavy metal contents in 2015 and 2022 were higher than the background soil values of Ningbo city, and there was an accumulation of heavy metals over these 7 years. The contents of heavy metals in green belts and woodland in 2022 were higher than those in 2015, while there was no significant change in agricultural land. The heavy metal contents in both years were mainly in the order green belts > agricultural land > woodland. The spatiotemporal distribution of heavy metal content showed that heavy metal pollution in Beilun District was concentrated in five industrial areas, and there was a trend toward the disappearance of highly polluted points. But the single-factor pollution index, pollution load index (PLI), and geoaccumulation index (Igeo) indicated that there was no significant heavy metal pollution in Beilun District, and individual elements at specific points showed slight pollution. The source analysis results showed that the main source of Hg is chemical, As is mainly derived from agricultural, Cr, Ni and Cu are mainly derived from natural, the main sources of Zn and Cd are electroplating and machinery activities, and the main source of Pb is traffic. These results specify a reference for future investigation on urban soil heavy metals, and the source apportionment results provide a scientific foundation for subsequent soil heavy metal pollution treatment.

Assessing the ecological and health risks associated with heavy metal pollution levels in sediments of Big Giftun and Abu Minqar Islands, East Hurghada, Red Sea, Egypt

This study assessed pollution levels, ecological and health risk, and spatial distribution of eight heavy metals in sediments of Big Giftun and Abu Minqar Islands, Red Sea, Egypt. Iron (Fe) and manganese (Mn) had the highest contents in both island sediments, while cobalt (Co) in Big Giftun and cadmium (Cd) in Abu Mingar had the lowest values. The obtained PCA data exhibited positively significant loadings of Cd, Co, copper (Cu), nickel (Ni), and zinc (Zn) with 51.03 % of data variance in Big Giftun, and lead (Pb), Cu, Mn, Ni, Zn, and Fe (37.7 %) in Abu Minqar sediments. The contamination factor (CF) showed low contamination for all metals, except cadmium; Cd (moderate). The geo-accumulation index (Igeo) values showed uncontaminated (Cd, Co), moderately (Cu), extremely contaminated (Fe, Mn) (Igeo > 5) in Big Giftun, and uncontaminated (Cd), moderately to strongly contaminated (Cu, Ni), and extremely contaminated (Fe, Mn, and Zn) in Abu Minqar sediments. The pollution load index (PLI) values indicated baseline level of contamination (PLI <1), and degree of contamination (DC) indicated low degree of contamination (DC < n) in all sediments. Nemerow pollution index (NPI) showed unpolluted sediments in Abu Minqar (NPI ≤1) and slight pollution (1 < NPI ≤2) in Big Giftun. Cd showed moderate potential ecological risk (40 ≤ Eri < 80) in Big Giftun sediments. Potential ecological risk index (PERI) indicated low risk sediments (PERI <150). Mean effects range median quotient (MERMQ) indicated low-priority risk of toxicity (MERMQ ≤0.1), and toxic risk index (TRI) showed no toxic risk in all sediments (TRI <5). The modified hazard quotient (mHQ) indicated very low severity of contamination (mHQ <0.5). The hazard quotient (HQ) levels of all metals were below the safe value (HQ <1). The hazard index (HI) levels indicated that no chronic risks occur (HI <1). The total cancer risk (TCR) for all metals were below the safe level (1 × 10-4) of the United States Environmental Protection Agency (U.S. EPA) guidelines.

Impacts of the steel industry on sediment pollution by heavy metals in urban water system

The impact of the steel industry on sediment heavy metal (HM) pollution in urban aquatic environments was investigated in a major iron ore-producing area (Ma'anshan) in China. The concentrations of Cd, Cr, Cu, Ni, Pb, and Zn were 9.68 ± 3.56, 170.31 ± 82.40, 90.62 ± 19.54, 30.61 ± 6.72, 125.43 ± 63.60, and 1276.59 ± 701.90 mg/kg in the steel industry intruded upon sediments and 4.63 ± 1.41, 87.60 ± 10.96, 52.67 ± 19.99, 37.49 ± 6.17, 35.84 ± 11.41, and 189.02 ± 95.57 mg/kg in the control area, respectively. Comparing with the local soil background (0.08 mg/kg for Cd, 62.6 mg/kg for Cr, 19.3 mg/kg for Cu, 28.1 mg/kg for Ni, 26.0 mg/kg for Pb, and 58.0 mg/kg for Zn), significantly higher levels of Cd, Cr, Cu, Pb, and Zn were detected in the steel industry affected sediments. The enrichment factor and principal component analysis indicated that the heavy metals (HMs), except for Ni, were primarily derived from anthropogenic inputs, particularly from steel industrial activities. Multiple risk assessment models suggested that the sediments affected by industrial activities showed significant toxic effects for Cd, Cr, Pb, and Zn, with Cd being the main contributor to sediment toxicity. However, the alkaline nature of the sediments (pH = 7.85 ± 0.57) and the high proportion of residual fraction Cd (61.09% ± 26.64%) may help to reduce the toxic risks in the sediments. Effective measures to eliminate tinuous thethe continous input of Cd and Zn via surface runoff are crucial.

Assessment of heavy metals contamination of sediments and surface waters of Bitter lake, Suez Canal, Egypt: Ecological risks and human health

The concentrations of heavy metals in the surface waters and sediments of Bitter Lake were investigated to assess the level, distribution, and source of pollution and the associated ecological and human health risks. The ecological indices of the lake water indicate low contamination degrees by heavy metals. A dermal exposure-based health risk evaluation revealed no carcinogenic or non-carcinogenic impact on human health. The contamination factor (CF) for Cu, Ni, Pb, Mn, Fe, and Zn (CF < 1) indicate low contamination levels, while Cd reaches very high contamination in most sediment sites (CF ranges from 6.2 to 72.4). Furthermore, the potential ecological risk factor (Erⁱ) and modified hazard quotient (mHQ) indicate low ecological risk for all metals except Cd, revealing high to very high-level ecological risk in most sites (Erⁱ ranges from 185 to 2173 and mHQ from 1.8 to 6.3). This emphasizes the urgency of prompt actions to improve the environment in Bitter Lake.

Risk assessment and source apportionment for metals in sediments of Kaptai Lake in Bangladesh using individual and synergistic indices and a receptor model

Metal enrichment in lake sediments originating from multiple sources can threaten both the aquatic ecosystem and human health. Therefore, assessment of the eco-environmental risks and potential sources of metals in the sediments is essential for effective lake management. Here, we analyzed the sediment metal contents of Kaptai Lake, the largest lake in Bangladesh for the first time with this study. The results indicated that only Cr and Ni contents among the metals studied exceeded the probable effect concentrations (PEC) at 25.42 % and 55.93 % of the sampling stations, respectively. All metals at most sampling stations showed low contamination and low ecological risk based on the individual indices (geoaccumulation index, contamination factor, ecological risk factor, enrichment factor and modified hazard quotient). There was no significant risk from the combined metals in the sediments of the lake according to the synergistic indices (toxic risk index, Nemerow risk index, ecological risk index, Nemerow pollution index and pollution load index). Organic matter and silt were significant sediment parameters that favored the accumulation of Cr, Fe, Cu, Pb and Mn. In the absolute principle component scores-multiple linear regression model (APCS-MLR), five potential sources of metals were identified in the sediments: Zn, Mn, Co and Cd mainly from natural sources and to a lesser extent from agricultural and aquacultural activities, Ni, Cr and Fe from parent materials, Pb and Cu mainly from natural sources and to a lesser extent from vehicle emissions, Hg and U from lithogenic sources, and As from natural sources. This study will improve our knowledge of the sedimentary metal contents of Kaptai Lake and provide helpful information for developing effective lake management and pollution control strategies.

A novel methodological framework for risk zonation and source-sink response concerning heavy-metal contamination in agroecosystems

The accurate identification of high-risk zones and risk source-sink responses for heavy-metal (HM) contamination of agroecosystems remains challenging due to involving multiple environmental media such as soils, dustfall, and crops and a wide range of evaluation criteria and constraints. This study established a novel evaluation model based on the integration of Geographical Information Systems (GIS) and multi-criteria decision analysis (MCDA) to assess agroecosystem risk in the Lihe River watershed, China. Bivariate local indicators of spatial association (LISA) were adopted to explore the spatial interaction of risk sources and sinks with outputs ranging from 0.0003 (no risk) to 0.83 (high risk). Areas with moderate, considerable, and high risk constituted 67.4 % of the total land area, and only 1.8 % of the area was classed as low risk. Central urban and eastern areas around Taihu Lake were risk accumulation regions that needed more remedial attention. Risk cluster zones in the central urban area involved significant source-sink response relationships with the spatial distribution of industries, whereas eastern zones were linked to vehicular traffic distribution, accounting for 27.5 % and 16.5 % of the total area, respectively. This study provides a new methodological framework for the assessment of environmental risk, risk zonation, and risk source-sink spatial interaction in agroecosystems.