Evaluation of soil heavy metal(loid)s contamination and its impact on food safety in the suburbs of an industrial city, Henan Province, China DOI Creative Commons
Lei Shi,

Shuaixia Liu,

Ziyu Han

et al.

Deleted Journal, Journal Year: 2025, Volume and Issue: 7(3)

Published: March 10, 2025

Abstract Rapid industrial development increases soil contamination risks in suburban agricultural areas; however, the extent and sources of heavy metal(loid)s pollution during this process are not well understood. This study investigated concentrations, spatial distribution, potential (As, Hg, Cd, Cr, Pb) wheat samples from an area. The found that Cd was main pollutant with highest enrichment factor 15.9 21.6% having concentrations exceeding China's limit 0.1 mg/kg. Soil As, Pb were concentrated northwest, while Cr high southeast. is more severe than other poses a slight ecological risk. Monte Carlo simulations showed hazard quotient for all five less 1, being highest. 1.35% children 0.87% adults exceeded carcinogenic risk level 0.54% exhibited above threshold Cr. Children most sensitive to exposure contaminated areas, metal(loid)s) concentration key influencing health risks. Source apportionment via PCA-APCS-MLR model correlation analysis revealed originated activities industrial-traffic. assessed pollution, risks, sources, residents consumption, providing evidence managing food safety.

Language: Английский

Characteristics and correlation analysis of heavy metal distribution in China's freshwater aquaculture pond sediments DOI

Shouzhuang Liu,

Kaixuan Wu, Yao Lu

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 931, P. 172909 - 172909

Published: May 3, 2024

Language: Английский

Citations

9
Analysis of heavy metal and arsenic sources in mangrove surface sediments at Wulishan Port on Leizhou Peninsula, China, using the APCS-MLR model DOI Creative Commons

Suyan Deng,

Songying Luo,

Qiance Lin

et al.

Ecotoxicology and Environmental Safety, Journal Year: 2024, Volume and Issue: 283, P. 116788 - 116788

Published: July 27, 2024

Mangrove forests are sources and sinks for various pollutants. This study analyzed the current status of heavy metal arsenic (As) pollution in mangrove surface sediments rapidly industrializing urbanizing port cities. Surface mangroves at Wulishan Port on Leizhou Peninsula, China, were using inductively coupled plasma emission spectrometry (ICP-AES) mass (ICP-MS) presence Cr, Pb, Ni, Zn, Cd, Cu, As, Hg. The Pollution load index, Nemerow Potential ecological risk index employed to evaluate pollutant. Multivariate statistical methods applied qualitative analysis pollutant sources, APCS-MLR receptor model was used quantification. indicated following results: (1) average content eight pollutants surpassed local background level but did not exceed Marine Sediment Quality standard. levels across four sampling areas ranked as Ⅲ > Ⅳ Ⅰ Ⅱ. area Ⅱ exhibited relatively lower with grain size dominated by sand, which conducive adsorption enrichment. (2) factor cluster analyses identified three primary contamination. Pb originated from nearby industrial activities their associated wastewater, suggesting that source source. Zn stem cement columns utilized oyster farming, alongside discharges mariculture pig establishing a secondary agricultural Hg ship exhaust burning oil vehicle emissions vicinity, representing third traffic (3) results demonstrated industrial, agricultural, contributing 47.19 %, 33.13 13.03 respectively, 6.65 % attributed unidentified sources.

Language: Английский

Citations

8
Machine learning-based analysis of heavy metal contamination in Chinese lake basin sediments: Assessing influencing factors and policy implications DOI Creative Commons
Luqi Wang, Dongsheng Liu, Yifan Sun

et al.

Ecotoxicology and Environmental Safety, Journal Year: 2024, Volume and Issue: 283, P. 116815 - 116815

Published: Aug. 1, 2024

Sediments are important heavy metal sinks in lakes, crucial for ensuring water environment safety. Existing studies mainly focused on well-studied leaving gaps understanding pollution patterns specific basins and influencing factors.We compiled comprehensive sediment contamination data from literature public datasets, including hydro-geomorphological, climatic, soil, landscape, anthropogenic factors. Using advanced machine learning, we analyzed typical factors to infer potential sources migration pathways of pollutants predicted levels with limited availability. Our analysis pollutant distribution revealed that Cd had the most extensive range, severe occurring Huaihe Yangtze River basins. Furthermore, identified distinct groups driving various metals. Cd, Cr, Pb were primarily influenced by human activities, while Cu Ni affected both natural factors, Zn tended more towards sources. predictions indicated that, addition highly polluted areas, risk is higher Xinjiang, Tibet Qinghai, higher. presented lower risks, except Basins. Temperature, wind, precipitation, precipitation rate, cation exchange capacity soil significantly impacted sediments, suggesting particulate migration, rainfall runoff, erosion likely main into sediments. Considering pathways, pollutants, propose strategies such as low-impact development promoting sustainable transportation mitigate pollution. This study provides latest insights Chinese lake offering references policy-making resource management.

Language: Английский

Citations

8
Soil pollution and elemental sources along Barapukuria coal mine, Bangladesh: Implications for eco-environmental and health risk assessment DOI Creative Commons
Israt Jahan,

A.H.M. Selim Reza,

Md. Masidul Haque

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(12), P. e32620 - e32620

Published: June 1, 2024

For the first time, different pollution indices and a receptor model have been used to quantify eco-environmental health risk assessments as well identify sources of potentially toxic elements in soil along Barapukuria Coal Mine (BCM). Individual include enrichment contamination factors showing samples are moderately highly contaminated by arsenic, cobalt, chromium, copper, lead, zinc heavily sulfur. According geo-accumulation index, there is significant with arsenic (1.24 ± 0.38), lead (1.49 0.58), cobalt sulfur (1.63 0.38). Modified hazard quotient ecological factor values also suggest low moderate environmental hazards from same elements. The nemerow load index range 1.65 3.03, 0.82-1.23, 11-26, 77-165, 6.82-11.76 pollution, among other synergistic indices. Health assessment indicates that iron poses lower cancer for children than adults, while both face unacceptable risks inhaling or arsenic. Principal component phylogenetic cluster analysis extracted multiple linear regression absolute principal score (APCS-MLR) refer fact manganese, iron, titanium, nickel originated geogenic sources, coal mine effluents enrich like zinc, uranium, sulfur, thorium, phosphorous sourced agriculture. In addition, anthropogenic including agriculture activities, could pollute ecosystem. findings crucial regional national planners devising strategies mitigate element areas.

Language: Английский

Citations

7
Particle Size-Dependent Monthly Variation of Pollution Load, Ecological Risk, and Sources of Heavy Metals in Road Dust in Beijing, China DOI Creative Commons
Cong Men,

Donghui Li,

Yunqi Jing

et al.

Toxics, Journal Year: 2025, Volume and Issue: 13(1), P. 40 - 40

Published: Jan. 7, 2025

Road dust carries various contaminants and causes urban non-point source pollution in waterbodies through runoff. samples were collected each month two years then sieved into five particle size fractions. The concentrations of ten heavy metals (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn, Fe) fraction measured. load index, coefficient divergence, Nemerow integrated risk index used to analyze the temporal variation ecological different advanced three-way model wavelet analysis quantitative identification time-series sources. Results showed that both most a decreasing trend from finest (P1) coarsest (P5). frequency P1 posing extreme was about times P5. Main types metal sources similar among fractions, whereas impact intensity these varied Traffic exhaust tended accumulate finer particles, its contribution Cu P5 only 35-55% other Construction contributed more coarser Pb increased 45.34% 65.35% Wavelet indicated traffic periodicities 5-8 10-13 months. Fuel combustion displayed strongest periodicity 12-15 months, peaking winter.

Language: Английский

Citations

1
Analysis of heavy metal sources and potential ecological risk assessment of mangroves in Aojiang Estuary DOI
Yadong Ma,

Yiyi Sun,

Jing Wang

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 173, P. 113343 - 113343

Published: March 14, 2025

Language: Английский

Citations

1
Risk assessment of heavy metals in agricultural soil based on the coupling model of Monte Carlo simulation-triangular fuzzy number DOI

Minsi Xiao,

Lidan Qian,

Bing Yang

et al.

Environmental Geochemistry and Health, Journal Year: 2024, Volume and Issue: 46(2)

Published: Jan. 31, 2024

Language: Английский

Citations

6
Evaluation of ecological and health risks of trace elements in soils of olive orchards and apportionment of their sources using the APCS-MLR receptor model DOI Creative Commons
Aişe DELİBORAN, Memet Varol, Halil Aytop

et al.

Environmental Geochemistry and Health, Journal Year: 2024, Volume and Issue: 46(9)

Published: July 16, 2024

İzmir, Turkey's third most populous city, is in an important position terms of both agriculture and industry. The province, which contributes 9.3% to the country's industrial production, also has potential olive cultivation. However, until now, no research been undertaken analyze content trace elements (TEs) soil orchards İzmir. This study was carried out determine pollution level ecological risks TEs soils İzmir reveal their sources evaluate health risks. Among TEs, average only Ni (37.9 mg/kg) exceeded world (29 mg/kg), while Cd (0.176 upper continental crust (0.09 mg/kg). Enrichment factor revealed that there significant enrichment for 73.6%, 11.6% Cr 5.4% orchards, respectively, due polluted irrigation water agrochemicals. Similarly, risk indicated were moderate considerable 48.8% 23.3% respectively. Absolute principal component scores-multiple linear regression (APCS-MLR) model showed area are affected by agricultural sources, Al, Co, Cu, Fe, Mn, Pb Zn originate from lithogenic originates mixed sources. Based on evaluation methods, non-carcinogenic carcinogenic effects would not be expected residents. provides knowledge evaluating TE serves a source apportionment human other regions.

Language: Английский

Citations

6
Determining the priority control factor of toxic metals in cascade reservoir sediments via source-oriented ecological risk assessment DOI
Zhenjie Zhao, Shehong Li, Yunlong Li

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 631, P. 130755 - 130755

Published: Jan. 24, 2024

Language: Английский

Citations

5
Source Apportionment and Risk Assessment of Heavy Metals in Agricultural Soils in a Typical Mining and Smelting Industrial Area DOI Open Access
Wei Li, Xudong Cao, Yuanan Hu

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(4), P. 1673 - 1673

Published: Feb. 18, 2024

Source apportionment and risk assessment are critical for making effective pollution prevention control policies. The study was carried out to assess source-specific ecological human health risks associated with heavy metals in farmland soils Yingtan City based on results of receptor models. Multivariate analysis the APCS-MLR model consistently revealed that As, Ni, Cr agricultural may be mainly derived from natural sources, while contents Cu, Zn, Cd, Pb have been significantly elevated by activities. According outputs model, Cu (34.3%), Zn (67.2%), (75.1%), Cd (67.9%) primarily originated industrial activities related mineral mining non-ferrous metal smelting processes. indicated sources were primary contributor total risks, posing moderate high southern mountainous regions. Natural origins played a significant role due substantial amounts As naturally occurring soils. findings could guide development management measures

Language: Английский

Citations

5