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Huang JH, Berg B, Chen C, Thimonier A, Schmitt M, Osterwalder S, Alewell C, Rinklebe J, Feng X. Predominant contributions through lichen and fine litter to litterfall mercury deposition in a subalpine forest. ENVIRONMENTAL RESEARCH 2023; 229:116005. [PMID: 37116676 DOI: 10.1016/j.envres.2023.116005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/23/2023] [Accepted: 04/25/2023] [Indexed: 05/03/2023]
Abstract
Litterfall, typically referring to needles/leaves, may stand for >50% of the total mercury (Hg) deposition in forest ecosystems. By detailed categorisation, we reveal for the first time that the contributions through lichens and fine litter, together 9.98 μg Hg m-2 yr-1, could be as high as that in needle litter (9.96 μg m-2 yr-1) to the annual total Hg deposition (44.6 μg m-2 yr-1) in a subalpine forest in Switzerland. Noticeably, needle litter had the highest contribution (53%) to total Hg in the autumn litterfall but lichens and fine litter together predominated in other seasons (47-59%). Such a seasonal pattern is caused by the high ability of lichens and fine litter to accumulate Hg and the high needle litterfall in autumn, which is related to a good rainfall in summer followed by a dry period in autumn. The constantly higher Hg levels in lichens and fine litter than in needle litter together with similar seasonal patterns of litterfall during 2009-2019 and rainfall during 1980-2019 suggest that our finding can be generally valid. Here, we highlight not only the considerable role of non-needle litterfall in Hg deposition but also the association with weather for seasonal Hg dynamics in different litterfall components.
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Affiliation(s)
- Jen-How Huang
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, 550081, China; Environmental Geosciences, University of Basel, 4056, Basel, Switzerland.
| | - Björn Berg
- Department of Forest Sciences, University of Helsinki, FIN-00014, Helsinki, Finland
| | - Chaoyue Chen
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, 550081, China.
| | - Anne Thimonier
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903, Birmensdorf, Switzerland
| | - Maria Schmitt
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903, Birmensdorf, Switzerland
| | - Stefan Osterwalder
- Environmental Geosciences, University of Basel, 4056, Basel, Switzerland; Institute of Agricultural Sciences, ETH Zurich, 8092, Zurich, Switzerland
| | - Christine Alewell
- Environmental Geosciences, University of Basel, 4056, Basel, Switzerland
| | - Jörg Rinklebe
- University of Wuppertal, School of Architecture and Civil Engineering, Institute of Foundation Engineering, Water- and Waste-Management, Laboratory of Soil- and Groundwater-Management, 42285, Wuppertal, Germany
| | - Xinbin Feng
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, 550081, China
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Characteristics and Health Risk Assessment of Mercury Exposure via Indoor and Outdoor Household Dust in Three Iranian Cities. ATMOSPHERE 2022. [DOI: 10.3390/atmos13040583] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
This study aims to increase our current knowledge on the concentration of particulate-bound mercury (PBM) in urban environments of three Iranian cities, where high concentrations of dust particles can act as carriers for mercury transport and deposition. A total of 172 dust samples were collected from Ahvaz, Asaluyeh, and Zabol residential houses and in outdoor air and were analyzed for total mercury content. Ahvaz is a highly industrialized city with large metallurgical plants, refineries, and major oil-related activities, which were assumed to contribute to elevated contents of PBM in this city. Very high levels of Hg contamination in Ahvaz indoor dust samples were calculated (Contamination Factor: CF > 6). Sampling sites in Asaluyeh are influenced by Hg emissions from the South Pars Gas Field. However, the results revealed a relatively lower concentration of PBM in Asaluyeh, with a low-to-moderate level of Hg contamination. This is likely ascribed to the lower content of total mercury in hydrocarbon gases than crude oil, in addition to the absence of metal smelting plants in this city compared to Ahvaz. Zabol, as a city devoid of industrial activity, presented the lowest levels of PBM concentration and contamination. Indoor dust in Ahvaz showed considerable potential to cause a non-carcinogenic health risk for children, mainly through the inhalation of PBM, while the health risk for other cities was below safe limits. The trend of health risk was found in the order of indoor > outdoor and children > adults in all studied cities.
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Chai L, Wang Y, Wang X, Ma L, Cheng Z, Su L, Liu M. Quantitative source apportionment of heavy metals in cultivated soil and associated model uncertainty. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2021; 215:112150. [PMID: 33756290 DOI: 10.1016/j.ecoenv.2021.112150] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2020] [Revised: 02/27/2021] [Accepted: 03/11/2021] [Indexed: 06/12/2023]
Abstract
To estimate spatial distribution, source analysis and uncertainty of heavy metals (Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni) based on geographic information system (GIS), positive matrix factorization model (PMF) and bootstrap (BS) using 382 soil samples collected from cultivated soils in Lanzhou. The mean contents of Cd, Hg, Cu, Zn and Ni were high as 1.7,1.7, 2.1, 1.5 and 1.3 times local background values, mean contents of Pb, Cr and As were lower than local background values. However, the mean contents of eight heavy metals were lower environmental quality risk control standard for soil contamination of agricultural soil. Proportions of four sources were identified: Cr was predominantly contributed by natural sources (29.14%), Cu, Zn and Ni was primarily from industrial sources (25.26%), Hg and As were mainly of agricultural sources (27.49%), Pb and Cd mainly came from traffic source and smelting-related activities (18.09%). Uncertainties analysis contained three aspects: bootstrap runs, factor contributions in the PMF solution, and coefficient of variation (CV) values. By combining the four pollution source factors with bootstrap runs, the accuracy of the four pollution source factors were reliable based on PMF model. The median values in the BS runs was considered the most true factor contribution, and the 5th-95th quartile interval represents the variability of each factor, Factor 4 (traffic source) R2 was 0.70 and lower variability. The highest CV value usually means a significantly deviation degree. In this study, the CV values of Cr in Factor 1, Cu, Zn, and Ni in Factor 2, Hg, and As in Factor 3, Pb, and Cd in Factor 4 were lower, indicates a lower deviation degree. and with the lowest content among heavy metals usually was also with the greatest uncertainties. In this study improves understanding of the reduction of heavy metal pollution in cultivated soil, and also serves as reference for pollution source apportionment in other regions.
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Affiliation(s)
- Lei Chai
- Collage of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China
| | - Yuhong Wang
- Collage of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China; Lanzhou Center for Disease Control and Prevention, Lanzhou 730030, China.
| | - Xin Wang
- Lanzhou Center for Disease Control and Prevention, Lanzhou 730030, China
| | - Liang Ma
- Lanzhou Center for Disease Control and Prevention, Lanzhou 730030, China
| | - Zhenxiang Cheng
- Lanzhou Center for Disease Control and Prevention, Lanzhou 730030, China
| | - Limin Su
- Lanzhou Center for Disease Control and Prevention, Lanzhou 730030, China
| | - Minxia Liu
- Collage of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China.
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4
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Geochemical Mapping, Risk Assessment, and Source Identification of Heavy Metals in Road Dust Using Positive Matrix Factorization (PMF). ATMOSPHERE 2021. [DOI: 10.3390/atmos12050614] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Heavy metals in road dust pose a significant threat to human health. This study investigated the concentrations, patterns, and sources of eight hazardous heavy metals (Cr, Ni, Cu, Zn, As, Cd, Pb, and Hg) in the street dust of Zhengzhou city of PR China. Fifty-eight samples of road dust were analyzed based on three methods of risk assessment, i.e., Geo-Accumulation Index (Igeo), Potential Ecological Risk Assessment (RI), and Nemerow Synthetic Pollution Index (PIN). The results exhibited higher concentrations of Hg and Cd 14 and 7 times higher than their background values, respectively. Igeo showed the risks of contamination in a range of unpolluted (Cr, Ni) to strongly polluted (Hg and Cd) categories. RI came up with the contamination ranges from low (Cr, Ni, Cu, Zn, As, and Pb) to extreme (Cd and Hg) risk of contamination. The risk of contamination based on PIN was from safe (Cu, As, and Pb) to seriously high (Cd and Hg). The results yielded by PIN indicated the extreme risk of Cd and Hg in the city. Positive Matrix Factorization was used to identify the sources of contamination. Factor 1 (vehicular exhaust), Factor 2 (coal combustion), Factor 3 (metal industry), and Factor 4 (anthropogenic activities), respectively, contributed 14.63%, 35.34%, 36.14%, and 13.87% of total heavy metal pollution. Metal’s presence in the dust is a direct health risk for humans and warrants immediate and effective pollution control and prevention measures in the city.
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Men C, Liu R, Xu L, Wang Q, Guo L, Miao Y, Shen Z. Source-specific ecological risk analysis and critical source identification of heavy metals in road dust in Beijing, China. JOURNAL OF HAZARDOUS MATERIALS 2020; 388:121763. [PMID: 31818668 DOI: 10.1016/j.jhazmat.2019.121763] [Citation(s) in RCA: 133] [Impact Index Per Article: 33.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 11/24/2019] [Accepted: 11/25/2019] [Indexed: 05/11/2023]
Abstract
To explore the spatial variation of source-specific ecological risks and identify critical sources of heavy metals in road dust, 36 road dust samples collected in Beijing in March 2017 were analyzed for heavy metals. A new method that takes into consideration the heavy-metal toxic response and is flexible to changes in the number of calculated heavy metals, called the Nemerow integrated risk index (NIRI), was developed for ecological risk assessment. The NIRI indicated that heavy metals posed considerable to high risks at the majority of sites, and 22 % of the sites suffered extreme risk in spring (NIRI > 320). Four main sources were identified based on positive matrix factorization (PMF): traffic exhaust, fuel combustion, construction, and use of pesticides and fertilizers. Owing to the lower toxic response factors of representative heavy metals of fuel combustion than those of other sources, although fuel combustion had the highest contribution (34.21 %) to heavy metals in spring, it only contributed 5.57 % to ecological risks. Critical sources and critical source areas were determined by considering the contributions to both heavy metals and ecological risks. The use of pesticide and fertilizer and traffic-related exhaust were identified as critical sources of heavy metals in spring. Source-specific ecological risks and critical sources of heavy metals changed with the changing seasons, which suggests that different strategies should be adopted in different seasons.
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Affiliation(s)
- Cong Men
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Ruimin Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Libing Xu
- College of Agronomy, Nanjing Agricultural University, Nanjing, 210095, China
| | - Qingrui Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Lijia Guo
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Yuexi Miao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Zhenyao Shen
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
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Navrátil T, Nováková T, Roll M, Shanley JB, Kopáček J, Rohovec J, Kaňa J, Cudlín P. Decreasing litterfall mercury deposition in central European coniferous forests and effects of bark beetle infestation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 682:213-225. [PMID: 31121348 DOI: 10.1016/j.scitotenv.2019.05.093] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 05/06/2019] [Accepted: 05/07/2019] [Indexed: 06/09/2023]
Abstract
We evaluated a 14-year trend (2003-2017) in mercury (Hg) concentrations and fluxes in six litterfall categories (needles, bark, twigs, cones, lichen, and a mixture of unidentified fragments) at six research plots situated in two central European unmanaged mountain forest stands, dominated by mature Norway spruce. One of the stands (catchment of Plešné Lake, PL) was infested by bark beetle and all mature spruces died at three of four research plots during the study. One PL plot and two plots in the second stand (catchment of Čertovo Lake, CT) were intact and used as a control. At the intact plots, the litterfall Hg deposition averaged 45 and 32 μg/m2/year in the PL and CT catchments, respectively, while bulk precipitation Hg deposition was an order of magnitude lower (2.6 μg/m2/year). In the individual litter categories, Hg concentrations averaged 223, 195, 126, 81, 79 and 30 μg/kg in lichen, unidentified fragments, bark, twigs, needles and cones, respectively. As a result of decreasing European Hg emissions, Hg concentrations in most litter categories decreased from 2003 to 2017. Consequently, the litter-associated Hg flux to the forest floor decreased from 66 to 23 μg/m2/year during 2003-2017. The litterfall mass fluxes exhibited no trends at the intact plots. In contrast, the litter-associated Hg flux increased 5-fold after tree dieback due to elevated litterfall, averaging 218 μg/m2/year Hg at the PL infested plots during 2004-2009. The relative contribution of individual litter categories to the total Hg flux shifted from needle to bark and twig dominance. Starting in 2010, Hg flux decreased to pre-disturbance levels for the following decade. The tree mortality in the PL catchment provided a unique opportunity to evaluate changes in litter-associated Hg fluxes to the forest floor during and after natural tree dieback.
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Affiliation(s)
- Tomáš Navrátil
- Institute of Geology of the Czech Academy of Sciences, Rozvojová 269, 165 00 Prague 6, Czech Republic.
| | - Tereza Nováková
- Institute of Geology of the Czech Academy of Sciences, Rozvojová 269, 165 00 Prague 6, Czech Republic
| | - Michal Roll
- Institute of Geology of the Czech Academy of Sciences, Rozvojová 269, 165 00 Prague 6, Czech Republic; Institute of Geochemistry, Mineralogy and Mineral Resources, Faculty of Science, Charles University, Albertov 6, 128 43 Praha 2, Czech Republic
| | | | - Jiří Kopáček
- Biology Centre of the Czech Academy of Sciences, Institute of Hydrobiology, 370 05 České Budějovice, Czech Republic
| | - Jan Rohovec
- Institute of Geology of the Czech Academy of Sciences, Rozvojová 269, 165 00 Prague 6, Czech Republic
| | - Jiří Kaňa
- Biology Centre of the Czech Academy of Sciences, Institute of Hydrobiology, 370 05 České Budějovice, Czech Republic
| | - Pavel Cudlín
- Global Change Research Centre of the Czech Academy of Sciences, Poříčí 3b, 60 300 Brno, Czech Republic
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Liu Y, Song S, Bi C, Zhao J, Xi D, Su Z. Occurrence, Distribution and Risk Assessment of Mercury in Multimedia of Soil-Dust-Plants in Shanghai, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16173028. [PMID: 31438583 PMCID: PMC6747141 DOI: 10.3390/ijerph16173028] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 08/10/2019] [Accepted: 08/16/2019] [Indexed: 02/03/2023]
Abstract
The urban environment is a complex ecosystem influenced by strong human disturbances in multi-environmental media, so it is necessary to analyze urban environmental pollutants through the comprehensive analysis of different media. Soil, road dust, foliar dust, and camphor leaves from 32 sample sites in Shanghai were collected for the analysis of mercury contamination in soil–road dust–leaves–foliar dust systems. Mercury concentrations in surface soils in Shanghai were the highest, followed by road dust, foliar dust, and leaves, successively. The spatial distribution of mercury in the four environmental media presented different distribution patterns. Except for the significant correlation between mercury concentrations in road dust and mercury concentrations in leaves (r = 0.56, p < 0.001), there was no significant correlation between the other groups in the four media. Besides this, there was no significant correlation between mercury concentrations and land types. The LUR (Land use regression) model was used to assess the impact of urbanization factors on mercury distribution in the environment. The results showed that soil mercury was affected by factories and residential areas. Foliar dust mercury was affected by road density and power plants. Leaf mercury was affected by power plants and road dust mercury was affected by public service areas. The highest average HI (Hazard index) value of mercury in Shanghai was found in road dust, followed by surface soil and foliar dust. The HI values for children were much higher than those for adults. However, the HI values of mercury exposure in all sampling sites were less than one, suggesting a lower health risk level. The microscopic mechanism of mercury in different environmental media was suggested to be studied further in order to learn the quantitative effects of urbanization factors on mercury concentrations.
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Affiliation(s)
- Yanzhuo Liu
- Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Shanshan Song
- Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Chunjuan Bi
- Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China.
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China.
- Institute of Eco-Chongming (IEC), East China Normal University, Shanghai 202150, China.
| | - Junli Zhao
- Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Di Xi
- Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Ziqi Su
- Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
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8
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Men C, Liu R, Wang Q, Guo L, Miao Y, Shen Z. Uncertainty analysis in source apportionment of heavy metals in road dust based on positive matrix factorization model and geographic information system. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 652:27-39. [PMID: 30352344 DOI: 10.1016/j.scitotenv.2018.10.212] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Revised: 10/15/2018] [Accepted: 10/15/2018] [Indexed: 06/08/2023]
Abstract
Based on 36 road dust samples from an urbanized area of Beijing in September 2016, the information about sources (types, proportions, and intensity in spatial) of heavy metals and uncertainties were analyzed using positive matrix factorization (PMF) model, bootstrap (BS), geographic information system (GIS) and Kriging. The mean concentration of most heavy metals was higher than the corresponding background, and mean concentration of Cd was six times of its background value. Types and proportions of four sources were identified: fuel combustion (33.64%), vehicle emission (25.46%), manufacture and use of metallic substances (22.63%), and use of pesticides, fertilizers, and medical devices (18.26%). The intensity of vehicle emission and the use of pesticides, fertilizers, and medical devices were more homogeneous in spatial (extents were 1.285 and 0.955), while intensity of fuel combustion and the manufacture and use of metallic substances varied largely (extents were 4.172 and 5.518). Uncertainty analysis contained three aspects: goodness of fit, bias and variability in the PMF solution, and impact of input data size. Goodness of fit was assessed by coefficient of determination (R2) of predicted and measured values, and R2 of most species were higher than 0.56. Influenced by an outlier, R2 of Ni decreased from 0.59 to 0.11. Result of bootstrap (BS) showed good robust of this four-factor configuration in PMF model, and contributions of base run of factors to most species were contained in the small interquartile range and close to median values of bootstrap. Size of input data also had influence on results of PMF model. Residuals changed largely with the increase of number of site, it varied at first and then kept stable after number of site reached 70.
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Affiliation(s)
- Cong Men
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
| | - Ruimin Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China.
| | - Qingrui Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
| | - Lijia Guo
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
| | - Yuexi Miao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
| | - Zhenyao Shen
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
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9
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Men C, Liu R, Wang Q, Guo L, Shen Z. The impact of seasonal varied human activity on characteristics and sources of heavy metals in metropolitan road dusts. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 637-638:844-854. [PMID: 29763865 DOI: 10.1016/j.scitotenv.2018.05.059] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2018] [Revised: 05/04/2018] [Accepted: 05/05/2018] [Indexed: 06/08/2023]
Abstract
Due to significant human activity, road dust is becoming contaminated by heavy metals in many cities. To comprehensively investigate the variation of contamination level and sources of heavy metals in road dust, 10 heavy metals in road dust samples from Beijing, China, in both summer and winter, were evaluated by spatial analysis using geographic information system (GIS) mapping technology and the positive matrix factorization (PMF) Model. Although the concentrations of some heavy metals between summer and winter had similarities, the differences of others and spatial distributions of heavy metals between summer and winter were considerable. The mean concentrations of As, Cd, Cr, Cu, and Fe were lower in winter, while those of Hg, Mn, Ni, Pb, and Zn were higher. According to the values of the Pollution Index (PI) and Nemerow Integrated Pollution Index (NIPI), there were no obvious differences between summer and winter, but the range between different sites in winter was nearly twice that of summer. Based on the PMF model, four sources of heavy metals in the dust samples were identified. Although the types of sources were consistent, the relative contributions of each source differed between summer and winter. Non-exhaust vehicle emissions was the most important source in summer (34.47 wt%), while fuel combustion contributed the largest proportion to the total heavy metals in winter (32.40 wt%). The impact of each source also showed spatial variation different trends in summer and winter. With the alteration of seasons, intensity of human activities also changed, such as the number of tourists, energy needs for building temperature regulation, construction, and the amount of pesticides and fertilizer. That might be the reason for the variation of heavy metal concentrations and relative contribution of their sources between summer and winter.
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Affiliation(s)
- Cong Men
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
| | - Ruimin Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China.
| | - Qingrui Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
| | - Lijia Guo
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
| | - Zhenyao Shen
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
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10
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Men C, Liu R, Xu F, Wang Q, Guo L, Shen Z. Pollution characteristics, risk assessment, and source apportionment of heavy metals in road dust in Beijing, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 612:138-147. [PMID: 28850834 DOI: 10.1016/j.scitotenv.2017.08.123] [Citation(s) in RCA: 269] [Impact Index Per Article: 44.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Revised: 08/11/2017] [Accepted: 08/12/2017] [Indexed: 05/22/2023]
Abstract
To analyze the spatial distribution patterns, risks, and sources of heavy metals (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn, Fe), 36 road dust samples were collected from an urbanized area of Beijing in June 2016. The mean concentration of most metals, except As and Mn, exceeded their corresponding background values, with the mean concentration of Cd being 8 times that of its background. Spatially, for most heavy metals, except As and Mn, the high concentration areas were mainly within the 5th ring road, especially the northern area. The geo-accumulation index of Cd and Cu indicated moderate contamination at many sites. The entire study area was prone to potential ecological risks, with higher risks within the 4th ring road. Cd caused high potential ecological risk at most sites. According to the health risk assessment results, the non-carcinogenic risks that human beings suffered from heavy metals were insignificant. However, the carcinogenic risks due to Ni and Cr exceeded the acceptable level. Based on the source apportionment using positive matrix factorization, four factors were defined for the heavy metals. Factor 1, which was traffic-related exhaust, accounted for 34.47% of the concentration of heavy metals. The contributions of Factors 2 and 3 were approximately 25% each. Factor 2 was potentially related to coal combustion, while Factor 3 could be related to the manufacture and use of metal components. Factor 4, which could be related to the use of pesticides, fertilizers, and medical devices, accounted for 14.88%, which was the lowest.
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Affiliation(s)
- Cong Men
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
| | - Ruimin Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China.
| | - Fei Xu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
| | - Qingrui Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
| | - Lijia Guo
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
| | - Zhenyao Shen
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
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11
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Wiśniewska K, Lewandowska AU, Witkowska A. Factors determining dry deposition of total mercury and organic carbon in house dust of residents of the Tri-city and the surrounding area (Baltic Sea coast). AIR QUALITY, ATMOSPHERE, & HEALTH 2017; 10:821-832. [PMID: 29046736 PMCID: PMC5624982 DOI: 10.1007/s11869-017-0471-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Accepted: 03/08/2017] [Indexed: 06/07/2023]
Abstract
The purpose of this study was to find out what factors determine the deposition levels of mercury and organic carbon in household dust in the Tri-city region (southern Baltic Sea coast). Analyses were performed on samples collected over the period of 2 years, from 2013 to 2015, always in the heating season. The deposition of organic carbon was between 4and 210 mg m-2 month-1, while mercury deposition ranged from 4 to 1336 ng m-2 month-1. Deposition of mercury in household dust during the heating season was three times lower and deposition of organic carbon one and a half times lower than outdoor deposition obtained in the Baltic Sea region by other researchers. In the non-heating period, deposition of mercury in household dust was similar to outdoor deposition while deposition of OC was one and a half times higher. Both of the analyzed dust components reached higher deposition in rural areas than in cities, and both mercury and organic carbon were found to have higher deposition in single-family houses than in buildings housing several families. The increased level of OC was conditioned by the vicinity of the building to a road or street with a high level of traffic, and dust collected on the ground floor had higher Hg depositions. The presence of plants and pets, as well as smoking more than ten cigarettes per day, resulted in higher depositions of both the compounds present in household dust within the Tri-city region.
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Affiliation(s)
- Kinga Wiśniewska
- Institute of Oceanography, University of Gdansk, Al. Marszałka J. Piłsudskiego 46, 81-378 Gdynia, Poland
| | - Anita Urszula Lewandowska
- Institute of Oceanography, University of Gdansk, Al. Marszałka J. Piłsudskiego 46, 81-378 Gdynia, Poland
| | - Agnieszka Witkowska
- Institute of Oceanography, University of Gdansk, Al. Marszałka J. Piłsudskiego 46, 81-378 Gdynia, Poland
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