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Relative importance of natural and anthropogenic proton sources in soils in the Netherlands.
1986
Vries W. de | Breeuwsma A.
Anthropogenic lead distribution in soils under arable land and permanent grassland estimated by Pb isotopic compositions
2008
Fernandez , Christelle (INRA , Versailles (France). UR 0251 Physico-chimie et Ecotoxicologie des Sols d'agrosystèmes contaminés) | Monna , Fabrice (Centre National de la Recherche Scientifique, Dijon(France). Centre des Sciences de la Terre) | Labanowski , Jérome (INRA , Versailles (France). UR 0251 Physico-chimie et Ecotoxicologie des Sols d'agrosystèmes contaminés) | Loubet , Michel (Université Toulouse 3, Toulouse(France). Laboratoire de Géochimie) | Van Oort , Folkert (INRA , Versailles (France). UR 0251 Physico-chimie et Ecotoxicologie des Sols d'agrosystèmes contaminés)
The role of land use on fate of metals in soils is poorly understood. In this work, we studied the incorporation of lead in two neighboring soils with comparable pedogenesis but under long-term different agricultural management. Distributions of anthropogenic Pb were assessed from concentrations and isotopic compositions determined on bulk horizon samples, systematical 5–10 cm increment samples, and on 24-h EDTA extracts. Minor amounts of anthropogenic lead were detected until 1-m depth under permanent grassland, linked to high earthworm activity. In arable land, exogenous Pb predominantly accumulated at depths <60 cm. Although the proximity between the two sites ensured comparable exposition regarding atmospheric Pb deposition, the isotopic compositions clearly showed the influence of an unidentified component for the cultivated soil. This work highlights the need for exhaustive information on historical human activities in such anthropized agrosystems when fate of metal pollution is considered.
Afficher plus [+] Moins [-]Effects of intense agricultural practices on heterotrophic processes in streams
2009
Piscart, Christophe | Genoel, Romuald | Dolédec, Sylvain | Chauvet, Eric | Marmonier, Pierre | Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO) ; Université de Rennes (UR)-Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) ; Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS) | Laboratoire d'Ecologie des Hydrosystèmes Fluviaux (EHF) ; Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS) | Hydrobiologie et Ecologie Souterraines ; Laboratoire d'Ecologie des Hydrosystèmes Fluviaux (EHF) ; Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO) ; Université de Rennes (UR)-Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) ; Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) ; Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS) | Équipe 1 - Biodiversité des Écosystèmes Lotiques (BEL) ; Laboratoire d'Ecologie des Hydrosystèmes Naturels et Anthropisés (LEHNA) ; Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS) | Laboratoire Ecologie Fonctionnelle et Environnement (LEFE) ; Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3) ; Université de Toulouse (UT)-Université de Toulouse (UT)-Observatoire Midi-Pyrénées (OMP) ; Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) ; Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP) ; Université de Toulouse (UT) | Ecologie, Evolution, Ecosystèmes Souterrains ; Laboratoire d'Ecologie des Hydrosystèmes Fluviaux (EHF) ; Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO) ; Université de Rennes (UR)-Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) ; Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) ; Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS)
International audience
Afficher plus [+] Moins [-]Effects of intense agricultural practices on heterotrophic processes in streams
2009
Piscart, Christophe | Genoel, Romuald | Dolédec, Sylvain | Chauvet, Eric | Marmonier, Pierre | Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO) ; Université de Rennes (UR)-Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) ; Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS) | Laboratoire d'Ecologie des Hydrosystèmes Fluviaux (EHF) ; Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS) | Hydrobiologie et Ecologie Souterraines ; Laboratoire d'Ecologie des Hydrosystèmes Fluviaux (EHF) ; Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO) ; Université de Rennes (UR)-Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) ; Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) ; Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS) | Équipe 1 - Biodiversité des Écosystèmes Lotiques (BEL) ; Laboratoire d'Ecologie des Hydrosystèmes Naturels et Anthropisés (LEHNA) ; Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS) | Laboratoire Ecologie Fonctionnelle et Environnement (LEFE) ; Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3) ; Université de Toulouse (UT)-Université de Toulouse (UT)-Observatoire Midi-Pyrénées (OMP) ; Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) ; Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP) ; Université de Toulouse (UT) | Ecologie, Evolution, Ecosystèmes Souterrains ; Laboratoire d'Ecologie des Hydrosystèmes Fluviaux (EHF) ; Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO) ; Université de Rennes (UR)-Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) ; Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) ; Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS)
International audience
Afficher plus [+] Moins [-]GIS-Based Surface Runoff Modeling Using Empirical Technique For A River Basin In South India
2021
B. Prabhu Dass Batvari | K. Nagamani
Precipitation is the primary source of fresh water in the world. Surface runoff will happen when the amount of rainfall is greater than the soil’s infiltration capacity. In most water resource applications, runoff is the most important hydrological variable. Aside from these rainfall characteristics, there are a number of catchment-specific elements that have a direct impact on runoff amount and volume. This research focuses on estimating surface runoff over the lower Vellar basin, a river basin in the southern part of India, by integrating Soil Conservation Service-Curve Number (SCS-CN) method with GIS. This technique is one of the most common methods used by hydrologists for estimating surface runoff. Curve Number (CN) is an index established by the Natural Resource Conservation Service (NRCS) to denote the potential for stormwater runoff. The nature of the watershed is explored first by creating land use and land cover pattern followed by the preparation of slope, drainage, and location maps. The area taken for this study is the lower Vellar basin situated in the Cuddalore District of Tamil Nadu, India. The curve number is analyzed using the rainfall data of 15 years (2001-2015) and the runoff is being calculated. The watershed pattern of the study area is also explored being analyzed and executed. Preservation of the runoff water is also discussed.
Afficher plus [+] Moins [-]Modeling exposure to airborne metals using moss biomonitoring in cemeteries in two urban areas around Paris and Lyon in France
2022
Lequy, Emeline | Meyer, Caroline | Vienneau, Danielle | Berr, Claudine | Goldberg, Marcel | Zins, Marie | Leblond, Sébastien | de Hoogh, Kees | Jacquemin, Bénédicte
Exposure of the general population to airborne metals remains poorly estimated despite the potential health risks. Passive moss biomonitoring can proxy air quality at fine resolution over large areas, mainly in rural areas. We adapted the technique to urban areas to develop fine concentration maps for several metals for Constances cohort's participants. We sampled Grimmia pulvinata in 77 and 51 cemeteries within ∼50 km of Paris and Lyon city centers, respectively. We developed land-use regression models for 14 metals including cadmium, lead, and antimony; potential predictors included the amount of urban, agricultural, forest, and water around cemeteries, population density, altitude, and distance to major roads. We used both kriging with external drift and land use regression followed by residual kriging when necessary to derive concentration maps (500 × 500 m) for each metal and region. Both approaches led to similar results. The most frequent predictors were the amount of urban, agricultural, or forest areas. Depending on the metal, the models explained part of the spatial variability, from 6% for vanadium in Lyon to 84% for antimony in Paris, but mostly between 20% and 60%, with better results for metals emitted by human activities. Moss biomonitoring in cemeteries proves efficient for obtaining airborne metal exposures in urban areas for the most common metals.
Afficher plus [+] Moins [-]Interaction between walkability and fine particulate matter on risk of ischemic stroke: A prospective cohort study in China
2022
Yang, Zongming | Wu, Mengyin | Lu, Jieming | Gao, Kai | Yu, Zhebin | Li, Tiezheng | Liu, Wen | Shen, Peng | Lin, Hongbo | Shui, Liming | Tang, Mengling | Jin, Mingjuan | Chen, Kun | Wang, Jianbing
Living in walkable neighborhoods has been reported to be associated with a lower risk of cardiovascular disease. Features of walkable neighborhoods, however, may be related to particulate matter with an aerodynamic diameter ≤2.5 μm (PM₂.₅), which could increase risk of cardiovascular disease. The interaction effect between walkability and PM₂.₅ on risk of ischemic stroke remains to be elucidated. In this study, we recruited a total of 27,375 participants aged ≥40 years from Yinzhou District, Ningbo, Zhejiang Province, China to investigate the associations of walkability and PM₂.₅ with risk of ischemic stroke. We used amenity categories and decay functions to evaluate walkability and high-spatiotemporal-resolution land-use regression models to assess PM₂.₅ concentrations. We used Cox proportional hazards regression models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). During a median follow-up of 4.08 years, we identified a total of 637 incident cases of ischemic stroke in the entire cohort. Higher walkability was associated with a lower risk of ischemic stroke (quartile, Q4 vs. Q1 walkability: HR = 0.59, 95% CI: 0.47–0.75), whereas PM₂.₅ was positively associated with risk of ischemic stroke (Q4 vs. Q1 PM₂.₅: HR = 1.70, 95% CI: 1.29–2.25). Furthermore, we observed a significant interaction between walkability and PM₂.₅ on risk of ischemic stroke. Walkability was inversely associated with risk of ischemic stroke at lower PM₂.₅ concentrations, but this association was attenuated with increasing PM₂.₅ concentrations. Although walkable neighborhoods appear to decrease the risk of ischemic stroke, benefits may be offset by adverse effects of PM₂.₅ exposure in the most polluted areas. These findings are meaningful for future neighborhood design, air pollution control, and stroke prevention.
Afficher plus [+] Moins [-]Emissions of biogenic volatile organic compounds from urban green spaces in the six core districts of Beijing based on a new satellite dataset
2022
Li, Xin | Chen, Wenjing | Zhang, Hanyu | Xue, Tao | Zhong, Yuanwei | Qi, Min | Shen, Xianbao | Yao, Zhiliang
Urban green spaces (UGSs) are often positively associated with the health of urban residents. However, UGSs may also have adverse health effects by releasing biogenic volatile organic compounds (BVOCs) and increasing the ambient concentrations of ozone (O₃) and secondary organic aerosols in urban areas. BVOC emissions from UGSs might be underestimated because of the lack of consideration of the UGS land-use type in urban areas. As such, in this study, we used a newly released satellite dataset, Sentinel-2, with a resolution of 10 m, to derive the classification distribution of UGSs and predict the UGS emissions of BVOCs in Beijing in 2019. The results showed that the annual emissions of BVOCs from UGSs were approximately 2.9 Gg C (95% confidence interval (CI): 2.4–3.3) in the six core districts, accounting for approximately 39% of the total UGS emissions in Beijing. Compared with the results based on Sentinel-2, the BVOC emissions might be underestimated by approximately 37% (95% CI: 11–63) using the commonly used satellite dataset. UGSs produced the highest BVOC emissions in summer (from June to August), accounting for 75.2% of the annual emissions. UGSs contributed the most to the O₃ formation potential in summer, accounting for 41.5% of the total. We could attribute a considerable amount of the O₃ concentration (27.0 μg m⁻³, 95% CI: 21.4–32.6) to the UGS BVOCs produced in the core districts of Beijing in July. The new BVOC emissions dataset based on Sentinel-2 vegetation information facilitates modeling studies on the formation of surface O₃ in urban areas and assessments of the impact of UGSs on public health.
Afficher plus [+] Moins [-]Potential hot spots contaminated with exogenous, rare earth elements originating from e-waste dismantling and recycling
2022
Wang, Siyu | Xiong, Zhunan | Wang, Lingqing | Yang, Xiao | Yan, Xiulan | Li, You | Zhang, Chaosheng | Liang, Tao
Dismantling and recycling e-waste has been recognized as a potential emission source of rare earth elements (REEs). However, the presence of REEs in typical regional soils has yet to be studied. Given the potential health implications of such soil contamination, it is vital to study the characteristics, spatial distribution, and pollution level of REEs caused by e-waste dismantling as well as determine the influencing mechanism. This study focused on Guiyu Town as an example site, which is a typical e-waste dismantling base. From the site, 39 topsoil samples of different types were collected according to grid distribution points. Soil profiles were also collected in the dismantling and non-dismantling areas. The REE characteristic parameters showed that the REE distribution was abnormal and was affected by multiple factors. The results of the integrated pollution index showed that approximately 61.5% of soil samples were considered to be lightly polluted. Spatial distribution and correlation analysis showed that hot spots of REE-polluted soil coincided with known, main pollution sources. Moreover, there was a significant negative correlation (p ≤0.05) between the REE concentration and the distance from the pollution source. E-waste disassembly and recycling greatly affect the physical and chemical properties of the surrounding soil as well as downward migration areas. In the disassembly area, REE accumulated more easily in the surface layer (0–20 cm). Geographical detector results showed that distance factor was the main contribution factor for both light rare earth elements (LREE) and heavy rare earth element (HREE) (q = 34.59% and 53.33%, respectively). REE distribution in soil was nonlinear enhanced by different factors. Taken together, these results showed that e-waste disassembling and recycling not only directly affected the spatial distribution of REEs, but that their distribution was also affected by land use type and soil properties.
Afficher plus [+] Moins [-]Riparian vegetation as a trap for plastic litter
2022
Cesarini, Giulia | Scalici, Massimiliano
Plastic pollution represents the most widespread threaten throughout the world and, amongst aquatic habitats, freshwaters and in particular riparian zones seems to be highly disturbed. Since the plastic storage and accumulation on the riparian vegetation have not yet been deeply investigated, here, we focussed on the riparian zone's function in trapping plastic litter. To do so, we assessed the occurrence and density of plastics in different vegetated (arboreal, shrubby, herbaceous, reed, bush) and unvegetated types in 8 central Italian rivers, running in different land use contexts. Our results showed that plastic pieces, bags, bottles and food containers were the most abundant specific categories on the vegetated types, demonstrating the riparian vegetation role in trapping plastic litter. Specifically, the highest plastic density was found on the shrubby type suggesting that a tree shape retains plastics more easily than all other vegetated and unvegetated types. Shape and size classification of plastics are not significantly different between vegetated and unvegetated types. These findings allow to collect important information on how the riparian vegetation can be exploited in management activities for removing plastic litters from both freshwater and sea, being the former considered the main plastic source for the latter. This study highlights a further ecosystem service as mechanical filter provided by the riparian zone, even if further studies ought to be performed to understand the role of vegetation as plastic trap and the possible detrimental effects of plastics on the plant health status.
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