The chemical composition and sources of road dust, and of tire and road wear particles–A review

The Science of The Total Environment, Год журнала: 2024, Номер 926, С. 171694 - 171694

Опубликована: Март 13, 2024

To gain better understanding of how the transition to electric vehicles affects road dust (RD) composition, and potential health environmental risks, it is crucial analyze chemical composition RD identify its sources. Sources include wear tire tread (TT), brake (BW) (RW). A relevant component are particles (TRWPs). This literature review compiles data on bulk sources, in Asia, Europe North America TRWP as a component. The focus elements such Cd, Co, Cr, Cu, Ni, Pb, V, Zn. Although comparability global limited due differences sampling analytical methods, no significant from Europe, were found for most investigated studied, except V. Source analyzed using elemental markers. On average TT, BW, RW contributed 3 %, 1 96 respectively. highest concentrations TT (9 %) BW (2 observed particle size fraction ≤ 10 μm. It recommended that these results be verified additional marker compounds. TRWPs different sources revealed (i) isolated tunnel sample composed 31 % 6 62 RW, (ii) test material stands show similar content but likely because e.g., missing BW. Therefore, need chemically characterized prior their use hazard testing validate representativeness.

Язык: Английский

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Deep optimization of water quality index and positive matrix factorization models for water quality evaluation and pollution source apportionment using a random forest model

Environmental Pollution, Год журнала: 2024, Номер 347, С. 123771 - 123771

Опубликована: Март 15, 2024

Язык: Английский

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How the EU Soil Observatory is providing solid science for healthy soils

European Journal of Soil Science, Год журнала: 2024, Номер 75(3)

Опубликована: Май 1, 2024

Abstract Healthy soils are essential for sustainable food production, achieving climate neutrality and halting the loss of biodiversity. The European Commission turned spotlights on these vital aspects with launch EU Soil Observatory (EUSO) in 2021 to support Green Deal. Also, Strategy 2030 proposed Monitoring Law marked a major milestone soil protection. This article provides an overview functioning EUSO within this policy context. Through its activities, supports EU‐wide monitoring system wide range areas. Moreover, monitors state health through Health Dashboard. comprehensive easy understandable tool shows, first time, where current scientific evidence converges indicate areas likely be affected by degradation. Furthermore, research innovation, enhances capacity functionality Data Centre citizen engagements regarding matters. Overall, since 2021, has successfully taken up role principal knowledge hub information data underpin development implementation. Also next years, will continue provide monitor, safeguard restore EU.

Язык: Английский

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Modeling arsenic in European topsoils with a coupled semiparametric (GAMLSS-RF) model for censored data

Environment International, Год журнала: 2024, Номер 185, С. 108544 - 108544

Опубликована: Март 1, 2024

Arsenic (As) is a versatile heavy metalloid trace element extensively used in industrial applications. As carcinogen, poses health risks through both inhalation and ingestion, associated with an increased risk of liver, kidney, lung, bladder tumors. In the agricultural context, repeated application arsenical products leads to elevated soil concentrations, which are also affected by environmental management variables. Since exposure risks, effective assessment tools support policies needed. However, most comprehensive data available, Land Use/Cover Area frame statistical Survey (LUCAS) database, contains severe limitations due high detection limits. Although within International Organization for Standardization standards, limits preclude adoption standard methodologies analysis. The present work focused on developing new method model contamination European soils using LUCAS samples. We introduce GAMLSS-RF model, novel approach that couples Random Forests Generalized Additive Models Location, Scale, Shape. semiparametric can capture non-linear interactions among input variables while accommodating censored non-censored observations be calibrated include information from other campaign databases. After fitting validating spatial we produced European-scale concentration maps at 250 m resolution evaluated patterns against reference values (i.e., two action levels background concentration). found significant variability across continent, lower concentrations Northern countries higher Portugal, Spain, Austria, France Belgium. By overcoming existing databases methodologies, provides alternative way handle highly data. consists valuable probabilistic tool assessing soils, contributing informed policy-making protection.

Язык: Английский

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Quantitative analysis of the compliance of EU Sewage Sludge Directive by using the heavy metal concentrations from LUCAS topsoil database

Environmental Science and Pollution Research, Год журнала: 2024, Номер unknown

Опубликована: Янв. 16, 2024

Abstract In the European Union (EU), a common understanding of potential harmful effect sewage sludge (SS) on environment is regulated by Sewage Sludge Directive 86/278/EEC (SSD). Limit values (LVs) for concentrations heavy metals in soil are listed Impact Assessment this directive, and they were transposed EU member states using different criteria. Member adopted either single limit or based factors such as pH texture to define maximum soils. Our work presents first quantitative analysis SSD at level Land Use Coverage Area Frame Survey (LUCAS) 2009 topsoil database. The reference arranged taking into account upper value (EU_UL) lower (EU_LL) each metal (arsenic, cadmium, copper, chromium, mercury, nickel, lead, zinc) well (cadmium, introduced Annex IA. Single integrated contamination rate indices developed identify those agricultural soils that exceeded metal. total, 10%, 36%, 19% LUCAS samples values. Additionally, 12% 16% concentration least one when LVs fixed following Strategy II compared national ones I. Generally, all apply similar stricter than laid down SSD. indicates choosing quantitatively affects further actions monitoring remediation contaminated actual parameters, from database, could be used SSD-involved policy stakeholders not only lay but also compliance grade surveys over time (past upcoming datasets).

Язык: Английский

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Empirical estimation of saturated soil-paste electrical conductivity in the EU using pedotransfer functions and Quantile Regression Forests: A mapping approach based on LUCAS topsoil data

Geoderma, Год журнала: 2025, Номер 454, С. 117199 - 117199

Опубликована: Фев. 1, 2025

Язык: Английский

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Prediction of Zinc, Cadmium, and Arsenic in European Soils Using Multi-End Machine Learning Models

Journal of Hazardous Materials, Год журнала: 2025, Номер 490, С. 137800 - 137800

Опубликована: Март 3, 2025

Язык: Английский

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Geospatial evaluation of the agricultural suitability and land use compatibility in Europe's temperate continental climate region

International Soil and Water Conservation Research, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Land suitability assessment is used in conjunction with geographic information systems to spatially model diverse aspects of soil functions, having the potential facilitate a sustainable increase agricultural production, reduce land degradation, or aid humans adapting climate change. Compared existing datasets, this study provides new higher resolution geospatial for several crops and uses temperate continental across Europe. To we data depicting seventeen eco-pedological indicators (e.g. texture, pH, porosity, temperature, precipitation, slope). evaluate how utilized, maps have been cross-tabulated crop map. Over entire area, wheat barley showed significant suitable southern part, potatoes, sugar beet exhibited highest extent northern parts, while corn sunflower much lower land. Water table depth, terrain slope, SOC, topsoil texture emerged as limiting factors area. Our results show that arable does not space left expansion crops, however, identified regions extensive cultivation on unsuitable more such barley, sunflower, beet, potato. It seems one action can enhance practices area better allocate each cultivated lands.

Язык: Английский

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Geospatial prediction of total soil carbon in European agricultural land based on deep learning

The Science of The Total Environment, Год журнала: 2023, Номер 912, С. 169647 - 169647

Опубликована: Дек. 26, 2023

Язык: Английский

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Application of untreated versus pyrolysed sewage sludge in agriculture: A life cycle assessment

Journal of Cleaner Production, Год журнала: 2024, Номер 454, С. 142249 - 142249

Опубликована: Апрель 15, 2024

Язык: Английский

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