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.

International audience

International audience | The paper presents an analysis of runoff behaviour of four urban catchments between the municipalities of Belo Horizonte and Contagem in Brazil, linked to their land use. Two years of online measurement of flow data, combined with spatial analysis, was linked through runoff modelisation with EPA SWMM. The coefficients of Nash obtained varying between 0.75 and 0.87 demonstrated an adequate modelling approach. A 1-year rain series was applied to evaluate the runoff behaviour of actual land cover and that of 2002. The peak flows normalised to watershed surfaces revealed as the most urbanised (85%) watershed Ressaca with 178 L/ha/s, three times more runoff intensive than the least urbanised (41%) Mergulhão with 67 L/ha/s. Statistical analysis of land cover data and modelling results on watershed and sub-watershed level showed main correlations between hydrological parameters such as peak flow, average event flow and restitution time, but also between land cover and runoff coefficient. This approach gave a linear relation between runoff and green surface, with a runoff coefficient of 0.86 for fully urbanised zone and 0.43 for full “green” cover. Prospective simulation with actual urbanisation rates varying from 4 to 34 ha/year suggested an increase between 6 and 18% of the flows and a possible end of urbanisation within the next two to three decades. These findings should contribute to a better understanding of hydrological impact of Belo Horizonte urbanisation and to the restauration of its Lake Pampulha.

Nitrogen loss via overland flow from agricultural land use is a global threat to waterways. On-farm denitrifying woodchip bioreactors can mitigate NO₃⁻ exports by increasing denitrification capacity. However, denitrification in sub-optimal conditions releases the greenhouse gas nitrous oxide (N₂O), swapping the pollution from aquatic to atmospheric reservoirs. Here, we assess NO₃⁻-N removal and N₂O emissions from a new edge-of-field surface-flow bioreactor during ten rain events on intensive farming land. Nitrate removal rates (NRR) varied between 5.4 and 76.2 g NO₃⁻-N m⁻³ wetted woodchip d⁻¹ with a mean of 30.3 ± 7.3 g NO₃⁻-N m⁻³. The nitrate removal efficiency (NRE) was ∼73% in ideal hydrological conditions and ∼18% in non-ideal conditions. The fraction of NO₃⁻-N converted to N₂O (rN₂O) in the bioreactor was ∼3.3 fold lower than the expected 0.75% IPCC emission factor. We update the global bioreactor estimated Q₁₀ (NRR increase every 10 °C) from a recent meta-analysis with previously unavailable data to >20 °C, yielding a new global Q₁₀ factor of 3.1. Mean N₂O CO₂-eq emissions (431.9 ± 125.4 g CO₂-eq emissions day⁻¹) indicate that the bioreactor was not significantly swapping aquatic NO₃⁻ for N₂O pollution. Our estimated NO₃⁻-N removal from the bioreactor (9.9 kg NO₃⁻-N ha⁻¹ yr⁻¹) costs US$13.14 per kg NO₃⁻-N removed and represents ∼30% NO₃⁻-N removal when incorporating all flow and overflow events. Overall, edge-of-field surface-flow bioreactors seem to be a cost-effective solution to reduce NO₃⁻-N runoff with minor pollution swapping to N₂O.

Excessive enrichment of fluoride threatens ecological stability and human health. The high-fluoride groundwater in the Chagan Lake area has existed for a long time. With the land consolidation and irrigation area construction, the distribution and migration process of fluoride have changed. It is urgent to explore the evolution of fluoride under the dual effects of nature and human. Based on 107 groundwater samples collected in different land use periods, hydrogeochemistry and isotope methods were combined to explore the evolution characteristics and hydrogeochemical processes of fluoride in typical high-fluoride background area and elucidate the impact of anthropogenic activities on fluoride migration. The results indicate that large areas of paddy fields are developed from saline-alkali land, and its area has increased by nearly 30%. The proportion of high-fluoride groundwater (>2 mg/L) has increased by nearly 10%, mainly distributed in the new irrigation area. Hydrogeochemical processes such as dissolution of fluorine-containing minerals, precipitation of carbonate minerals and exchange of Na⁺, Ca²⁺ on the water-soil interface control the enrichment of fluoride. The groundwater d-excess has no obvious change with the increase of TDS, and human activities are one of the reasons for the increase of fluoride. The concentration of fluoride is diluted due to years of diversion irrigation in old irrigation area, whereas the enrichment of δ²H, δ¹⁸O and Cl⁻ in new irrigation area indicates that the vertical infiltration of washing alkali and irrigation water brought fluoride and other salts to groundwater. Fertilizer and wastewater discharges also contribute to the accumulation of fluoride, manifesting as co-increasing nitrate and chloride salts. The results of this study provide a new insight into fluoride migration under anthropogenic disturbance in high-fluoride background areas.

Groundwater nitrate (NO₃⁻) pollution is a worldwide environmental problem. Therefore, identification and partitioning of its potential sources are of great importance for effective control of groundwater quality. The current study was carried out to identify the potential sources of groundwater NO₃⁻ pollution and determine their apportionment in different land use/land cover (LULC) types in a traditional agricultural area, Weining Plain, in Northwest China. Multiple hydrochemical indices, as well as dual NO₃⁻ isotopes (δ¹⁵N–NO₃ and δ¹⁸O–NO₃), were used to investigate the groundwater quality and its influencing factors. LULC patterns of the study area were first determined by interpreting remote sensing image data collected from the Sentinel-2 satellite, then the Bayesian stable isotope mixing model (MixSIAR) was used to estimate proportional contributions of the potential sources to groundwater NO₃⁻ concentrations. Groundwater quality in the study area was influenced by both natural and anthropogenic factors, with anthropological impact being more important. The results of LULC revealed that the irrigated land is the dominant LULC type in the plain, covering an area of 576.6 km² (57.18% of the total surface study area of the plain). On the other hand, the results of the NO₃⁻ isotopes suggested that manure and sewage (M&S), as well as soil nitrogen (SN), were the major contributors to groundwater NO₃⁻. Moreover, the results obtained from the MixSIAR model showed that the mean proportional contributions of M&S to groundwater NO₃⁻ were 55.5, 43.4, 21.4, and 78.7% in the forest, irrigated, paddy, and urban lands, respectively. While SN showed mean proportional contributions of 29.9, 43.4, 61.5, and 12.7% in the forest, irrigated, paddy, and urban lands, respectively. The current study provides valuable information for local authorities to support sustainable groundwater management in the study region.

We determined the distribution and temporal variation of Carbapenem Resistant Enterobacterales (CRE), carbapenemase-encoding genes and other antibiotic resistance genes (ARGs) in a highly polluted river (Lis River; Portugal), also assessing the potential influence of water quality to this distribution. Water samples were collected in two sampling campaigns performed one year apart (2018/2019) from fifteen sites and water quality was analyzed. CRE were isolated and characterized. The abundance of four ARGs (blaNDM, blaKPC, tetA, blaCTX₋M), two Microbial Source Tracking (MST) indicators (HF183 and Pig-2-Bac) and the class 1 integrase gene (IntI1) was measured by qPCR. confirmed the poor quality of the Lis River water, particularly in sites near pig farms. A collection of 23 CRE was obtained: Klebsiella (n = 19), Enterobacter (n = 2) and Raoultella (n = 2). PFGE analysis revealed a clonal relationship between isolates obtained in different sampling years and sites. All CRE isolates exhibited multidrug resistance profiles. Klebsiella and Raoultella isolates carried blaKPC while Enterobacter harbored blaNDM. Conjugation experiments were successful for only four Klebsiella isolates. All ARGs were detected by qPCR on both sampling campaigns. An increase in ARGs and IntI1 abundances was detected in sites located downstream of wastewater treatment plants. Strong correlations were observed between blaCTX₋M, IntI1 and the human-pollution marker HF183, and also between tetA and the pig-pollution marker Pig-2-bac, suggesting that both human- and animal-derived pollution in the Lis River are a potential source of ARGs. Plus, water quality parameters related to eutrophication and land use were significantly correlated with ARGs abundances. Our findings demonstrated that the Lis River encloses high levels of antibiotic resistant bacteria and ARGs, including CRE and carbapenemase-encoding genes. Overall, this study provides a better understanding on the impacts of water pollution resulting from human and animal activities on the resistome of natural aquatic systems.

Land use regression (LUR) models have been widely used in epidemiological studies and risk assessments related to air pollution. Although efforts have been made to improve the performance of LUR models so that they capture the spatial heterogeneity of fine particulate matter (PM₂.₅) in high-density cities, few studies have revealed the vertical differences in PM₂.₅ exposure. This study proposes a three-dimensional LUR (3-D LUR) assessment framework for PM₂.₅ exposure that combines a high-resolution LUR model with a vertical PM₂.₅ variation model to investigate the results of horizontal and vertical mobile PM₂.₅ monitoring campaigns. High-resolution LUR models that were developed independently for daytime and nighttime were found to explain 51% and 60% of the PM₂.₅ variation, respectively. Vertical measurements of PM₂.₅ from three regions were first parameterized to produce a coefficient of variation for the concentration (CVC) to define the rate at which PM₂.₅ changes at a certain height relative to the ground. The vertical variation model for PM₂.₅ was developed based on a spline smoothing function in a generalized additive model (GAM) framework with an adjusted R² of 0.91 and explained 92.8% of the variance. PM₂.₅ exposure levels for the population in the study area were estimated based on both the LUR models and the 3-D LUR framework. The 3-D LUR framework was found to improve the accuracy of exposure estimation in the vertical direction by avoiding exposure estimation errors of up to 5%. Although the 3-D LUR-based assessment did not indicate significant variation in estimates of premature mortality that could be attributed to PM₂.₅, exposure to this pollutant was found to differ in the vertical direction. The 3-D LUR framework has the potential to provide accurate exposure estimates for use in future epidemiological studies and health risk assessments.

Spatiotemporal variability complicates source apportionment of metals in urban lakes, especially when rainfall drives urban non-point source pollution. As, Cd, Cr, Pb, Hg, Ag, Co, Cu, Fe, Mn, Ni, Sb, Sr and Zn concentrations in 648 water samples collected before and after rain in 6 urban lakes of Beijing, China were determined during 2013–2015. The response of metals concentrations after rain to the interaction between rainfall and antecedent dry days was significant. Metals concentrations were normalized pursuant to the interaction effect as the input of positive matrix factorization (PMF) to develop the interaction normalized-PMF (IN-PMF). Four primary pollution sources were diagnosed. Sediment release was considered to be the main source of Fe, Co and Ni independent of rainfall. Hg, As and some Cr associated with pesticides and fertilizers were likely to come from soil erosion and runoff from green space. It is probable that road runoff was the dominant source for heavy metals related to traffic emissions, including Pb, Cd, Cu, Sb, Mn and Zn. Cr, Sr and some Cu and Zn as key elements of rooftops can be regarded as from roof runoff. The IN-PMF lowered roof and road runoff contributions and raised the contribution of soil erosion from green space, with Pb, Sb, Cu, Zn, Cd and Mn increasing by 15.9%, 10.7%, 13.1%, 12.2%, 13.3% and 16.8%. The results shed more light on the stormwater runoff pollution mitigation on impervious surfaces and metals enrichment problems in infiltration soil on green space in the low impact development (LID) setting. The Bayesian network revealed the spatial variability of transport and fate of metal elements from land surfaces to urban lakes, supplementing the secondary pollution sources from different land use. This study will provide new insights for source apportionment of non-point source pollution under the background of sponge city construction.