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A quantitative assessment of the behavior of metallic elements in urban soils exposed to industrial dusts near Dunkerque (northern France)

Abstract. In urban and industrialized areas, soil contamination and degradation caused by industrial dust deposition may pose significant health and environmental risks. Generally, the mobility and thus bioavailability of potentially toxic elements (PTEs) are key factors in these issues. In the Dunkerque agglomeration, one of the most industrialized regions in France, the soils are periodically exposed to metallurgical dust fallout, rich in PTEs. However, no study has reported on the behavior of these PTEs once integrated into the soils. The aim of this study is therefore to assess the fate of PTEs in the urban soils of Dunkerque in terms of vertical migration and potential bioavailability. Four soil short cores were collected in the city of Gravelines (Dunkerque agglomeration) along a gradient from industrial emitters to deposition sites. Each soil core was cut into discrete 1 cm sections for PTE concentration analyses (ICP-AES/MS). Single HCl extractions were performed to evaluate PTE mobility in soils and their behavior according to the current soil parameters. For this purpose, key soil properties were identified, including grain-size distribution, mineralogy, pH, cation exchange capacity (CEC), TOC (total organic carbon), calcium carbonates and water contents in addition to the soil chemical composition (XRF, ICP-AES/MS). The studied soils revealed globally low absorbent capacities for pollutants (CEC averaging 5.3meq/100g), partially counterbalanced by the buffering effect of calcium carbonates (contents ranging from 8 %–30 %). Near the industrial emitters, minor (1<EF<3) to moderately severe (5<EF<10) enrichment factors (EFs) were highlighted for industrial PTE (Cr, Ni, Mo, Mn, Cd and Zn) in the top 3 cm of soils near the industrial emitters. The contamination profiles of these soils are assigned to atmospheric inputs of metallurgical dust. Using a relatively strong leaching reagent (1 M HCl), we estimated a low vertical mobility for Cr, Ni and Mo (average leached ratios<25 %) in soils, suggesting their association with refractory phases (natural or anthropogenic). In contrast, Mn, Cd and Zn, which are related to industrial and/or urban sources, present a higher mobility (average leached ratios>60 % for Mn and Cd and about 44 % for Zn). Our study points out the stability of industrial PTEs in soils under the current physicochemical conditions (calcareous soils with a slightly basic pH of 7.8). In this context, the monitoring of industrial PTEs in these urban soils is highly recommended, considering (1) the presence of allotment gardens in the vicinity of emitters and (2) the potential evolution of soil conditions due to increasing flood events.

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Methane oxidation potential of soils in a rubber plantation in Thailand affected by fertilization

Abstract. Forest soils, as crucial sinks for atmospheric methane in terrestrial ecosystems, are significantly impacted by changes in ecosystem dynamics due to deforestation and agricultural practices. This study investigated the methane oxidation potential of rubber plantation soils in Thailand, focusing on the effect of fertilization. The methane oxidation activity of the topsoils (0–10 cm) in the dry season was extremely low and increased slightly in the wet season, with lower activity for higher fertilization levels. The methane oxidation potential of the topsoil was too low to explain the in situ methane uptake. Soils below 10 cm depth in unfertilized rubber plantations showed higher activity than the surface soils, and methane oxidation was detected down to, at least, 60 cm depth. In contrast, soils under the high-fertilization treatment exhibited similarly low activity of methane oxidation up to 60 cm depth compared to surface soils during both dry and wet seasons, indicating that fertilization of para rubber plantations negatively impacts the methane oxidation potential of the soils over the deep profile without recovery in the dry (off-harvesting) season with no fertilization. Methane uptake per area, estimated by integrating the methane oxidation potentials of soil layers, was comparable to the field flux data, suggesting that methane oxidation in the soil predominantly occurs at depths below the surface layer. These findings have significant implications for understanding the environmental impacts of tropical forest land uses on methane dynamics and underscore the importance of understanding methane oxidation processes in soils.

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Pooled error variance and covariance estimation of sparse in situ soil moisture sensor measurements in agricultural fields in Flanders

Abstract. Accurately quantifying errors in soil moisture measurements from in situ sensors at fixed locations is essential for reliable state and parameter estimation in probabilistic soil hydrological modeling. This quantification becomes particularly challenging when the number of sensors per field or measurement zone (MZ) is limited. When direct calculation of errors from sensor data in a certain MZ is not feasible, we propose to pool systematic and random errors of soil moisture measurements for a specific measurement setup and derive a pooled error covariance matrix that applies to this setup across different fields and soil types. In this study, a pooled error covariance matrix was derived using soil moisture sensor measurements from three TEROS 10 (Meter Group, Inc., USA) sensors per MZ and soil moisture sampling campaigns conducted over three growing seasons, covering 93 cropping cycles in agricultural fields with diverse soil textures in Belgium. The MZ soil moisture estimated from a composite of nine soil samples with a small standard error (0.0038 m3 m−3) was considered the “true” MZ soil moisture. Based on these measurement data, we established a pooled linear recalibration of the TEROS 10 manufacturer's sensor calibration function. Then, for each individual sensor as well as for each MZ, we identified systematic offsets and temporally varying residual deviations between the calibrated sensor data and sampling data. Sensor deviations from the “true” MZ soil moisture were defined as observational errors and lump both measurement errors and representational errors. Since a systematic offset persists over time, it contributes to the temporal covariance of sensor observational errors. Therefore, we estimated the temporal covariance of observational errors of the individual and the MZ-averaged sensor measurements from the variance of the systematic offsets across all sensors and MZ averages, while the random error variance was derived from the variance of the pooled residual deviations. The total error variance was then obtained as the sum of these two components. Due to spatial soil moisture correlation, the variance and temporal covariance of MZ-averaged sensor observational errors could not be derived accurately from the individual sensor error variances and temporal covariances, assuming that the individual observational errors of the three sensors in a MZ were not correlated with each other. The pooled error covariance matrix of the MZ-averaged soil moisture measurements indicated a significant autocorrelation of sensor observational errors of 0.518, as the systematic error standard deviation (σα‾= 0.033 m3 m−3) was similar to the random error standard deviation (σϵ‾= 0.032 m3 m−3). To illustrate the impact of error covariance in probabilistic soil hydrological modeling, a case study was presented incorporating the pooled error covariance matrix in a Bayesian inverse modeling framework. These results demonstrate that the common assumption of uncorrelated random errors to determine parameter and model prediction uncertainty is not valid when measurements from sparse in situ soil moisture sensors are used to parameterize soil hydrological models. Further research is required to assess to what extent the error covariances found in this study can be transferred to other areas and how they impact parameter estimation in soil hydrological modeling.

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Using 3D observations with high spatio-temporal resolution to calibrate and evaluate a process-focused cellular automaton model of soil erosion by water

Abstract. Future global change is likely to give rise to novel combinations of the factors which enhance or inhibit soil erosion by water. Thus, there is a need for erosion models, necessarily process-focused ones, which are able to reliably represent the rates and extents of soil erosion under unprecedented circumstances. The process-focused cellular automaton erosion model RillGrow is, given initial soil surface microtopography for a plot-sized area, able to predict the emergent patterns produced by runoff and erosion. This study explores the use of structure-from-motion photogrammetry as a means to calibrate and evaluate this model by capturing detailed, time-lapsed data for soil surface height changes during erosion events. Temporally high-resolution monitoring capabilities (i.e. 3D models of elevation change at 0.1 Hz frequency) permit the evaluation of erosion models in terms of the sequence of the formation of erosional features. Here, multiple objective functions using three different spatio-temporal averaging approaches are assessed for their suitability in calibrating and evaluating the model's output. We used two sets of data from field- and laboratory-based rainfall simulation experiments lasting 90 and 30 min, respectively. By integrating 10 different calibration metrics, the outputs of 2000 and 2400 RillGrow runs for, respectively, the field and laboratory experiments were analysed. No single model run was able to adequately replicate all aspects of either the field or the laboratory experiments. The multiple objective function approaches highlight different aspects of model performance, indicating that no single objective function can capture the full complexity of erosion processes. They also highlight different strengths and weaknesses of the model. Depending on the focus of the evaluation, an ensemble of objective functions may not always be necessary. These results underscore the need for more nuanced evaluation of erosion models, e.g. by incorporating spatial-pattern comparison techniques to provide a deeper understanding of the model's capabilities. Such calibrations are an essential complement to the development of erosion models which are able to forecast the impacts of future global change. For the first time, we use data with a very high spatio-temporal resolution to calibrate a soil erosion model.

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Soil contamination in arid environments and assessment of remediation applying surface evaporation capacitor model: a case study from the Judean Desert, Israel

Abstract. Due to the presence of highly pollutant industries in arid areas, many of the globe's arid areas are exposed to severe local soil contamination events. In this work, the nature of solute and contaminant transport in the sandy terraces of an ephemeral stream that was exposed to a severe pollution event was examined. Here, the Ashalim Basin in the Judean Desert, Israel, is utilized as a case study. In order to shed new light on contaminant distribution along the soil profile and on transport mechanisms in arid environments, three complementary approaches were used: (1) periodic on-site soil profile sampling, recording the annual solute transport dynamics; (2) laboratory analyses and controlled experiments in a rain simulator to characterize solute release and transport; and (3) numerical simulation, used to define and understand the main associated processes. The study highlights the persistent nature of the pollutants in these natural settings, which dictates that they remain near the soil surface despite the presence of sporadic rain events. It was shown that a vertical circulation of the contaminates is occurring with soil wetting and drying cycles. The “surface evaporation capacitor” concept of Or and Lehmann (2019) was examined and compared to field measurements and numerical simulations and was found to be a useful tool for predicting the fate of the contaminants along the soil profile.

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Calcium is associated with specific soil organic carbon decomposition products

Abstract. Calcium (Ca) may contribute to the preservation of soil organic carbon (SOC) in more ecosystems than previously thought. Here, we provide evidence that Ca is co-located with SOC compounds that are enriched in aromatic and phenolic groups, across different acidic soil types and locations with different ecosystem properties, differing in terms of climate, parent material, soil type, and vegetation. In turn, this co-localised fraction of Ca–SOC is removed through cation exchange, and the association is then only re-established during decomposition in the presence of Ca (Ca addition incubation). Thus, this highlights a causative link between decomposition and the co-location of Ca with a characteristic fraction of SOC. Decomposition increases the relative proportion of negatively charged functional groups, which can increase the propensity for the association between SOC and Ca; in turn, this association can inhibit dissolved organic carbon export or further decomposition. We propose that this mechanism could be driven by Ca hotspots at the microscale shifting local decomposition processes and thereby explaining the co-location of Ca with SOC of a specific composition across different acidic soil environments. Incorporating this biogeochemical process into Earth system models could improve our understanding, predictions, and management of carbon dynamics in soils, as well as accounting for their response to Ca-rich amendments.

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Gradual drying of permafrost peat decreases carbon dioxide production in drier peat plateaus but not in wetter fens and bogs

Abstract. Permafrost thawing of northern peatlands can cause the local collapse of peat plateaus into much wetter thermokarst bogs and fens, dominated by Sphagnum mosses and graminoids, respectively. However, permafrost thaw can also improve landscape drainage and, thus, lead to the regional drying of peatlands. How gradual drying of these thawing permafrost peatlands affects the subsequent microbial production of carbon dioxide (CO2) and nitrous oxide (N2O) is uncertain because of landscape heterogeneity in moisture, peat quality, and vegetation. Here, we collected near-surface peat samples (5–20 cm) from Alberta, Canada, across transects representing a thaw gradient from peat plateaus to a fen or bog. We incubated the samples for 2 weeks under either field moisture or under gradual drying to reduce moisture by ∼ 80 %. Only the fen sites, which had high moisture and a high percentage of total N, produced N2O (0.06–6.7 µg N2O-N per gram of dry peat), but N2O production was unaffected by the drying treatments. Peat CO2 production was greatest from the fen and the youngest stage of the thermokarst bog, despite them having the most water-saturated field conditions, likely reflecting their more labile plant inputs and, thus, more decomposable peat. We found that CO2 respiration was enhanced by drying at relatively wet sites like the fens and young bog but was suppressed by drying in relatively drier peat plateaus. Further, gradual drying increased 13C-CO2 respiration, suggesting a possible shift to more decomposed, older C being lost with peat drying. Thus, our study suggests that future peat CO2 and N2O production from peatlands will depend on whether peat plateaus thaw into fens or bogs and on their diverging responses of peat respiration to more moisture-limited conditions.

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Missing the input: the underrepresentation of plant physiology in global soil carbon research

Abstract. Plant processes regulating the quantity and quality of soil organic carbon inputs such as photosynthesis, above- and below-ground plant growth, and root exudation are integral to our understanding of soil carbon dynamics. However, based on a bibliometric analysis including more than 55 000 scientific papers, we found that plant physiology has been severely underrepresented in global soil organic carbon research. Less than 10 % of peer-reviewed soil organic carbon research published in the last century addressed plant physiological processes relevant to soil carbon inputs. Similarly, plant physiology was overlooked by the overwhelming majority (>90 %) of the peer-reviewed literature investigating linkages between soil organic carbon, climate change, and land use and land management. These findings show that our understanding of both soil carbon dynamics and the carbon sequestration potential of terrestrial ecosystems is largely built on research that neglects the fundamental processes underlying organic carbon inputs. We maintain that the active engagement of plant scientists in soil carbon research is imperative for shedding light on this blind spot. Long-term interdisciplinary research will be essential for developing a comprehensive perspective of soil carbon dynamics and informing and designing effective policies that support soil carbon sequestration.

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The clay mineralogy rather than the clay content determines radiocaesium adsorption in soils on a global scale

Abstract. The transfer of radiocaesium (137Cs) from soil to crops is the main long-term radiation risk after nuclear accidents. The prevailing concept is that 137Cs sorption in soil – and, hence, its bioavailability – is controlled by soil clay content (0–2 µm). This study tested this assumption using 24 soils collected worldwide. The radiocaesium interception potential (RIP), i.e., 137Cs adsorption, was measured for the bulk soils and for their clay and silt fractions. The RIP varied by a factor of 438 among soils and was unrelated to the clay content (p > 0.05). The RIP in the clay fractions was lowest for young volcanic soils with allophane and mica and for highly weathered tropical soils with kaolinite. In contrast, RIP values about 2 orders of magnitude higher were found in intermediate-weathered temperate soils dominated by illite. Soil RIP was, hence, related to soil illite content (R2= 0.50; p < 0.001). A significant fraction of soil RIP originated from clay minerals embedded in the silt fraction. The sum of RIP in clay and silt fractions overestimated the soil RIP by, on average, a factor of 2, indicating that the isolation of clay opens selective 137Cs sorption sites inaccessible in intact soils. Soil mineralogy, not just clay content, governs soil RIP. In terms of validity, existing 137Cs bioavailability models require recalibration for use on a global scale.

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