This study presents a new, low-cost sensor system for measuring soil CO₂ gas continuously over long periods. Built using easy-to-get hardware components, the system costs USD700. It was tested for six months in desert soil, proving to be reliable, easy to maintain, and capable of capturing important changes in soil CO₂. The CO₂ flux calculations from this system closely matched those from a standard measurement device, making it a practical tool for research requiring multiple sensor systems.

This study explores the link between soil magnetic susceptibility and cation exchange capacity (CEC) to improve prediction models for CEC in European soils. Results show that magnetic susceptibility significantly enhances CEC prediction in sandy soils, achieving high accuracy (R² = 0.94). This offers a rapid, cost-effective way to estimate CEC, emphasizing the value of geophysical data integration in soil assessment.

We developed a method to estimate errors in soil moisture measurements using limited sensors and infrequent sampling. By analyzing data from 93 cropping cycles in agricultural fields in Belgium, we identified both systematic and random errors for our sensor setup. This approach reduces the need for extensive sensor networks and is applicable to agricultural and environmental monitoring, and ensures more reliable soil moisture data, enhancing water management and improving model predictions.

This study evaluated the impact of diverse cover crops on topsoil mineral nitrogen (SMN), N₂O emissions, and carbon (C) sequestration. Non-legume cover crops reduced SMN levels, showed potential for mitigating indirect N₂O emissions, and increased C sequestration, but did not significantly reduce cumulative N₂O emissions compared to fallow. The results highlight the need for tailored cover crop strategies to balance SMN capture, N₂O emissions, and C sequestration effectively.

This study examines soils in the highly industrialized Dunkerque agglomeration in France. Our work reveals the contamination of urban soils by metals from industrial dust, including Cr, Ni, Mo, Mn, Cd and Zn. While Cr, Ni and Mo are relatively stable in soils, Mn, Cd and Zn are more mobile and may pose environmental and health problems. Our findings highlight the need of careful consideration of future land use near industrial emitters, such as allotment gardens, due to these potential hazards.

This study investigates if more detailed water depth and water chemistry data can improve greenhouse gas (GHG) emission estimations from rewetted peatlands under paludiculture. Results showed that in enriched nutrient areas, greenhouse gas emissions can potentially be reduced by paludiculture, depending on the end use of the harvested biomass, additionally, more data on water depth and water chemistry can improve GHG emission estimations, which is especially relevant in rewetted peatlands.

To use fertilizers more effectively, non-invasive geophysical methods can be used to understand nutrient distribution in the soil. We utilize in a long-term field study geophysical techniques to study soil properties and conditions under different fertilizer treatments. We compared the geophysical responds with soil samples and soil sensor data. Especially, electromagnetic induction and electrical resistivity tomography were effective in monitoring changes in nitrate levels over time.

Tropical forest soils are vital for methane uptake, but deforestation and agriculture can alter soil methane oxidation. An experiment in Thailand shows that fertilization significantly suppresses methane oxidation in rubber plantation soils, affecting depths up to 60 cm. Without fertilization, deeper soil layers (below 10 cm) actively oxidize methane. These findings suggest that fertilization negatively impacts the methane uptake capacity of deep-layer soils in rubber plantations.

We integrate various methods to create soil property maps for soil surveyors, which they can utilize as a reference before beginning their fieldwork. A new sampling design based on a geographical stratification is proposed focussing on local feature space variability. It allows for a systematic analysis of predictive accuracy for varying densities. The spectral and spatial models yielded high accuracies. Our study highlights the value of integrating pedometric technologies in soil surveys.

Soil microbial fuel cell (SMFC) to eliminate Cr(VI) from paddy soil and metal tolerance analysis; 76 % of Cr(VI) elimination, 0.97 V power output, and heavy metal resistance genes elevation; Enrichment of exoelectrogens, Cr(VI) reducers, and tolerators contributed to SMFC performance; Bio-physical adsorption and electrochemical-microbial reduction simultaneously reduced Cr(VI).

This study shows that cultivating natural soils disrupts crucial mineral-organic associations, leading to carbon loss and reduced soil fertility. By analyzing soil samples from a forest and crop andosols, we found that these associations exist as amorphous coprecipitates (nanoCLICs). Cultivation reduces quantities of nanoCLICs by 50 %, highlighting their vulnerability to environmental changes and the need to develop strategies to preserve them to maintain soil fertility.

Soil health is of critical importance and many soils are threatened. Benchmarking sustainable soil management is a challenge as there is no comprehensive indicator set. Here, I introduce a novel conceptual approach to soil health, representing soil functions as complex and hard to measure variables. I outline a new methodology to study soil multifunctionality using latent variable models to represent soil functions. This is a new starting point for soil health research and ultimately monitoring.