Soil Temperature Research Articles

Long-term phosphorus addition alters soil enzyme kinetics with limited impact on their temperature sensitivity in an alpine meadow.

The soil enzymes excreted by soil microorganisms and plant roots are essential for decomposing organic matter and regulating ecosystem function. However, phosphorus (P) deposition effects on the kinetics and thermodynamics of soil enzymes remain poorly understood. Here, a 11-year, multi-level P addition experiment was conducted in the alpine meadows of the Qinghai-Tibet Plateau, a region known as one of the most sensitive to global changes. We measured Vmax, Km and their temperature sensitivities (Q10) for six hydrolytic enzymes, along with soil properties and microbial community composition. P addition significantly reduced total soil organic C (SOC) and soil available N (NH4+-N and NO3--N), but increased dissolved organic N (DON), soil total P (TP) and available P (AP). Furthermore, P addition markedly decreased the abundance of Ascomycota, while increased that of Basidiomycota. However, the abundance of bacterial phyla remained unaffected by P addition. We found that P addition significantly increased the Vmax of β-glucosidase (BG), β-xylosidase (BX), cellobiohydrolase (CBH) and N-acetyl-glucosaminidase (NAG), but decreased that of acid phosphatase (APA) and L-leucine-aminopeptidase (LAP). P addition had no effect on Km of BX and CBH, but significantly lowered it for other enzymes. Specifically, P addition significantly reduced the Vmax-Q10 of BG and BX, but did not affect that of other enzymes. Conversely, P addition significantly increased the Km-Q10 of BG, while decreased the Km-Q10 of NAG, with no change in other enzymes. Variation partitioning analysis confirmed that microbial biomass and fungal community composition are crucial in influencing Vmax, Km, as well as their temperature sensitivities. This study highlights the critical influence of P addition on soil enzyme kinetics and temperature sensitivity and their relationships with microbial community, enhancing predictions of how microbial community and substrate availability interact to regulate the soil nutrient cycle under global environmental changes.

Permafrost Thawing and Estimates of Vulnerable Carbon in the Northern High Latitude

AbstractThe degradation of permafrost in the Northern Hemisphere is expected to persist and potentially worsen as the climate continues to warm. Thawing permafrost results in the decomposition of organic matter frozen in the ground, which stores large amounts of soil organic carbon (SOC), leading to carbon being emitted into the atmosphere in the form of carbon dioxide and methane. This process could potentially contribute to positive feedback between global climate change and permafrost carbon emissions. Accurate projections of permafrost thawing are key to improving our estimates of the global carbon budget and future climate change. Using data from the latest generation of climate models (CMIP6), this paper explores the challenges involved in assessing the annual active layer thickness (ALT), defined as the maximum annual thaw depth of permafrost, and estimated carbon released under various Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5). We find that the ALT estimates derived from CMIP6 model soil temperatures show significant deviations from the observed ALT values. This could lead to inconsistent estimates of carbon release under climate change. We propose a simplified approach to improve the estimate of the changes in ALT under future climate projections. These predicted ALT changes, combined with present-day observations, are used to estimate vulnerable carbon under future climate projections. CMIP6 models project ALT changes of 0.1–0.3 m per degree rise in local temperature, resulting in an average deepening of approx. 1.2–2.1 m in the northern high latitudes under different scenarios. With increasing temperatures, permafrost thawing starts in Southern Siberia, Northern Canada, and Alaska, progressively extending towards the North Pole by the end of the century under high emissions scenarios (SSP5-8.5). Using projections of ALT changes and vertically resolved SOC data, we estimate the ensemble mean of decomposable carbon stocks in thawed permafrost to be approximately 115 GtC (gigatons of carbon in the form of CO2 and CH4) under SSP1-2.6, 180 GtC under SSP2-4.5, 260 GtC under SSP3-7.0, and 300 GtC under SSP5-8.5 by the end of the century.

A novel conceptual model coupling crop growth and soil water-heat-salt processes in arid area

In arid farmland, the soil water, heat, and salt movement tightly couple with crop growth. Accurately expressing the coupling relationships is essential to understanding the complex agricultural hydrological system and enhancing agricultural water productivity. A novel conceptual model coupling crop growth, soil water-heat-salt movement, and energy balance in arid area with shallow groundwater was developed which has potential for use in large heterogeneous irrigation districts. The model can calculate the crop-soil system through the effect of crop canopy and leaf area index (LAI) on potential evapotranspiration and the stress of soil moisture, temperature, and salinity status to root water uptake. The energy balance equation was used for calculating the upper boundary condition for soil temperature. The model was calibrated and validated using four years of field monitoring data for two crops located in a typical arid agricultural area in China. The model performed well in simulated field hydrology and crop growth processes. The model can capture soil water-heat-salt dynamics and model field evapotranspiration with RMSE below 1.14 mm/day, and crop transpiration with R2 of above 0.61. Furthermore, the model can accurately describe crop growth processes with R2 of 0.95 and RMSE of 0.49 for LAI, and R2 of 0.99, RMSE of 12.95 cm for crop height. With few parameters, our work supplies an alternative method for quantifying agricultural hydrological processes. In particular, the model has potential to simulate the regional crop growth and soil water-heat-salt processes for heterogeneous agricultural area. This method is helpful in determining the scientific irrigation management schedule.

Research on Fault Diagnosis of Agricultural IoT Sensors Based on Improved Dung Beetle Optimization–Support Vector Machine

The accuracy of data perception in Internet of Things (IoT) systems is fundamental to achieving scientific decision-making and intelligent control. Given the frequent occurrence of sensor failures in complex environments, a rapid and accurate fault diagnosis and handling mechanism is crucial for ensuring the stable operation of the system. Addressing the challenges of insufficient feature extraction and sparse sample data that lead to low fault diagnosis accuracy, this study explores the construction of a fault diagnosis model tailored for agricultural sensors, with the aim of accurately identifying and analyzing various sensor fault modes, including but not limited to bias, drift, accuracy degradation, and complete failure. This study proposes an improved dung beetle optimization–support vector machine (IDBO-SVM) diagnostic model, leveraging the optimization capabilities of the former to finely tune the parameters of the Support Vector Machine (SVM) to enhance fault recognition under conditions of limited sample data. Case analyses were conducted using temperature and humidity sensors in air and soil, with comprehensive performance comparisons made against mainstream algorithms such as the Backpropagation (BP) neural network, Sparrow Search Algorithm–Support Vector Machine (SSA-SVM), and Elman neural network. The results demonstrate that the proposed model achieved an average diagnostic accuracy of 94.91%, significantly outperforming other comparative models. This finding fully validates the model’s potential in enhancing the stability and reliability of control systems. The research results not only provide new ideas and methods for fault diagnosis in IoT systems but also lay a foundation for achieving more precise, efficient intelligent control and scientific decision-making.

Microbial Bioremediation of Petroleum Contaminated Soil: Structural Complexity, Degradation Dynamics and Advanced Remediation Techniques

Soil contamination with petroleum hydrocarbons poses a significant environmental challenge, necessitating effective remediation strategies to mitigate ecological risks. This review paper systematically examines the current state of knowledge regarding soil contamination with petroleum hydrocarbons, focusing on diverse sources and the extent of contamination. The investigation encompasses a range of hydrocarbon compounds, including aliphatic and aromatic fractions, emphasizing the dynamic nature of the contamination scenarios. A thorough review of bioremediation techniques, which have shown promise and sustainability as methods for cleaning up soil contaminated with petroleum hydrocarbons are also involved in order to solve these issues. Each of the three microbial processes, biodegradation, bioaugmentation, and biostimulation, is covered in detail in the paper, along with the complex mechanics underlying each technique. The report also emphasises new developments in genetics and molecular biology that add to our understanding of the metabolic pathways and microbial interactions involved in hydrocarbon breakdown. The effectiveness of plant-assisted bioremediation coupled with bioaugmentation and stimulation, specifically phytoremediation, is also explored, emphasizing the potential of certain plant species to enhance the removal of petroleum hydrocarbons from contaminated soils through rhizosphere interactions and plant-associated microbial activities. Furthermore, the paper evaluates the influence of environmental variables including soil composition, temperature, and moisture content on the effectiveness of bioremediation techniques, offering valuable perspectives on enhancing remediation efficiency through optimal conditions. The possibility for enhancing conventional bioremediation techniques through the incorporation of cutting-edge technology like nano-remediation is also explored.

Sensitivity of the Northern Hemisphere Warming Trend to Snowpack Variability

Abstract A marked decrease in land surface snow cover within the Northern Hemisphere under global warming will warm the atmosphere near the land surface. However, minimal information exists regarding the contribution of snowpack variation to interannual surface air temperature variability. The current study investigates the effects caused by snow water equivalent (SWE) change on surface air temperature (SAT). To this end, an SWE pacemaker experiment of land–atmosphere coupling (AMIP-type) is undertaken for the period 1901–2010, during which the Model for Interdisciplinary Research on Climate, version 6 (MIROC6), atmospheric general circulation model’s SWE is continuously nudged toward SWE derived from an land-only (LMIP-type) experiment. Compared to a reference MIROC6 simulation without SWE nudging, the spatial correlation of 1980–2010 interannual SWE trends in our experiment with those in GlobSnow observation data increased by 0.31 over the Northern Hemisphere. Similarly, the linear correlation of interannual SAT with reanalysis data is greater by 0.04, 0.04, 0.08, and 0.07 for autumn, winter, spring, and summer over the region from the reference experiment, respectively. It is shown that due to this SWE nudging, the modeled interannual SAT change in the Northern Hemisphere becomes more accurate. Through a surface energy budget analysis, changes in SAT are attributed to changes in surface albedo, soil evaporation, and soil temperature. Areas of greater contribution of SWE variability to SAT variability appear to shift from south to north areas as snow melts. These results highlight surface albedo, snow hydrological, and land heat storage effects through which the SWE interannual trend on the land surface significantly controls atmospheric air temperature variability near the land surface. Significance Statement This study investigates the contribution of land snowpack to surface air temperature in the Northern Hemisphere using a climate model updated with observation-based estimates of snow water equivalent. A marked decrease in snowpack under global warming is expected to warm the atmosphere near the land surface. Variations in surface albedo, soil evaporation, and soil temperature through the snow–soil–atmosphere processes during the early snow-melting season are crucial for accurately simulating surface air temperature in the Northern Hemisphere. Moreover, terrestrial snowpack is a significant factor in global warming rates.

Influence of clouds on planetary boundary layer height: A comparative study and factors analysis

Clouds are one of the key factors influencing the evolution of the planetary boundary layer (PBL). Understanding the complex interactions between clouds and PBL height (PBLH) is essential for accurately simulating and predicting PBL processes. This study investigates the impact of clouds on PBLH evolution based on the lidar, radiosonde, ceilometer, and meteorological parameters observations at the Southern Great Plains site during the period January 2013 to December 2020. The findings indicates that the presence of clouds has an impact on the evolution of the PBLH. During the daytime, PBLH is lower under cloudy conditions than clear conditions, whereas during nighttime, PBLH is higher under cloudy conditions. This phenomenon arises because the intense solar radiation on clear days and strong turbulent mixing on cloudy nights contribute to the formation and maintenance of PBLH. Furthermore, during the daytime, clouds scatter and absorb solar radiation, leading to lower net radiation (NetR), sensible heat flux (SHF), surface temperature (TEM), and soil temperature (SoilT). These conditions, coupled with weaker turbulence intensity and high relative humidity (RH), leading to lower PBLH under cloudy conditions. Although TEM and SoilT are relatively high during clear nights, rapid surface radiative cooling and strong atmospheric stability inhibit the development of the PBLH. Consequently, during cloudy nights, clouds absorb and reflect longwave radiation from the surface, reducing surface radiative cooling rates, enhancing atmospheric instability and turbulence intensity. Furthermore, higher NetR and SHF, along with decreased RH, result in slightly deeper PBLH compared to clear conditions. Overall, this study systematically elucidates the influence of clouds on PBLH evolution and contributes to the understanding of the modulation of cloud on PBL structure.

Optimization of Soil Temperature Dynamics under Different Irrigation Schedules, Tillage Methods, and NPK Fertilizer Application Rates

Optimization of Soil Temperature Dynamics under Different Irrigation Schedules, Tillage Methods, and NPK Fertilizer Application Rates

Effects of increased rainfall on heat and mass transfer and deformation of sulfate saline soil: An experimental investigation

To study the effect of increased rainfall on the heat and mass transfer and deformation characteristics of sulfate saline soil, a geometric similarity ratio model (1:6) of the natural site was created inside the self-developed indoor baseplate-atmospheric dual-temperature control model box. For the first time, combined with the characteristics of the surface energy change, the characteristics of water-heat-salt-mechanical coupling changes within sulfate saline soil under normal rainfall and twice the increase in rainfall were studied. The results show that the increased rainfall leads to a more significant decrease in upward shortwave radiation and downward longwave radiation, as well as a more significant increase in the surface net radiation and surface evaporation rate. Additionally, the increase in rainfall leads to an obvious cooling trend in the surface temperature. Compared with normal rainfall, an increase in rainfall leads to a significant increase in soil water content and conductivity, while soil heat flux and temperature significantly decrease. The increased rainfall caused a temperature drop of 1.6 °C at 5 cm of saline soil. Moreover, the increased rainfall leads to an increase in the heat release time of sulfate saline soil. Meanwhile, the impact of increased rainfall on the soil water content, conductivity, and temperature gradually weakens with increasing depth. The increased rainfall can exacerbate thawing settlement deformation and alleviate salt frost heave deformation. Compared with normal rainfall, twice the increase in rainfall results in a 0.9 mm increase in thawing settlement deformation and a 2.5 mm decrease in salt frost heave deformation.

Respuesta morfométrica de seis variedades de café (Coffea arabica L.) durante las épocas lluviosa y seca

The research emphasizes the need to improve coffee production and sustainability. The study of the agronomic response of six coffee varieties (Coffea arabica) during the rainy and dry seasons under different climatic conditions in Guasaganda, with the aim of analyzing how factors intervene in growth and identifying the most suitable variety to optimize production. . The research was carried out at the "Sacha Wiwa" Experimental Center at an altitude of 510 meters, with an average annual temperature of 23ºC and sandy loam soil. The study used a completely randomized block design to evaluate six coffee varieties during the rainy and dry seasons. Variables measured included plant height, stem diameter, and number of branches. The results indicated that the Sarchimor variety had the highest plant height with 165.58cm in the rainy season and 188.07cm in the dry season, followed by Bourbon with 126.99cm in the rainy season and 141.54cm in the rainy season. The Geisha variety showed the best production in stem diameter with 3.02cm in the rainy season and 3.35cm in the dry season. Regarding the number of branches, Sarchimor with 30, 93, Catimor with 28.70 and Geisha with 30.30 had the best performance during the dry season, while Sarchimor with 35.64 and Geisha with 35.70 led during the season. rainy The study concludes that the Sarchimor and Geisha varieties demonstrated superior agronomic results, being suitable under the climatic conditions of Guasaganda.

Measurements of hydrogen deposition velocities by farmland soil using D2 gas.

Using D2 gas as a substrate, this study investigated the hydrogen deposition velocities of farmland soils around a reprocessing plant located in Rokkasho Village, Aomori, Japan. To determine the hydrogen deposition velocities, closed chambers with fans were set on the soils of farmlands that grow Japanese radishes, and changes in D2 concentration in the chambers were measured by gas chromatography. Results showed hydrogen deposition velocities of six soils were within the range of 1.0×10-4~2.0×10-4ms-1. The heavy water (HDO) formations were detected in the soil after the experiment, showing the oxidation of D2 and conversion to water. Relationships between the obtained hydrogen deposition velocities and environmental conditions such as soil temperature, moisture and porosity were examined. A correlation was found between the hydrogen deposition velocities and soil gas phase rate (r=0.98, p<0.05).

Understanding soil and ecosystem respiration in a dune-meadow cascade ecosystem

Arid and semi-arid regions, which account for more than 30% of the Earth's land area, increasingly dominate the spatiotemporal trends in global carbon fluxes. The Horqin Sandy Land is a typical semi-arid fragile ecosystem in northern China. Understanding the components of the carbon budget in ecosystems under conditions of extreme soil moisture limitations provides a foundation for comprehending the carbon balance in semi-arid ecosystems. The seasonal and diurnal variations in soil respiration (Rs) in semi-mobile dune (SD) and meadow wetland (MW) ecosystems of the Horqin Sandy Land were examined, and the sources of CO2 emissions from Rs were identified using stable carbon isotopes. The responses of Rs and ecosystem respiration (Reco) to environmental temperature, moisture and leaf area index (LAI) were revealed. The results showed that on a seasonal scale, in SD with soil moisture content (Ms) below field capacity (FC), Ms had a greater influence on Rs than soil temperature (Ts) during the growing season. Changes in the LAI during the middle and late growth period affected Rs by altering root carbon supply. In MW, the most favorable Ms for Rs was near FC. The increase in LAI before mowing could effectively promote root and soil microbial respiration, and the decomposition of litter driven by Ts was the main form of Rs at this time. After mowing, root respiration and soil microbial respiration were the main processes contributing to CO2 emissions. On a daily scale, relative humidity (RH) dominated the Rs variation under dry conditions, whereas in other conditions, the Rs was adequately explained by temperature in SD and MW. The overall Reco was larger than Rs, but occasionally Rs was greater than Reco. The effects of temperature, moisture and LAI on Reco and Rs varied with growing season. Adding factors, such as ecosystem type, vegetation growth, water, and heat, to the carbon cycle model can improve predictions of carbon emissions, and aid in further management decisions in arid and semi-arid areas.

Forest soil CO2 emission in Quercus robur level II monitoring site

Abstract In this study, the soil CO2 emission was analysed at the level II ICP Forests monitoring plot in Serbia in the pedunculate oak forest. Two plots of pedunculate oak (Quercus robur L.) were selected for this study. The main question was to determine the differences in the impact of management (human impact) on CO2 emission. Different time periods were compared to identify the main factors affecting soil CO2 emission. Sampling was done by chambers. During the study period, climate indicators were quite different. A strong positive correlation between the soil temperature and soil CO2 emission, as well as a strong negative correlation between the soil moisture and soil CO2 emission, was found in the spring aspect (Plot). In other cases, a moderate to weak correlation was found. Multiple linear regressions showed that CO2 emission from soil was primarily controlled by soil moisture. Increasing soil water content had a positive effect on soil respiration (except in spring). The effect of soil temperature appeared in the multiple regressions as a secondary factor during the period studied, and an increase in temperature resulted in a decrease in soil respiration (except in spring).

Identification of optimum scopes of environmental drivers for schistosome-transmitting Oncomelania hupensis using agent-based model in Dongting Lake Region, China.

Oncomelania hupensis (O. hupensis), the sole intermediate host of Schistosoma japonicum, greatly influence the prevalence and distribution of schistosomiasis japonica. The distribution area of O. hupensis has remained extensive for numerous years. This study aimed to establish a valid agent-based model of snail density and further explore the environmental conditions suitable for snail breeding. A marshland with O. hupensis was selected as a study site in Dongting Lake Region, and snail surveys were monthly conducted from 2007 to 2016. Combined with the data from historical literature, an agent-based model of snail density was constructed in NetLogo 6.2.0 and validated with the collected survey data. BehaviorSpace was used to identify the optimal ranges of soil temperature, pH, soil water content, and vegetation coverage for snail growth, development and reproduction. An agent-based model of snail density was constructed and showed a strong agreement with the monthly average snail density from the field surveys. As soil temperature increased, the snail density initially rose before declining, reaching its peak at around 21°C. There were similar variation patterns for other environmental factors. The findings from the model suggested that the optimum ranges of soil temperature, pH, soil water content and vegetation coverage were 19°C to 23 °C, 6.4 to 7.6, 42% to 75%, and 70% to 93%, respectively. A valid agent-based model of snail density was constructed, providing more objective information about the optimum ranges of environmental factors for snail growth, development and reproduction.

Acidified biochar one-off application for saline-alkali soil improvement: A three-year field trial evaluating the persistence of effects

Salinization is a global soil degradation issue threatening agricultural productivity and environmental sustainability. Native biochar is a promising soil amendment, but its high alkalinity limits its use in saline-alkali lands. Acidified biochar, with a lower pH, is theoretically more suitable. This study aims to evaluate the persistence of effects of acidified biochar one-off application on soil particle size distribution, physicochemical properties, water retention, temperature regulation, and evaporation conditions of saline-alkali soil, thereby verifying its feasibility and exploring the optimal application range. We conducted a three-year cotton field experiment using palm fruit branch biochar as the raw material, acidified with ferrous sulfate, which involved four biochar applications (0, 10, 20, and 30 t ha−1) and four irrigation quotas (60 %, 80 %, 100 % and 120 % ETc). The results indicated that the initial acidified biochar application slightly increased surface soil (0–20 cm) pH by 0.1 %–3.9 %, this negative effect was nearly eliminated by the third year. Biochar application significantly altered surface soil particle size distribution, increasing sand content by 1.6 %–8.4 %, and persistently improved soil hydraulic properties, with water holding capacity still showing a 6.5 %–16.7 % increase in the third year. Biochar enhanced soil thermal insulation and suppressed soil evaporation, but these benefits gradually diminished with increasing cultivation years. Acidified biochar effectiveness was closely linked to irrigation quota. Significant differences in soil water and heat indicators were observed between the 20 and 30 t ha⁻¹ biochar treatments only under low irrigation quotas. Under sufficient irrigation (100 % and 120 % ETc), the optimal biochar application range was 15–20 t ha⁻¹, while under low irrigation (60 % and 80 % ETc), the optimal range was 20–25 t ha⁻¹. This study demonstrated that acidified biochar one-off application has significant multi-year benefits in improving soil structure and hydrothermal properties, providing a scientific basis for the improvement and sustainable utilization of saline-alkali soil.

Soil temperature dynamics in the forest shelterbelt and in the field

Soil temperature dynamics in the forest shelterbelt and in the field

Optimizing fungicide application timing for spring dead spot based on soil temperature and season

AbstractSpring dead spot (SDS) (Ophiosphaerella spp.) is the most detrimental disease to warm‐season turfgrasses in areas with cold‐induced dormancy. Fungicide applications do not provide consistent SDS suppression. One reason for this inconsistency is the use of solely calendar‐based fungicide applications instead of considering both calendar date and soil temperature. A field study was conducted at three separate hybrid bermudagrass (Cynodon dactylon (L.) Pers. × transvaalensis Burtt Davy) locations in Virginia to determine the optimal soil temperature and timing for SDS suppression with tebuconazole and isofetamid. Tebuconazole (1.5 kg a.i. ha−1) and isofetamid (4.1 kg a.i. ha−1) were applied at 11 different timings throughout the year based on soil temperatures at a 0‐ to 10‐cm depth. Plots were assessed for SDS severity in the spring and early summer of 2021 and 2022. Two in vitro studies were also conducted with Ophiosphaerella herpotricha and Ophiosphaerella korrae isolates to (1) determine the optimal temperature for growth on potato dextrose agar (PDA) placed on a thermogradient table (13–33°C) and (2) compare the daily growth rate of O. herpotricha and O. korrae isolates at 11, 19, and 27.5°C on PDA. In the field study, isofetamid suppressed SDS more than tebuconazole. Fall applications when soil temperatures were 13°C consistently provided the best SDS suppression. For the in vitro studies, both species grew optimally between 24 and 25°C, yet O. korrae and O. herpotricha growth rates differed at 11°C.

Resource allocation design method based on WSN multi-dimension soil inspection

Abstract. With the industrialization of agriculture and the sharp rise of food prices, in order to promote the intensive development of natural resources and achieve economies of scale agriculture in production, people put forward the innovative strategy of "precision agriculture" to maintain the sustainable development of agriculture. To protect the environment and farmer communities and increase productivity. However, in the special context of precision agriculture, the problems related to energy consumption and electromagnetic wave propagation in complex environments have a significant impact on precision agriculture. In the case of no monitoring and harsh environment, wireless sensor networks (WSN) can complete the tasks of real-time monitoring and information collection. In the past, the understanding of WSN in agriculture was limited to unilateral detection, which led to the underutilization of the soil. This paper introduces an innovative solution for precision agriculture based on wireless sensor networks, which mainly focuses on the observation and impact assessment of soil water volume,PH value, temperature and pressure in agricultural production process. It aims to reduce the waste of natural resources and the use of fertilizer substances, while maintaining or improving the yield of farming, in order to better promote the development of WSN in the agricultural field.

Sustaining Soil Biological Activity: The Role of Extended Reduced and No-Tillage Techniques

Soil management techniques can have varying effects on various soil properties. This study investigated the impact of various tillage techniques on soil properties for 14 years. The experiment was conducted at the Çukurova University Research Station, located in a region with a dominant Mediterranean climate. The research aimed to assess the changes in soil organic matter (SOM) content, soil respiration (SR), dehydrogenase enzyme activity (DHA), and soil temperature (ST) under seven different long-term tillage practices. The results revealed significant increases (p ≤ 0.05) in SOM (17-115%), SR (19-37%), and DHA (63-142%), under conservation tillage compared to conventional tillage practices. Additionally, conventional tillage with stubble burned consistently had the lowest values across all measured properties. Seasons variations also significantly (p≤0.05) affected the observed values. These findings suggest that conventional tillage practices have a negative effect on the analyzed biological activities, with stubble burning further exacerbating this impact. Further research exploring the long-term effects of different tillage practices under varying crop rotations and soil conditions can contribute to the sustainable development of agricultural production in the region.

National investigation of bisphenols in the surface soil in China

The long-term production and extensive use have resulted in the widespread presence of bisphenols (BPs) in the environment. In order to clarify the pollution characteristics and potential sources of BPs, the national scale surface soil samples were collected in China in 2019. The results demonstrated that 32 target BPs existed widely in soil with the highest concentration for bisphenol A (BPA), and at least 2 BPs were detected in each sample. The total concentration of Σ32BPs (from 0.387 to 713 ng/g) exhibited a stepwise decrease from southeastern coast to inland regions, and due to the presence of more pollution sources concentrations of Σ32BPs in urban areas were slightly higher than rural areas. The different industrial structures (such as plastics, epoxy resins, and thermal paper) may be the important factors for the different pollution levels between southeastern coast and other regions. In addition, the high organic matter content in soil and low temperature may be the reasons for high concentrations of Σ32BPs in Northeast China. The results of source identification using the Positive Matrix Factorization model indicated that BPs in soil were originated from three sources: old sources represented by BPA, relatively new sources characterized by bisphenol S, and sources from specific industries using bisphenol F. The estimated daily intake indicated that BPA exposure through soil accounted for only a small proportion of the total exposure compared to other exposure routes, and the risk by BPA in soil can be negligible to human health. In summary, the study provided basic pollution information of BPs in Chinese surface soil for future related studies.