Adsorption Properties of Dissolved Gas Molecules in Transformer Oil on the ReSe2 Monolayer: A DFT Study.

Based on density functional theory, the adsorption behavior of seven typical dissolved gas molecules (CO, CO2, H2, CH4, C2H2, C2H4, and C2H6) and H2O molecule on the ReSe2 monolayer was systematically investigated. The interactions between the ReSe2 monolayer and eight gas molecules were investigated by calculating the adsorption energies, charge transfer, density of states (DOS), and deformation charge density (DCD) for eight different adsorption systems. The gas sensitivity of the ReSe2 monolayer toward these gases was studied using frontier molecular orbital theory and work function analysis. The results demonstrate that compared to other gas molecules, the ReSe2 monolayer exhibits a stronger interaction with CO with an adsorption energy of -1.49 eV. It also displays excellent sensitivity and selectivity toward CO making it a promising candidate for CO gas sensing applications. We aspire that this research will offer theoretical guidance for the development of ReSe2-based gas sensors and contribute to state monitoring technology in oil-immersed power equipment.

Relationship between the Electrical Characteristics of Molecules and Fast Streamers in Ester Insulation Oil.

The effects of C=C, ester and ß-H groups on the ionization potential (IP) and electron affinity (EA) of molecules in natural ester insulation oil were investigated by density functional theory (DFT). The major contribution to the highest occupied molecular orbital (HOMO) comes from the carbon atoms adjacent to C=C. Thus, the IPs of triglycerides decrease as the number of C=C double bonds increases. The C=C in alkanes may also lower the IP. However, the ß-H in triglycerides has little effect on the IP, and C=C and ß-H have only a small effect on the EAs of the triglycerides because of the major contributions of atoms near the ester group in triglycerides to the lowest unoccupied molecular orbital (LUMO). This study calculated the IPs of 53 kinds of molecules in FR3, which are significantly lower compared with those of molecules in mineral oil (MO) and trimethylolpropane triester without C=C. However, the lightning impulse breakdown voltage (LI Vb) of trimethylolpropane triester is still significantly lower than that of MO at the large gap. Therefore, the transition from slow to fast streamers under low lighting impulse voltage is determined by the ester group rather than by C=C and ß-H. The ester group may attract more electrons, impacting itself more compared to alkane in MO and facilitating the transition from slow to fast streamers.

Estimation of Soil Water Content Based on Hyperspectral Features and the ANN Model.

Soil water content (θ) is an important factor for the crop growth and crop production. The objectives of this study were to (i) test various regression models for estimating θ based on spectral feature parameters, and (ii) compare the performance of the proposed models by using artificial neural networks (ANN) and spectral feature parameters. The θ data of sand and loam and concurrent spectral parameters were acquired at the laboratory experiment in 2014. The results showed that: (1) the maximum reflectance with 900～970 nm and the sum reflectance within 900～970 nm estimate θ had the significant, when sand bulk density was 1.40 g·cm-3; the maximum reflectance with blue edge and the sum reflectance within 900～970 nm had the best correlation (R2>0.70) when sand bulk density was 1.50 g·cm-3; while soil bulk density was 1.60 g·cm-3, the sum reflectance within 780～970 nm and normalized absorption depth in 560～760 nm reached a significant (R2>0.90); when soil bulk density was 1.70 g·cm-3, the maximum reflectance with 900～970 nm and the sum reflectance within 900～970 nm had the best correlation estimate θ (R2>0.88). 2) When the soil type was loam, the maximum reflectance with 900～970 nm and the sum reflectance within 900～970 nm had a best correlation estimate θ. The spectral feature parameters the sum reflectance within blue edge (R2=0.26 and RMSE=0.09 m3·m-3) and 780～970 nm absorption depth (R2=0.32 and RMSE=0.10 m3·m-3) were best correlated with θ in the sand. The θ model based on maximum reflectance with 900～970 nm (R2=0.92 and RMSE=0.05 m3·m-3) and the sum reflectance within 900～970 nm had a high correlation (R2=0.92 and RMSE=0.04 m3·m-3) in the loam. The BP-ANN model presented a better estimation accuracy of θ (R2=0.87 and RMSE=0.05 m3·m-3) in two soils. Thus, the ANN model has great potential for estimating θ. Thus, the BP-ANN model has great potential for θ estimation.

Can nitrate contaminated groundwater be remediated by optimizing flood irrigation rate with high nitrate water in a desert oasis using the WHCNS model?

Nitrate contamination of groundwater is an environmental concern in intensively cultivated desert oases where this polluted groundwater is in turn used as a major irrigation water resource. However, nitrate fluxes from root zone to groundwater are difficult to monitor in this complex system. The objectives of this study were to validate and apply the WHCNS (soil Water Heat Carbon Nitrogen Simulator) model to simulate water drainage and nitrate leaching under different irrigation and nitrogen (N) management practices, and to assess the utilization of groundwater nitrate as an approach to remediate nitrate contaminated groundwater while maintain crop yield. A two-year field experiment was conducted in a corn field irrigated with high nitrate groundwater (20 mg N L(-1)) in Alxa, Inner Mongolia, China. The experiment consisted of two irrigation treatments (Istd, standard, 750 mm per season; Icsv, conservation, 570 mm per season) factorially combined with two N fertilization treatments (Nstd, standard, 138 kg ha(-1); Ncsv, conservation, 92 kg ha(-1)). The validated results showed that the WHCNS model simulated values of crop dry matter, yield, soil water content and soil N concentration in soil profile all agreed well with the observed values. Compared to the standard water management (Istd), the simulated drainage and nitrate leaching decreased about 65% and 59%, respectively, under the conservation water management (Icsv). Nearly 55% of input N was lost by leaching under the IstdNstd and IstdNcsv treatments, compared to only 26% under the IcsvNstd and IcsvNcsv treatments. Simulations with more than 240 scenarios combing different levels of irrigation and fertilization indicated that irrigation was the main reason leading to the high risk of nitrate leaching, and the nitrate in irrigation groundwater can be best utilized without corn yield loss when the total irrigation was reduced from the current 750 mm to 491 mm. This reduced irrigation rate facilitated the use of approximately 42 kg N ha(-1) yr(-1) of nitrate from groundwater, which would gradually improve the groundwater quality. Future field studies on nitrate leaching in this area are suggested to investigate water and N dynamics under irrigation rates near 490 mm per season.

Modeling Nitrogen Fate and Water and Nitrogen Use Efficiencies under Different Greenhouse Vegetable Production Systems Using the WHCNS-Veg Model.

Quantitative evaluation of the effects of diverse greenhouse vegetable production systems (GVPS) on vegetable yield, soil water consumption, and nitrogen (N) fates could provide a scientific basis for identifying optimum water and fertilizer management practices for GVPS. This research was conducted from 2013 to 2015 in a greenhouse vegetable field in Quzhou County, North China. Three production systems were designed: conventional (CON), integrated (INT), and organic (ORG) systems. The WHCNS-Veg model was employed for simulating vegetable growth, water dynamics, and fates of N, as well as water and N use efficiencies (WUE and NUE) for four continuous growing seasons. The simulation results revealed that nitrate leaching and gaseous N emissions constituted the predominant N loss within GVPS, which separately accounted for 11.5-59.4% and 6.0-21.1% of the N outputs. The order of vegetable yield, N uptake, WUE, and NUE under different production systems was ORG > INT > CON, while the order of nitrate leaching and gaseous N loss was CON > INT > ORG. Compared to CON, ORG exhibited a significant increase in yield, N uptake, WUE, and NUE by 24.6%, 24.2%, 26.1%, and 89.7%, respectively, alongside notable reductions in nitrate leaching and gaseous N loss by 67.7% and 63.2%, respectively. The ORG system should be recommended to local farmers.

[Diagnosis of nitrogen content in upper and lower corn leaves based on hyperspectral data].

Based on the spectral characters of corn leaf nitrogen content in the space, the spectral models for rapid estimating crop nitrogen content were set up, which is practically meaningful to effectively providing the guidance in fertilization. Spectral technology was applied to explore corn leaves nitrogen content distribution regularity and the relationship between the nitrogen content and plant index was analysed and then the estimation models were built. The results showed N content in upper leaves is higher than that in lower leaves in four growing stages; lower leaves at tassel emerge stage are sensitive to nitrogen losses, which could be used in guiding fertilization in grain production; optimum estimation models were built atjointing stage, the full-grown stage and tasseling stage, The research results provided the proof of crop nutrient analysis and rational fertilization.

Effects of the Ratio of Substituting Mineral Fertilizers with Manure Nitrogen on Soil Properties and Vegetable Yields in China: A Meta-Analysis.

Substituting mineral fertilizers (MFs) with manure nitrogen (N) can not only reduce environmental pollution, but also improve soil quality. However, the effects of various manure N substitution ratios (SRs, the ratio of manure N over total N applied) on soil properties and vegetable yields in China are poorly studied. Here, through a meta-analysis of 667 observations, we assessed the effects of three manure N SRs (low (SR ≤ 35%), medium (35% < SR ≤ 70%), and high (SR > 70%)) on vegetable yields and soil properties (soil organic carbon, SOC; soil total nitrogen, STN; microbial biomass carbon (C) and nitrogen (N), MBC/N; and available phosphorus and potassium, (AP/AK)) in the 0-20 cm soil under different climatic conditions, initial soil properties, and management practices. The results show that the SOC and STN contents increased by 28.5% and 21.9%, respectively, under the medium SRs compared to the MF, which were the highest among the three SRs. Both soil MBC and MBN increased with the increase in the SRs, and the increased ratios in the high SRs reached 203.4% and 119.3%, respectively. In addition, the AP also increased with the increase in the SR, but the AK was not significantly changed with the low and medium SRs compared with the MF. Overall, the medium SR produced the highest vegetable yield among the three SRs with an increase of 18.6%. Additionally, a random forest analysis indicated that the N application rate, planting years, and mean annual precipitation were the most important factors influencing vegetable yield. In conclusion, the SR of 35-70% is more conducive to increasing soil nutrient contents significantly and improves vegetable yields in Chinese vegetable fields.

Improvement of Water and Nitrogen Use Efficiencies by Alternative Cropping Systems Based on a Model Approach.

The conventional double cropping system of winter wheat and summer maize (WW-SUM) in the North China Plain (NCP) consumes a large amount of water and chemical fertilizer, threatening the sustainable development of agriculture in this region. This study was based on a three-year field experiment of different cropping systems (2H1Y-two harvests in one year; 3H2Y-three harvests in two years; and 1H1Y-one harvest in one year). The 2H1Y system had three irrigation-fertilization practices (FP-farmer's practice; RI-reduced input; and WQ-Wuqiao pattern in Wuqiao County, Hebei Province). A soil-crop system model (WHCNS-soil water heat carbon nitrogen simulator) was used to quantify the effects of different cropping systems on water and nitrogen use efficiencies (WUE and NUE, respectively), and to explore the trade-offs between crop yields and environmental impacts. The results showed that annual yield, water consumption, and the WUE of 2H1Y were higher than those of the 3H2Y and 1H1Y systems. However, local precipitation during the period of crop growth could only meet 65%, 76%, and 91% of total water consumption for the 2H1Y, 3H2Y and 1H1Y systems, respectively. Nearly 65% of irrigation water (groundwater) was used in the period of wheat growth that contributed to almost 40% of the annual yield. Among the three patterns of the 2H1Y system, the order of the WUE was 2H1Y_RI > 2H1Y_WQ > 2H1Y_FP. Compared to 2H1Y_FP, the total fertilizer N application rates in 2H1Y_WQ, 2H1Y_RI, and 3H2Y were reduced by 25%, 65%, and 74%, respectively. The 3H2Y system had the highest NUE of 34.3 kg kg-1, 54% greater than the 2H1Y_FP system (22.2 kg kg-1). Moreover, the 3H2Y system obviously reduced nitrate leaching and gaseous N loss when compared with the other two systems. The order of total N loss of different cropping systems was 2H1Y (261 kg N ha-1) > 1H1Y (78 kg N ha-1) > 3H2Y (70 kg N ha-1). Considering the agronomic and environmental effects as well as economic benefits, the 3H2Y cropping system with optimal irrigation and fertilization would be a promising cropping system in the NCP that could achieve the balance between crop yield and the sustainable use of groundwater and N fertilizer.

Cropland carbon stocks driven by soil characteristics, rainfall and elevation.

Soil organic carbon (SOC) can influence atmospheric CO2 concentration and then the extent to which the climate emergency is mitigated globally. It follows the elucidation of the driving factors of cropland SOC stocks, which is fundamental to reducing soil carbon loss and promoting soil carbon sequestration. Here, we examined the influence of 16 environmental variables on SOC stocks and sequestration based on three machine learning soil mapping methods, i.e. multiple linear regression (MLR), random forest (RF) and extreme gradient boosting (XGBOOST), with 2875 observed soil samples from cropland topsoil across Hunan Province, China in 2010. We employed a structural equation model (SEM) to extricate the driving mechanisms of environmental variables on SOC stocks at the regional scale. Our results show that XGBOOST had the most reliable performance in predicting SOC stocks, explaining 66 % of the total SOC stock variation. Croplands with high SOC stocks were distributed in low-altitude and water-sufficient areas. The partial dependence of SOC on precipitation showed a trend of increasing and then slowly decreasing. In addition, the grid-based SEM results clearly presented the direct and indirect routes of environmental variables' impacts on cropland SOC stocks. Soil properties regulated by elevation, were the most influential natural factor on SOC stocks. Precipitation and elevation drove SOC stocks through direct and indirect effects respectively. Our SEM combined with machine learning approach can provide an effective explanation of the driving mechanism for SOC accumulation. We expect our proposed modelling approach can be applied to other regions and offer new insights, as a reference for mitigating cropland soil carbon loss under climate emergency conditions.

Ag-Doped MoSe2/ZnO Heterojunctions: A Highly Responsive Gas-Sensitive Material for Selective Detection of NO Based on DFT Study.

In this work, the adsorption and sensing behavior of Ag-doped MoSe2/ZnO heterojunctions for H2, CH4, CO2, NO, CO, and C2H4 have been studied based on density functional theory (DFT). In gas adsorption analysis, the adsorption energy, adsorption distance, transfer charge, total electron density, density of states (DOS), energy band structure, frontier molecular orbital, and work function (WF) of each gas has been calculated. Furthermore, the reusability and stability of the Ag-doped MoSe2/ZnO heterojunctions have also been studied. The results showed that Ag-doped MoSe2/ZnO heterojunctions have great potential to be a candidate of highly selective and responsive gas sensors for NO detection with excellent reusability and stability.

Ground Cover Rice Production System Affects Soil Water, Nitrogen Dynamics and Crop Growth Differentially with or without Climate Stress.

The ground cover rice production system (GCRPS) has been proposed as a potential solution to alleviate seasonal drought and early low-temperature stress in hilly mountainous areas; clarifying its impact on crop growth is crucial to enhance rice productivity in these areas. A two-year (2021-2022) field experiment was conducted in the hilly mountains of southwest China to compare the effects of the traditional flooding paddy (Paddy) and GCRPS under three different nitrogen (N) management practices (N1, zero-N fertilizer; N2, 135 kg N ha-1 as a urea-based fertilizer; and N3, 135 kg N ha-1 with a 3:2 base-topdressing ratio as urea fertilizer for the Paddy or a 1:1 basal application ratio as urea and manure for GCRPS) on soil water storage, soil mineral N content and crop growth parameters, including plant height, tiller numbers, the leaf area index (LAI), aboveground dry matter (DM) dynamics and crop yield. The results showed that there was a significant difference in rainfall between the two growth periods, with 906 mm and 291 mm in 2021 and 2022, respectively. While GCRPS did not significantly affect soil water storage, soil mineral N content, and plant height, it led to a reduction in partial tiller numbers (1.1% to 31.6%), LAI (0.6% to 20.4%), DM (4.4% to 18.8%), and crop yield (7.4% to 22.0%) in 2021 (wet year) compared to the Paddy. However, in 2022 (dry year), GCRPS led to an increase in tiller numbers (13.7% to 115.4%), LAI (17.3% to 81.0%), DM (9.0% to 62.6%), and crop yield (2.9% to 9.2%) compared to the Paddy. Structural equation modeling indicated that GCRPS significantly affected tiller numbers, plant height, LAI, DM, and productive tiller numbers, which indirectly influenced crop yield by significantly affecting tiller numbers and productive tiller numbers in 2022. Overall, the effects of GCRPS on soil water and N dynamics were not significant. In 2021, with high rainfall, no drought, and no early, low-temperature stress, the GCRPS suppressed crop growth and reduced yield, while in 2022, with drought and early low-temperature stress and low rainfall, the GCRPS promoted crop growth and increased yield, with tiller numbers and productive tiller numbers being the key factors affecting crop yield.

Effects of the Combining Straw Return with Urease Inhibitor on Ammonia Volatilization, Nitrogen Use Efficiency, and Rice Yield in Purple Soil Areas.

Straw return in rice (Oryza sativa L.) paddy has been heavily criticized for its potential to influence ammonia (NH3) volatilization loss due to irrational fertilizer N application. Therefore, improving the N fertilization strategies within residue straw systems is necessary to reduce N loss from NH3 volatilization. This study investigated how the incorporation of oilseed rape straw and the urease inhibitor affected NH3 volatilization, fertilizer N use efficiency (FNUE), and rice yields over two growing seasons (2018-2019) in the purple soil region. This study arranged eight treatments combined straw (2, 5, 8 ton ha-1, named 2S, 5S, 8S, respectively), with urea or urease inhibitor (UI, 1% NBPT) with three replicates, which included control (CK), UR (Urea, 150 kg N ha-1), UR + 2S, UR + 5S, UR + 8S, UR + 2S + UI, UR + 5S + UI, UR + 8S + UI, based on the randomized complete block method. Our results indicated that incorporating oilseed rape straw increased NH3 losses by 3.2-30.4% in 2018 and 4.3-17.6% in 2019 than the UR treatment, attributing to the higher NH4+-N content and pH value within floodwater. However, the UR + 2S + UI, UR + 5S + UI and UR + 8S + UI treatments reduced NH3 losses by 3.8%, 30.3%, and 8.1% in 2018 and 19.9%, 39.5%, and 35.8% in 2019, separately compared to their corresponding UR plus straw treatments. According to the findings, adding 1% NBPT significantly decreased NH3 losses while incorporating 5 ton ha-1 oilseed rape straw. Furthermore, adding straw, either alone or in conjunction with 1% NBPT, increased rice yield and FNUE by 0.6-18.8% and 0.6-18.8%, respectively. Otherwise, NH3 losses scaled by yield in the UR + 5S + UI treatment decreased significantly between all treatments in 2018 and 2019. These results suggest that optimizing the oilseed rape straw rate combined with 1% NBPT applied with urea efficiently increased rice yield and reduced NH3 emissions in the purple soil region of Sichuan Province, China.

Simulating the Effects of Different Textural Soils and N Management on Maize Yield, N Fates, and Water and N Use Efficiencies in Northeast China.

Determining the best management practices (BMPs) for farmland under different soil textures can provide technical support for improving maize yield, water- and nitrogen-use efficiencies (WUE and NUE), and reducing environmental N losses. In this study, a two-year (2013−2014) maize cultivation experiment was conducted on two pieces of farmland with different textural soils (loamy clay and sandy loam) in the Phaeozems zone of Northeast China. Three N fertilizer treatments were designed for each farmland: N168, N240, and N312, with N rates of 168, 240, and 312 kg ha−1, respectively. The WHCNS (soil Water Heat Carbon Nitrogen Simulator) model was calibrated and validated using the observed soil water content, soil nitrate concentration, and crop biological indicators. Then, the effects of soil texture combined with different N rates on maize yield, water consumption, and N fates were simulated. The integrated index considering the agronomic, economic, and environmental impacts was used to determine the BMPs for two textural soils. Results indicated that simulated soil water content and nitrate concentration at different soil depths, leaf area index, dry matter, and grain yield all agreed well with the measured values. Both soil texture and N rates significantly affected maize yield, N fates, WUE, and NUE. The annual average grain yield, WUE, and NUE under three N rates in sandy loam soil were 8257 kg ha−1, 1.9 kg m−3, and 41.2 kg kg−1, respectively, which were lower than those of loam clay, 11440 kg ha−1, 2.7 kg m−3, and 46.7 kg kg−1. The order of annual average yield and WUE under two textural soils was N240 > N312 > N168. The average evapotranspiration of sandy loam (447.3 mm) was higher than that of loamy clay (404.9 mm). The annual average N-leaching amount of different N treatments for sandy loam ranged from 5.1 to 13.2 kg ha−1, which was higher than that of loamy clay soil, with a range of 1.8−5.0 kg ha−1. The gaseous N loss in sandy loam soil accounted for 14.7% of the fertilizer N application rate, while it was 11.1%in loamy clay soil. The order of the NUEs of two textural soils was: N168 > N240 > N312. The recommended N fertilizer rates for sandy loam and loamy clay soils determined by the integrated index were 180 and 200 kg ha−1, respectively.

Constructing a defect-rich hydroxide nanoenzyme sensor based on dielectric barrier discharge microplasma etching for sensitive detection of thiamine hydrochloride and hydrogen peroxide.

In this work, a novel approach was designed to fabricate a defect-rich hydroxide nanoenzyme sensor based on transition metal cobalt derived from metal-organic framework (MOF). Facile preparation was realized by room-temperature reaction and chemical etching via dielectric barrier discharge (DBD) microplasma, which possesses great chemical reactivity to obtain defect-rich and ultrathin structures. The prepared cobalt hydroxide (Co(OH)2) emerges with superior catalytic activity for thiamine hydrochloride (TCL) and hydrogen peroxide (H2O2) assay. The linear ranges were 0.0006 mM to 2.75 mM for TCL detection and 0.001 mM to 5.5 mM for H2O2 detection with low limit of detections (LODs) of 14 nM and 93 nM, respectively. Meanwhile, the as-prepared sensor provides excellent long-term durability (>25 days), as well as high sensitivity (12730 µA mM-1cm-2 and 5199.3 µA mM-1 cm-2) for TCL and H2O2 assay. TCL in serum samples has been detected with satisfactory results by the proposed material, while the H2O2 in Hela cells was also successfully measured. The developed sensor provides several advantages including simplicity, high sensitivity, and efficient preparation.

Can conservation agriculture mitigate climate change and reduce environmental impacts for intensive cropping systems in North China Plain?

Determining appropriate farming management practices to adapt to climate change with lower environmental costs is important for sustainable agricultural production. In this study, a long-term experiment (1985-2019) was conducted under different management practices combining fertilization rate (no, low and high N fertilizer, N0, N1 and N2), straw additions (no, low and high addition, S0, S1 and S2) with conservation tillage (no-tillage, NT) in the North China Plain (NCP). The Denitrification-Decomposition (DNDC) model was firstly evaluated using the experimental data, and then applied to simulate the changes of crop yields, soil organic carbon (SOC), and N2O emissions under different management practices combined with climate change scenarios, under low and high emission scenarios of societal development pathways (SSP245 and SSP585, respectively) with climate projections from 2031 to 2100. Under the low emission scenario (SSP245), wheat yields were the highest with the NT-N1-S2 treatment (a 23% increase relative to the baseline (1981-2010)). For maize yields, the NT-N1-S1 treatment increased 46% relative to baseline under the SSP585, whereas, the yields increased less in all treatments under SSP245-2040s. The SOC was predicted to increase by 6-60% by 2100 under SSP245. Straw addition and tillage were the main factors influencing SOC. N fertilizer was the most important driver for wheat and maize yields, however, N2O emissions from soil increased with increased application of N fertilizer. Therefore, the no-tillage method under low N fertilizer and high straw addition (NT-N1-S2) is recommended to promote crop yields and substantially increase SOC under SSP245 and SSP585. Conservation agriculture practices can potentially offset crop yield reductions, increase soil quality, and reduce greenhouse gas emissions in the NCP, and ensure crop production to meet the growing demand for food under future climate change.

Increasing dominance of Indian Ocean variability impacts Australian wheat yields.

The relationships between crop productivity and climate variability drivers are often assumed to be stationary over time. However, this may not be true in a warming climate. Here we use a crop model and a machine learning algorithm to demonstrate the changing impacts of climate drivers on wheat productivity in Australia. We find that, from the end of the nineteenth century to the 1980s, wheat productivity was mainly subject to the impacts of the El Niño Southern Oscillation. Since the 1990s, the impacts from the El Niño Southern Oscillation have been decreasing, but those from the Indian Ocean Dipole have been increasing. The warming climate has brought more occurrences of positive Indian Ocean Dipole events, resulting in severe yield reductions in recent decades. Our findings highlight the need to adapt seasonal forecasting to the changing impacts of climate variability to inform the management of climate-induced yield losses.

Collaborative Assessment and Health Risk of Heavy Metals in Soils and Tea Leaves in the Southwest Region of China.

The collaborative assessment and health risk evaluation of heavy metals (HMs) enrichment in soils and tea leaves are crucial to guarantee consumer safety. However, in high soil HM geochemical background areas superimposed by human activities, the health risk associated with HMs in soil-tea systems is not clear. This study assessed the HMs concentration (i.e., chromium (Cr), cadmium (Cd), arsenic (As), and lead (Pb)) in tea leaves and their relationship with soil amounts in the southwest region of China to evaluate the associated health risk in adults. The results revealed that the average soil concentration of Cr was the highest (79.06 mg kg-1), followed by Pb (29.27 mg kg-1), As (14.87 mg kg-1), and Cd (0.18 mg kg-1). Approximately 0.71, 4.99, 7.36, and 10.21% of soil samples exceeded the threshold values (NY/T 853-2004) for Pb, Cr, As, and Cd, respectively. Furthermore, the average concentration of Pb, As, and Cd in tea leaves was below the corresponding residue limits, but Cr was above the allowed limits. Correlation analysis revealed that the Pb, Cr, As, and Cd amounts in tea leaves were positively correlated to their soil amounts (p < 0.01) with an R2 of 0.203 **, 0.074 **, 0.036 **, and 0.090 **, respectively. Additionally, approximately 40.38% of the samples were found to be contaminated. Furthermore, spatial distribution statistical analysis revealed that Lancang was moderately contaminated, while Yingjiang, Zhenkang, Yongde, Zhenyuan, Lüchun, Jingdong, Ximeng, and Menglian were slightly contaminated areas. The target hazard quotients (THQ; health risk assessment) of Pb, Cr, As, and Cd and the hazard index (HI) of all the counties were below unity, suggesting unlikely health risks from tea consumption.

The Adsorption and Sensing Performances of Ir-modified MoS2 Monolayer toward SF6 Decomposition Products: A DFT Study.

In this paper, the Ir-modified MoS2 monolayer is suggested as a novel gas sensor alternative for detecting the characteristic decomposition products of SF6, including H2S, SO2, and SOF2. The corresponding adsorption properties and sensing behaviors were systematically studied using the density functional theory (DFT) method. The theoretical calculation indicates that Ir modification can enhance the surface activity and improve the conductivity of the intrinsic MoS2. The physical structure formation, the density of states (DOS), deformation charge density (DCD), molecular orbital theory analysis, and work function (WF) were used to reveal the gas adsorption and sensing mechanism. These analyses demonstrated that the Ir-modified MoS2 monolayer used as sensing material displays high sensitivity to the target gases, especially for H2S gas. The gas sensitivity order and the recovery time of the sensing material to decomposition products were reasonably predicted. This contribution indicates the theoretical possibility of developing Ir-modified MoS2 as a gas sensor to detect characteristic decomposition gases of SF6.

Is rice field a nitrogen source or sink for the environment?

Rice field has been traditionally considered as a nonpoint source of reactive nitrogen (N) for the environment, while it, with surrounding ditches and ponds, also contributes to receiving N inputs from atmosphere and waterbodies and intercepting N outputs from rice field. However, a comprehensive assessment of the N source or sink of rice field for the environment is lacking. Here, we conducted the 3-year systematic observations and process-based simulations of N budget at the Jingzhou site in Central China. We identified the roles of rice field and evaluated the opportunities for shifting its role from N source (i.e., outputs > inputs) to sink (i.e., outputs ≤ inputs). Rice field was found to be a N source of 24.2-28.7 kg N ha-1 for waterbodies (including surface and ground waters), but a N sink (2.2-8.8 kg N ha-1) for the atmosphere for the wet and normal year climatic scenarios. The "4R-nutrient stewardship" (i.e., using the right type of N fertilizers, at right rate, right time, and in right place) applied in rice field was sufficient for the source-to-sink shift for the atmosphere for dry year climatic scenario, but needed to implement together with improvements of irrigation and drainage for waterbodies. Furthermore, with the combination of these improved management technologies, rice field played a role as a N sink of up to 22.8 kg N ha-1 for the atmosphere and up to 2.0 kg N ha-1 for waterbodies, along with 24% decrease in irrigation water use and 21% decrease in N application rate without affecting rice yield and soil fertility. Together these findings highlight a possibility to achieve an environmental-friendly rice field by improving agricultural management technologies.

Modeling nitrate leaching and optimizing water and nitrogen management under irrigated maize in desert oases in Northwestern China.

Understanding water and N transport through the soil profile is important for efficient irrigation and nutrient management to minimize nitrate leaching to the groundwater, and to promote agricultural sustainable development in desert oases. In this study, a process-based water and nitrogen management model (WNMM) was used to simulate soil water movement, nitrate transport, and crop growth (maize [Zea mays L.]) under desert oasis conditions in northwestern China. The model was calibrated and validated with a field experiment. The model simulation results showed that about 35% of total water input and 58% of the total N input were leached to <1.8 m depth under traditional management practice. Excessive irrigation and N fertilizer application, high nitrate concentration in the irrigation water, together with the sandy soil texture, resulted in large nitrate leaching. Nitrate leaching was significantly reduced under the improved management practice suggested by farm extension personnel; however, the water and nitrate inputs still far exceeded the crop requirements. More than 1700 scenarios combining various types of irrigation and fertilizer practices were simulated. Quantitative analysis was conducted to obtain the best management practices (BMPs) with simultaneous consideration of crop yield, water use efficiency, fertilizer N use efficiency, and nitrate leaching. The results indicated that the BMPs under the specific desert oasis conditions are to irrigate the maize with 600 mm of water in eight times with a single fertilizer application at a rate of 75 kg N ha(-1).