Article
Environmental Sciences
R. W. McDowell
Summary: The study indicates that controlling the cadmium content in phosphorus fertilizers can effectively reduce the concentration of cadmium in soil. The leaching of cadmium in soil is influenced by the frequency of irrigation, with an increase in irrigation frequency leading to a higher cadmium leaching rate. Estimations using a mass balance approach suggest an annual cadmium leaching rate of around 1.8 g per hectare.
ENVIRONMENTAL POLLUTION
(2022)
Article
Physiology
Gonzalo D. Maso Talou, Thiranja P. Babarenda Gamage, Martyn P. Nash
Summary: This study introduces a novel AI-based technique for identifying the mechanical properties of heart tissues and intra-ventricular pressure, with reliable parameter estimates obtained in less than 9 or 18 seconds.
FRONTIERS IN PHYSIOLOGY
(2021)
Article
Environmental Sciences
Tengqi Xu, Jiao Xi, Jihong Ke, Yufan Wang, Xiaotian Chen, Zengqiang Zhang, Yanbing Lin
Summary: Soil heavy metal pollution, especially cadmium, is a serious environmental problem in China. This study investigated the effects of different amendments and actinomycetes inoculants on wheat growth in Cd contaminated farmland. The results showed that organic fertilizer and actinomycetes are more ideal remediation strategies for Cd contaminated soil.
ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
(2023)
Article
Environmental Sciences
Jian-Hua Cheng, Xiang-Yu Tang, Zhuo Guan, Chen Liu
Summary: The study found variations of heavy metals, antibiotic resistance genes (ARGs), mobile genetic elements (MGEs), and microbiome in the soil surrounding a phosphorus chemical industrial zone. The primary factors controlling the distribution of ARGs were cadmium (Cd) and MGEs levels, with a stronger direct effect of Cd on ARG abundance compared to its indirect effect.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Energy & Fuels
Yifeng Li, Longgang Sun, Liuyue Cao, Jie Bao, Maria Skyllas-Kazacos
Summary: A model-based approach was developed to determine the membrane permeability properties for the vanadium redox flow battery (VRB) system, estimating vanadium ion and water transfer coefficients through nonlinear optimization with measured half-cell potentials. Experimental studies were conducted to validate the effectiveness of the proposed method using two different membranes as examples. This simplified approach is useful for predicting battery capacity decay and scheduling regular maintenance activities such as electrolyte rebalancing.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Environmental Sciences
Wenlu Zuo, Boyi Song, Yuxin Shi, Anze Zupanic, Shuxian Guo, He Huang, Ling Jiang, Yadong Yu
Summary: In this study, BtHM-311@HAP@biochar calcium alginate beads were developed to immobilize B. thuringiensis HM-311 in order to remediate Cd- and Pb-contaminated farmland soil. The beads effectively reduced the concentration of Pb2+ and Cd2+ in aqueous solution and decreased their bioavailability in soil, leading to decreased accumulation in rice and corn plants. The beads also improved microbial community diversity in the rhizosphere soil. These findings highlight the potential application of BtHM311@HAP@biochar beads in soil bioremediation.
Article
Agronomy
Shuaishuai Gao, Yuan Guo, Xueying Cao, Caisheng Qiu, Huajiao Qiu, Xinlin Zhao
Summary: Trace metal pollution in farmland poses a threat to crop and human health. Restoring and utilizing these polluted farmlands are necessary, but phytoremediation is limited by low efficiency and plant economic value. A field study found that a rotation of Sedum plumbizincicola and kenaf can effectively remediate heavy-metal-contaminated farmland. Kenaf had higher biomass but lower metal concentrations compared to S. plumbizincicola. The rotation increased metal removal by 7.88%, 126%, 33.5%, and 4.39% compared to monoculture of S. plumbizincicola.
Article
Meteorology & Atmospheric Sciences
Damian Esteban Tosoni, Francisco Javier Meza, Shaw Nozaki Lacy
Summary: The study utilized surface renewal analysis (SRA) to estimate turbulent fluxes and compared the results with eddy covariance (EC) measurements, showing a high agreement and suitability for heterogeneous canopies. SRA proved to be more economical and simpler, providing a flexible alternative for estimating turbulent fluxes on different surfaces.
THEORETICAL AND APPLIED CLIMATOLOGY
(2021)
Article
Agronomy
Xucheng Zhang, Huizhi Hou, Yanjie Fang, Hongli Wang, Xianfeng Yu, Yifan Ma, Kangning Lei
Summary: Plastic mulching combined with supplementary irrigation and organic fertilizer application significantly increased yield and water productivity of wheat and maize, and had a positive effect on soil water balance. Long-term effects of plastic mulching on soil organic carbon balance still need further investigation for sustainable agricultural production.
AGRICULTURAL WATER MANAGEMENT
(2022)
Article
Environmental Sciences
Yazhu Mi, Jun Zhou, Mengli Liu, Jiani Liang, Leyong Kou, Ruizhi Xia, Ruiyun Tian, Jing Zhou
Summary: Identification of heavy metal sources can effectively control and prevent agricultural soil pollution. A three-year mass balance study was conducted to quantify the potential contribution and net cadmium (Cd) fluxes and predict Cd concentration in rice grains using multiple regression (MR) and back propagation (BP) neural network. The major sources of Cd inputs were irrigation water in moderately polluted and background sites, while atmospheric deposition dominated in the highly polluted site. Surface runoff was the main Cd output in moderate and background sites, whereas phytoextraction by Sedum plumbizincicola contributed the most in the highly polluted site. The genetic algorithms (GA)-BP neural network model showed the highest prediction accuracy compared to BP neural network model and multivariate regression analysis. The model can rapidly assess health risks associated with rice consumption based on predicted Cd concentrations in rice grains.
Article
Environmental Sciences
Yu Zhang, Yanli Li, Yingming Xu, Qingqing Huang, Guohong Sun, Xu Qin, Lin Wang
Summary: This study found through field experiments that Mercapto-palygorskite (MP) can significantly reduce the content of cadmium (Cd) in soils by increasing the organic matter, soluble iron, manganese, and sulfur content in soil aggregates, thus reducing the levels of exchangeable and Fe/Mn oxide-bound Cd in the soil.
ENVIRONMENTAL RESEARCH
(2023)
Article
Ecology
Tian Xie, Meie Wang, Yuan Zhang, Changfeng Liu, Fei Lu, Shoukang Ding, Weiping Chen, Suriyanarayanan Sarvajayakesavalu
Summary: This study discussed the estimation methods of PAHs ambient backgrounds in Macau soil, revealing different results due to various calculation principles. A regression model based on urbanization duration was further used to explain the impact on ambient backgrounds, and credibility analysis confirmed the reliability of the estimation models.
ECOLOGICAL MODELLING
(2022)
Article
Environmental Sciences
Cong Liu, Wenlai Jiang, Yongfeng Wu, Yunfei Liu, Lijiang Liang
Summary: Using the modified Penman-Monteith equation and GIS technology, this study calculates the net crop irrigation water requirements for four main crops in Northeast China and analyzes their spatiotemporal distribution characteristics. The study also estimates the regional farmland irrigation water requirements, determines water balance, and analyzes the dominant factors affecting farmland irrigation water requirements in different regions.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Environmental Sciences
Jiaxin Chen, Jianfang Guo, Zuran Li, Xinran Liang, Yihong You, Mingrui Li, Yongmei He, Fangdong Zhan
Summary: The arbuscular mycorrhizal fungi (AMF) can enhance the growth and cadmium (Cd) uptake of maize in Cd-polluted soil. The effects of AMF on root morphology and low-molecular-weight organic acid secretion may play an important role in the increased Cd uptake of maize.
Article
Agronomy
Zhuangzhuang Feng, Qingfeng Miao, Haibin Shi, Weiying Feng, Xianyue Li, Jianwen Yan, Meihan Liu, Wei Sun, Liping Dai, Jing Liu
Summary: Rational irrigation is important for increasing crop yield and reducing water use. In this study, field experiments and numerical modeling were conducted to explore field evapotranspiration, crop water consumption, and soil water movement in sand-layered farmland. Results showed that increasing irrigation frequency and reducing irrigation quota are beneficial for increasing the water holding capacity for crop growth in the root zone. This study provides a basis for farmland water management in arid and semi-arid areas.
AGRICULTURAL WATER MANAGEMENT
(2023)
Article
Geosciences, Multidisciplinary
Wu Yu, Yefeng Jiang, Wandong Liang, Dan Wan, Bo Liang, Zhou Shi
Summary: Quantifying the spatial distribution of soil erodibility (K factor) in the Qinghai-Tibet Plateau is important for global soil erosion management. A random forest model was used to map the high-resolution spatial distribution of K factor values in southeastern Tibet, providing detailed information even in unsampled areas. The study also found that soil physical properties, climate, and topography have a significant influence on the K factor.
Article
Environmental Sciences
Yanyu Wang, Ziqiang Ma, Yuhong He, Wu Yu, Jinfeng Chang, Dailiang Peng, Xiaoxiao Min, Hancheng Guo, Yi Xiao, Lingfang Gao, Zhou Shi
Summary: This study characterized the spatiotemporal pattern and variation of vegetation disturbances on the Tibetan Plateau (TP) over the past decades, and identified the disturbance agents. The results showed that approximately 29.34% of the TP's area (75.71 M ha) experienced at least one disturbance, with 8.44 M ha area being subject to large-scale disturbances. The spatial distribution of these disturbances varied over time, with even distribution before 2002 possibly due to overgrazing and unscientific livestock management, and concentration in the south of the Yarlung Tsangpo after 2002 mainly caused by anthropogenic activities.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Soil Science
Ruiying Zhao, Wenxin Zhang, Zheng Duan, Songchao Chen, Zhou Shi
Summary: Calibrating ecosystem models through data assimilation can provide reliable estimates of soil carbon pool and fluxes in grasslands of the Qinghai-Tibet Plateau, improving the overestimation of the default model.
Article
Soil Science
Yongsheng Hong, Yiyun Chen, Songchao Chen, Ruili Shen, Long Guo, Yaolin Liu, Abdul Mounem Mouazen, Zhou Shi
Summary: Urban soils and cultural layers can store carbon over a long period, and the turnover rate of soil inorganic carbon is fast, which should be noticed for global carbon pool and atmospheric CO2 regulation. Visible and near infrared spectroscopy has the potential for soil characterization, but its application in estimating soil inorganic carbon in urban and suburban areas affected by human activities is limited.
Article
Environmental Sciences
Hancheng Guo, Yanyu Wang, Jie Yu, Lina Yi, Zhou Shi, Fumin Wang
Summary: Understanding terrestrial ecosystem dynamics requires a comprehensive examination of vegetation changes. Remote sensing technology has been established as an effective approach to comprehensively assess vegetation change. In this study, a novel framework integrating short-term disturbance detection and long-term trend analysis was proposed and applied to characterize vegetation changes in Zhejiang Province from 1990 to 2020. The results showed a browning trend in the plains and a greening trend in the mountains, with an overall greening of the vegetation during the study period.
ENVIRONMENTAL RESEARCH
(2023)
Article
Soil Science
Xiaolin Jia, Modian Xie, Bifeng Hu, Yin Zhou, Hongyi Li, Wanru Zhao, Wanming Deng, Zhou Shi
Summary: Accurate measurement of soil organic carbon (SOC) is crucial for managing agricultural production and mitigating climate change. This study validates the effectiveness of visible near-infrared spectroscopy for predicting SOC content at a local field scale in Tibet. By using direct standardization algorithms, environmental factors were successfully removed from the in situ spectra, leading to improved prediction accuracy. The results showed that the local spectral library models outperformed the national spectral library models, particularly for shrub meadows, forests, and the overall dataset.
EURASIAN SOIL SCIENCE
(2023)
Article
Soil Science
Xianglin Zhang, Songchao Chen, Jie Xue, Nan Wang, Yi Xiao, Qianqian Chen, Yongsheng Hong, Yin Zhou, Hongfen Teng, Bifeng Hu, Zhiqing Zhuo, Wenjun Ji, Yuanfang Huang, Yuxuan Gou, Anne C. Richer-de-Forges, Dominique Arrouays, Zhou Shi
Summary: In order to support decision-making for maintaining limited soil resources, the use of digital soil mapping (DSM) is crucial in obtaining spatially explicit soil information. Among various methods, modified greedy feature selection (MGFS) outperforms Boruta, recursive feature elimination (RFE), and variance inflation factor (VIF) analysis in terms of model parsimony and computation efficiency. The application of MGFS in mapping soil organic carbon density (SOCD) in Northeast and North China showed that it selected a more parsimonious model with better performance and lower global uncertainty compared to other methods. MGFS has great potential in fine-resolution soil mapping practices, especially for studies involving heavy computation on a large scale.
Article
Soil Science
Meihua Yang, Songchao Chen, Dongyun Xu, Yongsheng Hong, Shuo Li, Jie Peng, Wenjun Ji, Xi Guo, Xiaomin Zhao, Zhou Shi
Summary: The large-scale soil spectral library (SSL) provides abundant information for predicting soil properties, but using SSL for predicting soil information from in situ spectra is still a challenge. This study compared different strategies for predicting soil organic matter (SOM) using SSL and found that the mean squared Euclidean distance (msd) is an optimal indicator for selecting representative samples. The recommended strategy depends on the availability of in situ and dry spectra. These findings contribute to efficient SOM prediction in situ by integrating large-scale SSL.
Article
Soil Science
Songchao Chen, Nicolas P. A. Saby, Manuel P. Martin, Bernard G. Barthes, Cecile Gomez, Zhou Shi, Dominique Arrouays
Summary: Digital soil mapping is seen as an efficient approach to evaluate soil ecosystem services by providing fine-resolution and up-to-date soil information. However, limited budget for field work and soil laboratory analysis has led to the development of spectroscopy as an alternative method for rapid and cost-effective soil data collection. This study evaluates the potential of spectroscopically inferred (SI) data in digital soil mapping of soil properties at a national scale and shows that adding additional SI data can improve the accuracy of digital soil maps.
Article
Environmental Sciences
Bifeng Hu, Modian Xie, Hongyi Li, Rebin He, Yue Zhou, Yefeng Jiang, Wenjun Ji, Jie Peng, Fang Xia, Zongzheng Liang, Wanming Deng, Junjie Wang, Zhou Shi
Summary: The study investigates the spatio-temporal variation of soil nutrients and soil organic matter (SOM) in farmland over Jiangxi Province in Southern China. Based on a dataset of soil samples collected between 2005 and 2012, the study examines the changes in SOM, available nitrogen (N), phosphorus (P), potassium (K), pH, and cation exchange capacity. The results indicate significant temporal trends in the concentrations of SOM, available P, available N, and available K, with climate and soil management practices playing a dominant role in determining soil fertility.
JOURNAL OF SOILS AND SEDIMENTS
(2023)
Article
Geosciences, Multidisciplinary
Guocheng Wang, Liujun Xiao, Ziqi Lin, Qing Zhang, Xiaowei Guo, Annette Cowie, Shuai Zhang, Mingming Wang, Songchao Chen, Ganlin Zhang, Zhou Shi, Wenjuan Sun, Zhongkui Luo
Summary: Plant root-derived carbon inputs are the main source of carbon in mineral bulk soil, but a fraction of these inputs may be quickly lost without contributing to long-term soil carbon storage. This study quantified the loss of root-derived carbon on a global scale and found that about 80% of the carbon inputs are lost rather than stored in the soil. The depth distribution of root-derived carbon inputs and their contribution to soil carbon storage were also determined, and a global map of the lost carbon and its distribution was created.
SCIENCE CHINA-EARTH SCIENCES
(2023)
Review
Environmental Sciences
Yadong Guo, Zhenzhong Zeng, Junjian Wang, Junyu Zou, Zhou Shi, Songchao Chen
Summary: This review provides a concise framework for understanding the impact of climate change on soil organic carbon (SOC) dynamics. While valuable insights have been gained, there are still knowledge gaps that need to be addressed. Future research should focus on standardizing organismal traits, SOC fractions, and the interactions and biochemical pathways of biological communities. By integrating multidisciplinary knowledge and utilizing new technologies and methodologies, the accuracy of models can be enhanced, providing a scientific foundation for mitigating climate change.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Soil Science
Jie Xue, Xianglin Zhang, Songchao Chen, Rui Lu, Zheng Wang, Nan Wang, Yongsheng Hong, Xueyao Chen, Yi Xiao, Yuxin Ma, Zhou Shi
Summary: This study investigates the potential of visible near-infrared and mid-infrared spectroscopy, as well as three model averaging methods, in predicting soil health properties. The results show that the combination of mid-infrared spectroscopy and the S-GEM model performs the best in predicting soil organic matter and pH.
Article
Soil Science
Yongsheng Hong, Songchao Chen, Bifeng Hu, Nan Wang, Jie Xue, Zhiqing Zhuo, Yuanyuan Yang, Yiyun Chen, Jie Peng, Yaolin Liu, Abdul Mounem Mouazen, Zhou Shi
Summary: Visible-to-near-infrared (vis-NIR) and mid-infrared (MIR) spectroscopy are widely used to estimate soil organic carbon (SOC). The fusion of vis-NIR and MIR data can provide accurate prediction for SOC as the individual sensor range may lack important features. Six data fusion strategies were compared, with PI-CNN achieving the best accuracy (validation R2 = 0.84) for SOC estimation. The better performance of PI-CNN over DC-CNN demonstrates the necessity of using different kernel sizes in the CNN network for fusing vis-NIR and MIR spectral data. The deep-learning fusion method based on PI-CNN is an efficient tool for integrating data from multiple sensors in soil spectral modeling.
Article
Environmental Sciences
Bifeng Hu, Hanjie Ni, Modian Xie, Hongyi Li, Yali Wen, Songchao Chen, Yin Zhou, Hongfen Teng, Hocine Bourennane, Zhou Shi
Summary: Soil organic matter (SOM) is crucial for terrestrial ecosystem functioning and is linked to global issues such as soil fertility, soil health, and climate regulation. This study collected 16,580 soil samples from farmland in Jiangxi Province and compared different models to determine the factors influencing SOM. Anthropogenic activities were found to strongly affect SOM levels, with the amount of straw return being the most important factor (31.46%). The study also showed that returning straw can improve crop production and SOM content.
LAND DEGRADATION & DEVELOPMENT
(2023)
Article
Green & Sustainable Science & Technology
Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad
Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang
Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu
Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang
Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He
Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.
JOURNAL OF CLEANER PRODUCTION
(2024)
