Assessment of the potential for carbon sink enhancement in the overlapping ecological project areas of China by Xiaojuan Xu, Fusheng Jiao, Dayi Lin, Jie Qiu, Changxin Zou, Kun Zhang

“…Using the ensemble empirical mode decomposition method and machine learning algorithms (enhanced boosted regression trees), the aims of this study to elucidate the stability of carbon sinks and their driving mechanisms in areas where ecological projects overlap and to predict the potential enhancement in carbon sinks under varying climate and human activity scenarios. …”
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Modeling Bottom Dissolved Oxygen on the East China Sea Shelf Using Interpretable Machine Learning by Chengqing Zhang, Qicheng Meng, Xiao Ma, Anqi Liu, Feng Zhou

“…This study develops an interpretable machine learning framework to simulate the bottom DO distribution on the East China Sea (ECS) shelf and explore its potential driving mechanisms. …”
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Predictive maintenance based on anomaly detection in photovoltaic system using SCADA data and machine learning by Agussalim Syamsuddin, Andrew Cahyo Adhi, Amie Kusumawardhani, Toni Prahasto, Achmad Widodo

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Alternative lubrication-cooling approaches for broaching medium-carbon steel: Machining performance and life cycle analysis by Cristian Pérez-Salinas, Ander del Olmo, L. Norberto López de Lacalle, Diego Núñez, Leticia Mayorga, Maritza Ureña

“…The IPCC method assessed global warming potential (GWP) from greenhouse gas emissions, while CED method quantified total energy consumption throughout the process. …”
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Monitoring the dynamics of coastal wetlands ecosystems in Brittany (France) using LANDSAT time series and machine learning by Adrien Le Guillou, Simona Niculescu

“…The study exploits the potential of satellite image time series (SITS), machine learning (ML), and Random Forest (RF) algorithms.These algorithms enable the software to learn autonomously from multiple datasets, including Landsat 4/5 and 8 SITS archive images. …”
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Detection of Mycotoxins in Cereal Grains and Nuts Using Machine Learning Integrated Hyperspectral Imaging: A Review by Md. Ahasan Kabir, Ivan Lee, Chandra B. Singh, Gayatri Mishra, Brajesh Kumar Panda, Sang-Heon Lee

“…Food safety in these commodities is crucial, as they are highly susceptible to mold growth and mycotoxin contamination in warm, humid environments. This review explores hyperspectral imaging (HSI) integrated with machine learning (ML) algorithms as a promising approach for detecting and quantifying mycotoxins in cereal grains and nuts. …”
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Potential and Challenges of Biofuels from Keruing (Dipterocarpus spp.) to Support Sustainable Fuel Transition in the Transportation Sector by Nurin Alwaaritsy, Arista Romadan

“…This study aims to analyze the challenges of developing biofuel from keruing for the transportation sector in Indonesia, using a mixed method enhanced by machine learning for data analysis. The results show that keruing oil has potential as a biofuel, but the main challenges lie in infrastructure, knowledge limitations, and processing techniques. …”
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Monitoring Snow Water Equivalent (SWE) Using MODIS Time-Series Data and Machine Learning in Turnagain Arm, Alaska by K. Kazari, M. Hasanlou

“…This comprehensive approach demonstrates the potential of integrating remote sensing data and Machine Learning techniques to monitor environmental changes caused by global warming.…”
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Environmental Effects in Life Cycle Assessment of Machine-Vision-Driven Spall Repair Material Estimation for Sustainable Road Maintenance by Junhwi Cho, Shanelle Aira Rodrigazo, Hwang-Hee Kim, Su-Jin Lee, Chan Gi Park, Jaeheum Yeon

“…This study highlights the potential of machine-vision-driven repair material quantity takeoff as a more efficient and sustainable alternative. …”
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Machine Learning and Morphometric Analysis for Evaluating the Vulnerability of Tundra Landscapes to Thermokarst Hazards in the Lena Delta: A Case Study of Arga Island by Andrei Kartoziia

“…This approach enables big geodata-driven predictive modeling of permafrost hazards, improving thermokarst risk assessment. It highlights machine learning and Google Earth Engine’s potential for forecasting landscape transformations in vulnerable Arctic regions.…”
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To the issue of optimising the performance of a scroll compressor as part of a CO2 booster refrigerating machine in order to increase its efficiency by V. A. Pronin, A. V. Kovanov, V. A. Tsvetkov, E. N. Mikhailova, P. A. Belov

“…With the decreasing use of refrigerants with a high global warming potential, increasing the efficiency of refrigeration machines using natural working fluids is a very urgent task. …”
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A Comparative Analysis of Machine Learning Techniques for Predicting the Performance of Microchannel Gas Coolers in CO₂ Automotive Air-Conditioning Systems by Shehryar Ishaque, Naveed Ullah, Man-Hoe Kim

“…In this context, CO₂ microchannel gas coolers (MCGCs) have emerged as promising alternatives due to their low global warming potential (GWP) and environmental benefits. …”
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Life Cycle Assessment and Activity-Based Costing for Low-Cost Aluminum die manufacturing: A comparative study of machining process, conventional and rapid investment casting by Samina Bibi, Muhammad Sajid, Wasim Ahmad, Muhammad Asad Ali, Mirza Jahanzaib, Salman Hussain

“…LCA findings further position RIC as the most sustainable option, recording the lowest global warming potential (3.56865e+2 kg CO₂-eq), fossil fuel depletion (4.31693e+3 MJ), and acidification (1.78031 kg SO₂-eq). …”
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The Evolving Role of Extracorporeal In Situ Perfusion Technology in Organ Donor Recovery with Donation After Circulatory Determination of Death Organ Donors by Victoria R. Hammond, Marisa E. Franklin, Glen A. Franklin

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Comparison of Ammonia Volatilization from Inorganic and Organic Fertilizers during Chinese Cabbage Cultivation by Eun-Chae Im, Seong-Jik Park

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A novel model for mapping soil organic matter: Integrating temporal and spatial characteristics by Xinle Zhang, Guowei Zhang, Shengqi Zhang, Hongfu Ai, Yongqi Han, Chong Luo, Huanjun Liu

“…A novel approach is proposed that combines the CNN-LSTM model with a Cosine Annealing Warm Restarts learning rate (CNN-LSTM-CAWR) to enhance the accuracy of SOM mapping. …”
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Identifying a Pattern of Predictable Decadal North Pacific SST Variability in Historical Observations by Emily M. Gordon, Noah S. Diffenbaugh

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Clustering to Characterize Extreme Marine Conditions for the Benthic Region of the Northeastern Pacific Continental Margin by Amber M. Holdsworth, Andrew Shao, James R. Christian

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An Evidential Solar Irradiance Forecasting Method Using Multiple Sources of Information by Mohamed Mroueh, Moustapha Doumiati, Clovis Francis, Mohamed Machmoum

“…In the context of global warming, renewable energy sources, particularly wind and solar power, have garnered increasing attention in recent decades. …”
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Deep Learning Advances Arctic River Water Temperature Predictions by Shuyu Y. Chang, Jon Schwenk, Kurt C. Solander

“…Abstract The accelerated warming in the Arctic poses serious risks to freshwater ecosystems by altering streamflow and river thermal regimes. …”
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