Proportional impact prediction model of coating material on nitrate leaching of slow-release Urea Super Granules (USG) using machine learning and RSM technique

SS Swain, TK Khura, PK Sahoo, KA Chobhe… - Scientific Reports, 2024 - nature.com
An accurate assessment of nitrate leaching is important for efficient fertiliser utilisation and
groundwater pollution reduction. However, past studies could not efficiently model nitrate …

Application of Artificial Intelligence to Predict CO2 Emissions: Critical Step towards Sustainable Environment

AM Nassef, AG Olabi, H Rezk, MA Abdelkareem - Sustainability, 2023 - mdpi.com
Prediction of carbon dioxide (CO2) emissions is a critical step towards a sustainable
environment. In any country, increasing the amount of CO2 emissions is an indicator of the …

Post-COVID-19 pandemic and the Paris agreement: a socioeconomic analysis and carbon emissions forecasting in developed and developing countries

ZX Hoy, JF Leong, KS Woon - Clean Technologies and Environmental …, 2024 - Springer
The COVID-19 pandemic caused profound impacts on the global economy, resulting in a
sharp drop in carbon emissions as energy demand fell. The emissions reduction due to past …

Improving the spatial and temporal estimation of ecosystem respiration using multi-source data and machine learning methods in a rainfed winter wheat cropland

R Lu, P Zhang, Z Fu, J Jiang, J Wu, Q Cao… - Science of The Total …, 2023 - Elsevier
The investigation of ecosystem respiration (RE) and its vital influential factors along with the
timely and accurate detection of spatiotemporal variations in RE are essential for guiding …

Study on carbon emission reduction countermeasures based on carbon emission influencing factors and trends

X Tang, S Liu, Y Wang, Y Wan - Environmental Science and Pollution …, 2024 - Springer
The carbon mitigation response encompasses a variety of strategies aimed at mitigating
greenhouse gas emissions resulting from human activities. These measures are crafted to …

Forecasting of energy-related carbon dioxide emission using ANN combined with hybrid metaheuristic optimization algorithms

H Moayedi, A Mukhtar, NB Khedher… - Engineering …, 2024 - Taylor & Francis
Energy-related CO2 emissions are one of the biggest concerns facing urban design today,
increasing rapidly as cities grow. This study uses as inputs the GDP of the G8 nations (from …

The impact of double carbon goals on industrial structure in a region of China

Y Xie, H Zhang, Y Chen - Computers & Industrial Engineering, 2023 - Elsevier
As an extensive and profound systemic change, carbon emission reduction is driving the
reform and transformation of China's economic and industrial structure. Firstly, a variable …

Development and performance comparison of optimized machine learning-based regression models for predicting energy-related carbon dioxide emissions

E Koca Akkaya, AV Akkaya - Environmental Science and Pollution …, 2023 - Springer
Accurate prediction of CO2 emissions for the countries has become a crucial task in decision-
making processes for planning energy conversion and usage, supporting the design of …

[HTML][HTML] Integrating machine learning methods for computing greenhouse gas emissions baselines in agriculture

BR de Almeida Moreira, D Hine, S Yadav - Journal of Cleaner Production, 2024 - Elsevier
Addressing climate change requires significant reductions in global greenhouse gas (GHG)
emissions. In Australia, agriculture accounts for approximately 16.8% of total emissions …

Journey from an enabler to a strategic leader: integration of the medical affairs function in ESG initiatives and values

D Furtner, G Hutas, BJW Tan, R Meier - Pharmaceutical Medicine, 2023 - Springer
Like most private enterprises, the pharmaceutical industry has deeply rooted environmental,
social, and governance (ESG) matters that challenge its long-term sustainability …