Environmental Science and Pollution Research
This journal serves the international community in all broad areas of environmental science and related subjects with emphasis on chemical compounds.
Predicting Daily CO₂ Emissions with Machine Learning and Deep Learning Models
The recent devastating wildfires in California serve as a reminder of the urgent need for actionable climate solutions. These events, fueled by rising global temperatures and unchecked CO₂ emissions, highlight the importance of understanding and predicting carbon output on a more granular level.
The impact of renewable and non‑renewable energy consumption on aggregate output in Pakistan: robust evidence from the RALS cointegration test
This study investigates the impact of both non-energy factors and energy-specific factors on Pakistan’s aggregate output. By employing advanced econometric techniques such as the RALS cointegration test and ARDL methodology, the study explores the long-run relationships among these factors.
