Results 181 to 190 of about 366,742 (304)
ABSTRACT Firms are increasingly looking into carbon dioxide removal (CDR), a set of options to take past emissions of greenhouse gases out of the atmosphere. Often two basic categories of CDR are distinguished: nature‐based solutions, such as planting trees or restoring wetlands, and technology‐based solutions, such as various forms of carbon capture ...
Sabrina Mili +3 more
wiley +1 more source
Experimental investigation and AI-based prediction of engine performance and emissions using CeO<sub>2</sub>-enhanced biodiesel blends. [PDF]
K G +4 more
europepmc +1 more source
ABSTRACT This study examines climate change risk disclosure in the global energy sector, where firms face intense stakeholder scrutiny and legitimacy pressures. We develop a novel domain‐specific textual analysis measure to capture climate change risk disclosures, improving on prior approaches based on generic environmental terminology.
Khaldoon Albitar, Ali Meftah Gerged
wiley +1 more source
Mitigating increasing wildfire risk through fuel break innovations. [PDF]
Link NT +20 more
europepmc +1 more source
ABSTRACT Whether corporate carbon management can enhance productive efficiency is central to firms' long‐term competitiveness and determines whether carbon reduction efforts can be sustained beyond regulatory compliance. This study examines how corporate carbon risk and opportunity management affects firm productivity (measured by total factor ...
Nan Huang, Hanlu Fan, Ruoxin Zhu
wiley +1 more source
Using Low-Cost Sensors for Fenceline Monitoring to Measure Emissions from Prescribed Fires. [PDF]
Guth A, Dauner M, Coffey ER, Hannigan M.
europepmc +1 more source
Consumer Mobile Phone Recycling Behaviour: A Systematic Review and Future Research Agenda
ABSTRACT Mobile phone recycling has received increasing attention from scholars and practitioners due to its environmental, social, and economic impacts. However, knowledge about consumer mobile phone (MP) recycling behaviour is fragmented, making it challenging to develop effective strategies to promote this behaviour. This study follows the Preferred
Xinru (Angie) Jiang +4 more
wiley +1 more source
Machine learning predictions for enhancing engine performance and emission using aluminum oxide nano additives in castor biodiesel. [PDF]
Nachippan M +6 more
europepmc +1 more source
A machine‐learning framework integrating multimodel prediction, feature selection, and SHAP interpretability is developed to uncover structure–performance relationships of Cu‐based CO2‐to‐methanol catalysts. The optimized XGBoost model and an online prediction platform enable accurate selectivity prediction and data‐driven catalyst design.
Conglong Su +11 more
wiley +1 more source
Statistical dynamics of wildfire burned area from cellular-automata simulators. [PDF]
Sahila A +5 more
europepmc +1 more source

