Comprehensive model of environmental degradation assessment.

Area of Science:

• Environmental Science
• Techno-economic Modeling
• Lifecycle Impact Assessment

Background:

• Existing lifecycle impact assessment (LCIA) models like ReCiPe2016 have limitations in comprehensively evaluating environmental degradation.
• There is a need to integrate economic impacts, tourism potential, and intergenerational benefits into environmental degradation assessments.
• Energy-intensive industries require advanced models to understand their environmental footprint.

Purpose of the Study:

• To develop a comprehensive techno-economic model, Financial Developed ReCiPe (FDR), for assessing environmental degradation.
• To enhance the ReCiPe2016 approach by incorporating additional cause-and-effect pathways and environmental properties.
• To quantify environmental degradation considering economic impacts, tourism potential, and intergenerational benefits.

Main Methods:

• Development of a techno-economic model (FDR) based on the ReCiPe2016 approach.
• Quantification of environmental degradation using fate factors (FF), effect factors (EF), exposure factors (XF), and economic impacts.
• Inclusion of uncertainties using Individualist, Hierarchist, and Egalitarian perspectives and Monte Carlo Simulation (MCS).

Main Results:

• The FDR model reveals significant deviations in the Hierarchist perspective, with increased non-cancer diseases (17%) and malnutrition (13%).
• Forest destruction impacts include annual emissions of CO2 (86 tons/hectare), PM2.5 (426 tons/hectare), and crude oil (1540 tons/hectare).
• Ocean acidification contributes approximately 0.03% in the Hierarchist perspective compared to SO2 and terrestrial acidification.

Conclusions:

• The FDR model effectively bridges the gap in LCIA for energy-intensive industries.
• The model provides a more comprehensive assessment of environmental degradation by integrating economic and social factors.
• The findings highlight the importance of considering diverse environmental impacts and uncertainties in industrial assessments.