scholarly journals Finding Life Cycle Assessment Research Direction with the Aid of Meta-Analysis

2012 ◽  
Vol 16 ◽  
pp. S39-S52 ◽  
Author(s):  
Alessandra Zamagni ◽  
Paolo Masoni ◽  
Patrizia Buttol ◽  
Andrea Raggi ◽  
Roberto Buonamici
2006 ◽  
Vol 12 (6) ◽  
pp. 414-421 ◽  
Author(s):  
Nathan L. Pelletier ◽  
Nathan W. Ayer ◽  
Peter H. Tyedmers ◽  
Sarah A. Kruse ◽  
Anna Flysjo ◽  
...  

2020 ◽  
Vol 12 (3) ◽  
pp. 1033 ◽  
Author(s):  
Oriana Gava ◽  
Fabio Bartolini ◽  
Francesca Venturi ◽  
Gianluca Brunori ◽  
Alberto Pardossi

Life cycle assessment is a widespread method for measuring and monitoring the environmental impacts of production processes, thereby allowing the comparison of business-as-usual with more ecological scenarios. Life cycle assessment research can support evidence-based policy making by comparing and communicating the environmental impacts of agricultural and food systems, informing about the impact of mitigating interventions and monitoring sectoral progress towards sustainable development goals. This article aims at improving the contribution of science to evidence-based policies for agricultural sustainability and food security, while facilitating further research, by delivering a content-analysis based literature review of life cycle assessment research in agricultural and food economics. Results highlight that demand-side and system-level approaches need further development, as policies need to support redesigned agricultural systems and newly conceived dietary guidelines, which combine environmental protection and health benefits, without reducing productivity. Similarly, more research effort towards consequential life cycle assessment and multidimensional assessment may benefit policy makers by considering the rebound effects associated with the large-scale implementation of impact-mitigating interventions. Promising interventions involve the promotion of waste circularization strategies, which could also improve the profitability of agriculture. For effective policy making towards agricultural sustainability and food security worldwide, countries with the greatest expected population growth and raise of urbanization rates need more attention by researchers.


2016 ◽  
Vol 22 (2) ◽  
pp. 266-276 ◽  
Author(s):  
Cristina Gomes de Souza ◽  
Rafael Garcia Barbastefano ◽  
Renata Cristina Teixeira

2017 ◽  
Vol 76 ◽  
pp. 176-184 ◽  
Author(s):  
Shengnan Geng ◽  
Yuan Wang ◽  
Jian Zuo ◽  
Zhihua Zhou ◽  
Huibin Du ◽  
...  

2014 ◽  
Vol 19 (10) ◽  
pp. 1674-1685 ◽  
Author(s):  
Haibin Chen ◽  
Yu Yang ◽  
Yan Yang ◽  
Wei Jiang ◽  
Jingcheng Zhou

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4228 ◽  
Author(s):  
Steffi Weyand ◽  
Carolin Wittich ◽  
Liselotte Schebek

Emerging photovoltaic technologies are expected to have lower environmental impacts during their life cycle due to their extremely thin-film technology and resulting material savings. The environmental impacts of four emerging photovoltaics were investigated based on a meta-analysis of life-cycle assessment (LCA) studies, comprising a systematic review and harmonization approach of five key indicators to describe the environmental status quo and future prospects. The status quo was analyzed based on a material-related functional unit of 1 watt-peak of the photovoltaic cell. For future prospects, the functional unit of 1 kWh of generated electricity was used, including assumptions on the use phase, notably on the lifetime. The results of the status quo show that organic photovoltaic technology is the most mature emerging photovoltaic technology with a competitive environmental performance, while perovskites have a low performance, attributed to the early stage of development and inefficient manufacturing on the laboratory scale. The results of future prospects identified improvements of efficiency, lifetime, and manufacturing with regard to environmental performance based on sensitivity and scenario analyses. The developed harmonization approach supports the use of LCA in the early stages of technology development in a structured way to reduce uncertainty and extract significant information during development.


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