Energy Reports (Nov 2021)
Energy-environmental life cycle assessment and cumulative exergy demand analysis for horticultural crops (Case study: Qazvin province)
Abstract
Horticultural products are an important source of carbohydrates, proteins, organic acids, vitamins and minerals for human nutrition. The objective of this study is to evaluate energy use pattern, environmental impacts and cumulative exergy demand analysis under different cropping systems including pistachio, nectarine, peach and apple in Qazvin province of Iran. Results showed the total energy consumption of pistachios, nectarines, peaches and apples were 24100 MJ ha −1, 25150 MJ ha −1, 30100 MJ ha −1 and 26800 MJ ha −1, respectively. The life cycle assessment method is considered as an appropriate assessment tool for ecosystem analysis through identification, quantification and evaluation of discharged and released resources in the environment. Analysis used ReCiPe2016 method, three environmental categories including (human health, ecosystems and resources) in this study were selected to cover different environmental impacts. On-Orchard emissions and chemical fertilizers are two important factors in the environmental emissions of horticultural products. The share of On-Orchard publications in pistachio, nectarine and peach crops is more than 75% related to human damage category. In addition, the amount of nitrogen in the ecosystem category has a significant effect. The results related to the resource damage category show that the rate of nitrogen release in pistachios, nectarines, peaches and apples is about 45%, 40%, 35% and 30%, respectively. Cumulative exergy demand analysis shows that pistachio and nectarine products have the highest and lowest energy release in all forms, respectively. In general, it can be concluded that the use of organic fertilizers and replacement of worn equipment can help to produce more sustainable horticultural products. Also, it is recommended for future studies use of modeling methods to predict the products under study as well as fuzzy optimization methods to save energy and reduce environmental impact.
