Comparative LCA of diesel and grid electricity for agricultural irrigation in Iran: why diesel outperforms in fossil-reliant grids

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Abstract

This study presents a comparative environmental impact assessment of well water extraction systems employed for agricultural irrigation in Iran, focusing on two prevalent energy sources: diesel engines and grid-connected electricity. Utilizing life cycle assessment methodology, the research evaluates key environmental indicators, encompassing abiotic depletion, global warming potential (GWP), human toxicity, aquatic ecotoxicity, acidification, eutrophication, and photochemical oxidation. Data collected from 100 agricultural wells were analyzed to compare the environmental performance of each energy source. The objective is to provide policymakers with data-driven insights for the development of effective mitigation strategies. Environmental analysis revealed that diesel systems emit 1.34kg CO2/m3, compared to 1.59kg CO2/m3 in grid systems. While grid-connected systems avoid on-farm emissions, they suffer from high upstream impacts due to Iran’s fossil fuel-dominant electricity generation mix (94%). The diesel system showed lower impacts in seven of eleven categories, including GWP, abiotic depletion, and marine ecotoxicity. In contrast, grid systems had slightly lower values in eutrophication (5.29×10−4 vs. 1.66×10−3 kg PO4 eq) and ozone layer depletion. The overall Environmental Composite Index (ECI) was 3.68×10−4 nPt for diesel and 5.77×10−4 nPt for electricity, indicating a 56.79% higher burden for the grid-powered system. The findings emphasize the role of local energy mix, pump efficiency, and transmission losses in environmental outcomes, suggesting that improvements in Iran’s grid efficiency and a transition to renewable energy are key to reducing impacts.

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Namdari, M. (2025). Comparative LCA of diesel and grid electricity for agricultural irrigation in Iran: why diesel outperforms in fossil-reliant grids. PLOS ONE, 20(7 JULY). https://doi.org/10.1371/journal.pone.0324371

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