Multilevel life cycle assessment to evaluate prospective agricultural development scenarios in a semi-arid irrigated region of Tunisia

Abstract

Listen

Translate article

CONTEXTTo design policies for sustainable irrigation planning, public decision-makers need knowledge about the potential environmental impacts of irrigated farming systems. In a previous paper, we proposed to couple Life Cycle Assessment (LCA) and Agrarian System Diagnosis (ASD) to build the Life Cycle Inventory (LCI) of a farming region in a context of data scarcity and farming system diversity. This method was applied to the semi-arid irrigated plain of Kairouan (Tunisia). OBJECTIVESThe aim of the present paper is to demonstrate how this new ASD-based LCA method is used to conduct the impact assessment of this farming region, under current conditions and for two prospective scenarios. METHODSTwo functional units (FU) were used: the area and the gross product generated. Life Cycle Impact Assessment (LCIA) was conducted based on a multilevel process, by converting LCI data collected for each cropping/ livestock system into LCIA outputs, which were then consolidated at the farming system (FS) and at the regional scales. Two scenarios, based on observed trends, were assessed: the “agrarian” scenario (driven by a shift from family to corporate farming) and the “hydrological” scenario (driven by a water table drawdown). RESULTSEnvironmental hotspots were identified at each scale: the most impactful FS was the “mixed family farming” (intermediate access to water), because of its large share of land at the regional scale (45%). In this FS, the most harmful cropping system was input-intensive olive groves intercropped with a melon-pepper/ cereal/ tomato rotation, in which most impacts (35%) were attributable to the input-intensive “melon” crop, and more particularly to “manufacture and transport of fertilizer”, including farmyard manure. Globally, the most harmful processes were water and fertilizer use (fertilizer manufacturing and transportation). This downscaling is very useful to inform public policies on the most harmful productions. The impacts in human, ecosystem and resource endpoints increased by 11%, 2%, 9% and 23%, 27% and 40%, for the agrarian and hydrological scenarios respectively. SIGNIFICANCEThese results show that observed trends in farming practices evolution (more irrigation) should be stopped. Our method has three main strengths: i) inter-farms synergies are accounted for in the LCIA, which is essential to promote circularity; ii) thanks to the innovative and multilevel approach, the origins of environmental hotspots can be investigated and later mitigated by future policies; iii) ASD helps to design sustainable scenarios by identifying current trends and regional thresholds (resources, pollution and workforce) that cannot be overcome.