Environmental sustainability of conventional and organic farming: Accounting for ecosystem services in life cycle assessment.

Today, there is an ongoing debate about the environmental sustainability of the products of organic farming. To compare the performance of conventional and organic farming systems regarding environmental impact and productivity, the comprehensive environmental assessment tool 'life cycle assessment' can be used. The lower crop yields attained by organic systems compared to conventional farming systems might, however, outweigh the benefits of the use of more environmental-friendly practices when evaluating the environmental impact per product unit. Although these practices are beneficial for the environment, which is reflected in the delivery of a range of ecosystem services (ES), the focus is traditionally put only on the (harvested) product. Because the agricultural product involves actually a bundle of ES, the impact should be allocated among the whole output of an agricultural system. In this study, we propose an allocation procedure based on the capacity of agricultural systems to deliver ES to divide the environmental impact over all agricultural outputs (i.e. provisioning and other ES). Allocation factors are developed for conventional and organic arable farming systems. Applying these allocation factors, we demonstrate that for about half of the studied food products (including maize, potato), organic farming has clear environmental benefits in terms of resource consumption in comparison to conventional cultivation methods. This allocation approach allows a more complete comparison of the environmental sustainability of organically and conventionally produced food.

Introduction of a natural resource balance indicator to assess soil organic carbon management: Agricultural Biomass Productivity Benefit.

The rising demand for feed and food has put an increasing pressure on agriculture, with agricultural intensification as a direct response. Notwithstanding the higher crop productivity, intensive agriculture management entails many adverse environmental impacts. Worldwide, soil organic carbon (SOC) decline is hereby considered as a main danger which affects soil fertility and productivity. The life cycle perspective helps to get a holistic overview when evaluating the environmental sustainability of agricultural systems, though the impact of farm management on soil quality aspects is often not integrated. In this paper, we introduce an indicator called Agricultural Biomass Productivity Benefit of SOC management (ABB_SOC), which, relying on natural resource consumption, enables to estimate the net effect of the efforts made to attain a better soil quality. Hereby the focus is put on SOC. First, we introduce a framework to describe the SOC trend due to farm management decisions. The extent to which remediation measures are required are used as a measure for the induced SOC losses. Next, ABB_SOC values are calculated as the balance between the natural resource consumption of the inputs (including remediation efforts) and the desired output of arable crop production systems. The models RothC and EU-Rotate_N are used to simulate the SOC evolution due to farm management and the response of the biomass productivity, respectively. The developed indicator is applied on several rotation systems in Flanders, comparing different remediation strategies. The indicator could be used as a base for a method to account for soil quality in life cycle analysis.

Environmental life cycle assessment of grain maize production: An analysis of factors causing variability.

To meet the growing demand, high yielding, but environmentally sustainable agricultural plant production systems are desired. Today, life cycle assessment (LCA) is increasingly used to assess the environmental impact of these agricultural systems. However, the impact results are very diverse due to management decisions or local natural conditions. The impact of grain maize is often generalized and an average is taken. Therefore, we studied variation in production systems. Four types of drivers for variability are distinguished: policy, farm management, year-to-year weather variation and innovation. For each driver, scenarios are elaborated using ReCiPe and CEENE (Cumulative Exergy Extraction from the Natural Environment) to assess the environmental footprint. Policy limits fertilisation levels in a soil-specific way. The resource consumption is lower for non-sandy soils than for sandy soils, but entails however more eutrophication. Farm management seems to have less influence on the environmental impact when considering the CEENE only. But farm management choices such as fertiliser type have a large effect on emission-related problems (e.g. eutrophication and acidification). In contrast, year-to-year weather variation results in large differences in the environmental footprint. The difference in impact results between favourable and poor environmental conditions amounts to 19% and 17% in terms of resources and emissions respectively, and irrigation clearly is an unfavourable environmental process. The best environmental performance is obtained by innovation as plant breeding results in a steadily increasing yield over 25 years. Finally, a comparison is made between grain maize production in Flanders and a generically applied dataset, based on Swiss practices. These very different results endorse the importance of using local data to conduct LCA of plant production systems. The results of this study show decision makers and farmers how they can improve the environmental performance of agricultural systems, and LCA practitioners are alerted to challenges due to variation.