An LCA impact assessment model linking land occupation and malnutrition-related DALYs

Abstract

So far, land occupation impact assessment models in life-cycle assessment have predominantly considered biodiversity, ecosystem quality and ecosystem services. However, in a manner similar to water consumption, land occupation has the potential to impact food production and thereby human health. In this study, the impact pathway linking land occupation and protein-energy malnutrition was modelled, establishing a new set of regionalised characterisation factors which were applied in a case study of cotton cultivation. The impact assessment model has three main components: a food production model, a food trade model and an effect factor that relates potential food deficits to malnutrition expressed in disability-adjusted life years (DALYs). The food production model uses an NPP-based index to account for variation in the productive capability of land, as well as data on irrigation water supply and national agricultural yields to account for variation in prevailing agricultural technologies. Food production losses have the potential to impact national and global food supplies according to trade status and economic adaptation capacity assessed using the Inequality-adjusted Human Development Index. Health damage data from the Global Burden of Disease report and depth of national food deficit data from the FAO are the basis of the effect factor. The model reports potential human health impacts related to land occupation (DALY/m2 year) at 5-arc-minute spatial resolution. The model is relevant to all kinds of land occupation, including food production, as no assumptions are made about the ways food products are utilised, which can be many. The model delivers results sensibly in proportion to potential human health impacts of freshwater consumption, i.e. greater in tropical areas and lesser in arid areas. The case study showed that land occupation impacts on human health might cause one DALY/t seed cotton in extreme cases and less than one DALY per thousand tonnes in others. In the case of India, ~ 9% of national malnutrition-related DALYs were attributable to cotton cultivation which occupies ~ 8% of arable land. This new model will enable more complete assessment of land occupation impacts in LCA and is especially relevant to the assessment of food, fibre, and bioenergy products. In addition, the model enhances the ability to assess trade-offs which frequently occur, such as between land and water use and GHG emissions. The cotton case study showed that human health impacts can be grossly underestimated in LCA studies when land occupation impacts are not included.