When the Background Matters: Using Scenarios from Integrated Assessment Models in Prospective Life Cycle Assessment

Prospective life cycle assessment (LCA) needs to deal with the large epistemological uncertainty about the future to support more robust future environmental impact assessments of technologies. This study proposes a novel approach that systematically changes the background processes in a prospective LCA based on scenarios of an integrated assessment model (IAM), the IMAGE model. Consistent worldwide scenarios from IMAGE are evaluated in the life cycle inventory using ecoinvent v3.3. To test the approach, only the electricity sector was changed in a prospective LCA of an internal combustion engine vehicle (ICEV) and an electric vehicle (EV) using six baseline and mitigation climate scenarios until 2050. This case study shows that changes in the electricity background can be very important for the environmental impacts of EV. Also, the approach demonstrates that the relative environmental performance of EV and ICEV over time is more complex and multifaceted than previously assumed. Uncertainty due to future developments manifests in different impacts depending on the product (EV or ICEV), the impact category, and the scenario and year considered. More robust prospective LCAs can be achieved, particularly for emerging technologies, by expanding this approach to other economic sectors beyond electricity background changes and mobility applications as well as by including uncertainty and changes in foreground parameters. A more systematic and structured composition of future inventory databases driven by IAM scenarios helps to acknowledge epistemological uncertainty and to increase the temporal consistency of foreground and background systems in LCAs of emerging technologies.     

Land-use changes assessed by overlay or mosaic methods: Which method is best for management planning?

Environmental planning must determine management practices for a given territory based on the landscape processes that have occurred over time and their consequences. Therefore, environmental planning decisions must be based on strong empirical evidence that can be easily understood by all involved parties. Several studies have highlighted the methodological deficiencies that occur when obtaining and interpreting such issues, particularly in heterogeneous landscapes with complex interactions. In this paper, we evaluated two methodological approaches that are used in management planning, land use/cover change (LUCC) and mosaic change (MC) to compare their effectiveness and suitability for supporting decision-making. We applied these methods to the coastal landscape of São Sebastião Island, Brazil, which has undergone many changes in the last 50 years. For two years, land use/cover maps were produced using GIS and assessed according to changes in landscape elements (LUCC) and boundaries (MC). Overall, the LUCC failed to identify sets with similar structural heterogeneities in the landscape. However, the LUCC is easier for stakeholders to understand and apply than the MC. The MC method better presented the evolution of the relationship between the landscape elements and heterogeneity.     

Introduction: A perspective from the humanities-science boundary

The articles in this special issue range across such influences on climate as solar emissions, orbital precession, atmosphere, oceans, and precipitation, and generally approach, each in some context, human implications of these phenomena. The common underlying theme of all of the papers is the effect the phenomena have on radiation balance as measured by global average temperature. This introductory paper undertakes a formulation of radiation balance theory that makes it serviceable to students of regional science. The objective is to go beyond inference of cause and effect by correlation to causal accounts of cause and effect through regional climatic and cultural processes. This is accomplished primarily by revisualization of the energy system with regions as dependent spatiotemporal entities, and temporally through a protocol for regional episode definition.This special issue ofHuman Ecology consists of the American Anthropological Association Invited Symposium on Global Climate Change.     

LiGAPS-Beef,a mechanistic model to explore potential and feed-limited beef production 1: model description and illustration

The expected increase in the global demand for livestock products calls for insight in the scope to increase actual production levels across the world. This insight can be obtained by using theoretical concepts of production ecology. These concepts distinguish three production levels for livestock: potential (i.e. theoretical maximum) production, which is defined by genotype and climate only; feed-limited production, which is limited by feed quantity and quality; and actual production. The difference between the potential or limited production and the actual production is the yield gap. The objective of this paper, the first in a series of three, is to present a mechanistic, dynamic model simulating potential and feed-limited production for beef cattle, which can be used to assess yield gaps. A novelty of this model, named LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems – Beef cattle), is the identification of the defining factors (genotype and climate) and limiting factors (feed quality and available feed quantity) for cattle growth by integrating sub-models on thermoregulation, feed intake and digestion, and energy and protein utilisation. Growth of beef cattle is simulated at the animal and herd level. The model is designed to be applicable to different beef production systems across the world. Main model inputs are breed-specific parameters, daily weather data, information about housing, and data on feed quality and quantity. Main model outputs are live weight gain, feed intake and feed efficiency (FE) at the animal and herd level. Here, the model is presented, and its use is illustrated for Charolais and Brahman × Shorthorn cattle in France and Australia. Potential and feed-limited production were assessed successfully, and we show that FE of herds is highest for breeds most adapted to the local climate conditions. LiGAPS-Beef also identified the factors that define and limit growth and production of cattle. Hence, we argue the model has scope to be used as a tool for the assessment and analysis of yield gaps in beef production systems.