Carbon footprint of food - approaches from national input-output statistics and a LCA of a food portion

The aim of the study, on which this paper is based, was to provide guidance to consumers to make environmentally responsible choices in their food consumption, to assist food supply chain stakeholders to identify the key areas for environmental improvements, and to provide policy makers with a tool for monitoring the potential impacts on climate change resulting from developments within the food sector. At the macro level, the EIO-LCA model was developed specifically for the Finnish food chain; at the micro level, LCAs were performed on 30 lunch portions. The contribution of the Finnish food chain to climate change was 14%, which comprised 40% CO₂ emissions, 25% CH₄ emissions, and 34% N₂O emissions. The share of impacts from domestic agricultural processes was the highest, at 69%. The impact of a single lunch portion ranged between 0.65 and 3.80 kg of equivalent CO₂. According to the EIO-LCA model, the average impact was 7.7 kg CO₂ eq/person daily. The consumer phase accounted for between 8 and 47% of the climate change impacts for homemade portions. In ready-to-eat portions industry and retail phases were emphasized, representing 25-38% of climate change impacts. We present an approach to steer the Finnish food sector onto an environmentally sustainable path; practical tools for consumers and farmers will especially need to be developed further.     

Pedestrian behavior and exit selection in evacuation of a corridor - An experimental study

In this paper, we present an experiment whose purpose was to study evacuees’ exit selection under different behavioral objectives. The experiment was conducted in a corridor with two exits located asymmetrically. This geometry was used to make most participants face a nontrivial decision on which exit to use. We analyze the behavior on a macroscopic level using statistical methods. Our results suggest that the members of an evacuating crowd may not be able to make optimal decisions when assessing the fastest exit to evacuate. In addition, the egress time of the whole crowd turns out to be shorter when the evacuees behave egoistically instead of behaving cooperatively. This is an interesting result because many studies on real emergencies show that evacuees tend to cooperate and act altruistically.     

An assessment of greenhouse gas emissions and material flows caused by the Finnish economy using the ENVIMAT model

An environmentally extended input-output (EE-IO) analysis - environmental impacts of material flows caused by the Finnish economy - was carried out in order to improve data on production and consumption in Finland. The study resulted in the ENVIMAT model, which can be used to analyze the relationship between material flows, environmental impacts and the economy. The model is based on monetary and physical input-output tables and an environmental life-cycle impact assessment. This article summarizes the main methodological aspects and findings regarding the material flows and climate impacts caused by the Finnish economy in 2002 and 2005. The Finnish model has relatively detailed input data with 150 industries and 918 products and the data on imports was assessed according to a mixed approach with the help of life-cycle inventory data. The results of the model showed that the Finnish economy uses imported material resources as much as domestic resources. Life-cycle greenhouse gas (GHG) emissions caused by imports were equivalent to 70-80% of domestic emissions. The GHG emissions embodied in imports (emissions abroad) and exports (emissions within Finland) were of the same magnitude. The analysis showed that the service sector accounted for 44% of GHG emissions caused by the domestic final use of products. Analysis of the results also showed that the indicator of total material requirement (TMR) should not be used for environmental impact comparisons of products and services. In the future, the aim is to use the ENVIMAT model for assessing temporal changes in the economy; for monitoring sustainable development; for planning climate change mitigation; and for identifying important factors in the economy and assessing their impacts.