Household consumption of durable goods is associated with environmental impacts in production, use and end-of-life treatment, all of which could be affected by actions to extend product lifetime. In order to estimate environmental benefits and direct strategies for lifetime extension we need to understand the consumption dynamics for durable goods. In this paper we present a stock-driven dynamic model of household durables based on material flow analysis (MFA) methodology. We investigate the stocks and flows of furniture and appliances in Norwegian households, using population and product ownership rate as drivers for stock levels and socioeconomic drivers project future stock requirements. The model is calibrated by collecting historical data on ownership, purchase, and disposal of such goods. The considered durables are divided into representative archetypes characterized by typical service lifetime. The dynamic, vintage modelling approach is well suited to consider effects such as an increased need for maintenance and/or operational energy among household products with prolonged lifetime. We illustrate uses for the model to quantify impacts caused by demand for goods and the environmental system effects associated with lifetime extension, and we discuss insights to direct effective measures. Potential applications include a support for product design, household behavior campaigns and environmental policy making.
Effective mitigation of greenhouse gas (GHG) emissions in the buildings sector requires a full understanding of the factors influencing emissions over the life-cycle of buildings, particularly in places where large additions to the building stock are expected. Currently, little is known about what affects the GHG emissions of buildings located in warmer climates, a typical situation for many emerging economies. This paper presents a study of emissions from Brazilian office buildings using building archetypes. A sensitivity analysis explores possible parameter ranges, various contributions to life-cycle impacts and their key drivers. For each of the 1000 building variations in the sample, the emissions were calculated using a life-cycle assessment. Multivariate regression analysis enabled the study of the results' sensitivity to 10 parameters, influencing building operation, design and others. The emissions ranged from 20 to 106 kg CO 2 -eq/m 2 gross floor area and year. Electricity mix, climate and cooling efficiency were the most impactful parameters, but building component service time was also significant.
POLICY RELEVANCEEmerging economies are expected to rapidly increase their building stock and energy use, particularly for cooling in the coming decades. The findings show the key factors influencing the GHG emissions of office buildings in warm climates, typical for many emerging economies, such as Brazil. For effective mitigation, priority should be placed on reducing the carbon intensity of electricity and encouraging highly efficient heating, ventilation and air-conditioning systems. Policymakers may want to offer incentives for office buildings with a combination of natural ventilation and mechanical cooling, because they were less emission-intensive in every investigated city. The benefits are the biggest for buildings in which a high proportion of windows can be opened for natural ventilation.
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