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An extensive body of literature demonstrates how higher density leads to more efficient energy use and lower greenhouse gas (GHG) emissions from transport and housing. However, our current understanding seems to be limited on the relationships between the urban form and the GHG emissions, namely how the urban form affects the lifestyles and thus the GHGs on a much wider scale than traditionally assumed. The urban form affects housing types, commuting distances, availability of different goods and services, social contacts and emulation, and the alternatives for pastimes, meaning that lifestyles are actually situated instead of personal projects. As almost all consumption, be it services or products, involves GHG emissions, looking at the emissions from transport and housing may not be sufficient to define whether one form would be more desirable than another. In the paper we analyze the urban form-lifestyle relationships in Finland together with the resulting GHG implications, employing both monetary expenditure and time use data to portray lifestyles in different basic urban forms: metropolitan, urban, semi-urban and rural. The GHG implications are assessed with a life cycle assessment (LCA) method that takes into account the GHG emissions embedded in different goods and services. The paper depicts that, while the direct emissions from transportation and housing energy slightly decrease with higher density, the reductions can be easily overridden by sources of indirect emissions. We also highlight that the indirect emissions actually seem to have strong structural determinants, often undermined in studies concerning sustainable urban forms. Further, we introduce a concept of 'parallel consumption' to explain how the lifestyles especially in more urbanized areas lead to multiplication of consumption outside of the limits of time budget and the living environment. This is also part I of a two-stage study. In part II we will depict how various other contextual and socioeconomic variables are actually also very important to take into account, and how diverse GHG mitigation strategies would be needed for different types of area in different locations towards a low-carbon future.

Urban structure influences directly or indirectly the majority of all green house gas (GHG) emissions in cities. The prevailing belief is that dense metropolitan areas produce less carbon emissions on a per capita basis than less dense surrounding rural areas. Consequently, density targets have a major role in low-carbon urban developments. However, based on the results of this study, the connection seems unclear or even nonexistent when comprehensive evaluation is made. In this letter, we propose a hybrid life cycle assessment (LCA) method for calculating the consumption-based carbon footprints in metropolitan areas, i.e. carbon consumption, with the emphasis on urban structures. The method is input-output-based hybrid LCA, which operates with the existing data from the region. The study is conducted by performing an analysis of the carbon consumption in two metropolitan areas in Finland, including 11 cities. Both areas consist of a dense city core and a less dense surrounding suburban area. The paper will illustrate that the influence of urban density on carbon emissions is insignificant in the selected metropolitan areas. In addition, the utilized consumption-based method links the climate effects of city-level development to the global production of emissions.

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The study fills a gap in existing literature by comparing process-based and E10-based life cycle assessment (LCA) methods empirically in service industries. Despite the numerous methodological differences, the methods were found mostly to produce the same environmentally significant processes for the case organization: the use of electricity in the premises, the construction of the premises, the business travel by cars, the heating of the premises, and the business flights. However, the process-based LCA could not be used to assess the environmental impacts of purchased services properly. The study also recognized most of the theoretical differences listed in the literature, and found the ones related to the cut-offs in purchased services, the price inhomogeneity, and the industry-atypical electricity production have the greatest influence on results.

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