Environmental life cycle assessment (LCA) is increasingly being used to evaluate infrastructure products and to inform their funding, design and construction. As such, recognition of study limitations and consideration of uncertainty are needed; however, most infrastructure LCAs still report deterministic values. Compared to other LCA subfields, infrastructure LCA has developed relatively recently and lags in adopting uncertainty analysis. This paper presents four broad categories of infrastructure LCA uncertainty. These contain 11 drivers focusing on differences between infrastructure and manufactured products. Identified categories and drivers are: application of ISO 14040/14044 standards (functional unit, reference flow, boundaries of analysis); spatiotemporal realities underlying physical construction (geography, local context, manufacturing time); nature of the construction industry (repetition of production, scale, and division of responsibilities); and characteristics of infrastructure projects (agglomeration of other products, and recurring embodied energy). Infrastructure products are typically large, one-off projects with no two being exactly alike in terms of form, function, temporal or spatial context. As a result, strong variability between products is the norm and much of the uncertainty is irreducible. Given the inability to make significant changes to an infrastructure project ex-post and the unique nature of infrastructure, ex-ante analysis is of particular importance. This paper articulates the key drivers of infrastructure specific LCA uncertainty laying the foundation for future refinement of uncertainty consideration for infrastructure. As LCA becomes an increasingly influential tool in decision making for infrastructure, uncertainty analysis must be standard practice, or we risk undermining the fundamental goal of reduced real-world negative environmental impacts.
The building sector is a voracious consumer of primary materials. However, the study of building material use and associated impacts is challenged by the paucity of publicly available data in the field and the heterogeneity of data organization and classification between published studies. This paper makes two main contributions. First, we propose and demonstrate a building material data structure adapted from UniFormat and MasterFormat, two widely used construction classification systems in North America. Second, the dataset included provides fine grained material data for 70 buildings in North America. The dataset was developed by collecting design or construction drawings for the studied buildings and performing material takeoffs based on these drawings. The ontology is based on UniFormat and MasterFormat to facilitate interoperability with existing construction management practices, and to suggest a standardized structure for future material intensity studies. The data structure supports investigation into how form and building design are driving material use, opportunities to reduce construction material consumption and better understanding of how materials are used in buildings.
Changes in travel behavior near the Sheppard Subway Line in Toronto, Ontario, Canada, and the associated greenhouse gas impacts were examined. A study looked at initial changes in mode share after the line opened in 2002 and examined ongoing mode share trends through 2012. The initial mode shift was assessed through an analysis of bus boardings, subway platform counts, and traffic counts made between 2000 and 2012. Longitudinal changes in mode share were assessed with the use of transit survey data. For the first 6 years of operation, the Sheppard Subway Line produced more greenhouse gas (GHG) per passenger kilometer traveled (PKT) than the bus that it had replaced. A net GHG reduction of 66.4 kilotons of CO2 equivalent was calculated but was wholly dependent on avoided car PKTs that may have been offset in their entirety by induced travel on Sheppard Avenue.
Isochrone analysis and assessments of cumulative opportunities are a common way to quantify accessibility. However, different time cut-offs have been used by different researchers, with little investigation into what is the ‘best’ cut-off time. Outstanding questions remain concerning the most effective or predictive cut-off time and the potential implications of choosing one time limit over another. The primary objective of this paper is to explore how different cut-off times affect the calculation of isochrone-based accessibility measurements and their potential to predict travel-mode choice. Fifty dissemination areas (DAs) within the Greater Toronto and Hamilton Area (GTHA) are selected to test the impact of different isochrone cut-off times in 5-minute intervals for public transit, automobile, and walking accessibility. The relative predictive power of 30- and 45-minute isochrones in modeling mode choice is also examined. This paper finds that different cut-off times do impact the interpretability of accessibility measurements in the isochrone approach, but a defined cut-off time for general use cannot be determined based on the analysis.
As cities work to reduce their total greenhouse gas (GHG) emissions, the transportation sector is lagging, accounting for a growing percentage of total emissions in many cities. The provision of public transit, and specifically urban rail transit, is widely seen as a useful tool for reducing urban transportation GHG emissions. There is, however, limited understanding of the net impact of new metro rail infrastructure on urban emissions. This paper examines the net GHG emissions the Sheppard Subway Line in Toronto, Canada. The GHG emissions associated with construction, operation, ridership and changes in residential density associated with the provision of the new metro rail infrastructure are assessed. These components are then combined and compared to calculate the net GHG impact across the study period, which extends from opening in 2002 through 2011. The GHG payback period is calculated. After nine years of operation, the Sheppard Subway Line is found to have nearly paid back its initial GHG investment in the optimistic case. The payback was due to the calculated mode shift from automobiles and changes in residential density and associated energy saving in the station pedestrian catchment areas. The payback period is very sensitive to the potential for induced demand to backfill the mode shifted automobile kilometres.
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