Spatial-modal scenarios of greenhouse gas emissions from commuting in Hong Kong

Transportation is a major source of greenhouse gas emissions in cities. Multiple strategies including green technologies, transport management, urban planning and behavior changes are required to mitigate transport emissions. This paper aims to introduce an analytical framework to investigate the impacts of different spatial-modal strategies on reducing commuting emissions. Based on the optimization approach of excess commuting, the proposed framework incorporates the minimum, maximum and random (unpredictable) travel outcomes to inform planning of an urban form embedded with fewer emissions. This analytical framework is applied to Hong Kong to estimate the emissions ranges (the minimum and maximum amounts) under 42 spatial-modal scenarios - a combination of six spatial strategies (status quo, monocentric, highly polycentric, moderately polycentric, dual-centric and tri-centric) and seven modal strategies (status quo, pro-rail (high), pro-rail (moderate), pro bus (high), pro-bus (moderate), pro-car (high) and pro-car (moderate)). The findings illustrate the emissions impacts if Hong Kong is further developed following a job concentration or decentralization principle. It also indicates that if Hong Kong is reconstructed to be a city with multiple CBDs, a dual-centric strategy is desirable because both minimum and maximum commuting are shorter than that of a tri-centric strategy. Moreover, the modal strategy to actively promote rail usage shows more impacts on emissions reduction and car usage should be maintained at the current level. If commuter's travl is less predictable, the high rail usage under a dual-centric city form is a more sustainable spatial-modal strategy. The proposed analytical framework of city's commuting emissions affected by structural and modal changes is transferrable to other places and could offer planners different benchmarks of travel pattern to substantiate their sustainable city planning vision. (C) 2016 Elsevier Ltd. All rights reserved.