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Transportation Greenhouse Gas Emissions and its Relationship with Urban Form, Transit Accessibility and Emerging Green Technologies: A Montreal Case Study

机译:交通温室气体排放及其与城市形态,公共交通可达性和新兴绿色技术的关系:蒙特利尔案例研究

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摘要

This research aims at estimating a GHG emission inventory at the household level using completely disaggregate tripuddata and taking into account all emitting modes. The impact of urban form (UF) and transit accessibility (TA)udcharacteristics on household level GHG emissions is then quantified and compared to the impact of the introductionudof emerging green technologies. Using a large and representative sample of household diaries, trip-level GHGudemissions are estimated by combining different sources of data (origin-destination (OD) survey data, vehicle fleetudcharacteristics, transit ridership data, etc.) and by using modelling tools (traffic assignment and GHGs models).udMoreover, UF and TA indicators are developed and combined to generate neighbourhood typologies. A simultaneousudequation modelling framework is then implemented to investigate the link between UF, TA, socio-demographics, andudtravel GHGs, taking into account the well known “self-selection” issue. The potential impact of land use and transit supply strategies with emerging green technological scenarios is then compared. This is evaluated through theudmodification of current fuel consumption rates with those provided by new technologies such as hybrid transit busesudand continuous improvement of vehicle fuel consumption rates. Our findings are consistent with the literature, moreudspecifically we have found that the built environment (BE) attributes are statistically significant (10% increase inuddensity, transit accessibility and land-use mix, results in 3.5 %, 5.8% and 2.5% reduction in GHG respectively),udnumber of workers and retirees at the household level play an important role in the contribution to GHG emissionsud(102% increase by adding one worker and 51% decrease by adding a retiree to the household). Moreover, neighbourhood types represented by the combined effects of UF and TS have important effects on GHGs. Also it is found that by replacing transit fleet by electric trains and hybrid buses, the share of transit GHGs would decrease by 32%. With respect to the private motor-vehicle fleet, if current trends persist, the constant improvement of car fueludconsumption economy would reduce car GHGs by 7%. According to our results, the two most efficient strategies to reduce GHGs at the regional and household level seem to be the continuous fuel-efficiency improvement of the private motor-vehicle fleet and the increase of transit accessibility.
机译:这项研究旨在使用完全分解的旅行数据/ uddata并考虑所有排放模式来估算家庭层面的温室气体排放清单。然后,量化城市形式(UF)和交通可及性(TA)特征对家庭水平GHG排放的影响,并将其与引进绿色技术的影响进行比较。使用大量有代表性的家庭日记样本,通过组合不同的数据源(出发地(OD)调查数据,车队特征,过境出行数据等)来估计出行级别的GHG 排放量工具(交通分配和GHGs模型)。 ud此外,UF和TA指标已开发并组合以生成邻域类型。然后,考虑到众所周知的“自我选择”问题,实施一个同步/配量建模框架来研究超滤,TA,社会人口统计数据和//差旅温室气体之间的联系。然后比较了新兴的绿色技术情景下土地利用和过境供应战略的潜在影响。通过使用新技术(例如混合动力公交车)提供的当前燃料消耗率的修改/对车辆燃料消耗率的不断改进来评估。我们的发现与文献相符,更具体而言,我们发现建筑环境(BE)属性具有统计学意义(密度,交通可及性和土地利用组合增加10%,分别为3.5%,5.8%和2.5)家庭水平的工人和退休人员数量在温室气体排放的贡献中起着重要作用(增加一名工人增加102%,增加一名退休人员减少51%)。而且,以UF和TS的综合作用为代表的邻里类型对GHG具有重要影响。还发现,通过用电动火车和混合动力公交车取代公交车队,公交温室气体的份额将减少32%。对于私家车队,如果当前趋势持续下去,则汽车燃料/消费经济的不断改善将使汽车温室气体减少7%。根据我们的结果,在区域和家庭层面减少温室气体的两个最有效的策略似乎是不断提高私人汽车车队的燃油效率和增加公共交通的可达性。

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