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首页> 外文期刊>IEEE transactions on automation science and engineering: a publication of the IEEE Robotics and Automation Society >Low Emission Road Transport Scenarios: An Integrated Assessment of Energy Demand, Air Quality, GHG Emissions, and Costs
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Low Emission Road Transport Scenarios: An Integrated Assessment of Energy Demand, Air Quality, GHG Emissions, and Costs

机译:低排放道路运输情景:能源需求、空气质量、温室气体排放和成本的综合评估

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This article proposes an integrated assessment methodology aimed at supporting decision-makers in design energy production scenarios to power a low emissions traffic fleet. The Multidimensional Air Quality (MAQ) system is used to define and solve a decision problem that selects a set of energy production scenarios minimizing costs, impacts on air quality, and greenhouse gases (GHGs) emissions. This study focuses on the road transport sector, that is responsible for 25 of European GHGs emissions and 39 of NOx emission, a precursor of both NO2 and PM10 concentrations. The electrification of the light vehicle fleet and the use of biomethane to power heavy vehicles are analyzed, estimating the electricity demand increase, exploring different energy production mixes, and assessing the impacts on air quality, costs, and GHGs according to the fuels/ sources used to satisfy the energy demand. A case study over Lombardy region, in Northern Italy, is proposed.Note to Practitioners-The study designs a new decision problem implemented and solved through the Multidimensional Air Quality system (MAQ), an integrated assessment modeling tool. Such system integrates a set of databases, models, optimization, and enumeration algorithms. Composing these elements, specific multiobjective decision problems can be designed defining domain (mesoscale, regional, urban), objectives (air quality index, greenhouse gas emissions, costs, population exposure, health impacts), decision variables (technologies, behavioral measures, energy production, fuel switch), and constraints. MAQ system allows the comprehensive analysis of energy, technological, behavioral policies estimating impacts on air quality, human health, GHGs emissions, and costs.
机译:本文提出了一种综合评估方法,旨在支持决策者设计能源生产场景,为低排放交通车队提供动力。多维空气质量 (MAQ) 系统用于定义和求解决策问题,该决策问题选择一组能源生产方案,以最大限度地降低成本、对空气质量的影响和温室气体 (GHG) 排放。本研究的重点是道路运输部门,该部门占欧洲温室气体排放量的 25% 和 NOx 排放量的 39%,NO2 和 PM10 浓度的前体。分析了轻型车队的电气化和使用生物甲烷为重型车辆提供动力,估计了电力需求的增加,探索了不同的能源生产组合,并根据用于满足能源需求的燃料/来源评估了对空气质量、成本和温室气体的影响。提出了对意大利北部伦巴第大区的案例研究。从业者须知 - 该研究设计了一个新的决策问题,通过多维空气质量系统(MAQ)实施和解决,这是一个综合评估建模工具。该系统集成了一组数据库、模型、优化和枚举算法。通过这些要素,可以设计特定的多目标决策问题,定义领域(中尺度、区域、城市)、目标(空气质量指数、温室气体排放、成本、人口暴露、健康影响)、决策变量(技术、行为测量、能源生产、燃料转换)和约束。MAQ 系统允许对能源、技术、行为政策进行全面分析,估计对空气质量、人类健康、温室气体排放和成本的影响。

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