Evaluation of Mobile Source Greenhouse Gas Emissions for Assessment of Traffic Management Strategies PDF Download
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Author: Qinyi Shi
Publisher:
ISBN:
Category : Air
Languages : en
Pages : 92
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Book Description
Author: Qinyi Shi
Publisher:
ISBN:
Category : Air
Languages : en
Pages : 92
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Book Description
Author:
Publisher: World Business Pub.
ISBN: 9781569735688
Category : Business enterprises
Languages : en
Pages : 0
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Book Description
The GHG Protocol Corporate Accounting and Reporting Standard helps companies and other organizations to identify, calculate, and report GHG emissions. It is designed to set the standard for accurate, complete, consistent, relevant and transparent accounting and reporting of GHG emissions.
Author: Cambridge Systematics
Publisher:
ISBN: 9780874201185
Category : Political Science
Languages : en
Pages : 0
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Book Description
"Both the public and private sectors are grappling with decisions regarding policies that will lead to reductions in greenhouse gas (GHG) emissions. Moving Cooler analyzes and assesses the effectiveness and costs of almost 50 transportation strategies for reducing GHG emissions, as well as evaluates combinations of those strategies. The findings of this study can help decision makers coordinate and shape effective approaches to reducing GHG emissions at all levels - national, regional, and local - while also meeting broader transportation objectives." --Book Jacket.
Author: Haneen Khreis
Publisher: Elsevier
ISBN: 0128181230
Category : Transportation
Languages : en
Pages : 650
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Book Description
Traffic-Related Air Pollution synthesizes and maps TRAP and its impact on human health at the individual and population level. The book analyzes mitigating standards and regulations with a focus on cities. It provides the methods and tools for assessing and quantifying the associated road traffic emissions, air pollution, exposure and population-based health impacts, while also illuminating the mechanisms underlying health impacts through clinical and toxicological research. Real-world implications are set alongside policy options, emerging technologies and best practices. Finally, the book recommends ways to influence discourse and policy to better account for the health impacts of TRAP and its societal costs. - Overviews existing and emerging tools to assess TRAP's public health impacts - Examines TRAP's health effects at the population level - Explores the latest technologies and policies--alongside their potential effectiveness and adverse consequences--for mitigating TRAP - Guides on how methods and tools can leverage teaching, practice and policymaking to ameliorate TRAP and its effects
Author: Reid H. Ewing
Publisher: Urban Land Institute
ISBN:
Category : Architecture
Languages : en
Pages : 186
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Book Description
Based on a comprehensive study review by leading urban planning researchers, this investigative document demonstrates how urban development is both a key contributor to climate change and an essential factor in combating it -- by reducing vehicle greenhouse gas emissions.
Author: OECD
Publisher: OECD Publishing
ISBN: 9264195971
Category :
Languages : en
Pages : 67
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Book Description
This report, which has been prepared by an OECD Working Group, uses a number of illustrative and pragmatic cases to provide important insights into reducing greenhouse gas emissions from road transport.
Author:
Publisher:
ISBN:
Category : Power resources
Languages : en
Pages : 484
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Book Description
Author: National Institute of Standards and Technology (U.S.)
Publisher:
ISBN:
Category :
Languages : en
Pages : 1162
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Book Description
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 892
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Book Description
Author: Nikolaos Tsanakas
Publisher: Linköping University Electronic Press
ISBN: 9176850927
Category :
Languages : en
Pages : 143
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Book Description
Traffic congestion increases travel times, but also results in higher energy usage and vehicular emissions. To evaluate the impact of traffic emissions on environment and human health, the accurate estimation of their rates and location is required. Traffic emission models can be used for estimating emissions, providing emission factors in grams per vehicle and kilometre. Emission factors are defined for specific traffic situations, and traffic data is necessary in order to determine these traffic situations along a traffic network. The required traffic data, which consists of average speed and flow, can be obtained either from traffic models or sensor measurements. In large urban areas, the collection of cross-sectional data from stationary sensors is a costefficient method of deriving traffic data for emission modelling. However, the traditional approaches of extrapolating this data in time and space may not accurately capture the variations of the traffic variables when congestion is high, affecting the emission estimation. Static transportation planning models, commonly used for the evaluation of infrastructure investments and policy changes, constitute an alternative efficient method of estimating the traffic data. Nevertheless, their static nature may result in an inaccurate estimation of dynamic traffic variables, such as the location of congestion, having a direct impact on emission estimation. Congestion is strongly correlated with increased emission rates, and since emissions have location specific effects, the location of congestion becomes a crucial aspect. Therefore, the derivation of traffic data for emission modelling usually relies on the simplified, traditional approaches. The aim of this thesis is to identify, quantify and finally reduce the potential errors that these traditional approaches introduce in an emission estimation analysis. According to our main findings, traditional approaches may be sufficient for analysing pollutants with global effects such as CO2, or for large-scale emission modelling applications such as emission inventories. However, for more temporally and spatially sensitive applications, such as dispersion and exposure modelling, a more detailed approach is needed. In case of cross-sectional measurements, we suggest and evaluate the use of a more detailed, but computationally more expensive, data extrapolation approach. Additionally, considering the inabilities of static models, we propose and evaluate the post-processing of their results, by applying quasi-dynamic network loading.
