Improved Operational Efficiency and the Impact on Greenhouse Gas Emissions

Focus Area

Climate Change

Subcommittee

Air Quality, Environmental Process

Status

Archived

Cost

$250k-$499k

Timeframe

Unknown

Research Idea Scope

TERI Administrator Note (May 2011): FHWA has a project underway that is addressing these issues. (John Davies is FHWA contract point.)

Problem
One of the approaches for reducing transportation-related greenhouse gas (GHG) emissions is to improve the operational efficiency and reliability of the surface transportation network, specifically through the implementation of transportation systems management and operational (TSMO) strategies and the supporting ITS technologies. Moreover, such strategies are most effective when implemented on a regional basis.
 
Recent studies have shown that such operational improvements can reduce GHG emissions, but the estimated reductions vary widely between studies (refer to “Related Work” herein). Additionally , information on the effectiveness of individual strategies (e.g., ramp management, transit priority and bus rapid transit, speed and lane control / active traffic management, managed lanes, incident management, coordinated signal control, integrated corridor management, automated fleet inspections) and the supporting technologies, and in various combinations under different conditions and scenarios , is sparse. 
 
Currently, little is known about how changes in traffic flow affect the carbon emissions from new vehicle propulsion technologies, such as hybrids, plug-in hybrids, EV’s and fuel cells. For example, the lifetime of a battery may differ based on its discharge cycle, which may or may not be influenced by changes in traffic flow conditions. These issues will become increasingly important to fully understand how operational improvements ultimately affect greenhouse gas emissions (e.g., some evidence suggests hybrid vehicles are more efficient in slow stop and go traffic, compared to free flowing conditions).
 
A related issue is the carbon footprint resulting from the deployment, operation and maintenance of these transportation management systems (e.g., power supply for Transportation Management Center (TMC), central equipment and field devices, transportation by staff to/from TMC, maintenance activities).
 
The ability to accurately estimate GHG reductions resulting from operational improvements (e.g., reduced congestion, improved reliability) is expected to become a critical need in the near future. For example, current draft legislation before the US Congress requires States and MPOs to develop a transportation greenhouse gas reduction plans and prioritized list of projects to support the plan, including “surface transportation system operation improvements, including intelligent transportation systems or other operational improvements to reduce long-term greenhouse gas emissions through reduced congestion and improved system management.”Moreover, the development of these strategies are to “be based on emission models and related methodologies.”
 
Objectives
This project would:
·      Analyze and identify the reasons why recent studies show such different results in the potential reduction in GHG emissions resulting from the implementation of ITS and operational strategies (e.g., strategies considered, geographic area of analysis, time frame, models and analytical tools utilized, assumptions regarding latent demand and TSMO carbon footprint).
·      Identify and analyze the available tools, simulation models, and other analyses techniques for quantifying and estimating reductions in GHG emissions resulting from existing and planned TSMO programs including any features and limitations (e.g., which strategies can be modeled, inputs required including information / linkages from other models, and comparison of results between models for similar strategies and a variety of scenarios). This effort should include MOVES2010 (Mobile Vehicle Emission Simulator), the EPA’s new emission modeling system for estimating emissions for on-road and non-road mobile sources. Identify the extent to which, and how, these models and tools incorporate different types of vehicles (e.g., light duty (gas and diesel), trucks and other heavy duty (gas and diesel), hybrid, electrical, vehicle age), within the traffic flow in varying combinations, recognizing that different types of vehicles (and vehicle ages) will have different curves relating grams of CO2 / mile to vehicle speed. The manner in which these models and tools account for the impacts of acceleration and deceleration on emissions should also be addressed.
·      Analyze and estimate the reduced GHG emissions from various TSMO strategies and supporting ITS technologies – individually and in combination – for various scenarios (e.g., levels of traffic flows, location characteristics, with and without managed lanes, freight operations, transit vehicles)
·      Define components of the TSMO / ITS carbon footprint, identify tools for calculating this footprint, and recommend practices for reducing this carbon footprint.
 
Related Work
·      Moving Cooler – An Analysis of Transportation Strategies for Reducing Greenhouse Gas Emissions, Urban Land Institute, 2009
·      “Real-World CO2Impacts of Traffic Congestion”, Matthew Barth, 2008 TRB Paper
·      “Reducing Transport GHG Emissions  – Opportunities and Costs”, International Transport Forum
·      http://www.epa.gov/otaq/models/moves/
·      NCHRP Project 20-24/Task 72: Maximizing Highway Operational Strategies to Reduce Greenhouse Gas (GHG) Emissions. (Note – This is a recently approved project that might address some of the items proposed in this research statement. The stated objectives of this research are to “support efforts to maximize operational strategies to reduce highway GHG, by (a) documenting a full range of operational strategies to reduce highway GHG, (b) indicating the circumstances and locales where these strategies could be most effective in reducing GHG, (c) providing quantitative estimates of their GHG reduction potential, both individually and in combination; (d) estimating their costs and cost-effectiveness; (e) identifying collateral benefits and dis-benefits; and (f) identifying policies and actions that could be taken to maximize their GHG reduction effect.”)
 
Urgency/PriorityThe results of this effort are very important in terms of identifying the most appropriate models and analysis tools for use by States and MPO’s in developing transportation greenhouse gas reduction plans and prioritized lists of projects to support plan (as required by proposed federal legislation).

Urgency and Payoff

Implementation
The findings of the proposed research could be implemented in several ways by local and state transportation agencies and MPO’s, including:
·      Analyzing and selecting operational strategies and supporting ITS technologies for inclusion in “transportation greenhouse gas reduction plans” and the prioritized lists of projects to support the plans (and subsequently integrated into TIPs.)
·      Reducing the carbon footprint of current and future transportation management systems
·      Identifying current and future operational improvements and quantifying the reduced emissions as possible “offset credits” under a cap and trade system.
 
EffectivenessThis research would promote greater understanding in the transportation and environmental communities and among the public of the linkage between operational strategies and technologies – resulting in improved roadway and surface transit efficiency and reliability – and GHG emissions. It would provide transportation planners and system owners with a more rational basis for selecting cost-effective transportation systems management and operations strategies with the goal of reducing GHG emissions. TSMO strategies and supporting technologies could be more readily and evenly compared with other approaches (e.g., VMT reduction via congestion pricing and taxation) for addressing climate change.

Suggested By

RNS. Sponsoring Committee: A0020T, Special Task Force on Climate Change and Energy Source Info: Special Task Force on Climate Change and Energy January 2010 Workshop

Submitted

08/06/2010