Friday, July 24, 3:30 pm
Using Data from the Massachusetts Vehicle Census (MAVC) to Estimate Municipal Greenhouse Gas Emissions from Transportation
Presenter: Conor Gately, Metropolitan Area Planning Council
Lily Perkins-High, Metropolitan Area Planning Council
Megan Aki, Metropolitan Area Planning Council
Tim Reardon, Metropolitan Area Planning Council
Communities across Metro Boston are organizing themselves to combat climate change through policies and programs designed to reduce local greenhouse gas (GHG) emissions. For many cities and towns, one important step is the development of a baseline GHG inventory to establish current or historical emissions levels, which can be used to inform targets, establish a data-driven framework for emissions reduction, and track progress toward goals. The Global Protocol for Community-Scale Greenhouse Gas Emission Inventories, developed by the World Resources Institute, C40 Cities Climate Leadership Group and ICLEI – Local Governments for Sustainability (ICLEI), provides an approach for baseline emissions reporting at the municipal level. This approach requires local, regional, or state agencies to leverage local-scale, publicly accessible, and policy-responsive datasets.
In 2019, the Metropolitan Area Planning Council (MAPC) partnered with consulting firm DN VGL and the municipalities of Arlington, Melrose, and Natick to expand a tool previously developed for the City of Cambridge for use across the greater Boston area. MAPC’s Data Services department led the development of four datasets for the transportation sector, including a new tabulation of the Massachusetts Vehicle Census (MAVC) to estimate emissions resulting from on-road personal and commercial vehicles, spatial downscaling techniques to assign EPA MOVES county-scale non-road vehicle activity to local municipalities, and a route-frequency-weighted estimation of emissions from bus, light rail, and heavy rail public transit vehicles. These datasets will be published to the MAPC DataCommon, along with the expanded tool, later this year.
In this conference session, we will describe the development of the MAVC, which is sourced from vehicle registrations, inspection records, mileage ratings, and other sources, and discuss its application in greenhouse gas inventories. The MAVC is a unique dataset in the context of GHG inventories, as it captures the emissions from vehicles registered to a given location, as opposed to traditional Scope 1 inventory methods which estimate emissions occurring on roads within a given area. Our discussion will include our approach for developing MAVC-based GHG emissions, an evaluation of the strengths and weaknesses of our dataset and our method, and the new policy applications made possible by this unique dataset. Participants will leave with a broad understanding of this new data resource and ideas for how they can apply it in their own communities.
Mapping Environmental Conditions Experienced by Riders of the T at High Resolution
Presenter: Edgar Castro, Northeastern University
Matthew Eckelman, Northeastern University Department of Civil and Environmental Engineering
Nick Boyd, Massachusetts Department of Transportation
Norman Michaudm, Massachusetts Bay Transportation Authority
Preston Horton, Massachusetts Bay Transportation Authority
Amy Mueller, Northeastern University Department of Civil and Environmental Engineering
The MBTA serves riders taking over 1.2 million trips taken daily, of which 55% are on the subway, making it one of the top five busiest subways in the United States. Monitoring studies conducted in the past 10-15 years in other global cities (e.g., Seoul, New York City, and Cairo) have examined the rider experience by characterizing environmental conditions on a number of different dimensions, including air quality, vibration, and noise levels; however, to date a similar comprehensive mapping of the T had not been conducted. This study aimed to collect a multi-modal dataset characterizing the overall environmental conditions experienced by riders of the rail-based rapid transit components of the T to better understand heterogeneous conditions in the system (e.g., potentially identify hotspots where remediation would be beneficial) and determine whether there are any significant disparities in exposure between serviced Boston-area communities. This talk will present the collected data sets and an initial evaluation of the overall conditions in the system as well as identify key determining factors that explain differences in conditions between track segments/lines. The ultimate aim of the work is to determine whether environmental conditions in any part of the system may pose risks to T riders.
Data on the following parameters were collected along all MBTA subway lines (including all branches of the Green Line): temperature, humidity, noise, vibration, and air quality (particulate matter). In general, measurements were taken during non-peak hours, both to characterize baseline exposures and to minimize impact on other riders. Particulate matter measurements were also taken during peak travel hours to assess the impact of rider volume on air quality. A low-cost, integrated sensing system was developed to enable logging of data at intervals of less than one minute for certain parameters, allowing us to evaluate parameters on relevant time scales. For example, vibration measurements can be separately considered during different train phases: entering a station, leaving a station, between stations.
The data show evidence of quantitative differences in rider experience between subway lines, e.g. higher particle number concentrations in the Cambridge/Somerville portion of the Red Line than in the rest of the system and lowest concentrations along western portions of the Green Line. Vehicle loading and track segment grade (above/below ground) both have statistically significant effects on air quality. Key next steps of ongoing work on this project include interpreting the human health implications of the collected data and identifying potential exposure disparities.
Quantifying the Health Impacts of Eliminating Air Pollution Emissions in the City of Boston
Presenter: Matthew Raifman, Boston University
Armistead G. Russell, Georgia Tech
T. Nash Skipper, Georgia Tech
Patrick L. Kinney, Boston University
Background. Cities around the world are taking action to limit greenhouse gas emissions through ambitious climate targets and climate action plans. These strategies are likely to simultaneously improve local air quality, leading to public health and monetary co-benefits. In this study, we sought to estimate the health impacts of the City of Boston’s climate action plan, Carbon Free Boston, and in doing so consider the importance of evaluating the health impacts of local climate action alongside intended environmental impacts.
Methods. We simulated at a 4km resolution how the elimination of anthropogenic emissions from the City of Boston would impact air quality across a 120km by 120km study domain using the Community Multiscale Air Quality (CMAQ) model. We then estimated how this change in air quality would impact incidence of mortality and a number of additional annual health outcomes, as well as their monetary valuation, using the U.S. Environmental Protection Agency Benefits Mapping Analysis Program (BenMAP).
Results. We estimate that eliminating anthropogenic emissions from the City of Boston would result in a decline in particulate matter (PM2.5) concentration across the entire study region ranging from 8.5 ug/m3 in the City of Boston to less than 1 ug/m3 elsewhere in the domain. Conversely, we estimate that summer ozone would increase for the Greater Boston Area and areas west. The monetary impact of the change in air quality on health is estimated to be a $2.4 billion per year savings across the full domain and $1.7 billion within Suffolk County only, which is home to the City of Boston. The annual net monetary savings for Suffolk County is comparable to 1.5% of the gross city product of Boston. We estimate that 288 deaths would be avoided per year across the study domain, about six deaths avoided, annually, per 100,000 people. Within Suffolk County, we estimate that eliminating emissions would result in 47 fewer deaths per 100,000 people, around 16% of all-cause premature mortality in the county. Across the study domain, these health benefits would be disproportionately be conferred upon people of color.
Conclusions. Our findings suggest that the Greater Boston Area would realized substantial health benefits should the City of Boston achieve the ambitious climate policy goals set forth in the Carbon Free Boston plan. Our results suggest that municipal climate policies have great potential to achieve health co-benefits, and that health impacts merit consideration as a core part of the way climate policies are evaluated by policymakers and the public.
A Co-Simulated Energy and Indoor Air Quality Housing Model to Inform Decisions for Retrofits and Health
Presenter: Catherine L. Connolly, Boston University
Chad W Milando, Boston University
W Stuart Dols, NIST
Jonathan I Levy, Boston University
M Patricia Fabian, Boston University
This presentation describes the development and application of a set of building models, or templates, to simulate energy, airflow, and indoor air quality (IAQ). Co-simulation is performed between two public domain software programs, EnergyPlus and CONTAM. EnergyPlus, developed by the U.S. Department of Energy, performs dynamic heat transfer analysis to simulate multi-zone, whole-building energy use. CONTAM, developed by the National Institute of Standards and Technology, simulates airflow and contaminant transport. During the co-simulation, EnergyPlus provides indoor room temperatures to CONTAM, which in turn calculates infiltration and inter-zone airflow along with resultant contaminant transport within the building. CONTAM accounts for ambient air contaminants, internal contaminant sources, and removal mechanisms including filtration. Together, these models provide a novel method for examining complex drivers of exposure to air pollutants in the indoor environment, as well as potential intervention strategies. We first constructed a coupled representation of a mid-rise multi-family apartment building, prevalent in greater Boston and elsewhere, based on an existing EnergyPlus template. We created a corresponding CONTAM template to enable simultaneous tracking of energy use and indoor air contaminants over time. Results include dynamic energy consumption and occupant exposure for periods up to one year. Our coupled model provides insight into the relationship between energy consumption and IAQ, and how retrofits or changes in human behavior can influence both. In particular, by continuing the development of templates for various housing types and incorporating local weather conditions, we can develop insight regarding housing in the greater Boston area or other geographic regions. These templates can be modified to represent various ranges of building performance including leakage rates across the building envelope and internal partitions, insulation levels, and ventilation system types as well as the effects of the climate zone and localized weather effects. Human behavior can also be incorporated by simulating occupant activities such as window opening, cooking, smoking, and exhaust fan use in the home. The aging housing stock in cities like Boston leads to issues with both energy efficiency and IAQ, so a model that can incorporate both dimensions can help identify optimal interventions. Furthermore, energy use and IAQ will be affected by climate change, reinforcing the importance of simultaneously evaluating two intricately linked issues: health and housing. This co-simulation framework has the potential to inform these topics through modeling different scenarios related to housing type, building characteristics, and ambient weather conditions in the context of a changing climate. Through collaboration with multiple stakeholders, we can develop retrofit scenarios that are realistic and reflective of pending policy decisions.
Moderator: Paulina Muratore, Union of Concerned Scientists