Quantifying Diurnal and Seasonal Variation in On-road CO2 Emissions Across the Northeastern U.S.

Abstract:

On-road emissions comprised 29% of U.S. fossil fuel carbon dioxide emissions in 2012, with 64% of those emissions occurring in urban areas. Understanding the social, economic and technological factors that influence urban emissions requires the development of emissions inventories that are resolved at fine spatial and temporal scales. As city governments are increasingly at the forefront of developing policies to mitigate greenhouse gas emissions from vehicles, high-resolution, bottom-up inventories will support local and regional emissions benchmarking, as well as the monitoring, reporting, and verification of trends in emissions across time and space. To that end, we combine a large regional dataset of hourly traffic counts with the 1km gridded estimates of on-road CO2 emissions from the Database of Road Transportation Emissions (DARTE) to develop hourly CO2 emissions estimates for the year 2012 that cover 12 northeastern states. The inventory scope covers several large metropolitan regions as well as many small- and medium-sized urban, suburban and exurban population centers, altogether representing 20% of urban and 17% of total U.S. on-road CO2 emissions in 2012.

We identify significant variation in the time structure of vehicle emissions across the urban-suburban gradients of the Boston, New York, and Washington, D.C. metropolitan areas. In particular we note considerable spatial variation between morning and evening peak periods, both within and between cities, as well as variations in the duration of peak periods, depending on time of year and spatial location. We also examine the relationship between the temporal and spatial structure of morning and evening peak period emissions and the spatial distribution of population and employment density across urban to rural gradients. Finally we utilize data on minute-by-minute vehicle speeds to quantify the effect of traffic congestion on vehicle CO2 emission rates across the Boston metro area, and we highlight the sensitivity of congestion to small sub-hourly variations in traffic flows at key periods of the morning and evening rush hours. Results from our analysis demonstrate the potential for reducing vehicle emissions through time-sensitive toll pricing or commuter incentive schemes targeting peak period vehicle use on urban freeways.