Modeling and validation of on-road CO2 emissions inventories at the urban regional scale

Brondfield, Max N.; Hutyra, Lucy R.; Gately, C.; Raciti, Steve M.; Peterson, Scott

doi:10.1016/j.envpol.2012.06.003

Cited by 43 publications

(26 citation statements)

References 18 publications

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“…The differences between statewide fuel sales and fuel quantities accounted for as outlined above (accounting for ~20–30% of fuel use) are assigned to remaining portions of the roadway network (i.e., those roads without traffic count data), using road length as a proxy. This is done separately for urban and rural grid cells to ensure that rural emissions are not overestimated, as travel on rural roads is expected to be lower [ Brondfield et al ., ]. For example, in California ~30% of total vehicle travel occurs on roads without traffic counts, and of this subset ~90% is urban and ~10% is rural (Table S1).…”

Section: Methodsmentioning

confidence: 99%

High‐resolution mapping of motor vehicle carbon dioxide emissions

et al. 2014

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A fuel-based inventory for vehicle emissions is presented for carbon dioxide (CO 2 ) and mapped at various spatial resolutions (10 km, 4 km, 1 km, and 500 m) using fuel sales and traffic count data. The mapping is done separately for gasoline-powered vehicles and heavy-duty diesel trucks. Emission estimates from this study are compared with the Emissions Database for Global Atmospheric Research (EDGAR) and VULCAN. All three inventories agree at the national level within 5%. EDGAR uses road density as a surrogate to apportion vehicle emissions, which leads to 20-80% overestimates of on-road CO 2 emissions in the largest U.S. cities. High-resolution emission maps are presented for Los Angeles, New York City, San Francisco-San Jose, Houston, and Dallas-Fort Worth. Sharp emission gradients that exist near major highways are not apparent when emissions are mapped at 10 km resolution. High CO 2 emission fluxes over highways become apparent at grid resolutions of 1 km and finer. Temporal variations in vehicle emissions are characterized using extensive day-and time-specific traffic count data and are described over diurnal, day of week, and seasonal time scales. Clear differences are observed when comparing light-and heavy-duty vehicle traffic patterns and comparing urban and rural areas. Decadal emission trends were analyzed from 2000 to 2007 when traffic volumes were increasing and a more recent period (2007)(2008)(2009)(2010) when traffic volumes declined due to recession. We found large nonuniform changes in on-road CO 2 emissions over a period of~5 years, highlighting the importance of timely updates to motor vehicle emission inventories.

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Section: Methodsmentioning

confidence: 99%

High‐resolution mapping of motor vehicle carbon dioxide emissions

et al. 2014

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“…This strategy usually entails measuring trace gas mixing ratios from a ground-based vehicle either on public roads (e.g., Maness et al, 2015) or private roads in partnership with the facility owner (e.g., Roscioli et al, 2015). Existing studies often target oil and gas facilities (e.g., Roscioli et al, 2015;Brantley et al, 2014;Jackson et al, 2014;Lan et al, 2015;Mitchell et al, 2015;Subramanian et al, 2015) and mobile CO 2 emissions (e.g., Brondfield et al, 2012;Maness et al, 2015). In the case of oil and gas emissions, Brantley et al (2014) explain that mobile measurements capture an integrated plume that includes all leaks from a given facility but rarely indicate which components caused those leaks.…”

Section: Recent Direct Measurements That Support Bottom-up Effortsmentioning

confidence: 99%

Constraining sector-specific CO<sub>2</sub> and CH<sub>4</sub> emissions in the US

Miller

Michalak

2017

Atmos. Chem. Phys.

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Abstract. This review paper explores recent efforts to estimate state-and national-scale carbon dioxide (CO 2 ) and methane (CH 4 ) emissions from individual anthropogenic source sectors in the US. Nearly all state and national climate change regulations in the US target specific source sectors, and detailed monitoring of individual sectors presents a greater challenge than monitoring total emissions. We particularly focus on opportunities to synthesize disparate types of information on emissions, including emission inventory data and atmospheric greenhouse gas data.We find that inventory estimates of sector-specific CO 2 emissions are sufficiently accurate for policy evaluation at the national scale but that uncertainties increase at state and local levels. CH 4 emission inventories are highly uncertain for all source sectors at all spatial scales, in part because of the complex, spatially variable relationships between economic activity and CH 4 emissions. In contrast to inventory estimates, top-down estimates use measurements of atmospheric mixing ratios to infer emissions at the surface; thus far, these efforts have had some success identifying urban CO 2 emissions and have successfully identified sector-specific CH 4 emissions in several opportunistic cases. We also describe a number of forward-looking opportunities that would aid efforts to estimate sector-specific emissions: fully combine existing top-down datasets, expand intensive aircraft measurement campaigns and measurements of secondary tracers, and improve the economic and demographic data (e.g., activity data) that drive emission inventories. These steps would better synthesize inventory and topdown data to support sector-specific emission reduction policies.

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“…Individuals' vehicle travel was found to be best predicted by household income, vehicle ownership, and commuting distance, and the estimated relationships have been used to impute on-road emissions at the zip code level (20). Directly measured roadway CO 2 concentrations have also been parsimoniously modeled using only the local fraction of impervious surface and a traffic volume-weighted road density index (21). In selected US states and cities, local traffic count data and state-level fuel consumption have been used to downscale emissions to a 500-m grid (22).…”

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confidence: 99%

Cities, traffic, and CO ₂ : A multidecadal assessment of trends, drivers, and scaling relationships

Gately

Hutyra

Wing

2015

Proc. Natl. Acad. Sci. U.S.A.

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101

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Emissions of CO 2 from road vehicles were 1.57 billion metric tons in 2012, accounting for 28% of US fossil fuel CO 2 emissions, but the spatial distributions of these emissions are highly uncertain. We develop a new emissions inventory, the Database of Road Transportation Emissions (DARTE), which estimates CO 2 emitted by US road transport at a resolution of 1 km annually for 1980-2012. DARTE reveals that urban areas are responsible for 80% of on-road emissions growth since 1980 and for 63% of total 2012 emissions. We observe nonlinearities between CO 2 emissions and population density at broad spatial/temporal scales, with total on-road CO 2 increasing nonlinearly with population density, rapidly up to 1,650 persons per square kilometer and slowly thereafter. Per capita emissions decline as density rises, but at markedly varying rates depending on existing densities. We make use of DARTE's bottom-up construction to highlight the biases associated with the common practice of using population as a linear proxy for disaggregating national-or state-scale emissions. Comparing DARTE with existing downscaled inventories, we find biases of 100% or more in the spatial distribution of urban and rural emissions, largely driven by mismatches between inventory downscaling proxies and the actual spatial patterns of vehicle activity at urban scales. Given cities' dual importance as sources of CO 2 and an emerging nexus of climate mitigation initiatives, high-resolution estimates such as DARTE are critical both for accurately quantifying surface carbon fluxes and for verifying the effectiveness of emissions mitigation efforts at urban scales.emissions | carbon dioxide | urban | transportation | on-road

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Modeling and validation of on-road CO2 emissions inventories at the urban regional scale

Cited by 43 publications

References 18 publications

High‐resolution mapping of motor vehicle carbon dioxide emissions

High‐resolution mapping of motor vehicle carbon dioxide emissions

Constraining sector-specific CO<sub>2</sub> and CH<sub>4</sub> emissions in the US

Cities, traffic, and CO ₂ : A multidecadal assessment of trends, drivers, and scaling relationships

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Modeling and validation of on-road CO2 emissions inventories at the urban regional scale

Cited by 43 publications

References 18 publications

High‐resolution mapping of motor vehicle carbon dioxide emissions

High‐resolution mapping of motor vehicle carbon dioxide emissions

Constraining sector-specific CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions in the US

Cities, traffic, and CO 2 : A multidecadal assessment of trends, drivers, and scaling relationships

Contact Info

Product

Resources

About

Constraining sector-specific CO<sub>2</sub> and CH<sub>4</sub> emissions in the US

Cities, traffic, and CO ₂ : A multidecadal assessment of trends, drivers, and scaling relationships