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Spatio-temporal Variations in on-road CO2 Emissions in the Los Angeles Megacity

Authors :
Preeti Rao
Kevin R. Gurney
Risa Patarasuk
Yang Song
Charles E. Miller
Riley M. Duren
Annmarie Eldering
Source :
AIMS Geosciences, Vol 3, Iss 2, Pp 239-267 (2017)
Publication Year :
2017
Publisher :
AIMS Press, 2017.

Abstract

We quantify hourly on-road fossil fuel carbon dioxide (FFCO2) emissions at the road segment level for the Los Angeles (LA) megacity based on observed traffic data, and characterize emission patterns across space and time. This on-road FFCO2 emissions dataset for LA (from Hestia version 1.0), based on actual traffic volume, provides emissions per vehicle kilometer travelled (VKT)—an important metric for greenhouse gas (GHG) reductions. We further identify emissions hotpots that can help state and local policy makers plan the most effective GHG reduction strategies. On-road vehicle traffic accounts for half of the FFCO2 emissions in LA, of which 41% is from arterials (intermediate road type). Arterials also have the largest C emissions intensity—FFCO2 per VKT—possibly from high traffic congestion and fleet composition. Non-interstate emissions hotspots (> 419 tC lane-km-1) are equally dominated by arterials and collectors (the lowest road type) in terms of FFCO2 emissions though collectors have a higher VKT. These hotspots occur in densely populated areas and developed landuse classes, largely in LA (67%) and Orange (18%) counties, and provide specific targets for emissions reduction efforts. The estimated uncertainties for interstate, arterial and collector emissions per road length are ± 2.1, ± 0.5 and ± 18.0%, respectively. Our overall estimates compare reasonably well with other products, DARTE and FIVE but with substantial differences in spatial distribution. The method for developing this dataset is easily replicable in other urban landscapes, and represents a powerful tool for carbon cycle science and regional policy makers.

Details

Language :
English
ISSN :
24712132
Volume :
3
Issue :
2
Database :
Directory of Open Access Journals
Journal :
AIMS Geosciences
Publication Type :
Academic Journal
Accession number :
edsdoj.422309bf6554261a1fe832ff1e7de1a
Document Type :
article
Full Text :
https://doi.org/10.3934/geosci.2017.2.239