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Downscaling global anthropogenic emissions for high-resolution urban air quality studies

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Standard

Downscaling global anthropogenic emissions for high-resolution urban air quality studies. / Valencia, Victor H.; Levin, Gregor; Ketzel, Matthias.
In: Atmospheric Pollution Research, Vol. 13, No. 10, 101516, 10.2022.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

Harvard

Valencia, VH, Levin, G & Ketzel, M 2022, 'Downscaling global anthropogenic emissions for high-resolution urban air quality studies', Atmospheric Pollution Research, vol. 13, no. 10, 101516. https://doi.org/10.1016/j.apr.2022.101516

APA

Valencia, V. H., Levin, G., & Ketzel, M. (2022). Downscaling global anthropogenic emissions for high-resolution urban air quality studies. Atmospheric Pollution Research, 13(10), [101516]. https://doi.org/10.1016/j.apr.2022.101516

CBE

Valencia VH, Levin G, Ketzel M. 2022. Downscaling global anthropogenic emissions for high-resolution urban air quality studies. Atmospheric Pollution Research. 13(10):Article 101516. https://doi.org/10.1016/j.apr.2022.101516

MLA

Valencia, Victor H., Gregor Levin, and Matthias Ketzel. "Downscaling global anthropogenic emissions for high-resolution urban air quality studies". Atmospheric Pollution Research. 2022. 13(10). https://doi.org/10.1016/j.apr.2022.101516

Vancouver

Valencia VH, Levin G, Ketzel M. Downscaling global anthropogenic emissions for high-resolution urban air quality studies. Atmospheric Pollution Research. 2022 Oct;13(10):101516. doi: 10.1016/j.apr.2022.101516

Author

Valencia, Victor H. ; Levin, Gregor ; Ketzel, Matthias. / Downscaling global anthropogenic emissions for high-resolution urban air quality studies. In: Atmospheric Pollution Research. 2022 ; Vol. 13, No. 10.

Bibtex

@article{f6a7d96653d3454e864d247424f3e864,
title = "Downscaling global anthropogenic emissions for high-resolution urban air quality studies",
abstract = "This study presents a method for “downscaling” aggregated global emissions of CO, NOx, and PM2.5 based on georeferenced information (spatial proxies). We distribute ECLIPSE-CLE emissions for Quito, Ecuador, in 2015 and 2017. The study area is a grid of 0.5 × 0.5 km2 cells over a 110 × 110 km2 area. The emission sectors (proxies in parenthesis) are agricultural (land-use maps), domestic (land-use and population density), energy, industry, and waste disposal (point source location from local inventory), and transport (population, vehicle traffic, and road density). Emission distribution quality is satisfactorily evaluated (graphically and statistically) by implementing them in the UBM model and comparing modeled concentrations with observations. This study also explores an alternative proxy set-up for main road emissions based on road density, which, for some modeling sites, results in a better agreement with the observations. Finally, this methodology is applied for comparing air pollution due to two urban growth types for Quito in 2040: sprawl and densification. Both scenarios lead to lower concentrations than in 2017, except for O3. Although the two scenarios attain similar concentrations, urban sprawl presents, in general, noticeably higher values for NOx and NO2.",
author = "Valencia, {Victor H.} and Gregor Levin and Matthias Ketzel",
year = "2022",
month = oct,
doi = "10.1016/j.apr.2022.101516",
language = "English",
volume = "13",
journal = "Atmospheric Pollution Research",
issn = "1309-1042",
publisher = "Turkish National Committee for Air Pollution Research and Control",
number = "10",

}

RIS

TY - JOUR

T1 - Downscaling global anthropogenic emissions for high-resolution urban air quality studies

AU - Valencia, Victor H.

AU - Levin, Gregor

AU - Ketzel, Matthias

PY - 2022/10

Y1 - 2022/10

N2 - This study presents a method for “downscaling” aggregated global emissions of CO, NOx, and PM2.5 based on georeferenced information (spatial proxies). We distribute ECLIPSE-CLE emissions for Quito, Ecuador, in 2015 and 2017. The study area is a grid of 0.5 × 0.5 km2 cells over a 110 × 110 km2 area. The emission sectors (proxies in parenthesis) are agricultural (land-use maps), domestic (land-use and population density), energy, industry, and waste disposal (point source location from local inventory), and transport (population, vehicle traffic, and road density). Emission distribution quality is satisfactorily evaluated (graphically and statistically) by implementing them in the UBM model and comparing modeled concentrations with observations. This study also explores an alternative proxy set-up for main road emissions based on road density, which, for some modeling sites, results in a better agreement with the observations. Finally, this methodology is applied for comparing air pollution due to two urban growth types for Quito in 2040: sprawl and densification. Both scenarios lead to lower concentrations than in 2017, except for O3. Although the two scenarios attain similar concentrations, urban sprawl presents, in general, noticeably higher values for NOx and NO2.

AB - This study presents a method for “downscaling” aggregated global emissions of CO, NOx, and PM2.5 based on georeferenced information (spatial proxies). We distribute ECLIPSE-CLE emissions for Quito, Ecuador, in 2015 and 2017. The study area is a grid of 0.5 × 0.5 km2 cells over a 110 × 110 km2 area. The emission sectors (proxies in parenthesis) are agricultural (land-use maps), domestic (land-use and population density), energy, industry, and waste disposal (point source location from local inventory), and transport (population, vehicle traffic, and road density). Emission distribution quality is satisfactorily evaluated (graphically and statistically) by implementing them in the UBM model and comparing modeled concentrations with observations. This study also explores an alternative proxy set-up for main road emissions based on road density, which, for some modeling sites, results in a better agreement with the observations. Finally, this methodology is applied for comparing air pollution due to two urban growth types for Quito in 2040: sprawl and densification. Both scenarios lead to lower concentrations than in 2017, except for O3. Although the two scenarios attain similar concentrations, urban sprawl presents, in general, noticeably higher values for NOx and NO2.

UR - http://www.scopus.com/inward/record.url?scp=85137302571&partnerID=8YFLogxK

U2 - 10.1016/j.apr.2022.101516

DO - 10.1016/j.apr.2022.101516

M3 - Journal article

AN - SCOPUS:85137302571

VL - 13

JO - Atmospheric Pollution Research

JF - Atmospheric Pollution Research

SN - 1309-1042

IS - 10

M1 - 101516

ER -