A Regression Approach for Estimation of Anthropogenic Heat Flux Based on a Bottom-Up Air Pollutant Emission Database

Authors

Sanghyun Lee, Kongju National University
Stuart A. McKeen, NOAA Earth System Research Laboratory
David J. Sailor, Portland State UniversityFollow

Published In

Atmospheric Environment

Document Type

Article

Publication Date

10-2014

Subjects

Heat flux, Emissions -- Anthropogenic, Regression analysis, Energy consumption

Abstract

A statistical regression method is presented for estimating hourly anthropogenic heat flux (AHF) using an anthropogenic pollutant emission inventory for use in mesoscale meteorological and air-quality modeling. Based on bottom-up AHF estimated from detailed energy consumption data and anthropogenic pollutant emissions of carbon monoxide (CO) and nitrogen oxides (NO_x) in the US National Emission Inventory year 2005 (NEI-2005), a robust regression relation between the AHF and the pollutant emissions is obtained for Houston. This relation is a combination of two power functions (Y = aX^b) relating CO and NO_x emissions to AHF, giving a determinant coefficient (R²) of 0.72. The AHF for Houston derived from the regression relation has high temporal (R = 0.91) and spatial (R = 0.83) correlations with the bottom-up AHF. Hourly AHF for the whole US in summer is estimated by applying the regression relation to the NEI-2005 summer pollutant emissions with a high spatial resolution of 4-km. The summer daily mean AHF range 10–40 W m^-2 on a 4 × 4 km² grid scale with maximum heat fluxes of 50–140 W m^-2 for major US cities. The AHFs derived from the regression relations between the bottom-up AHF and either CO or NOx emissions show a small difference of less than 5% (4.7 W m^-2) in city-scale daily mean AHF, and similar R² statistics, compared to results from their combination. Thus, emissions of either species can be used to estimate AHF in the US cities. An hourly AHF inventory at 4 × 4 km² resolution over the entire US based on the combined regression is derived and made publicly available for use in mesoscale numerical modeling.

Description

To the best of our knowledge this work was authored as part of a Contributor's official duties as an Employee of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.

This is the pdf of an article published by Elsevier 2014. The final definitive version can also be found on the publisher website. http://dx.doi.org/10.1016/j.atmosenv.2014.07.009

DOI

10.1016/j.atmosenv.2014.07.009

Persistent Identifier

http://archives.pdx.edu/ds/psu/12635

Citation Details

Lee, S. H., McKeen, S. A., & Sailor, D. J. (2014). A regression approach for estimation of anthropogenic heat flux based on a bottom-up air pollutant emission database. Atmospheric Environment, 95, 629-633.