Mass concentration coupled with mass loading rate for evaluating PM(2.5) pollution status in the atmosphere: A case study based on dairy barns

HungSoo Joo; Kihong Park; Kwangyul Lee; Pius M Ndegwa

doi:10.1016/j.envpol.2015.09.048

Mass concentration coupled with mass loading rate for evaluating PM(2.5) pollution status in the atmosphere: A case study based on dairy barns

Environ Pollut. 2015 Dec:207:374-80. doi: 10.1016/j.envpol.2015.09.048. Epub 2015 Nov 2.

Authors

HungSoo Joo¹, Kihong Park², Kwangyul Lee², Pius M Ndegwa³

Affiliations

¹ Department of Biological Systems Engineering, Washington State University, PO Box 646120, Pullman, WA 99164, USA; Aerosol Technology and Monitoring Laboratory, School of Environmental Science and Engineering, Gwangju Institute of Science and Technology (GIST), 123 Cheomdan-Gwagiro, Buk-gu, Gwangju 500-712, Republic of Korea.
² Aerosol Technology and Monitoring Laboratory, School of Environmental Science and Engineering, Gwangju Institute of Science and Technology (GIST), 123 Cheomdan-Gwagiro, Buk-gu, Gwangju 500-712, Republic of Korea.
³ Department of Biological Systems Engineering, Washington State University, PO Box 646120, Pullman, WA 99164, USA. Electronic address: ndegwa@wsu.edu.

PMID: 26452004
DOI: 10.1016/j.envpol.2015.09.048

Abstract

This study investigated particulate matter (PM) loading rates and concentrations in ambient air from naturally ventilated dairy barns and also the influences of pertinent meteorological factors, traffic, and animal activities on mass loading rates and mass concentrations. Generally, relationships between PM2.5 concentration and these parameters were significantly poorer than those between the PM loading rate and the same parameters. Although ambient air PM2.5 loading rates correlated well with PM2.5 emission rates, ambient air PM2.5 concentrations correlated poorly with PM2.5 concentrations in the barns. A comprehensive assessment of PM2.5 pollution in ambient air, therefore, requires both mass concentrations and mass loading rates. Emissions of PM2.5 correlated strongly and positively with wind speed, temperature, and solar radiation (R(2) = 0.84 to 0.99) and strongly but negatively with relative humidity (R(2) = 0.93). Animal activity exhibited only moderate effect on PM2.5 emissions, while traffic activity did not significantly affect PM2.5 emissions.

Keywords: Air exchange rate; Animal activity; Dispersion; Emissions; Traffic activity.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Air / analysis*
Air Pollutants / analysis*
Animals
Cattle
Dairying*
Environmental Monitoring / methods*
Particle Size
Particulate Matter / analysis*
Temperature
Wind

Substances

Air Pollutants
Particulate Matter