Simulating the effect of variations in emission source start times on indoor PM concentrations

James A. McGrath; Miriam A. Byrne; Mike R. Ashmore; Andrew C. Terry; Sani Dimitroulopoulou

Simulating the effect of variations in emission source start times on indoor PM concentrations

James A. McGrath^*, Miriam A. Byrne, Mike R. Ashmore, Andrew C. Terry, Sani Dimitroulopoulou

^*Corresponding author for this work

Head Of Department EHE

Research output: Contribution to conference › Paper › peer-review

2 Citations (Scopus)

Abstract

This paper presents the simulation of concentrations with variations in the start times of indoor PM emission sources, as exact details can be uncertain or vary over population groups, as a result of differences in their activity profiles. Probability density functions are used to generate a distribution of potential start times, predicting the range of possible indoor PM concentrations. This technique captures details on the concentration distribution, in contrast to a single peak concentration, but the consequence of using this is an under-prediction of peak concentrations.

Original language	English
Pages	304-306
Number of pages	3
Publication status	Published - 2014
Event	13th International Conference on Indoor Air Quality and Climate, Indoor Air 2014 - Hong Kong, Hong Kong Duration: 7 Jul 2014 → 12 Jul 2014

Conference

Conference	13th International Conference on Indoor Air Quality and Climate, Indoor Air 2014
Country/Territory	Hong Kong
City	Hong Kong
Period	7/07/14 → 12/07/14

Keywords

Emissions
Indoor air quality
PM
Probabilistic modelling

Cite this

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title = "Simulating the effect of variations in emission source start times on indoor PM concentrations",

abstract = "This paper presents the simulation of concentrations with variations in the start times of indoor PM emission sources, as exact details can be uncertain or vary over population groups, as a result of differences in their activity profiles. Probability density functions are used to generate a distribution of potential start times, predicting the range of possible indoor PM concentrations. This technique captures details on the concentration distribution, in contrast to a single peak concentration, but the consequence of using this is an under-prediction of peak concentrations.",

keywords = "Emissions, Indoor air quality, PM, Probabilistic modelling",

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AU - McGrath, James A.

AU - Byrne, Miriam A.

AU - Ashmore, Mike R.

AU - Terry, Andrew C.

AU - Dimitroulopoulou, Sani

PY - 2014

Y1 - 2014

N2 - This paper presents the simulation of concentrations with variations in the start times of indoor PM emission sources, as exact details can be uncertain or vary over population groups, as a result of differences in their activity profiles. Probability density functions are used to generate a distribution of potential start times, predicting the range of possible indoor PM concentrations. This technique captures details on the concentration distribution, in contrast to a single peak concentration, but the consequence of using this is an under-prediction of peak concentrations.

AB - This paper presents the simulation of concentrations with variations in the start times of indoor PM emission sources, as exact details can be uncertain or vary over population groups, as a result of differences in their activity profiles. Probability density functions are used to generate a distribution of potential start times, predicting the range of possible indoor PM concentrations. This technique captures details on the concentration distribution, in contrast to a single peak concentration, but the consequence of using this is an under-prediction of peak concentrations.

KW - Emissions

KW - Indoor air quality

KW - PM

KW - Probabilistic modelling

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M3 - Paper

AN - SCOPUS:84924690029

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T2 - 13th International Conference on Indoor Air Quality and Climate, Indoor Air 2014

Y2 - 7 July 2014 through 12 July 2014

ER -

Simulating the effect of variations in emission source start times on indoor PM concentrations

Abstract

Conference

Keywords

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