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Source specific exposure and risk assessment for indoor aerosols

Koivisto, Antti Joonas ; Kling, Kirsten Inga ; Hänninen, Otto ; Jayjock, Michael ; Löndahl, Jakob LU orcid ; Wierzbicka, Aneta LU orcid ; Fonseca, Ana Sofia ; Uhrbrand, Katrine ; Boor, Brandon E. and Jiménez, Araceli Sánchez , et al. (2019) In Science of the Total Environment 668. p.13-24
Abstract

Poor air quality is a leading contributor to the global disease burden and total number of deaths worldwide. Humans spend most of their time in built environments where the majority of the inhalation exposure occurs. Indoor Air Quality (IAQ) is challenged by outdoor air pollution entering indoors through ventilation and infiltration and by indoor emission sources. The aim of this study was to understand the current knowledge level and gaps regarding effective approaches to improve IAQ. Emission regulations currently focus on outdoor emissions, whereas quantitative understanding of emissions from indoor sources is generally lacking. Therefore, specific indoor sources need to be identified, characterized, and quantified according to their... (More)

Poor air quality is a leading contributor to the global disease burden and total number of deaths worldwide. Humans spend most of their time in built environments where the majority of the inhalation exposure occurs. Indoor Air Quality (IAQ) is challenged by outdoor air pollution entering indoors through ventilation and infiltration and by indoor emission sources. The aim of this study was to understand the current knowledge level and gaps regarding effective approaches to improve IAQ. Emission regulations currently focus on outdoor emissions, whereas quantitative understanding of emissions from indoor sources is generally lacking. Therefore, specific indoor sources need to be identified, characterized, and quantified according to their environmental and human health impact. The emission sources should be stored in terms of relevant metrics and statistics in an easily accessible format that is applicable for source specific exposure assessment by using mathematical mass balance modelings. This forms a foundation for comprehensive risk assessment and efficient interventions. For such a general exposure assessment model we need 1) systematic methods for indoor aerosol emission source assessment, 2) source emission documentation in terms of relevant a) aerosol metrics and b) biological metrics, 3) default model parameterization for predictive exposure modeling, 4) other needs related to aerosol characterization techniques and modeling methods. Such a general exposure assessment model can be applicable for private, public, and occupational indoor exposure assessment, making it a valuable tool for public health professionals, product safety designers, industrial hygienists, building scientists, and environmental consultants working in the field of IAQ and health.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Air quality, Emission, Health, Mass balance, Modeling, Regulation
in
Science of the Total Environment
volume
668
pages
12 pages
publisher
Elsevier
external identifiers
  • scopus:85062356173
  • pmid:30851679
ISSN
0048-9697
DOI
10.1016/j.scitotenv.2019.02.398
language
English
LU publication?
yes
id
8129e19c-c0a6-4237-ac3e-7b8939cba2c4
date added to LUP
2019-03-12 11:04:17
date last changed
2024-04-30 02:18:55
@article{8129e19c-c0a6-4237-ac3e-7b8939cba2c4,
  abstract     = {{<p>Poor air quality is a leading contributor to the global disease burden and total number of deaths worldwide. Humans spend most of their time in built environments where the majority of the inhalation exposure occurs. Indoor Air Quality (IAQ) is challenged by outdoor air pollution entering indoors through ventilation and infiltration and by indoor emission sources. The aim of this study was to understand the current knowledge level and gaps regarding effective approaches to improve IAQ. Emission regulations currently focus on outdoor emissions, whereas quantitative understanding of emissions from indoor sources is generally lacking. Therefore, specific indoor sources need to be identified, characterized, and quantified according to their environmental and human health impact. The emission sources should be stored in terms of relevant metrics and statistics in an easily accessible format that is applicable for source specific exposure assessment by using mathematical mass balance modelings. This forms a foundation for comprehensive risk assessment and efficient interventions. For such a general exposure assessment model we need 1) systematic methods for indoor aerosol emission source assessment, 2) source emission documentation in terms of relevant a) aerosol metrics and b) biological metrics, 3) default model parameterization for predictive exposure modeling, 4) other needs related to aerosol characterization techniques and modeling methods. Such a general exposure assessment model can be applicable for private, public, and occupational indoor exposure assessment, making it a valuable tool for public health professionals, product safety designers, industrial hygienists, building scientists, and environmental consultants working in the field of IAQ and health.</p>}},
  author       = {{Koivisto, Antti Joonas and Kling, Kirsten Inga and Hänninen, Otto and Jayjock, Michael and Löndahl, Jakob and Wierzbicka, Aneta and Fonseca, Ana Sofia and Uhrbrand, Katrine and Boor, Brandon E. and Jiménez, Araceli Sánchez and Hämeri, Kaarle and Maso, Miikka Dal and Arnold, Susan F. and Jensen, Keld A. and Viana, Mar and Morawska, Lidia and Hussein, Tareq}},
  issn         = {{0048-9697}},
  keywords     = {{Air quality; Emission; Health; Mass balance; Modeling; Regulation}},
  language     = {{eng}},
  pages        = {{13--24}},
  publisher    = {{Elsevier}},
  series       = {{Science of the Total Environment}},
  title        = {{Source specific exposure and risk assessment for indoor aerosols}},
  url          = {{http://dx.doi.org/10.1016/j.scitotenv.2019.02.398}},
  doi          = {{10.1016/j.scitotenv.2019.02.398}},
  volume       = {{668}},
  year         = {{2019}},
}