PANDORA:用于室内空气质量建模的开放式室内污染物排放率数据库

IF 7.4 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Marc Abadie , Eol Geffre , Charles-Florian Picard , Marcel Loomans , Francesco Babich , Aurora Monge-Barrio , Dusan Licina , Gráinne McGill , Linda Toledo , Ann Marie Coggins , Mohsen Pourkiaei , Núria Casquero-Modrego , Constanza Molina , Sasan Sadrizadeh , James McGrath , Gabriel Rojas-Kopeinig
{"title":"PANDORA:用于室内空气质量建模的开放式室内污染物排放率数据库","authors":"Marc Abadie ,&nbsp;Eol Geffre ,&nbsp;Charles-Florian Picard ,&nbsp;Marcel Loomans ,&nbsp;Francesco Babich ,&nbsp;Aurora Monge-Barrio ,&nbsp;Dusan Licina ,&nbsp;Gráinne McGill ,&nbsp;Linda Toledo ,&nbsp;Ann Marie Coggins ,&nbsp;Mohsen Pourkiaei ,&nbsp;Núria Casquero-Modrego ,&nbsp;Constanza Molina ,&nbsp;Sasan Sadrizadeh ,&nbsp;James McGrath ,&nbsp;Gabriel Rojas-Kopeinig","doi":"10.1016/j.jobe.2025.114216","DOIUrl":null,"url":null,"abstract":"<div><div>Modeling indoor air quality requires reliable data on pollutant emission rates (ERs) from indoor sources. While many studies focus on measuring indoor pollutant concentrations, far fewer provide the source-specific ERs needed for predictive modeling, and those that do often report fragmented and non-standardized formats that limit their use. This paper addresses this gap by introducing PANDORA (a comPilAtioN of inDOor aiR pollutAnt emissions), an internet-based open-access database designed to improve consistency and transparency in indoor air quality assessments. PANDORA systematically compiles ERs data for gaseous and particulate pollutants from a wide range of indoor sources. It classifies 747 sources into comprehensive categories such as construction and decoration materials (354), furniture (38), cleaning products and air fresheners (123), occupants and occupant activities (134), heating and cooking appliances (48), electrical equipment (40), whole room or building (6) and others (4). In this paper, we summarize key experimental methods used to assess the pollutants. To aid in informed decision-making, statistical analyses are provided for selected indoor pollutants of interest, including PM<sub>2.5</sub>, formaldehyde, benzene, and TVOC. Additionally, we compare the impact of using three different modeling approaches and assumptions through a case study that uses the PANDORA data to evaluate indoor pollutant ERs in a room. This application shows how PANDORA supports more transparent and consistent use of emission rate data. Our findings highlight that, despite compiling 9968 emission rate entries, expanding PANDORA with new measurements will further strengthen the accuracy and reliability of indoor air quality modeling and exposure assessments.</div></div>","PeriodicalId":15064,"journal":{"name":"Journal of building engineering","volume":"114 ","pages":"Article 114216"},"PeriodicalIF":7.4000,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PANDORA: An open-access database of indoor pollutant emission rates for IAQ modeling\",\"authors\":\"Marc Abadie ,&nbsp;Eol Geffre ,&nbsp;Charles-Florian Picard ,&nbsp;Marcel Loomans ,&nbsp;Francesco Babich ,&nbsp;Aurora Monge-Barrio ,&nbsp;Dusan Licina ,&nbsp;Gráinne McGill ,&nbsp;Linda Toledo ,&nbsp;Ann Marie Coggins ,&nbsp;Mohsen Pourkiaei ,&nbsp;Núria Casquero-Modrego ,&nbsp;Constanza Molina ,&nbsp;Sasan Sadrizadeh ,&nbsp;James McGrath ,&nbsp;Gabriel Rojas-Kopeinig\",\"doi\":\"10.1016/j.jobe.2025.114216\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Modeling indoor air quality requires reliable data on pollutant emission rates (ERs) from indoor sources. While many studies focus on measuring indoor pollutant concentrations, far fewer provide the source-specific ERs needed for predictive modeling, and those that do often report fragmented and non-standardized formats that limit their use. This paper addresses this gap by introducing PANDORA (a comPilAtioN of inDOor aiR pollutAnt emissions), an internet-based open-access database designed to improve consistency and transparency in indoor air quality assessments. PANDORA systematically compiles ERs data for gaseous and particulate pollutants from a wide range of indoor sources. It classifies 747 sources into comprehensive categories such as construction and decoration materials (354), furniture (38), cleaning products and air fresheners (123), occupants and occupant activities (134), heating and cooking appliances (48), electrical equipment (40), whole room or building (6) and others (4). In this paper, we summarize key experimental methods used to assess the pollutants. To aid in informed decision-making, statistical analyses are provided for selected indoor pollutants of interest, including PM<sub>2.5</sub>, formaldehyde, benzene, and TVOC. Additionally, we compare the impact of using three different modeling approaches and assumptions through a case study that uses the PANDORA data to evaluate indoor pollutant ERs in a room. This application shows how PANDORA supports more transparent and consistent use of emission rate data. Our findings highlight that, despite compiling 9968 emission rate entries, expanding PANDORA with new measurements will further strengthen the accuracy and reliability of indoor air quality modeling and exposure assessments.</div></div>\",\"PeriodicalId\":15064,\"journal\":{\"name\":\"Journal of building engineering\",\"volume\":\"114 \",\"pages\":\"Article 114216\"},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2025-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of building engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352710225024532\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of building engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352710225024532","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

室内空气质量建模需要可靠的室内污染源污染物排放率(er)数据。虽然许多研究侧重于测量室内污染物浓度,但提供预测建模所需的特定于源的er的研究少之又少,而那些经常报告碎片化和非标准化格式的研究也限制了它们的使用。本文通过引入PANDORA(室内空气污染物排放汇编)来解决这一差距,PANDORA是一个基于互联网的开放访问数据库,旨在提高室内空气质量评估的一致性和透明度。PANDORA系统地汇编了来自各种室内来源的气体和颗粒污染物的ERs数据。它将747个来源分为综合类别,如建筑和装饰材料(354),家具(38),清洁产品和空气清新剂(123),居住者和居住者活动(134),加热和烹饪器具(48),电气设备(40),整个房间或建筑物(6)和其他(4)。本文综述了用于评价污染物的主要实验方法。为了帮助明智的决策,提供了对选定的室内污染物的统计分析,包括PM2.5,甲醛,苯和TVOC。此外,我们通过一个使用PANDORA数据评估室内污染物er的案例研究,比较了使用三种不同建模方法和假设的影响。这个应用程序显示了潘多拉如何支持更透明和一致的排放率数据的使用。我们的研究结果强调,尽管汇编了9968个排放率条目,但使用新的测量方法扩展PANDORA将进一步加强室内空气质量建模和暴露评估的准确性和可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PANDORA: An open-access database of indoor pollutant emission rates for IAQ modeling
Modeling indoor air quality requires reliable data on pollutant emission rates (ERs) from indoor sources. While many studies focus on measuring indoor pollutant concentrations, far fewer provide the source-specific ERs needed for predictive modeling, and those that do often report fragmented and non-standardized formats that limit their use. This paper addresses this gap by introducing PANDORA (a comPilAtioN of inDOor aiR pollutAnt emissions), an internet-based open-access database designed to improve consistency and transparency in indoor air quality assessments. PANDORA systematically compiles ERs data for gaseous and particulate pollutants from a wide range of indoor sources. It classifies 747 sources into comprehensive categories such as construction and decoration materials (354), furniture (38), cleaning products and air fresheners (123), occupants and occupant activities (134), heating and cooking appliances (48), electrical equipment (40), whole room or building (6) and others (4). In this paper, we summarize key experimental methods used to assess the pollutants. To aid in informed decision-making, statistical analyses are provided for selected indoor pollutants of interest, including PM2.5, formaldehyde, benzene, and TVOC. Additionally, we compare the impact of using three different modeling approaches and assumptions through a case study that uses the PANDORA data to evaluate indoor pollutant ERs in a room. This application shows how PANDORA supports more transparent and consistent use of emission rate data. Our findings highlight that, despite compiling 9968 emission rate entries, expanding PANDORA with new measurements will further strengthen the accuracy and reliability of indoor air quality modeling and exposure assessments.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of building engineering
Journal of building engineering Engineering-Civil and Structural Engineering
CiteScore
10.00
自引率
12.50%
发文量
1901
审稿时长
35 days
期刊介绍: The Journal of Building Engineering is an interdisciplinary journal that covers all aspects of science and technology concerned with the whole life cycle of the built environment; from the design phase through to construction, operation, performance, maintenance and its deterioration.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信