Analysis of Factors Influencing Indoor PM2.5 and CO2 Concentrations in Households using IoT Technology after Indoor Garden Installation

Q3 Social Sciences
Ho-Hyeong Yang, Min-Jung Kwak, Kwang-Jin Kim, Ho-Hyun Kim
{"title":"Analysis of Factors Influencing Indoor PM2.5 and CO2 Concentrations in Households using IoT Technology after Indoor Garden Installation","authors":"Ho-Hyeong Yang, Min-Jung Kwak, Kwang-Jin Kim, Ho-Hyun Kim","doi":"10.11628/ksppe.2022.25.6.571","DOIUrl":null,"url":null,"abstract":"Background and objective: Plants are a natural and environmentally friendly way to improve indoor air quality. To evaluate indoor air quality, it is important to continuously measure and identify the influencing factors. This study aimed to identify the factors affecting PM2.5 concentration in indoor spaces with indoor garden installations.Methods: Factors influencing the concentration of indoor, airborne PM2.5 were monitored based on Internet of Things (IoT) technology. Ten households in South Korea were surveyed and categorized into Groups A (households without an indoor garden) and B (households with an indoor garden). An IoT-based device was used to monitor the indoor PM2.5 concentration and several environmental factors, including the outdoor PM2.5 (µg⋅m-3) and carbon dioxide (mL⋅m-3) concentrations, temperature (°C), and relative humidity (%). Further, the seasonal (spring, summer, fall, and winter) and temporal (dawn, morning, afternoon, and evening) variations in indoor PM2.5 concentration were monitored.Results: The indoor PM2.5 concentration decreased from 17.7 µg⋅m-3 to 16.7 µg⋅m-3, and from 15.5 µg⋅m-3 to 12.5 µg⋅m-3 in Groups A and B, respectively. A regression analysis showed that the indoor PM2.5 concentration was not significantly affected by the installation of the indoor garden (living rooms: p = .1577; kitchen: p = .4974); however, was influenced by the outdoor air conditions, as well as seasonal and temporal factors. Additionally, a subgrouping model demonstrated a statistical relationship between indoor garden installation and the environmental factors.Conclusion: These findings can assist in establishing guidelines for indoor air quality management.","PeriodicalId":52383,"journal":{"name":"Journal of People, Plants, and Environment","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of People, Plants, and Environment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11628/ksppe.2022.25.6.571","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0

Abstract

Background and objective: Plants are a natural and environmentally friendly way to improve indoor air quality. To evaluate indoor air quality, it is important to continuously measure and identify the influencing factors. This study aimed to identify the factors affecting PM2.5 concentration in indoor spaces with indoor garden installations.Methods: Factors influencing the concentration of indoor, airborne PM2.5 were monitored based on Internet of Things (IoT) technology. Ten households in South Korea were surveyed and categorized into Groups A (households without an indoor garden) and B (households with an indoor garden). An IoT-based device was used to monitor the indoor PM2.5 concentration and several environmental factors, including the outdoor PM2.5 (µg⋅m-3) and carbon dioxide (mL⋅m-3) concentrations, temperature (°C), and relative humidity (%). Further, the seasonal (spring, summer, fall, and winter) and temporal (dawn, morning, afternoon, and evening) variations in indoor PM2.5 concentration were monitored.Results: The indoor PM2.5 concentration decreased from 17.7 µg⋅m-3 to 16.7 µg⋅m-3, and from 15.5 µg⋅m-3 to 12.5 µg⋅m-3 in Groups A and B, respectively. A regression analysis showed that the indoor PM2.5 concentration was not significantly affected by the installation of the indoor garden (living rooms: p = .1577; kitchen: p = .4974); however, was influenced by the outdoor air conditions, as well as seasonal and temporal factors. Additionally, a subgrouping model demonstrated a statistical relationship between indoor garden installation and the environmental factors.Conclusion: These findings can assist in establishing guidelines for indoor air quality management.
应用物联网技术分析室内花园安装后家庭室内PM2.5和CO2浓度的影响因素
背景与目的:植物是改善室内空气质量的一种自然且环保的方式。为了评价室内空气质量,对影响因素进行持续的测量和识别是非常重要的。本研究旨在通过室内花园装置确定影响室内空间PM2.5浓度的因素。方法:基于物联网技术监测室内、空气中PM2.5浓度的影响因素。对韩国10个家庭进行了调查,分为A(没有室内花园的家庭)和B(有室内花园的家庭)两组。采用物联网设备监测室内PM2.5浓度及室外PM2.5(µg⋅m-3)、二氧化碳(mL⋅m-3)浓度、温度(°C)、相对湿度(%)等环境因子。此外,还监测了室内PM2.5浓度的季节(春、夏、秋、冬)和时间(黎明、早晨、下午和晚上)变化。结果:A组和B组室内PM2.5浓度分别由17.7µg⋅m-3和15.5µg⋅m-3降低至12.5µg⋅m-3。回归分析显示,室内PM2.5浓度不受室内花园设置的显著影响(客厅:p = .1577;厨房:p = .4974);然而,受室外空气条件以及季节和时间因素的影响。此外,一个亚分组模型显示了室内花园安装与环境因素之间的统计关系。结论:这些发现有助于建立室内空气质量管理的指导方针。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of People, Plants, and Environment
Journal of People, Plants, and Environment Social Sciences-Urban Studies
CiteScore
1.10
自引率
0.00%
发文量
42
×
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