Owain G. Rose, Dimitrios Bousiotis, Catrin Rathbone, Francis D. Pope
{"title":"调查学校教室内的室内空气污染来源和学生接触情况:使用低成本传感器和污染源分摊法","authors":"Owain G. Rose, Dimitrios Bousiotis, Catrin Rathbone, Francis D. Pope","doi":"10.1155/2024/5544298","DOIUrl":null,"url":null,"abstract":"<p>Indoor air quality is becoming one of the most important factors for public health, as people tend to spend more time indoors, either at home or at work. This paper combines the use of calibrated low-cost particulate matter (PM) sensors with source apportionment algorithms to understand the factors that affect the indoor air quality within a typical UK school. Low-cost optical particle counter (OPC) sensors were placed in three different classrooms within the school, measuring PM concentrations during a typical school week and the subsequent holiday period, to understand the role of occupancy within schools for air quality. When students were in attendance during school hours (09:00–15:30), the classroom with the greatest average PM levels had PM<sub>2.5</sub> and PM<sub>10</sub> mass concentrations of 14.4 and 51.0 <i>μ</i>g/m<sup>3</sup>, respectively. During school hours, when students were present, all classrooms had average PM<sub>2.5</sub> concentrations greater than 8.1 <i>μ</i>g m<sup>−3</sup> and average PM<sub>10</sub> concentrations greater than 13.1 <i>μ</i>g m<sup>−3</sup>. Notably, the English studies classroom exceeded the 24-h WHO ambient PM<sub>10</sub> guideline (45 <i>μ</i>g m<sup>−3</sup>). Employing the non-negative matrix factorization (NMF) algorithm for source apportionment revealed that between 93% and 98% of PM<sub>1</sub> observed within classrooms derived from outdoor sources. This contribution diminished as particle size increased, with outdoor sources accounting for 74%–89% of PM<sub>2.5</sub>, and 19%–40% of PM<sub>10</sub>, respectively. The differences in classroom PM concentration and source percentages are attributed to differences in lesson activities, lesson frequency, flooring (carpeted versus hard flooring), location within the school, and proximity to outdoor sources such as roads. The approach described within the paper is easily translated to other indoor locations and could also be straightforwardly scaled due to its relatively low cost. Thereby, it allows for air quality management in locations crucial for the public health and educational outcomes of children.</p>","PeriodicalId":13529,"journal":{"name":"Indoor air","volume":"2024 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/5544298","citationCount":"0","resultStr":"{\"title\":\"Investigating Indoor Air Pollution Sources and Student’s Exposure Within School Classrooms: Using a Low-Cost Sensor and Source Apportionment Approach\",\"authors\":\"Owain G. Rose, Dimitrios Bousiotis, Catrin Rathbone, Francis D. Pope\",\"doi\":\"10.1155/2024/5544298\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Indoor air quality is becoming one of the most important factors for public health, as people tend to spend more time indoors, either at home or at work. This paper combines the use of calibrated low-cost particulate matter (PM) sensors with source apportionment algorithms to understand the factors that affect the indoor air quality within a typical UK school. Low-cost optical particle counter (OPC) sensors were placed in three different classrooms within the school, measuring PM concentrations during a typical school week and the subsequent holiday period, to understand the role of occupancy within schools for air quality. When students were in attendance during school hours (09:00–15:30), the classroom with the greatest average PM levels had PM<sub>2.5</sub> and PM<sub>10</sub> mass concentrations of 14.4 and 51.0 <i>μ</i>g/m<sup>3</sup>, respectively. During school hours, when students were present, all classrooms had average PM<sub>2.5</sub> concentrations greater than 8.1 <i>μ</i>g m<sup>−3</sup> and average PM<sub>10</sub> concentrations greater than 13.1 <i>μ</i>g m<sup>−3</sup>. Notably, the English studies classroom exceeded the 24-h WHO ambient PM<sub>10</sub> guideline (45 <i>μ</i>g m<sup>−3</sup>). Employing the non-negative matrix factorization (NMF) algorithm for source apportionment revealed that between 93% and 98% of PM<sub>1</sub> observed within classrooms derived from outdoor sources. This contribution diminished as particle size increased, with outdoor sources accounting for 74%–89% of PM<sub>2.5</sub>, and 19%–40% of PM<sub>10</sub>, respectively. The differences in classroom PM concentration and source percentages are attributed to differences in lesson activities, lesson frequency, flooring (carpeted versus hard flooring), location within the school, and proximity to outdoor sources such as roads. The approach described within the paper is easily translated to other indoor locations and could also be straightforwardly scaled due to its relatively low cost. 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Investigating Indoor Air Pollution Sources and Student’s Exposure Within School Classrooms: Using a Low-Cost Sensor and Source Apportionment Approach
Indoor air quality is becoming one of the most important factors for public health, as people tend to spend more time indoors, either at home or at work. This paper combines the use of calibrated low-cost particulate matter (PM) sensors with source apportionment algorithms to understand the factors that affect the indoor air quality within a typical UK school. Low-cost optical particle counter (OPC) sensors were placed in three different classrooms within the school, measuring PM concentrations during a typical school week and the subsequent holiday period, to understand the role of occupancy within schools for air quality. When students were in attendance during school hours (09:00–15:30), the classroom with the greatest average PM levels had PM2.5 and PM10 mass concentrations of 14.4 and 51.0 μg/m3, respectively. During school hours, when students were present, all classrooms had average PM2.5 concentrations greater than 8.1 μg m−3 and average PM10 concentrations greater than 13.1 μg m−3. Notably, the English studies classroom exceeded the 24-h WHO ambient PM10 guideline (45 μg m−3). Employing the non-negative matrix factorization (NMF) algorithm for source apportionment revealed that between 93% and 98% of PM1 observed within classrooms derived from outdoor sources. This contribution diminished as particle size increased, with outdoor sources accounting for 74%–89% of PM2.5, and 19%–40% of PM10, respectively. The differences in classroom PM concentration and source percentages are attributed to differences in lesson activities, lesson frequency, flooring (carpeted versus hard flooring), location within the school, and proximity to outdoor sources such as roads. The approach described within the paper is easily translated to other indoor locations and could also be straightforwardly scaled due to its relatively low cost. Thereby, it allows for air quality management in locations crucial for the public health and educational outcomes of children.
期刊介绍:
The quality of the environment within buildings is a topic of major importance for public health.
Indoor Air provides a location for reporting original research results in the broad area defined by the indoor environment of non-industrial buildings. An international journal with multidisciplinary content, Indoor Air publishes papers reflecting the broad categories of interest in this field: health effects; thermal comfort; monitoring and modelling; source characterization; ventilation and other environmental control techniques.
The research results present the basic information to allow designers, building owners, and operators to provide a healthy and comfortable environment for building occupants, as well as giving medical practitioners information on how to deal with illnesses related to the indoor environment.