利用低成本传感器测量孟加拉国达卡住宅的室内外 PM2.5 浓度特征

IF 4.2 2区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Atmospheric Environment Pub Date : 2024-11-21 DOI:10.1016/j.atmosenv.2024.120945

Provat K. Saha , Ahsan Habib , Dipika R. Prapti , Talha Jubair , Abu U. Zarrah , Chowdhury A. Hossain , Sheikh M. Rahman , Abdus Salam , Md Aynul Bari , Julian D. Marshall

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引用次数: 0

摘要

我们在孟加拉国达卡的 17 个家庭中同时采集了室内和室外 PM2.5 测量数据，以描述时空变化特征并确定影响室内和室外 PM2.5 水平的因素。在雨季和旱季期间，每户家庭都安装了一对 PurpleAir PM2.5 传感器，一个安装在室内，另一个安装在室外，并使用当地校准的数据进行分析。旱季的室内外 PM2.5 水平（室内 146 ± 22 μg/m³，室外 153 ± 23 μg/m³）是雨季（室内 52 ± 12 μg/m³，室外 50 ± 11 μg/m³）的三倍。两个季节的室内外（I/O）比值都接近 1（旱季：0.97 ± 0.14，雨季：1.05 ± 0.19）。这表明，地区背景污染水平对不同家庭的室内污染水平有很大影响。通过对室内和室外时间序列数据进行混合效应回归确定的渗透系数接近于 1（旱季：0.83 ± 0.12；雨季：0.87 ± 0.14），进一步凸显了室外污染对室内水平的重大影响。来自单个家庭的数据显示，两个季节的室内和室外污染水平之间存在很强的时间相关性（Pearson R：旱季为 0.82 ± 0.12，雨季为 0.83 ± 0.14），而各测量家庭的室内外空间相关性适中（旱季和雨季的 R 值分别为 0.49 和 0.62）。这些空间相关性和经验回归模型表明，虽然室外PM2.5水平的空间变化对室内PM2.5水平的空间变化有显著影响，但其他因素，如室内污染源活动和通风相关特征，在解释不同家庭室内PM2.5的变化方面起着至关重要的作用。总之，我们的研究表明，达卡市的室内环境几乎与室外环境污染一样严重，这一从当地得出的科学证据对于提高公众意识和制定缓解措施以减少孟加拉国的 PM2.5 暴露非常有价值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Characterizing indoor-outdoor PM2.5 concentrations using low-cost sensor measurements in residential homes in Dhaka, Bangladesh

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Characterizing indoor-outdoor PM2.5 concentrations using low-cost sensor measurements in residential homes in Dhaka, Bangladesh

We collected simultaneous indoor and outdoor PM_2.5 measurements from 17 homes in Dhaka, Bangladesh, to characterize spatio-temporal variations and identify factors influencing indoor and outdoor PM_2.5 levels. A pair of PurpleAir PM_2.5 sensors were deployed at each home, one indoors and the other outdoors, during the wet and dry seasons, and the locally calibrated data were used for analysis. Indoor and outdoor PM_2.5 levels were three times higher during the dry season (indoor 146 ± 22 μg/m³, outdoor 153 ± 23 μg/m³) than during the wet season (indoor 52 ± 12 μg/m³, outdoor 50 ± 11 μg/m³). Indoor to outdoor (I/O) ratios were close to 1 in both seasons (dry: 0.97 ± 0.14, wet: 1.05 ± 0.19). This suggests that regional background pollution levels significantly influence indoor levels observed in different households. Infiltration factors closer to 1 (dry: 0.83 ± 0.12; wet: 0.87 ± 0.14), determined through mixed-effects regression of indoor and outdoor time series data, further highlight the substantial impact of outdoor pollution on indoor levels. Data from individual households exhibited strong temporal correlation between indoor and outdoor levels in both seasons (Pearson R: 0.82 ± 0.12 during the dry season and 0.83 ± 0.14 during the wet season), whereas indoor-outdoor spatial correlations across measured households were moderate (R: 0.49 and 0.62 during dry and wet seasons, respectively). These spatial correlations and empirical regression modeling suggest that while the spatial variation of outdoor PM_2.5 levels significantly influences indoor levels' spatial variation, other factors such as indoor source activities and ventilation-related features play crucial roles in explaining variabilities in indoor PM_2.5 across homes. Overall, our study suggests that indoor environments in Dhaka city are nearly as polluted as outdoor settings, and this locally derived scientific evidence can be valuable for enhancing public awareness and developing mitigation measures to reduce PM_2.5 exposures in Bangladesh.

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来源期刊

Atmospheric Environment 环境科学-环境科学

CiteScore

9.40

自引率

8.00%

发文量

458

审稿时长

53 days

期刊介绍： Atmospheric Environment has an open access mirror journal Atmospheric Environment: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review. Atmospheric Environment is the international journal for scientists in different disciplines related to atmospheric composition and its impacts. The journal publishes scientific articles with atmospheric relevance of emissions and depositions of gaseous and particulate compounds, chemical processes and physical effects in the atmosphere, as well as impacts of the changing atmospheric composition on human health, air quality, climate change, and ecosystems.