Aerosol sources characterization and apportionment from low-cost particle sensors in an urban environment

IF 3.8 Q2 ENVIRONMENTAL SCIENCES
Vikas Kumar , Vasudev Malyan , Manoranjan Sahu , Basudev Biswal
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引用次数: 0

Abstract

Low-cost sensors (LCS) have the potential to provide accurate and reliable measurements of air quality in real-time. This improves our ability to monitor, identify sources of pollution and develop mitigation strategies for effective air quality management. However, recent research on LCS has primarily focused on monitoring, exposure assessment, and calibration. In this study, we investigate the applicability of LCS data collected at ambient sites for characterizing and apportioning aerosol sources. Non-negative matrix factorization (NMF) was applied to the size-resolved data collected across five sites within the Indian Institute of Technology Bombay (IITB) campus in Mumbai using the LCS Alphasense OPC-N2. The sampling was done for 15 days at 5 locations in IITB, and each site only had 3 days of data. NMF resolved two factors for three sites, namely aromas (S2), hostel hub (S3) and central library (S4), while three factors were resolved for two sites, namely construction site (S1) and main gate (S5). Two common sources were determined for all the sites: (i) dust and marine source and (ii) traffic and combustion sources, which agree with the sources identified by studies in the literature. The third factor resolved at sites S1 and S5 is representative of heavy-duty diesel vehicles (HDDVs), which is present for a very short period and is captured because of the capability of high temporal resolution of the LCS. This offers a unique, cost-effective advantage of LCS for capturing episodic activities. The study suggests that in low- and middle-income countries with limited air quality monitoring capabilities, the size-time-resolved PM concentration data obtained from a network of low-cost sensors can estimate the pollution sources. This study provided evidence that despite their inherent limitations, LCS can be useful in attaining interpretable information about pollution sources and recommends extensive use of LCS for source characterization in the future.

Abstract Image

利用城市环境中的低成本粒子传感器确定气溶胶源的特征和比例
低成本传感器(LCS)具有实时提供准确可靠的空气质量测量值的潜力。这提高了我们监测、识别污染源和制定有效空气质量管理的缓解策略的能力。然而,最近关于 LCS 的研究主要集中在监测、暴露评估和校准方面。在本研究中,我们研究了在环境站点收集的 LCS 数据在确定气溶胶源的特征和分布方面的适用性。使用 LCS Alphasense OPC-N2 将非负矩阵因式分解 (NMF) 应用于在孟买印度理工学院(IITB)校园内五个地点收集的粒度分辨数据。在印度理工学院孟买校区的 5 个地点进行了为期 15 天的采样,每个地点只有 3 天的数据。NMF 分解了三个地点的两个因子,即香气(S2)、宿舍中心(S3)和中央图书馆(S4),同时分解了两个地点的三个因子,即建筑工地(S1)和正门(S5)。所有场地都确定了两个共同来源:(i) 灰尘和海洋来源;(ii) 交通和燃烧来源,这与文献研究确定的来源一致。在站点 S1 和 S5 解决的第三个因素是重型柴油车 (HDDV),其存在时间很短,由于 LCS 具有高时间分辨率的能力,因此可以捕捉到。这使 LCS 在捕捉偶发活动方面具有独特的成本效益优势。该研究表明,在空气质量监测能力有限的中低收入国家,从低成本传感器网络获得的粒径-时间分辨率可吸入颗粒物浓度数据可以估算污染源。这项研究提供的证据表明,尽管有其固有的局限性,低成本传感器在获得可解释的污染源信息方面还是很有用的,并建议今后在污染源特征描述方面广泛使用低成本传感器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Atmospheric Environment: X
Atmospheric Environment: X Environmental Science-Environmental Science (all)
CiteScore
8.00
自引率
0.00%
发文量
47
审稿时长
12 weeks
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