Challenges and opportunities of low-cost sensors in capturing the impacts of construction activities on neighborhood air quality Article Swipe
Weaam Jaafar
,
Junshi Xu
,
Emily Farrar
,
Cheol–Heon Jeong
,
Arman Ganji
,
Greg J. Evans
,
Marianne Hatzopoulou
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.buildenv.2024.111363
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.buildenv.2024.111363
In large metropolitan areas such as Toronto, planners are increasingly relying on urban densification to accommodate population growth sustainably. While infill developments support the city's long-term climate goals, on-going construction impacts air quality for local communities. Understanding how neighborhoods are impacted by these localized sources can be achieved by implementing a network of low-cost sensors. In this study, we placed twelve low-cost sensors on balconies in a Toronto neighborhood impacted by various construction projects. The study aims to capture the impact of construction and heavy-duty traffic and provide a better understanding of spatial variability in fine particulate matter (PM2.5). The locations were compared using time series analysis, inverse distance weighing (IDW) for spatial heterogeneity, and spectral analysis to quantify the contribution of local sources. Sensors exhibited inter-sensor variability, which was corrected upon calibration. Sensors located near and far from construction sites showed similar temporal trends, however locations near construction sites measured greater PM2.5 concentrations, where the hourly average concentration for sensors near construction sites ranged between 6.8 and 8.5 μg/m3 and sensors further away ranged between 5.4 and 6.2 μg/m3. Spatial variability was also captured by IDW where sensors near construction sites were more heterogenous and exhibited greater concentrations. Spectral analysis demonstrated that local sources contributed up to 23% of PM2.5 levels near construction while distant locations had a maximum of 11% local contribution. By using a network of sensors, we explore how construction sites create localized hot spots within a neighborhood.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.buildenv.2024.111363
- OA Status
- hybrid
- Cited By
- 12
- References
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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- DOI
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https://doi.org/10.1016/j.buildenv.2024.111363Digital Object Identifier
- Title
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Challenges and opportunities of low-cost sensors in capturing the impacts of construction activities on neighborhood air qualityWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
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2024Year of publication
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2024-03-10Full publication date if available
- Authors
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Weaam Jaafar, Junshi Xu, Emily Farrar, Cheol–Heon Jeong, Arman Ganji, Greg J. Evans, Marianne HatzopoulouList of authors in order
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https://doi.org/10.1016/j.buildenv.2024.111363Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.buildenv.2024.111363Direct OA link when available
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Infill, Metropolitan area, Air quality index, Environmental science, Population, Sustainability, Wireless sensor network, Geography, Transport engineering, Civil engineering, Remote sensing, Computer science, Engineering, Meteorology, Biology, Archaeology, Sociology, Ecology, Demography, Computer networkTop concepts (fields/topics) attached by OpenAlex
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12Total citation count in OpenAlex
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2025: 7, 2024: 5Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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