Observing local CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; sources using low-cost, near-surface urban monitors

Shusterman, Alexis A.; Kim, Jinsol; Lieschke, Kaitlyn J.; Newman, Catherine; Wooldridge, P. J.; Cohen, R. C.

doi:10.5194/acp-18-13773-2018

Cited by 31 publications

(34 citation statements)

References 30 publications

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“…More recent studies have collected data to complement existing monitoring efforts (i.e., or have been operating as a sub network within a larger national network). These were in many cases associated with human health (Rogulski, 2018) or climate impacts (Shusterman et al, 2018;Šećerov et al, 2019) or had direct economic implications, for example through flooding (Horita et al, 2015) or fishing livelihoods (Wada et al, 2007). It should be noted that very few studies embraced the principles of open science and open data more generally (however see Rettig et al, 2014;Jones et al, 2015).…”

Section: Resultsmentioning

confidence: 99%

Low-Cost Environmental Sensor Networks: Recent Advances and Future Directions

et al. 2019

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The use of low-cost sensor networks (LCSNs) is becoming increasingly popular in the environmental sciences and the unprecedented monitoring data generated enable research across a wide spectrum of disciplines and applications. However, in particular, non-technical challenges still hinder the broader development and application of LCSNs. This paper reviews the development of LCSNs over the last 15 years, highlighting trends and future opportunities for a diverse range of environmental applications. We found air quality, meteorological and water-related networks were particularly well represented with few studies focusing on sensor networks for ecological systems. Furthermore, we identified bias toward studies that have direct links to human health, safety and livelihoods. These studies were more likely to involve downstream data analytics, visualizations, and multi-stakeholder participation through citizen science initiatives. However, there was a paucity of studies that considered sustainability factors for the development and implementation of LCSNs. Existing LCSNs are largely focused on detecting and mitigating events which have a direct impact on humans such as flooding, air pollution or geo-hazards, while these applications are important there is a need for future development of LCSNs for monitoring ecosystem structure and function. Our findings highlight three distinct opportunities for future research to unleash the full potential of LCSNs: (1) improvement of links between data collection and downstream activities; (2) the potential to broaden the scope of application systems and fields; and (3) to better integrate stakeholder engagement and sustainable operation to enable longer and greater societal impacts.

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Section: Resultsmentioning

confidence: 99%

Low-Cost Environmental Sensor Networks: Recent Advances and Future Directions

et al. 2019

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“…Low-cost technology has also been adopted in GHG research. Studies have utilized low-cost sensors to monitor atmospheric concentrations of CO2 (Shusterman et al, 2018) and CH4 (Riddick et al, 2020;Collier-Oxandale et al, 2018;Eugster et al, 2012) and to measure CO2 fluxes with chambers (Bastviken et al, 2020 and2015;Brändle and Kunert, 2019;Martinsen et al, 2018). Some studies have also demonstrated how to build low-cost gas sampling and analysis instruments (Carbone et al, 2019;Martinsen et al, 2018;Bastviken et al, 2015).…”

Section: Greenhouse Gas Fluxmentioning

confidence: 99%

Reviews and syntheses: Enhancing research and monitoring of land-to-atmosphere greenhouse gases exchange in developing countries

Kim

Bond‐Lamberty

Ryu

et al. 2021

Preprint

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Abstract. Greenhouse gas (GHG) research has traditionally required data collection and analysis using advanced and often expensive instruments, complex and proprietary software, and skilled technicians. Partly as a result, relatively little GHG research has been conducted in resource-constrained developing countries and a critical data gap exists in these regions. At the same time, these are the same countries and regions in which climate-change impacts will likely be strongest, and in which major science uncertainties are centered, given the importance of dryland and tropical systems to the global carbon cycle and climate. Increasingly, scientific communities have adopted appropriate technology and approach (AT&A) for GHG research, including low-cost and low-technology instruments, open source software and data, and participatory and networking-based research approaches. Adopting AT&A can mean acquiring data with fewer technical constraints and lower economic burden, and is thus a strategy for enhancing GHG research in developing countries. However, AT&A can be characterized by higher uncertainties; these can often be mitigated by carefully designing experimental set-up, providing clear protocols for data collection, and monitoring and validating the quality of obtained data. For implementing this approach in GHG research of developing countries, first, it is necessary to recognize the scientific and moral importance of AT&A. At the same time, new AT&A techniques should be identified and further developed. Finally, these processes should be promoted through training local staff and encouraged for wide use and further innovation in developing countries.

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“…The feasibility of deploying dense monitoring networks has increased with the availability of inexpensive sensors, although questions about sensor accuracy continue to be studied (e.g., Borrego et al, 2016;Castell et al, 2017;Li and Biswas, 2017;Schneider et al, 2017;Lim et al, 2019). Approaches that combine mobile monitoring with measurements made at stationary monitoring locations (Adams et al, 2012;Simon et al, 2018) or with modeling (Messier et al, 2018) are being actively researched.…”

Section: Introductionmentioning

confidence: 99%

Mobile-platform measurement of air pollutant concentrations in California: performance assessment, statistical methods for evaluating spatial variations, and spatial representativeness

Solomon

Vallano

Lunden³

et al. 2020

Atmos. Meas. Tech.

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Abstract. Mobile-platform measurements provide new opportunities for characterizing spatial variations in air pollution within urban areas, identifying emission sources, and enhancing knowledge of atmospheric processes. The Aclima, Inc., mobile measurement and data acquisition platform was used to equip four Google Street View cars with research-grade instruments, two of which were available for the duration of this study. On-road measurements of air quality were made during a series of sampling campaigns between May 2016 and September 2017 at high (i.e., 1 s) temporal and spatial resolution at several California locations: Los Angeles, San Francisco, and the northern San Joaquin Valley (including nonurban roads and the cities of Tracy, Stockton, Manteca, Merced, Modesto, and Turlock). The results demonstrate that the approach is effective for quantifying spatial variations in air pollutant concentrations over measurement periods as short as 2 weeks. Measurement accuracy and precision are evaluated using results of weekly performance checks and periodic audits conducted through the sampler inlets, which show that research instruments located within stationary vehicles are capable of reliably measuring nitric oxide (NO), nitrogen dioxide (NO2), ozone (O3), methane (CH4), black carbon (BC), and particle number (PN) concentration, with bias and precision ranging from < 10 % for gases to < 25 % for BC and PN at 1 s time resolution. The quality of the mobile measurements in the ambient environment is examined by comparisons with data from an adjacent (< 9 m) stationary regulatory air quality monitoring site and by paired collocated vehicle comparisons, both stationary and driving. The mobile measurements indicate that United States Environmental Protection Agency (US EPA) classifications of two Los Angeles stationary regulatory monitors' scales of representation are appropriate. Paired time-synchronous mobile measurements are used to characterize the spatial scales of concentration variations when vehicles were separated by < 1 to 10 km. A data analysis approach is developed to characterize spatial variations while limiting the confounding influence of diurnal variability. The approach is illustrated using data from San Francisco, revealing 1 km scale differences in mean NO2 and O3 concentrations up to 117 % and 46 %, respectively, of mean values during a 2-week sampling period. In San Francisco and Los Angeles, spatial variations up to factors of 6 to 8 occur at sampling scales of 100–300 m, corresponding to 1 min averages.

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Observing local CO<sub>2</sub> sources using low-cost, near-surface urban monitors

Cited by 31 publications

References 30 publications

Low-Cost Environmental Sensor Networks: Recent Advances and Future Directions

Low-Cost Environmental Sensor Networks: Recent Advances and Future Directions

Reviews and syntheses: Enhancing research and monitoring of land-to-atmosphere greenhouse gases exchange in developing countries

Mobile-platform measurement of air pollutant concentrations in California: performance assessment, statistical methods for evaluating spatial variations, and spatial representativeness

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