Mobile Measurement of Particulate Matter Concentrations on Urban Streets: System Development and Field Verification

Chiang, Yu-Lun; Wang, Jen-Cheng; Sun, Chih‐Hong; Wen, Tzai‐Hung; Juang, Jehn‐Yih; Jiang, Joe‐Air

doi:10.1109/access.2020.3034489

Cited by 6 publications

(3 citation statements)

References 37 publications

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“…This is greatly facilitated by the portability, ease to deploy, and low energy consumption of low-cost sensors, which offers great flexibility in the study design. Instrument miniaturization and cost reduction have allowed studies to comprehensively map air quality by deploying such devices on transport modes such as trash trucks, taxi fleets, and trams. ,, We notice a significant increase in studies carried out by bikes and persons, − which brings a unique opportunity to assess personal exposure at unprecedented temporal and spatial resolutions.…”

Section: Results and Discussionmentioning

confidence: 99%

Key Themes, Trends, and Drivers of Mobile Ambient Air Quality Monitoring: A Systematic Review and Meta-Analysis

Wang

Paul

deSouza

et al. 2023

Environ. Sci. Technol.

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Mobile ambient air quality monitoring is rapidly changing the current paradigm of air quality monitoring and growing as an important tool to address air quality and climate data gaps across the globe. This review seeks to provide a systematic understanding of the current landscape of advances and applications in this field. We observe a rapidly growing number of air quality studies employing mobile monitoring, with low-cost sensor usage drastically increasing in recent years. A prominent research gap was revealed, highlighting the double burden of severe air pollution and poor air quality monitoring in low- and middle-income regions. Experiment-design-wise, the advances in low-cost monitoring technology show great potential in bridging this gap while bringing unique opportunities for real-time personal exposure, large-scale deployment, and diversified monitoring strategies. The median value of unique observations at the same location in spatial regression studies is ten, which can be used as a rule-of-thumb for future experiment design. Data-analysis-wise, even though data mining techniques have been extensively employed in air quality analysis and modeling, future research can benefit from exploring air quality information from nontabular data, such as images and natural language.

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Section: Results and Discussionmentioning

confidence: 99%

Key Themes, Trends, and Drivers of Mobile Ambient Air Quality Monitoring: A Systematic Review and Meta-Analysis

Wang

Paul

deSouza

et al. 2023

Environ. Sci. Technol.

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“…Study [42] demonstrated the feasibility of high-resolution spatial and temporal analysis of particle concentrations in urban areas using mobile setups. Results comparable to fixed station network values, offering insights into PNC and particle concentration variability.…”

Section: Related Workmentioning

confidence: 96%

Advancements in Mobile-Based Air Pollution Detection: From Literature Review to Practical Implementation

Sladojevic,

Arsenovic,

Nikolic

et al. 2024

Journal of Sensors

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The aim of this paper is to investigate the effectiveness of combining mobile technologies and sensors to detect harmful particles in the air and address the problem of air pollution caused by traffic and exhaust emissions. The paper contains a systematic literature review of information technology research related to pollution detection in order to point out the main obstacles in the field and propose solutions. Furthermore, the paper presents the development of an Android smartphone-based real-time monitoring system that utilizes an external analog sensor board to acquire and evaluate physical measurements. The proposed system is calibrated for CO gas measurements, and it is compared with a commercial gas analyzer instrument. Results imply that the developed system is capable of detecting concentration levels in the air and that the accuracy is within the range of the industrial device’s accuracy.

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“…In addition, nitrogen dioxide is very harmful for human because it belongs to the second type of danger. According to statistic data, traffic pollution in large cities is from 70 to 90 percent among all pollution [6][7][8][9]. Therefore, monitoring of this substance is a very relevant topic [9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Modeling Based on the Analysis of Interval Data of Atmospheric Air Pollution Processes with Nitrogen Dioxide due to the Spread of Vehicle Exhaust Gases

et al. 2023

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The article deals with the issue of modeling taking into consideration nitrogen dioxide pollution of the atmospheric surface layer caused by vehicle exhaust gases. The interval data analysis methods were suggested. The method of identifying the mathematical model of the distribution of nitrogen dioxide as an atmospheric air pollutant based on the analysis of data with known measurement errors was proposed and grounded for the first time. The obtained mathematical model in the form of a difference equation is characterized by the guaranteed accuracy of forecasting nitrogen dioxide concentrations in a specified area of the city. It also adequately takes into account traffic changes which significantly reduces the costs of environmental control and monitoring. The proposed new model identification method is more effective in terms of computational time complexity compared to the known method and it is based on taking into account measurement errors which in the final case provides predictive properties of the model with guaranteed accuracy.

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Mobile Measurement of Particulate Matter Concentrations on Urban Streets: System Development and Field Verification

Abstract: The authors would like to thank the members of their research team for their valuable suggestions and contributions to this work.

Cited by 6 publications

References 37 publications

Key Themes, Trends, and Drivers of Mobile Ambient Air Quality Monitoring: A Systematic Review and Meta-Analysis

Key Themes, Trends, and Drivers of Mobile Ambient Air Quality Monitoring: A Systematic Review and Meta-Analysis

Advancements in Mobile-Based Air Pollution Detection: From Literature Review to Practical Implementation

Modeling Based on the Analysis of Interval Data of Atmospheric Air Pollution Processes with Nitrogen Dioxide due to the Spread of Vehicle Exhaust Gases

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