Mobile Measurements of Carbonaceous Aerosol in Microenvironments to Discern Contributions from Traffic and Solid Fuel Burning

Xiang, Sheng; Zhang, Shaojun; Wang, Hui; Wen, Yifan; Yu, Yu‐Ting; Li, Zhenhua; Wallington, Timothy J.; Shen, Wei; Deng, Ye; Tan, Qinwen; Zhou, Zhi-Yuan

doi:10.1021/acs.estlett.1c00657

Cited by 8 publications

(8 citation statements)

References 30 publications

(65 reference statements)

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“…Bicycles are the primary measurement platform the Smart-P was designed for [ 20 , 72 ]. To improve environmental quality and to promote healthy living, cities across the world are increasingly using bicycles as an eco-friendly, alternative mode of transportation, and motor vehicles remain an important contributor to pollutant emissions in many cities globally [ 73 ].…”

Section: Discussionmentioning

confidence: 99%

“…Mobile monitoring platforms, such as those based on cars and bicycles, can further improve the spatial and temporal resolution of PM 2.5 monitoring by providing real-time snapshots of PM 2.5 concentration profiles along chosen paths. Some mobile systems consist of research-grade monitors mounted in special vehicle-based laboratories [ 7 , 20 , 21 , 22 , 23 ]. Others are based on commercial, portable monitors mounted on bicycles [ 24 , 25 , 26 , 27 , 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

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Development and Performance Evaluation of a Low-Cost Portable PM2.5 Monitor for Mobile Deployment

Chen

Yuan

Cao

et al. 2022

Sensors

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The concentration of fine particulate matter (PM2.5) is known to vary spatially across a city landscape. Current networks of regulatory air quality monitoring are too sparse to capture these intra-city variations. In this study, we developed a low-cost (60 USD) portable PM2.5 monitor called Smart-P, for use on bicycles, with the goal of mapping street-level variations in PM2.5 concentration. The Smart-P is compact in size (85 × 85 × 42 mm) and light in weight (147 g). Data communication and geolocation are achieved with the cyclist’s smartphone with the help of a user-friendly app. Good agreement was observed between the Smart-P monitors and a regulatory-grade monitor (mean bias error: −3.0 to 1.5 μg m−3 for the four monitors tested) in ambient conditions with relative humidity ranging from 38 to 100%. Monitor performance decreased in humidity > 70% condition. The measurement precision, represented as coefficient of variation, was 6 to 9% in stationary mode and 6% in biking mode across the four tested monitors. Street tests in a city with low background PM2.5 concentrations (8 to 9 μg m−3) and in two cities with high background concentrations (41 to 74 μg m−3) showed that the Smart-P was capable of observing local emission hotspots and that its measurement was not sensitive to bicycle speed. The low-cost and user-friendly nature are two features that make the Smart-P a good choice for empowering citizen scientists to participate in local air quality monitoring.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development and Performance Evaluation of a Low-Cost Portable PM2.5 Monitor for Mobile Deployment

Chen

Yuan

Cao

et al. 2022

Sensors

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“…Field measurements were conducted in Chengdu, a megacity in southwest China. The study was part of the Chengdu Air Pollution Evaluation (CAPE) project . In CAPE, high-resolution (1 Hz) measurements of NO, NO x , BC, PN, PM 2.5 , and CO 2 concentrations were conducted with a mobile platform (gasoline-powered Buick GL8) equipped with a Global Positioning System (GPS) to record speed and geolocation at a 1 s resolution.…”

Section: Methodsmentioning

confidence: 99%

“…Measurements were divided into four on-road microenvironment categories: diesel plume, urban freeway, rural freeway, and urban street. Definitions of each category are discussed in detail elsewhere . In short, the diesel plume microenvironment was defined as measurements from plume-chasing a heavy-duty diesel vehicle (HDDV) within a 30 m distance (equivalent to 1.5 s residence time) on urban and rural freeways .…”

Section: Methodsmentioning

confidence: 99%

Variability of NO₂/NO_x Ratios in Multiple Microenvironments from On-Road and Near-Roadway Measurements

et al. 2022

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An understanding of the spatial distribution of nitrogen dioxide (NO2) in cities is required to improve health impact assessments for NO2 exposure. In this study, 32 702 5 s averaged on-road measurements and 125 hourly near-roadway measurements were used to evaluate the variability of NO2 and nitrogen oxide (NO x ) concentrations in multiple microenvironments during two sampling campaigns (nonholiday and holiday). Microenvironments impacted by heavy-duty diesel vehicles (HDDVs) had large variations in NO2/NO x ratios due to the holiday effect. There was a strong linear relationship between NO2/NO x ratios and ambient background O3 in on-road and near-roadway microenvironments. The slopes of the regression lines (Δ(NO2/NOx)/ΔO3) provide estimations of the change rate of NO2/NO x ratios with respect to ambient background O3. Variable slopes occurred in on-road but not for near-roadway microenvironments. This is evidence that the change rate of on-road NO2/NO x ratios is strongly affected by vehicle fleet composition (i.e., HDDV%), while the near-roadway NO2/NO x ratios are more influenced by the atmospheric turbulence. The findings indicate that HDDVs could be a valid indicator of variability in NO2/NO x ratios concerning ambient background O3 and the effect of HDDVs should be embedded into dispersion models for better prediction of NO2 concentrations in traffic-related environments.

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“…It is known that the interaction of emission sources and atmospheric transport results in significant variations in PM 2.5 concentrations. − Thus, the ability of regulatory monitoring networks to provide adequate spatial resolution is questionable. To aid in this limitation of regulatory monitoring networks, mobile monitoring has been increasingly employed to characterize hyper-localized air pollutant concentrations − and to evaluate the performance of regulatory monitoring networks. − The results from these studies indicate that the intracity spatial variability of air pollution could be significant, and the spatial representativeness of regulatory monitoring networks is limited. However, most of the mobile monitoring campaigns were conducted using a limited number (one or two) of vehicles driving in the city. , Therefore, these measurements can only measure at a single location at a time that leads to temporal sampling error.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of City-Scale Disparities in PM_2.5 Exposure Using Hyper-Localized Taxi-Based Mobile Monitoring

Xiang

Zhang³

et al. 2022

Environ. Sci. Technol.

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Efforts have been directed to pollution control of fine particles (PM 2.5 ) because exposure to PM 2.5 could result in adverse health effects. However, PM 2.5 exposure disparities persisted even with largely declined concentrations. Here, we applied taxi-based measurements to characterize hyper-localized PM 2.5 exposures (30 m resolution) in Xi'an in December 2019 and July 2020. A big data set was derived from the taxi-based measurements (∼6 × 10 6 hourly PM 2.5 ) and was used to evaluate the performance of existing regulatory measurements in urban and rural regions. Results from regulatory measurements tend to alleviate PM 2.5 exposure disparities compared with taxi-based measurements. The taxi-based measurements reported higher population-weighted average (PWA) exposure in December 2019 (90 μg/m 3 ) and July 2020 (27 μg/ m 3 ) compared to regulatory measurements (76 and 24 μg/m 3 in December and July, respectively) with a wider range of relative disparities. Results indicate that the urban region would be overrepresented by regulatory measurements, where regulatory measurements reported that 60.0−84.7% of inhabitants were exposed to PM 2.5 higher than PWA, while taxi-based ones reported a smaller portion (22.6−35.2%). Significant seasonal variability in PM 2.5 exposure levels was found by taxi-based measurements but not regulatory measurements. The results highlight the need for providing complementary measurements (e.g., low-cost) for exposure assessment because the rural regions could be disproportionately exposed and overlooked by existing regulatory measurements.

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Mobile Measurements of Carbonaceous Aerosol in Microenvironments to Discern Contributions from Traffic and Solid Fuel Burning

Cited by 8 publications

References 30 publications

Development and Performance Evaluation of a Low-Cost Portable PM2.5 Monitor for Mobile Deployment

Development and Performance Evaluation of a Low-Cost Portable PM2.5 Monitor for Mobile Deployment

Variability of NO₂/NO_x Ratios in Multiple Microenvironments from On-Road and Near-Roadway Measurements

Evaluation of City-Scale Disparities in PM_2.5 Exposure Using Hyper-Localized Taxi-Based Mobile Monitoring

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Mobile Measurements of Carbonaceous Aerosol in Microenvironments to Discern Contributions from Traffic and Solid Fuel Burning

Cited by 8 publications

References 30 publications

Development and Performance Evaluation of a Low-Cost Portable PM2.5 Monitor for Mobile Deployment

Development and Performance Evaluation of a Low-Cost Portable PM2.5 Monitor for Mobile Deployment

Variability of NO2/NOx Ratios in Multiple Microenvironments from On-Road and Near-Roadway Measurements

Evaluation of City-Scale Disparities in PM2.5 Exposure Using Hyper-Localized Taxi-Based Mobile Monitoring

Contact Info

Product

Resources

About

Variability of NO₂/NO_x Ratios in Multiple Microenvironments from On-Road and Near-Roadway Measurements

Evaluation of City-Scale Disparities in PM_2.5 Exposure Using Hyper-Localized Taxi-Based Mobile Monitoring