Development of urban air monitoring with high spatial resolution using mobile vehicle sensors

Yeom, Kiwon

doi:10.1007/s10661-021-09139-2

Cited by 15 publications

(4 citation statements)

References 36 publications

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“…Environmental stressors such as heat, noise, and air pollution are highly contextually distributed in space and time. Studies show that stationary measurements determine representative concentrations for the location of the measurement and its immediate vicinity (Yeom, 2021;Adams and Kanaroglou, 2016). In contrast, the distribution and concentration of stressors can be recorded in a large geographical area with the help of mobile sensors (Guillaume et al, 2019).…”

Section: Mobile Sensor Setmentioning

confidence: 99%

A game engine based application for visualising and analysing environmental spatiotemporal mobile sensor data in an urban context

Helbig

Becker

Masson

et al. 2022

Front. Environ. Sci.

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Climate change and the high proportion of private motorised transport leads to a high exposure of the urban population to environmental stressors such as particulate matter, nitrogen oxides, noise, and heat. The few fixed measuring stations for these stressors do not provide information on how they are distributed throughout the urban area and what influence the local urban structure has on hot and cold spots of pollution. In the measurement campaign “UmweltTracker” with 95 participants (cyclists, pedestrians), data on the stressors were collected via mobile sensors. The aim was to design and implement an application to analyse the heterogeneous data sets. In this paper we present a prototype of a visualisation and analysis application based on the Unity Game Engine, which allowed us to explore and analyse the collected data sets and to present them on a PC as well as in a VR environment. With the application we were able to show the influence of local urban structures as well as the impact of the time of day on the measured values. With the help of the application, outliers could be identified and the underlying causes could be investigated. The application was used in analysis sessions as well as a workshop with stakeholders.

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Section: Mobile Sensor Setmentioning

confidence: 99%

A game engine based application for visualising and analysing environmental spatiotemporal mobile sensor data in an urban context

Helbig

Becker

Masson

et al. 2022

Front. Environ. Sci.

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“…Analysis of long-term exposure to particulate matter at an individual level is challenging, but short-term wearable personal mobile monitors can be used. Sensors that constantly monitor particulate matter exposure such as mobile vehicle sensors are gaining popularity in studies done in busy cities [22,23]. There is need to harness data from such technologies but might not be immediately possible in low resource setting with high particulate matter air pollution.…”

Section: Particulate Matter and Gastric Cancer Riskmentioning

confidence: 99%

Environmental factors associated with gastric carcinogenesis

Kayamba

Kelly

2021

Current Opinion in Gastroenterology

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Purpose of reviewGastric cancer is one of the leading causes of cancer-related deaths globally. Several modifiable environmental factors have been linked to gastric carcinogenesis but in many cases, evidence is either weak or fragmented. In this review, we interrogate the latest evidence implicating environmental factors in the development of gastric cancer. Recent findingsWe are writing this review at a time when technological advancements are enabling scientists to effectively conduct large epidemiological studies with better tools for exposure estimations. We have highlighted risk factors that do not yet have enough evidence to be included as definite carcinogens in the International Agency for Research on Cancer monographs but have the potential for inclusion in the near future. Considered in our review are the links between gastric cancer and exposure to biomass smoke, particulate matter, occupational hazards and water contamination.

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“…Also this study highlights high variability of aerosol exposure along inner urban streets but the study was not laid out for spatial interpolation or modeling. Motor vehicles were used for high resolution recording of aerosol pollution in urban areas as well (Yeom, 2021;Zhao et al, 2021;Khuzestani et al, 2022). In contrast to walking and bicycle studies, the velocity of cars and their range focus on larger areas.…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal dynamics of aerosol distribution in an urban environment recorded in situ by means of a bike based monitoring system

Norra

Song²,

Gebhardt³

et al. 2023

Front. Environ. Sci.

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Aerosol pollution in urban areas is highly variable due to numerous single emission sources such as automobiles, industrial and commercial activities as well as domestic heating, but also due to complex building structures redirecting air mass flows, producing leeward and windward turbulences and resuspension effects. In this publication, it is shown that one or even few aerosol monitoring sites are not able to reflect these complex patterns. In summer 2019, aerosol pollution was recorded in high spatial resolution during six night and daytime tours with a mobile sensor platform on a trailer pulled by a bicycle. Particle mass loadings showed a high variability with PM10 values ranging from 1.3 to 221 μg m−3 and PM2.5 values from 0.7 to 69.0 μg m−3. Geostatistics were used to calculate respective models of the spatial distributions of PM2.5 and PM10. The resulting maps depict the variability of aerosol concentrations within the urban space. These spatial distribution models delineate the distributions without cutting out the built-up structures. Elsewise, the overall spatial patterns do not become visible because of being sharply interrupted by those cutouts in the resulting maps. Thus, the spatial maps allow to identify most affected urban areas and are not restricted to the street space. Furthermore, this method provides an insight to potentially affected areas, and thus can be used to develop counter measures. It is evident that the spatial aerosol patterns cannot be directly derived from the main wind direction, but result far more from an interplay between main wind direction, built-up patterns and distribution of pollution sources. Not all pollution sources are directly obvious and more research has to be carried out to explain the micro-scale variations of spatial aerosol distribution patterns. In addition, since aerosol load in the atmosphere is a severe issue for health and wellbeing of city residents more attention has to be paid to these local inhomogeneities.

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Development of urban air monitoring with high spatial resolution using mobile vehicle sensors

Cited by 15 publications

References 36 publications

A game engine based application for visualising and analysing environmental spatiotemporal mobile sensor data in an urban context

A game engine based application for visualising and analysing environmental spatiotemporal mobile sensor data in an urban context

Environmental factors associated with gastric carcinogenesis

Spatio-temporal dynamics of aerosol distribution in an urban environment recorded in situ by means of a bike based monitoring system

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