Spatial calibration and PM2.5 mapping of low-cost air quality sensors

Chu, Hsin; Ali, Muhammad Zeeshan; He, Yu Chen

doi:10.1038/s41598-020-79064-w

Cited by 39 publications

(21 citation statements)

References 21 publications

(38 reference statements)

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“…We conducted our study in Taiwan, which has a tropical monsoon climate in the south and subtropical monsoon climate in the north and an annual average temperature of 22°C. 11 Participants were part of an ongoing open cohort, for which details have been described in our previous publications. [12][13][14] In brief, the MJ Health Management Institution has been providing residents of Taiwan with a standard medical screening program since 1994.…”

Section: Study Design and Settingmentioning

confidence: 99%

Effects of air pollution and habitual exercise on the risk of death: a longitudinal cohort study

Guo

Chang

et al. 2021

CMAJ

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Background: Exercise may exacerbate the adverse health effects of air pollution by increasing the inhalation of air pollutants. We investigated the combined effects of long-term exposure to fine particle matter (PM 2.5 ) and habitual exercise on deaths from natural causes in Taiwan. Methods:We recruited 384 130 adults (aged ≥ 18 yr) with 842 394 medical examination records between 2001 and 2016, and followed all participants until May 31, 2019. We obtained vital data from the National Death Registry of Taiwan. We estimated PM 2.5 exposure using a satellitebased spatiotemporal model, and collected information on exercise habits using a standard self-administered questionnaire. We analyzed the data using a Cox regression model with timedependent covariates.This article has been peer reviewed.

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Section: Study Design and Settingmentioning

confidence: 99%

Effects of air pollution and habitual exercise on the risk of death: a longitudinal cohort study

Guo

Chang

et al. 2021

CMAJ

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“…It is well known that low-cost PM sensors have various measurement issues and are not as reliable as official measuring equipment. PM sensors are influenced by, for instance, meteorological conditions, such as relative humidity [ 33 ]. Moreover, low-cost sensors might differ in their particle-size selectivity.…”

Section: Discussionmentioning

confidence: 99%

Assessment of PM2.5 Exposure during Cycle Trips in The Netherlands Using Low-Cost Sensors

Wesseling

Hendricx

Ruiter

et al. 2021

IJERPH

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Air pollution, especially fine particulate matter (PM2.5), is a major environmental risk factor for human health in Europe. Monitoring of air quality takes place using expensive reference stations. Low-cost sensors are a promising addition to this official monitoring network as they add spatial and temporal resolution at low cost. Moreover, low-cost sensors might allow for better characterization of personal exposure to PM2.5. In this study, we use 500 dust (PM2.5) sensors mounted on bicycles to estimate typical PM2.5 levels to which cyclists are exposed in the province of Utrecht, the Netherlands, in the year 2020. We use co-located sensors at reference stations to calibrate and validate the mobile sensor data. We estimate that the average exposure to traffic related PM2.5, on top of background concentrations, is approximately 2 μg/m3. Our results suggest that cyclists close to major roads have a small, but consistently higher exposure to PM2.5 compared to routes with less traffic. The results allow for a detailed spatial representation of PM2.5 concentrations and show that choosing a different cycle route might lead to a lower exposure to PM2.5. Finally, we conclude that the use of mobile, low-cost sensors is a promising method to estimate exposure to air pollution.

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“…Nonspatial downscaling cannot provide any information of drought condition because of heterogenous nature of these variables. However, the nonspatial approach, that is, global linear transformation, can lead to biased estimations of regression model parameters because of the spatial samples [32]. This spatial downscaling approach is a local linear transformation used to model spatially varying relationships.…”

Section: Performance Of Spatial and Nonspatial Downscalingmentioning

confidence: 99%

“…The approach is a remote-sensing-based downscaling with spatial-weighted calibration. The model is an effective calibration process for the spatio-temporal mapping and estimation [27,32]. Spatial uncertainty of SPI characteristics can be conducted by spatially varying parameters using spatial regression.…”

Section: Strength Of Time-varying Spatial Downscaling and Future Workmentioning

confidence: 99%

Time Varying Spatial Downscaling of Satellite-Based Drought Index

et al. 2021

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Drought monitoring is essential to detect the presence of drought, and the comprehensive change of drought conditions on a regional or global scale. This study used satellite precipitation data from the Tropical Rainfall Measuring Mission (TRMM), but refined the data for drought monitoring in Java, Indonesia. Firstly, drought analysis was conducted to establish the standardized precipitation index (SPI) of TRMM data for different durations. Time varying SPI spatial downscaling was conducted by selecting the environmental variables, normalized difference vegetation index (NDVI), and land surface temperature (LST) that were highly correlated with precipitation because meteorological drought was associated with vegetation and land drought. This study used time-dependent spatial regression to build the relation among original SPI, auxiliary variables, i.e., NDVI and LST. Results indicated that spatial downscaling was better than nonspatial downscaling (overall RMSEs: 0.25 and 0.46 in spatial and nonspatial downscaling). Spatial downscaling was more suitable for heterogeneous SPI, particularly in the transition time (R: 0.863 and 0.137 in June 2019 for spatial and nonspatial models). The fine resolution (1 km) SPI can be composed of the environmental data. The fine-resolution SPI captured a similar trend of the original SPI. Furthermore, the detailed SPI maps can be used to understand the spatio-temporal pattern of drought severity.

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Spatial calibration and PM2.5 mapping of low-cost air quality sensors

Cited by 39 publications

References 21 publications

Effects of air pollution and habitual exercise on the risk of death: a longitudinal cohort study

Effects of air pollution and habitual exercise on the risk of death: a longitudinal cohort study

Assessment of PM2.5 Exposure during Cycle Trips in The Netherlands Using Low-Cost Sensors

Time Varying Spatial Downscaling of Satellite-Based Drought Index

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