Integrating low-cost sensor monitoring, satellite mapping, and geospatial artificial intelligence for intra-urban air pollution predictions

Environmental Pollution, Journal Year: 2023, Volume and Issue: 331, P. 121832 - 121832

Published: May 18, 2023

There is a growing need to apply geospatial artificial intelligence analysis disparate environmental datasets find solutions that benefit frontline communities. One such critically needed solution the prediction of health-relevant ambient ground-level air pollution concentrations. However, many challenges exist surrounding size and representativeness limited ground reference stations for model development, reconciling multi-source data, interpretability deep learning models. This research addresses these by leveraging strategically deployed, extensive low-cost sensor (LCS) network was rigorously calibrated through an optimized neural network. A set raster predictors with varying data quality spatial scales retrieved processed, including gap-filled satellite aerosol optical depth products airborne LiDAR-derived 3D urban form. We developed multi-scale, attention-enhanced convolutional reconcile LCS measurements estimating daily PM2.5 concentration at 30-m resolution. employs advanced approach using geostatistical kriging method generate baseline pattern multi-scale residual identify both regional patterns localized events high-frequency feature retention. further used permutation tests quantify importance, which has rarely been done in DL applications science. Finally, we demonstrated one application investigating inequality issue across within various urbanization levels block group scale. Overall, this demonstrates potential AI provide actionable addressing critical issues.

Language: Английский

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Leveraging machine learning algorithms to advance low-cost air sensor calibration in stationary and mobile settings

Atmospheric Environment, Journal Year: 2023, Volume and Issue: 301, P. 119692 - 119692

Published: March 1, 2023

Language: Английский

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I believe I can fly… but in polluted air, why? Bird feathers as an example of environmental contaminant monitoring

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 972, P. 179033 - 179033

Published: March 14, 2025

Language: Английский

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CdO–ZnO nanorices for enhanced and selective formaldehyde gas sensing applications

Environmental Research, Journal Year: 2021, Volume and Issue: 200, P. 111377 - 111377

Published: May 28, 2021

Language: Английский

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Calibrating networks of low-cost air quality sensors

Atmospheric measurement techniques, Journal Year: 2022, Volume and Issue: 15(21), P. 6309 - 6328

Published: Nov. 2, 2022

Abstract. Ambient fine particulate matter (PM2.5) pollution is a major health risk. Networks of low-cost sensors (LCS) are increasingly being used to understand local-scale air variation. However, measurements from LCS have uncertainties that can act as potential barrier effective decision making. data thus need adequate calibration obtain good quality PM2.5 estimates. In order develop factors, one or more typically co-located with reference monitors for short long periods time. A model then developed characterizes the relationships between raw output and monitors. This transferred other in network. Calibration models tend be evaluated based on their performance only at co-location sites. It often implicitly assumed conditions relatively sparse sites representative network overall not overfitted Little work has explicitly how transferable rest an network, even after appropriate cross-validation. Further, few studies sensitivity key use cases, such hotspot detection, applied. Finally, there been dearth research duration (short-term long-term) impact these results. paper attempts fill gaps using dense Denver deployed through city's “Love My Air” program. offers series transferability metrics networks some suggestions which would most useful achieving different end goals.

Language: Английский

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Highly sensitive and selective gas sensors based on nanoporous CN monolayer for reusable detection of NO, H2S and NH3: A first-principles study

Applied Surface Science, Journal Year: 2022, Volume and Issue: 606, P. 154806 - 154806

Published: Sept. 7, 2022

Language: Английский

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Gaps and future directions in research on health effects of air pollution

EBioMedicine, Journal Year: 2023, Volume and Issue: 93, P. 104668 - 104668

Published: June 25, 2023

Despite progress in many countries, air pollution, and especially fine particulate matter pollution (PM2.5) remains a global health threat: over 6 million premature cardiovascular respiratory deaths/yr. have been attributed to household outdoor pollution. In this viewpoint, we identify present gaps monitoring regulation, how they could be strengthened future mitigation policies more optimally reduce impacts. We conclude that there is need move beyond simply regulating PM2.5 mass concentrations at central site stations. A greater emphasis needed on: new portable affordable technologies measure personal exposures particle mass; the consideration of submicron (PM1) quality standard; further evaluations effects by composition source. emphasize enable studies on exposure–health relationships underserved populations are disproportionately impacted but not sufficiently represented current studies.

Language: Английский

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Low‐cost air quality monitoring networks for long‐term field campaigns: A review

Meteorological Applications, Journal Year: 2023, Volume and Issue: 30(6)

Published: Nov. 1, 2023

Abstract The application of low‐cost air quality monitoring networks has substantially grown over the last few years, following technological advances in production cheap and portable pollution sensors, thus potentially greatly increasing limited spatial information on conditions provided by traditional stations. However, use sensors still presents many limitations, mostly related to reliability their measurements. Despite number papers focusing these issues, some challenges connected are poorly investigated understood, considering particular those long‐term applications integration within reference system. present review aims at filling this gap, analysing characteristics that were run across field campaigns, including geographical location, pollutants monitored, type stations employed, length campaign, with a attention assessing for deployment evaluation official networks. Moreover, critical analysis most insightful suggestions recommendations delivered literature, as well relevant is presented, highlighting open research areas outlining future challenges.

Language: Английский

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Standardizing methane emission monitoring: A global policy perspective for the oil and gas industry

Engineering Science & Technology Journal, Journal Year: 2024, Volume and Issue: 5(6), P. 2027 - 2038

Published: June 13, 2024

Methane emissions from the oil and gas industry are a major contributor to climate change due their high global warming potential. Accurate standardized monitoring of these is essential for effective mitigation. This review explores current state methane emission technologies, highlighting strengths limitations direct measurement, remote sensing, modeling approaches. It also examines diverse regulatory frameworks practices, identifying key challenges such as accuracy, consistency, economic barriers. The paper proposes strategies harmonizing standards globally, including adopting international guidelines, certification programs, centralized reporting platforms. Additionally, it advocates innovative approaches that incentivize better practices emphasizes need cooperation through data sharing capacity building. concludes by discussing potential impact on industry, outlining future research development directions, calling proactive steps all stakeholders achieve reduction. Keywords: Emissions, Oil Gas Industry, Monitoring Technologies Regulatory Frameworks.

Language: Английский

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Improving PM10 sensor accuracy in urban areas through calibration in Timișoara

npj Climate and Atmospheric Science, Journal Year: 2024, Volume and Issue: 7(1)

Published: Nov. 1, 2024

Low-cost particulate matter sensors (LCS) are vital for improving the spatial and temporal resolution of air quality data, supplementing sparsely placed official monitoring stations. Despite their benefits, LCS readings can be biased due to physical properties aerosol particles device limitations. An optimization model is essential enhance data accuracy. This paper presents a calibration study network Timișoara, Romania. The began by selecting devices near National Air Quality Monitoring Network (NAQMN) stations developing parametric models, choosing best broader application. Plantower, Sensirion, Honeywell showed comparable Calibration involved clusters within 750 m radius around NAQMN Models incorporating RH corrections multiple linear regression (MLR) were fitted. was validated against from unseen sensors, leading mean bias errors (MBE) 9-17% RMSEs 33-35%, sensor uncertainty margins. Applied city-wide network, identified several regularly exceeding EU daily PM10 threshold, unnoticed limited coverage. highlights necessity granular accurately capture urban variations.

Language: Английский

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