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Related papers: Comprehensive Monitoring of Air Pollution Hotspots…

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Low-cost mobile sensors can be used to collect PM$_{2.5}$ concentration data throughout an entire city. However, identifying air pollution hotspots from the data is challenging due to the uneven spatial sampling, temporal variations in the…

Air pollution is a major global environmental health threat, in particular for people who live or work near pollution sources. Areas adjacent to pollution sources often have high ambient pollution concentrations, and those areas are…

Machine Learning · Computer Science 2022-11-16 Yawen Zhang , Michael Hannigan , Qin Lv

Global ambient air pollution, a transboundary challenge, is typically addressed through interventions relying on data from spatially sparse and heterogeneously placed monitoring stations. These stations often encounter temporal data gaps…

Machine Learning · Computer Science 2024-02-19 Liam J Berrisford , Hugo Barbosa , Ronaldo Menezes

Ambient air pollution remains a critical issue in the United Kingdom, where data on air pollution concentrations form the foundation for interventions aimed at improving air quality. However, the current air pollution monitoring station…

Applications · Statistics 2024-01-18 Liam J Berrisford , Lucy S Neal , Helen J Buttery , Benjamin R Evans , Ronaldo Menezes

Air pollutant exposure exhibits significant spatial and temporal variability, with localized hotspots, particularly in traffic microenvironments, posing health risks to commuters. Although widely used for air quality assessment, fixed-site…

Signal Processing · Electrical Eng. & Systems 2025-06-04 Hui Zhong , Hongliang Lu , Ting Gan , Yonghong Liu , Xinhu Zheng

Constructing high resolution air pollution maps at lower cost is crucial for sustainable city management and public health risk assessment. However, traditional fixed-site monitoring lacks spatial coverage, while mobile low-cost sensors…

Machine Learning · Computer Science 2025-03-18 Rui Xu , Dawen Yao , Yuzhuang Pian , Ruhui Cao , Yixin Fu , Xinru Yang , Ting Gan , Yonghong Liu

Air pollution poses a serious threat to human health as well as economic development around the world. To meet the increasing demand for accurate predictions for air pollutions, we proposed a Deep Inferential Spatial-Temporal Network to…

Machine Learning · Computer Science 2018-09-12 Hao Wang , Bojin Zhuang , Yang Chen , Ni Li , Dongxia Wei

Air pollution poses a significant threat to public health and well-being, particularly in urban areas. This study introduces a series of machine-learning models that integrate data from the Sentinel-5P satellite, meteorological conditions,…

Machine Learning · Computer Science 2024-05-31 Giacomo Blanco , Luca Barco , Lorenzo Innocenti , Claudio Rossi

Urban pollution poses serious health risks, particularly in relation to traffic-related air pollution, which remains a major concern in many cities. Vehicle emissions contribute to respiratory and cardiovascular issues, especially for…

Machine Learning · Computer Science 2024-12-30 Sen Yan , David J. O'Connor , Xiaojun Wang , Noel E. O'Connor , Alan F. Smeaton , Mingming Liu

This paper addresses the critical environmental challenge of estimating ambient Nitrogen Dioxide (NO$_2$) concentrations, a key issue in public health and environmental policy. Existing methods for satellite-based air pollution estimation…

Computer Vision and Pattern Recognition · Computer Science 2025-04-25 Ruben Gonzalez Avilés , Linus Scheibenreif , Damian Borth

With their continued increase in coverage and quality, data collected from personal air quality monitors has become an increasingly valuable tool to complement existing public health monitoring systems over urban areas. However, the…

Applications · Statistics 2022-06-01 Matthew Bonas , Stefano Castruccio

Current air pollution monitoring systems are bulky and expensive resulting in a very sparse deployment. In addition, the data from these monitoring stations may not be easily accessible. This paper focuses on studying the dense deployment…

Signal Processing · Electrical Eng. & Systems 2020-05-13 C. Rajashekar Reddy , T. Mukku , A. Dwivedi , A. Rout , S. Chaudhari , K. Vemuri , K. S. Rajan , A. M. Hussain

The use of low-cost sensors in air quality monitoring networks is still a much-debated topic among practitioners: they are much cheaper than traditional air quality monitoring stations set up by public authorities (a few hundred dollars…

Signal Processing · Electrical Eng. & Systems 2020-06-23 Thibaut Cassard , Grégoire Jauvion , David Lissmyr

Considerable financial resources are allocated for measuring ambient air pollution in the United States, yet the locations for these monitoring sites may not be optimized to capture the full extent of current pollution variability. Prior…

Applications · Statistics 2022-02-18 Makoto M. Kelp , Samuel Lin , J. Nathan Kutz , Loretta J. Mickley

Real-time air pollution monitoring is a valuable tool for public health and environmental surveillance. In recent years, there has been a dramatic increase in air pollution forecasting and monitoring research using artificial neural…

Machine Learning · Computer Science 2022-11-11 Chen Lin , Safoora Yousefi , Elvis Kahoro , Payam Karisani , Donghai Liang , Jeremy Sarnat , Eugene Agichtein

Traffic congestion is one of the most notable problems arising in worldwide urban areas, importantly compromising human mobility and air quality. Current technologies to sense real-time data about cities, and its open distribution for…

Physics and Society · Physics 2016-12-30 Albert Solé-Ribalta , Sergio Gómez , Alex Arenas

Currently, fixed static sensing is a primary way to monitor environmental data like air quality in cities. However, to obtain a dense spatial coverage, a large number of static monitors are required, thereby making it a costly option. Dense…

Machine Learning · Computer Science 2022-01-25 Charul Paliwal , Pravesh Biyani

Air pollution, particularly particulate matter (PM2.5), poses significant risks to public health and the environment, necessitating accurate prediction and continuous monitoring for effective air quality management. However, air quality…

Machine Learning · Computer Science 2024-09-19 Yohan Choi , Boaz Choi , Jachin Choi

Air pollution is a major driver of climate change. Anthropogenic emissions from the burning of fossil fuels for transportation and power generation emit large amounts of problematic air pollutants, including Greenhouse Gases (GHGs). Despite…

Machine Learning · Computer Science 2021-09-01 Linus Scheibenreif , Michael Mommert , Damian Borth

The spread of PM2.5 pollutants that endanger health is difficult to predict because it involves many atmospheric variables. These micron particles can spread rapidly from their source to residential areas, increasing the risk of respiratory…

Machine Learning · Computer Science 2021-01-18 Hsing-Chung Chen , Karisma Trinanda Putra , Jerry Chun-WeiLin
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