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Related papers: Pollution State Modeling for Mexico City

200 papers

This paper presents an approach to estimating the health effects of an environmental hazard. The approach is general in nature, but is applied here to the case of air pollution. It uses a computer model involving ambient pollution and…

Applications · Statistics 2007-11-01 Gavin Shaddick , Duncan Lee , James V. Zidek , Ruth Salway

Capturing the potentially strong dependence among the peak concentrations of multiple air pollutants across a spatial region is crucial for assessing the related public health risks. In order to investigate the multivariate spatial…

Applications · Statistics 2018-04-13 Sabrina Vettori , Raphaël Huser , Marc G. Genton

The sustainability of urban environments is an increasingly relevant problem. Air pollution plays a key role in the degradation of the environment as well as the health of the citizens exposed to it. In this chapter we provide a review of…

Machine Learning · Computer Science 2022-01-03 Pablo Torres , Beril Sirmacek , Sergio Hoyas , Ricardo Vinuesa

Monitoring urban air quality with high spatiotemporal resolution continues to pose significant challenges. We investigate the use of taxi fleets as mobile sensing platforms, analyzing over 100 million PM2.5 readings from more than 3,000…

Cost-effective sensors are capable of real-time capturing a variety of air quality-related modalities from different pollutant concentrations to indoor/outdoor humidity and temperature. Machine learning (ML) models are capable of performing…

Machine Learning · Computer Science 2023-08-04 Ahmad Mohammadshirazi , Aida Nadafian , Amin Karimi Monsefi , Mohammad H. Rafiei , Rajiv Ramnath

High air pollution levels are associated with school absences. However, low level pollution impact on individual school absences are under-studied. We modelled PM2.5 and ozone concentrations at 36 schools from July 2015 to June 2018 using…

Air pollution remains one of the most pressing environmental challenges of the modern era, significantly impacting human health, ecosystems, and climate. While traditional air quality monitoring systems provide critical data, their high…

Machine Learning · Computer Science 2025-03-17 Elie Azeraf , Audrey Wagner , Emilie Bialic , Samia Mellah , Ludovic Lelandais

Accurate air quality index (AQI) forecasting is essential for the protecting public health in rapidly growing urban regions, and the practical model evaluation and selection are often challenged by the lack of rigorous, region-specific…

Machine Learning · Computer Science 2026-03-30 Khawja Imran Masud , Venkata Sai Rahul Unnam , Sahara Ali

A typical problem in air pollution epidemiology is exposure assessment for individuals for which health data are available. Due to the sparsity of monitoring sites and the limited temporal frequency with which measurements of air pollutants…

This paper presents an engine able to forecast jointly the concentrations of the main pollutants harming people's health: nitrogen dioxyde (NO2), ozone (O3) and particulate matter (PM2.5 and PM10, which are respectively the particles whose…

Machine Learning · Computer Science 2020-06-17 Antoine Alléon , Grégoire Jauvion , Boris Quennehen , David Lissmyr

Remote sensing analysts continuously monitor the amount of pollutants in the atmosphere. They are usually performed via satellite images. However, these images suffer from low temporal and low spatial resolution. Therefore, observations…

Signal Processing · Electrical Eng. & Systems 2021-11-10 Nicholas Danesi , Mayank Jain , Yee Hui Lee , Soumyabrata Dev

The COVID-19 related lockdown measures offer a unique opportunity to understand how changes in economic activity and traffic affect ambient air quality and how much pollution reduction potential can the society offer through digitalization…

Machine Learning · Computer Science 2021-03-29 Johanna Einsiedler , Yun Cheng , Franz Papst , Olga Saukh

Air pollution, a pressing global problem, threatens public health, environmental sustainability, and climate stability. Achieving accurate and scalable forecasting across spatially distributed monitoring stations is challenging due to…

Machine Learning · Computer Science 2025-09-26 Junxin Lu , Shiliang Sun

Predicting the occurrence, level and duration of high air pollution concentrations exceeding a given critical level enables researchers to study the health impact of road traffic on local air quality and to inform public policy action.…

Applications · Statistics 2017-05-30 János Gyarmati-Szabó , Leonid V. Bogachev , Haibo Chen

This paper presents an engine able to predict jointly the real-time concentration of the main pollutants harming people's health: nitrogen dioxyde (NO2), ozone (O3) and particulate matter (PM2.5 and PM10, which are respectively the…

Machine Learning · Computer Science 2020-02-25 Grégoire Jauvion , Thibaut Cassard , Boris Quennehen , David Lissmyr

The substantial threat of concurrent air pollutants to public health is increasingly severe under climate change. To identify the common drivers and extent of spatio-temporal similarity of PM2.5 and ozone, this paper proposed a log…

Atmospheric and Oceanic Physics · Physics 2024-04-24 Jianan Pan , Kunyang He , Kai Wang , Qing Mu , Chengxiu Ling

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

The health effects of air pollution have been subject to intense study in recent decades. Exposure to pollutants such as airborne particulate matter and ozone has been associated with increases in morbidity and mortality, especially with…

Human-Computer Interaction · Computer Science 2019-07-25 Nitish Nag , Vaibhav Pandey , Likhita Navali , Prateek Mohan , Ramesh Jain

Mobile and ubiquitous sensing of urban air quality has received increased attention as an economically and operationally viable means to survey atmospheric environment with high spatial-temporal resolution. This paper proposes a machine…

Machine Learning · Computer Science 2020-03-03 Jun Song , Ke Han

In this paper, a useful reinterpretation of the city as a porous medium justifies the application of well-known models on fluid dynamics to develop a multi-model study of urban air pollution due to traffic flow in a large city. Thus, to…

Numerical Analysis · Mathematics 2025-02-21 N. Garcia-Chan , L. J. Alvarez-Vazquez , A. Martinez , M. E. Vazquez-Mendez