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Related papers: Superstatistical approach to air pollution statist…

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We consider the problem of real-time reconstruction of urban air pollution maps. The task is challenging due to the heterogeneous sources of available data, the scarcity of direct measurements, the presence of noise, and the large surfaces…

Machine Learning · Computer Science 2024-02-06 Matthieu Dolbeault , Olga Mula , Agustín Somacal

Air pollution is a chronic problem in large cities worldwide and awareness is rising as the long-term health implications become clearer. Vehicular traffic has been identified as a major contributor to poor air quality. In a lot of cities…

Air pollution constitutes the highest environmental risk factor in relation to heath. In order to provide the evidence required for health impact analyses, to inform policy and to develop potential mitigation strategies comprehensive…

Applications · Statistics 2021-08-23 Matthew L. Thomas , Gavin Shaddick , Daniel Simpson , Kees de Hoogh , James V. Zidek

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

Superstatistics is a general method from nonequilibrium statistical physics which has been applied to a variety of complex systems, ranging from hydrodynamic turbulence to traffic delays and air pollution dynamics. Here, we investigate…

Atmospheric and Oceanic Physics · Physics 2024-08-12 Benjamin Schäfer , Catherine M. Heppell , Hefin Rhys , Christian Beck

Atmospheric modeling has recently experienced a surge with the advent of deep learning. Most of these models, however, predict concentrations of pollutants following a data-driven approach in which the physical laws that govern their…

Applications · Statistics 2021-07-08 Javier Rubio-Herrero , Carlos Ortiz Marrero , Wai-Tong Louis Fan

Recent studies have shown associations between redlining policies (1935-1974) and present-day fine particulate matter (PM$_{2.5}$) and nitrogen dioxide (NO$_2$) air pollution concentrations. In this paper, we reevaluate these associations…

Applications · Statistics 2025-03-17 Xiaodan Zhou , Shu Yang , Brian J Reich

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

Air pollution remains one of the most formidable environmental threats to human health globally, particularly in urban areas, contributing to nearly 7 million premature deaths annually. Megacities, defined as cities with populations…

Machine Learning · Computer Science 2024-07-17 Harun Khan , Joseph Tso , Nathan Nguyen , Nivaan Kaushal , Ansh Malhotra , Nayel Rehman

Urban air quality is a major concern today. Concentrations of pollutants, such as nitrogen dioxide, must be monitored to ensure that they do not exceed hazardous thresholds. For this reason, scarse reference stations, which are generally…

Applications · Statistics 2026-03-30 Emma Thulliez , Camille Coron

We propose a new approach to estimate the causal effects of maritime traffic when natural or policy experiments are not available. We apply this method to the case of Marseille, a large Mediterranean port city, where air pollution emitted…

Applications · Statistics 2022-08-09 Léo Zabrocki , Marion Leroutier , Marie-Abèle Bind

Air quality monitoring requires to produce accurate estimation of nitrogen dioxide or fine particulate matter concentration maps, at different moments. A typical strategy is to combine different types of data. On the one hand, concentration…

Applications · Statistics 2025-02-13 Benjamin Auder , Camille Coron , Jean-Michel Poggi , Emma Thulliez

Phenomena such as air pollution levels are of greatest interest when observations are large, but standard prediction methods are not specifically designed for large observations. We propose a method, rooted in extreme value theory, which…

Applications · Statistics 2013-01-09 Daniel Cooley , Richard A. Davis , Philippe Naveau

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

Air pollution is one of the leading causes of mortality globally, resulting in millions of deaths each year. Efficient monitoring is important to measure exposure and enforce legal limits. New low-cost sensors can be deployed in greater…

Machine Learning · Computer Science 2024-04-22 Sigrid Passano Hellan , Christopher G. Lucas , Nigel H. Goddard

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

A spatiotemporal calibration and resolution refinement model was fitted to calibrate nitrogen dioxide (NO$_2$) concentration estimates from the Community Multiscale Air Quality (CMAQ) model, using two sources of observed data on NO$_2$ that…

Air pollution poses a serious threat to sustainable environmental conditions in the 21st century. Its importance in determining the health and living standards in urban settings is only expected to increase with time. Various factors…

Machine Learning · Computer Science 2022-06-16 Mayukh Bhattacharyya , Sayan Nag , Udita Ghosh

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

Nitrogen dioxide (NO2) is one of the most important atmospheric pollutants. However, current ground-level NO2 concentration data are lack of either high-resolution coverage or full coverage national wide, due to the poor quality of source…

Atmospheric and Oceanic Physics · Physics 2022-07-20 Xinyu Dou , Cuijuan Liao , Hengqi Wang , Ying Huang , Ying Tu , Xiaomeng Huang , Yiran Peng , Biqing Zhu , Jianguang Tan , Zhu Deng , Nana Wu , Taochun Sun , Piyu Ke , Zhu Liu