Urban Air Pollution Mapping Using Fleet Vehicles as Mobile Monitors and Machine Learning

2021 ◽  
Vol 55 (8) ◽  
pp. 5579-5588
Author(s):  
Bu Zhao ◽  
Long Yu ◽  
Chunyan Wang ◽  
Chenyang Shuai ◽  
Ji Zhu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Air Pollution ◽  
Urban Air Pollution ◽  
Urban Air

scholarly journals Air Pollution Modelling by Machine Learning Methods

Modelling ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 659-674
Author(s):  
Petra Vidnerová ◽  
Roman Neruda
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Air Pollution ◽  
Deep Neural Networks ◽  
Urban Air Pollution ◽  
Pollution Monitoring ◽  
Urban Air ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Regularization Networks

Precise environmental modelling of pollutants distributions represents a key factor for addresing the issue of urban air pollution. Nowadays, urban air pollution monitoring is primarily carried out by employing sparse networks of spatially distributed fixed stations. The work in this paper aims at improving the situation by utilizing machine learning models to process the outputs of multi-sensor devices that are small, cheap, albeit less reliable, thus a massive urban deployment of those devices is possible. The main contribution of the paper is the design of a mathematical model providing sensor fusion to extract the information and transform it into the desired pollutant concentrations. Multi-sensor outputs are used as input information for a particular machine learning model trained to produce the CO, NO2, and NOx concentration estimates. Several state-of-the-art machine learning methods, including original algorithms proposed by the authors, are utilized in this study: kernel methods, regularization networks, regularization networks with composite kernels, and deep neural networks. All methods are augmented with a proper hyper-parameter search to achieve the optimal performance for each model. All the methods considered achieved vital results, deep neural networks exhibited the best generalization ability, and regularization networks with product kernels achieved the best fitting of the training set.

An Urban Air Pollution Early Warning System Based on PM2.5 Prediction Applied in Ploiesti City

2017 ◽  
Vol 68 (4) ◽  
pp. 858-863
Author(s):  
Mihaela Oprea ◽  
Marius Olteanu ◽  
Radu Teodor Ianache
Keyword(s):  
Air Pollution ◽  
Early Warning ◽  
Urban Areas ◽  
Early Warning System ◽  
Urban Air Pollution ◽  
Warning System ◽  
Air Pollutant ◽  
Pollution Level ◽  
Urban Air ◽  
Prediction Approach

Fine particulate matter with a diameter less than 2.5 �m (i.e. PM2.5) is an air pollutant of special concern for urban areas due to its potential significant negative effects on human health, especially on children and elderly people. In order to reduce these effects, new tools based on PM2.5 monitoring infrastructures tailored to specific urban regions are needed by the local and regional environmental management systems for the provision of an expert support to decision makers in air quality planning for cities and also, to inform in real time the vulnerable population when PM2.5 related air pollution episodes occur. The paper focuses on urban air pollution early warning based on PM2.5 prediction. It describes the methodology used, the prediction approach, and the experimental system developed under the ROKIDAIR project for the analysis of PM2.5 air pollution level, health impact assessment and early warning of sensitive people in the Ploiesti city. The PM2.5 concentration evolution prediction is correlated with PM2.5 air pollution and health effects analysis, and the final result is processed by the ROKIDAIR Early Warning System (EWS) and sent as a message to the affected population via email or SMS. ROKIDAIR EWS is included in the ROKIDAIR decision support system.

scholarly journals Urban Air Pollution May Enhance COVID-19 Case-Fatality and Mortality Rates in the United States

2020 ◽  
Vol 1 (3) ◽  
pp. 100047 ◽  
Author(s):  
Donghai Liang ◽  
Liuhua Shi ◽  
Jingxuan Zhao ◽  
Pengfei Liu ◽  
Jeremy A. Sarnat ◽  
...  
Keyword(s):  
United States ◽  
Air Pollution ◽  
Urban Air Pollution ◽  
Case Fatality ◽  
The United States ◽  
Mortality Rates ◽  
Urban Air

The impact of COVID-19 pandemic in Mediterranean urban air pollution and mobility

2021 ◽  
pp. 1-16
Author(s):  
Nikolaos Sifakis ◽  
Maria Aryblia ◽  
Tryfon Daras ◽  
Stavroula Tournaki ◽  
Theocharis Tsoutsos
Keyword(s):  
Air Pollution ◽  
Urban Air Pollution ◽  
Urban Air ◽  
The Impact

Intensive field campaigns as a means for improving scientific knowledge to address urban air pollution

2021 ◽  
Vol 246 ◽  
pp. 118094
Author(s):  
Erik Velasco ◽  
Armando Retama ◽  
Miguel Zavala ◽  
Marc Guevara ◽  
Bernhard Rappenglück ◽  
...  
Keyword(s):  
Air Pollution ◽  
Scientific Knowledge ◽  
Urban Air Pollution ◽  
Urban Air ◽  
Field Campaigns

scholarly journals Pleural anthracosis as an indicator of lifetime exposure to urban air pollution: An autopsy-based study in Sao Paulo

2019 ◽  
Vol 173 ◽  
pp. 23-32 ◽  
Author(s):  
Ana Paula Cremasco Takano ◽  
Lisie Tocci Justo ◽  
Nathalia Villa dos Santos ◽  
Mônica Valeria Marquezini ◽  
Paulo Afonso de André ◽  
...  
Keyword(s):  
Air Pollution ◽  
Urban Air Pollution ◽  
Sao Paulo ◽  
Urban Air ◽  
São Paulo ◽  
Lifetime Exposure
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