A spatial multi-resolution multi-objective data-driven ensemble model for multi-step air quality index forecasting based on real-time decomposition

2021 ◽  
Vol 125 ◽  
pp. 103387
Author(s):  
Hui Liu ◽  
Rui Yang
2021 ◽  
Vol 1098 (4) ◽  
pp. 042090
Author(s):  
D Kurnia ◽  
F S Hadisantoso ◽  
A A Suprianto ◽  
E A Nugroho ◽  
J Janizal

Author(s):  
Hasan Tariq ◽  
Farid Touati

Environmental monitoring has gained significant importance in outdoor air quality measurement and assessment for fundamental survival as well as ambient assisted living. In real-time outdoor urban scale, instantaneous air quality index estimation, the electrochemical sensors warm-up time, cross-sensitivity computation-error, geo-location typography, instantaneous capacity or back up time; and energy efficiency are the six major challenges. These challenges lead to real-time gradient anomalies that effect the accuracy and pro-longed lags in air quality index mapping campaigns for state and environmental/meteorological agencies. In this work, a gradient-aware, multi-variable air quality-sensing node is proposed with event-triggered sensing based on position, gas magnitudes, and cross-sensitivity interpolation. In this approach, temperature, humidity, pressure, geo-position, photovoltaic power, volatile organic compounds, particulate matter (2.5), ozone, Carbon mono-oxide, Nitrogen dioxide, and Sulphur dioxide are the principle variables. Results have shown that the proposed system optimized the real-time air quality monitoring for the chosen geo-spatial cluster (Qatar University).


The surveys regarding air pollution shows that there has been a hasty growth due to the emission of fuels and exhaust gases from factories. The Air Quality Index (AQI) has been launched to note the contemporary status of the air quality. The intent of AQI is to aid every individual know how the regional air quality will make an impact on them. The Environmental Protection Agency assess the AQI for five major air pollutants namely Nitrogen dioxide (NO2), ground-level ozone (O3), particle pollution (PM10, PM2.5), carbon monoxide (CO), and sulphur dioxide (SO2). The intent of the project is to congregate real-time Air Quality Index from distinct monitoring stations across India, analysing the data and reporting on it. Collect the real-time data using the API key provided by Open Government Data (OGD) platform India. This is done by making use of Microsoft Business Intelligence (MSBI) and Power BI Tools to transform, analyse and visualize the data. This project can be utilized to develop various programs like Ozone today in Europe and in mobile applications which acts as an alert system that can protect people from air pollution.


2018 ◽  
Vol 5 (1) ◽  
pp. 186-198 ◽  
Author(s):  
Yuzhe Yang ◽  
Zijie Zheng ◽  
Kaigui Bian ◽  
Lingyang Song ◽  
Zhu Han

2015 ◽  
Vol 66 (2) ◽  
pp. 171-180
Author(s):  
Silvije Davila ◽  
Jadranka Pečar Ilić ◽  
Ivan Bešlić

Abstract This article presents a new, original application of modern information and communication technology to provide effective real-time dissemination of air quality information and related health risks to the general public. Our on-line subsystem for urban real-time air quality monitoring is a crucial component of a more comprehensive integrated information system, which has been developed by the Institute for Medical Research and Occupational Health. It relies on a StreamInsight data stream management system and service-oriented architecture to process data streamed from seven monitoring stations across Zagreb. Parameters that are monitored include gases (NO, NO2, CO, O3, H2S, SO2, benzene, NH3), particulate matter (PM10 and PM2.5), and meteorological data (wind speed and direction, temperature and pressure). Streamed data are processed in real-time using complex continuous queries. They first go through automated validation, then hourly air quality index is calculated for every station, and a report sent to the Croatian Environment Agency. If the parameter values exceed the corresponding regulation limits for three consecutive hours, the web service generates an alert for population groups at risk. Coupled with the Common Air Quality Index model, our web application brings air pollution information closer to the general population and raises awareness about environmental and health issues. Soon we intend to expand the service to a mobile application that is being developed.


2020 ◽  
Vol 15 (10) ◽  
pp. 1040a7
Author(s):  
Nico Schulte ◽  
Xiang Li ◽  
Jo Kay Ghosh ◽  
Philip M Fine ◽  
Scott A Epstein

Sign in / Sign up

Export Citation Format

Share Document