AiRe - A web-based R application for simple, accessible and repeatable analysis of urban air quality data. (April 2021)

• Record Type: Journal Article
• Authors: Díaz, Juan José; Mura, Ivan; Franco, Juan Felipe; Akhavan-Tabatabaei, Raha
• Is Part Of: Environmental modelling & software. Volume 138(2021)
• Publication Date: 2021-04
• Subjects: aiRe -- Air quality software -- Open source -- R -- Shiny web application; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2021.104976
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Recent technological advances in collecting data on emission sources, meteorological conditions and concentration of air pollutants in urban areas, offer invaluable opportunities for the better understanding of air quality problems. However, processing large sets of data to extract statistically valid evidence poses many challenges from both the conceptual and technical viewpoints. Air quality data acquisition, cleaning and authentication are necessary and crucial preliminary phases to support descriptive, predictive and prescriptive models and to ensure that aggregated and high-quality information is delivered to the central and local governments, decision makers and citizens. Automated software tools can facilitate drawing conclusions based on the information contained in the data, limiting subjective judgment and providing repeatability. However, the costly state-of-the-art software applications developed by major vendors are inaccessible to many cities and townships in the developing world. Moreover, their usage creates dependency on proprietary solutions, which can hinder the possibility of evolving the data processing and analysis protocols. We present an open-source web application for air quality data analysis and visualization, called aiRe, based on the R statistical framework and Shiny web package. aiRe has been developed in collaboration with the Colombian environmental authorities, and implements best practices validated by experts in air quality. We believe that the process of developing aiRe was extremely valuable with the ultimate purpose of supporting cities in air quality management, while strengthening local capabilities to improve urban air pollution. This open-access tool simplifies and makes air quality data analysis and visualization accessible, with the desirable effect of removing ownership costs, fostering appropriation by non-expert users and ultimately promoting informed decision-making for the general public and the local government authorities. We present the performance of this tool over a series of examples of open data collected by the air quality monitoring network of Bogotá, Colombia. Highlights: aiRe allows loading, cleaning and exploring air quality datasets. aiRe is Web-based and open-source, build with R and Shiny. aiRe was developed in close collaboration with environmental authorities. aiRe can be freely downloaded from an institutional repository. No specific expertise in data science is required for using aiRe.