Commenced in January 2007
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Edition: International
Paper Count: 3

air quality index Related Publications

3 Multi-Level Air Quality Classification in China Using Information Gain and Support Vector Machine

Authors: Pei-Chann Chang, Bingchun Liu, Natasha Huang, Dun Li

Abstract:

Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: Machine Learning, support vector machine, cross-validation, air quality index, information gain, air quality classification

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2 Annual and Seasonal Variations in Air Quality Index of the National Capital Region, India

Authors: Surinder Deswal, Vineet Verma

Abstract:

Air Quality Index (AQI) is used as a tool to indicate the level of severity and disseminate the information on air pollution to enable the public to understand the health and environmental impacts of air pollutant concentration levels. The annual and seasonal variation of criteria air pollutants concentration based on the National Ambient Air Quality Monitoring Programme has been conducted for a period of nine years (2006-2014) using the AQI system. AQI was calculated using IND-AQI methodology and Maximum Operator Concept is applied. An attempt has been made to quantify the variations in AQI on an annual and seasonal basis over a period of nine years. Further, year-wise frequency of occurrence of AQI in each category for all the five stations is analysed, which presents in depth analysis of trends over the period of study. The best air quality was observed in the Noida residential area, followed by Noida industrial area during the study period; whereas, Bulandshahar industrial area and Faridabad residential area were observed to have the worst air quality. A shift in the worst air quality from winter to summer season has also been observed during the study period. Further, the level of Respirable Suspended Particulate Matter was found to be above permissible limit at all the stations. The present study helps in enhancing public awareness and calls for the need of immediate measures to be taken to counter-effect the cause of the increasing level of air pollution.

Keywords: seasonal variation, air quality index, annual trends, criteria pollutants

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1 Analysis of Air Quality in the Outdoor Environment of the City of Messina by an Application of the Pollution Index Method

Authors: G. Cannistraro, L. Ponterio

Abstract:

In this paper is reported an analysis about the outdoor air pollution of the urban centre of the city of Messina. The variations of the most critical pollutants concentrations (PM10, O3, CO, C6H6) and their trends respect of climatic parameters and vehicular traffic have been studied. Linear regressions have been effectuated for representing the relations among the pollutants; the differences between pollutants concentrations on weekend/weekday were also analyzed. In order to evaluate air pollution and its effects on human health, a method for calculating a pollution index was implemented and applied in the urban centre of the city. This index is based on the weighted mean of the most detrimental air pollutants concentrations respect of their limit values for protection of human health. The analyzed data of the polluting substances were collected by the Assessorship of the Environment of the Regional Province of Messina in the year 2004. A statistical analysis of the air quality index trends is also reported.

Keywords: Statistical Analysis, Environmental Pollution, air quality index, Pollutants levels, Linearregression

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