Development of fuzzy air quality index using soft computing approach

Mandal, T. K.; Gorai, Amit Kumar; Pathak, Gopal

doi:10.1007/s10661-011-2412-0

Cited by 29 publications

(17 citation statements)

References 12 publications

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“…To overcome the deficiencies existing in aforementioned methods and taking all pollutants into consideration, the weighted arithmetic mean function is suggested to calculate the AQI. In [22], the formula used to determine the integrated AQI is expressed as:…”

Section: Methods Of the Weighted Arithmetic Mean Functionmentioning

confidence: 99%

“…Clearly, it is fairly unreasonable to assign the same weight to each air pollutant subjectively; since different air pollutants have varying health impacts and hence the corresponding weights of air pollutants are different in the determination of the overall AQI. For the sake of determining the weights of various pollutants, the AHP was applied into subsequent research by Mandal et al [22], Khan and Sadiq [30] and Upadhyay et al [31]. Meanwhile, other substitutable methods, such as expert scoring, fuzzy synthetic evaluation, and so on, can also be used to ascertain the weights of different pollutants.…”

Section: Methods Of the Weighted Arithmetic Mean Functionmentioning

confidence: 99%

“…Consequently, to obtain an integrated AQI and reflect the influence of each pollutant on air quality comprehensively, the weighted arithmetic mean function is suggested. Mandal et al [22] brought up a method that calculates the weighted average of IAQIs as the overall AQI, in which the weights are usually obtained by using the analytical hierarchy process (AHP). Kone and Buke [23] performed the air quality evaluation of Turkey in terms of the air pollution index, which was also derived from the weighted value of four different environmental threat categories.…”

Section: Introductionmentioning

confidence: 99%

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A Fuzzy Expression Way for Air Quality Index with More Comprehensive Information

et al. 2017

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Abstract:The Air Quality Index (AQI) is an evaluating indicator for the atmospheric environment released by various environmental monitoring centers to communicate the present air quality status to the public, which is calculated by the aid of the monitored concentrations of six common air pollutants and relevant computational formulae. Considering that the historical data of daily overall AQI illustrated by the traditional expression way merely contain limited information about the original data, this paper puts forward a more concrete and intuitive way to express the air quality in the past day. By analyzing the data concerning individual air quality indices of pollutants gathered from five cities of China for six consecutive months and conducting the curve fitting, each sub-index is recommended to be set as a Gaussian fuzzy number. Accordingly, taking advantage of the novel operational law for fuzzy numbers, the fuzzy distribution and membership function of the daily overall AQI can be deduced immediately, which as a reference contributes to the users acquiring the information more intuitively and facilitates making plans or decisions. Subsequently, a case study taking Shanghai as a background is conducted to elaborate the application of the proposed approach. Furthermore, the line chart reflecting the overall air quality status in a past period is depicted, based on which an example of selecting a tourist destination is given to demonstrate its utilization.

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Section: Methods Of the Weighted Arithmetic Mean Functionmentioning

confidence: 99%

Section: Methods Of the Weighted Arithmetic Mean Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Fuzzy Expression Way for Air Quality Index with More Comprehensive Information

et al. 2017

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“…Another study, using FLA to determine air quality, was conducted by Mandal, Gorai and Pathak in 2012. In this study, the AQI was modelled with the FLA as in the previous study, and the results are compared with the traditional analytical hierarchy approach [10]. In another study conducted by Assimakopoulos, Dounis, Spanou, and Santamouris in the same year, the AQI for indoor environments were evaluated with FLA according to CO2, PM10, PM2,5, PM1 pollutants and passenger counts measured in the Athens metro [11].…”

Section: Related Work On Fla-based Air Qualitymentioning

confidence: 99%

Modelling and Evaluating Air Quality with Fuzzy Logic Algorithm-Ankara-Cebeci Sample

Atacak

Arıcı

Guner

2017

ijisae

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Air is one of the most important life sources for all living things. Gases that are present and absent in the composition of clean air also considered as pollutants in the atmosphere. If the pollutants rise above a certain concentration level, air pollution occurs. Air pollution damages all living things, especially human health. Accurate estimation of pollutant concentrations through air pollution modeling has an important effect in reducing the adverse effects of air pollution and taking necessary precautions. Conventional statistical models are widely used in air pollution forecasting and modeling. As a different approach, in this study, fuzzy logic algorithm (FLA), which has been increasingly successful in many field applications, is used to model air quality and air pollution analyzes are made based on this model. Ankara province data is used in the sample of the research.

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“…Architecture of PCAneural network model for the forecasting of AQI. Mandal et al (2012) developed a method for predic tion of AQI on the basis of fuzzy aggregation. The out put AQI value using fuzzy aggregation method was compared to that of the output from conventional me thod.…”

Section: Aqi Based On Pca-neural Networkmentioning

confidence: 99%

A Review on Air Quality Indexing System

Kanchan¹,

Gorai²,

Goyal³

2015

Asian J. Atmos. Environ

104

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Air quality index (AQI) or air pollution index (API) is commonly used to report the level of severity of air pollution to public. A number of methods were dev eloped in the past by various researchers/environ mental agencies for determination of AQI or API but there is no universally accepted method exists, which is appropriate for all situations. Different method uses different aggregation function in calculating AQI or API and also considers different types and numbers of pollutants. The intended uses of AQI or API are to identify the poor air quality zones and public reporting for severity of exposure of poor air quality. Most of the AQI or API indices can be broad ly classify as single pollutant index or multipollut ant index with different aggregation method. Every indexing method has its own characteristic strengths and weaknesses that affect its suitability for particu lar applications. This paper attempt to present a review of all the major air quality indices developed worldwide.Key words: Air pollution, Air quality index, Health, Environmental factors, Literature review IntroductIonAir pollution is global environmental problem that influences mostly health of urban population. Over the past few decades, epidemiological studies have dem onstrated adverse health effects due to higher ambient levels of air pollution. Studies have indicated that rep eated exposures to ambient air pollutants over a pro longed period of time increases the risk of being sus ceptible to air borne diseases such as cardiovascular disease, respiratory disease, and lung cancer (WHO, 2009). Air pollution has been consistently linked to substantial burdens of illhealth in developed and devel oping countries Bruce et al., 2000;Smith et al., 2000; WHO, 1999;Schwartz, 1994).Globally, many cities continuously assess air quality using monitoring networks designed to measure and record air pollutant concentrations at several points deemed to represent exposure of the population to these pollutants. Current research indicates that guide lines of recommended pollution values cannot be regar ded as threshold values below which a zero adverse response may be expected. Therefore, the simplistic comparison of observed values against guidelines may mislead unless suitably quantified. In recent years, air quality information are provided by governments to the public comes in a number of forms like annual reports, environment reviews, and site or subject specific anal yses/report. These are generally having available or access to limited audiences and also require time, inter est and necessary background to digest its contents. Presently, governments throughout the world have also started to use realtime access to sophisticated database management programs to provide their citizens with access to sitespecific air quality index/air pollution index and its probable health consequences. Thus, a more sophisticated tool has been developed to commu nicate the health risk of ambient concentrations using air pollution index (API) or air quality i...

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Development of fuzzy air quality index using soft computing approach

Cited by 29 publications

References 12 publications

A Fuzzy Expression Way for Air Quality Index with More Comprehensive Information

A Fuzzy Expression Way for Air Quality Index with More Comprehensive Information

Modelling and Evaluating Air Quality with Fuzzy Logic Algorithm-Ankara-Cebeci Sample

A Review on Air Quality Indexing System

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