Research Article Open Access

MODELING OF AMBIENT FOR RSPM AND SPM POLLUTANTS THROUGH ARTIFICAL NEURAL NETWORK IN SENSITIVE AREA OF UJJAIN CITY

Abstract

This paper aims to analyze the pollutant level of the sensitive area in Ujjain. Application of Artificial Neural Network analyzes the pollutant RSPM and SPM. The result reported pertains to a site successive preliminary air sampling excessive carried out at selected location in Ujjain mahakal temple. The Artificial neural network system was run by giving the inputs of meteorological data’s and giving the outputs of concentration of various pollutants and accordingly the estimation of Errors was done by this study. Analysis of consecutive four years of data from the sensitive area through ANNS has been found, the concentrations of RSPM = 53.91 and SPM = 195. High volume sampler was used to measure the concentration of critical pollutants RSPM and SPM. This model calculates pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. The system is made of various devices which have to be chosen based on the characteristics of the pollutant: aerosol, solid particles, and droplets or gaseous. The chosen framework and facilities depend on the type of the pollutant: aerosol, solid particles, and droplets or gaseous. There are a number of basic parameters which have to be considered in order to define air pollution control devices. This study represents a modeling of the named parameters which are related to the framework and facilities of air pollution control. In order to set the optimal parameters of a purification device, a deterministic model of the process of purification should be determined.

SUDESHANA PANDEY, ALKA SRIVASTAVA, ASHOK K. SHARMA AND J.K. SRIVASTAVA

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