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Studies on Interrelations among SO2, NO2and PM10Concentrations and Their Predictions in Ambient Air in Kolkata

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Open Journal of Air Pollution 2012年第2期1卷 42-50页

作者： Sayanti Kar Phalguni Mukherjee Department of Environmental Studies Women’s Christian College Kolkata India Department of Mathematics and Post Graduate Department of Environmental Science Asutosh College Kolkata India

In this paper we have first of all studied the interrelations among the concentrations of SO2, NO2 and PM10 and then predicted their future level of concentrations in the ambient air of Kolkata. The data collected from West Bengal Pollution Control Board website have been used to construct second degree, third degree and four degree polynomial equations using MATLAB software. Since a curve in a small interval can be approximated by a line segment in that small interval, we have observed that better result can be achieved if we replace the curves piece meal wise in small intervals by line segments during January-April, May-August and September-December months. The multiple regression equations among the aforesaid three parameters have been established to predict the value of each parameter in terms of the remaining two. A further improvement in terms of reducing the number of dependent variables has been made using the results of correlation coefficients. Finally, we have predicted the value of each parameter in terms of only one dependent variable.

关键词： Ambient Air Multiple Correlation-Coefficients Kolkata

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A Novel Methodological Approach to Estimate the Impact of Natural Hazard-Induced Disasters on Country/Region-Level Economic Growth

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International Journal of Disaster Risk Science 2018年第1期9卷 74-85页

作者： sayanti Mukherjee Makarand Hastak Lyles School of Civil Engineering Purdue University School of Industrial Engineering Purdue University Division of Construction Engineering and Management Purdue University

With the increased frequency of extreme weather events and large-scale disasters, extensive societal and economic losses incur every year due to damage of infrastructure and private properties, business disruptions,fatalities, homelessness, and severe health-related issues. In this article, we analyze the economic and disaster data from1970 through 2010 to investigate the impact of disasters on country/region-level economic growth. We leveraged a random parameter modeling approach to develop the growth-econometrics model that identifies risk factors significantly influencing the country/region-level economic growth in the face of natural hazard-induced disasters,while controlling for country/region-and time-specific unobserved heterogeneities. We found that disaster intensity in terms of fatalities and homelessness, and economic characteristics such as openness to trade and a government's consumption share of purchasing power parity(PPP), are the significant risk factors that randomly vary for different countries/regions. Other significant factors found to be significant include population, real gross domestic product(GDP), and investment share of PPP converted GDP per capita. We also found that flood is the most devastating disaster to affect country/region-level economic growth. This growth-econometrics model will help in the policy and decision making of governmentsrelated to the investment needs for pre-and post-disaster risk mitigation and response planning strategies, to better protect nations and minimize disaster-induced economic impacts.

关键词： Disaster risk reduction Economic growth Growth econometrics Impact of natural hazard-induced disasters Panel data analysis Random parameter modeling

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Assessing Domains in Quality of Life―A Case Study

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Open Journal of Statistics 2014年第11期4卷 945-963页

作者： sayanti Sen Goutam Sen Department of Geography Bangabasi College Calcutta University Kolkata India School of Oceonographic Studies Jadavpur University Kolkata India

Mining in India has developed haphazardly with a significant part of mining activities being informal or unauthorised. Open cast quarries, coal washeries, thermal power plants, coke-oven plants, etc., contribute to serious air and water pollution. The aim of this paper is to assess the QoL of residents living in Jharia coalfield. In this study, QoL domains are analysed considering the social, cultural, environmental, health and economic condition of the study areas. A path model has been developed to analyse the cascading effect on domains. The purpose of investigating path model with overall quality of life was to contribute to the subjective wellbeing literature by analyzing the predictors of OQoL in the sample population. Therefore, OQoL was used as the dependent variable of a regression analysis using four domains as variables and leveraging path analysis method to arrive at the causal model.

关键词： Quality of Life Path Analysis Minning Jharia

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