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Managing Future Air Quality in Megacities: A case study for Delhi(Atmospheric Environment)
(Markus Amann, Pallav Purohit, Anil D. Bhanarkar, Imrich Bertok, Jens Borken-Kleefeld, JanuszCofala, Chris Heyes, Gregor Kiesewetter, ZbigniewKlimonta, Jun Liu, Dipanjali Majumdar, Binh Nguyen, Peter Rafaj, Padma S. Rao, Robert Sander, Wolfgang Schopp, Anjali Srivastava, B. Harsh Vardhan ,,,,Year : 2017)
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Megacities in Asia rank high in air pollution at the global scale. In many cities, ambient concentrations of fine particulate matter (PM2.5) have been exceeding both the WHO interim targets as well as respective national air quality standards. This paper presents a systems analytical perspective on management options that could efficiently improve air quality at the urban scale, having Delhi as a case study. We employ the newly developed GAINS-City policy analysis framework, consisting of a bottom up emission calculation combined with atmospheric chemistry-transport calculation, to derive innovative insights into the current sources of pollution and their impacts on ambient PM2.5, both from emissions of primary PM as well as precursors of secondary inorganic and organic aerosols. We outline the likely future development of these sources, quantify the related ambient PM2.5 concentrations and health impacts, and explore potential policy interventions that could effectively reduce environmental pollution and resulting health impacts in the coming years. The analysis demonstrates that effective improvement of Delhi's air quality requires collaboration with neighboring States and must involve sources that are less relevant in industrialized countries. At the same time, many of the policy interventions will have multiple co-benefits on development targets in Delhi and its neighboring States. Outcomes of this study, as well as the modelling tools used herein, are applicable to other urban areas and fast growing metropolitan zones in the emerging Asian regions
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Effects of unregulated anthropogenic activities on mixing ratios of volatile organic air pollutants(Air & Waste Management Association)
(Rao P. S, Majumdar, Dipanjali ,65,Issue 9,,Year : 2015)
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During the months of October to November, many important festivals are celebrated in India. Celebration of these festivals are marked by extensive use of fireworks or pyrotechnics, bonfire, incense burning, open air community cooking, and temporary eateries using crude fuel such as coal, wood, kerosene, cow dung, burning of raw/semiwood, and coconut shells. The present study deals with the influence of these unregulated anthropogenic activities on ambient mixing level of volatile organic compounds (VOCs), especially some carbonyl compounds. The study was undertaken in the metropolitan city of Kolkata, India, with very high population density, which is even higher during festival period. The average total carbonyl level at different sites in Kolkata varied from 134.8 to 516.5 μg m(-3) in pre-festival season, whereas in post-festival season the same varied from 252.2 to 589.3 μg m(-3). Formaldehyde to acetaldehyde ratio altered from 0.62 in pre-festival season to 1.78 in post-festival season. Diurnal variation also altered, indicating variation in source composition of carbonyls. The total ozone forming potential calculated for all 14 carbonyls in pre-festival season increased by 35% in post-festival season. The effect of anthropogenic activities typical to the event of Diwali night characterized by intense execution of pyrotechnics resulted in significantly high level of carbonyl VOCs. Principal component analysis study for the event of Diwali shows clear contribution of the event on certain carbonyl VOCs. The results indicate elevated primary emissions of these pollutants and also their effect on formation of secondary pollutants. The study emphasizes the need of generating awareness among the communities in society as well as need for regulations to minimize the emissions and related hazards to the extent possible
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Prediction of remotely sensed cloud related parameters over an inland urban city of India(Annals of GIS)
(Navneet Kumar, Anirban Middey and Padma Rao,22,Issue 1,71-84,Year : 2015)
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Artificial neural network (ANN) is a mathematical model useful for forecasting on the any type of available data. This tool is not only useful in environment but also covers wide ranges of applicability. Utilizing this model, a study was carried out in an inland area of Nagpur for forecasting satellite-derived cloud parameters. Nine ANN architects are developed based on five pollutant parameter (aerosol optical depth, RSPM, SPM, SO2, NOx), meteorological and some cloud parameter. The models are used to simulate concentration of pollutants as well as the forecast and validation of cloud top temperature, cloud ice water path and cloud liquid water path during different seasons (winter, pre-monsoon and post-monsoon). Models based on back-propagation neural network were tested using the collected data of study area. The ANN models were trained using gradient descent algorithms to check the robustness and adaptability of the models. ANN models based on both satellite and ground-based data variables demonstrate the best performance and are skilled at resolving patterns of pollutant dispersion to the atmosphere during 2006–2013 for Nagpur city
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Managing future air quality in megacities: Emission inventory and scenario analysis for the Kolkata Metropolitan City, India(Atmospheric Environment)
(Dipanjali Majumdar,Pallav Purohit, Anil D. Bhanarkar, Padma S. Rao, Peter Rafaj, Markus Amann, Robert Sander, Ankita Pakrashi, Anjali Srivastava,222,,117-135,Year : )
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