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Article: The influence of meteorological variables and lockdowns on COVID-19 cases in urban agglomerations of Indian cities.

Chelani, Asha B / Gautam, Sneha

Stochastic environmental research and risk assessment : research journal

2022 Volume 36, Issue 9, Page(s) 2949–2960

Abstract: Coronavirus has been identified as one of the deadliest diseases and the WHO has declared it a pandemic and a global health crisis. It has become a massive challenge for humanity. India is also facing its fierceness as it is highly infectious and ... ...

Abstract	Coronavirus has been identified as one of the deadliest diseases and the WHO has declared it a pandemic and a global health crisis. It has become a massive challenge for humanity. India is also facing its fierceness as it is highly infectious and mutating at a rapid rate. To control its spread, many interventions have been applied in India since the first reported case on January 30, 2020. Several studies have been conducted to assess the impact of climatic and weather conditions on its spread in the last one and half years span. As it is a well-established fact that temperature and humidity could trigger the onset of diseases such as influenza and respiratory disorders, the relationship of meteorological variables with the number of COVID-19 confirmed cases has been anticipated. The association of several meteorological variables has therefore been studied in the past with the number of COVID-19 confirmed cases. The conclusions in those studies are based on the data obtained at an early stage, and the inferences drawn based on those short time series studies may not be valid over a longer period. This study attempted to assess the influence of temperature, humidity, wind speed, dew point, previous day's number of deaths, and government interventions on the number of COVID-19 confirmed cases in 18 districts of India. It is also attempted to identify the important predictors of the number of confirmed COVID-19 cases in those districts. The random forest model and the hybrid model obtained by modelling the random forest model's residuals are used to predict the response variable. It is observed that meteorological variables are useful only to some extent when used with the data on the number of the previous day's deaths and lockdown information in predicting the number of COVID-19 cases. Partial lockdown is more important than complete or no lockdown in predicting the number of confirmed COVID-19 cases. Since the time span of the data in the study is reasonably large, the information is useful to policymakers in balancing the restriction activities and economic losses to individuals and the government.
Language	English
Publishing date	2022-01-25
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1481263-0
ISSN	1436-3259 ; 1435-151X ; 1436-3240 ; 0931-1955
ISSN (online)	1436-3259 ; 1435-151X
ISSN	1436-3240 ; 0931-1955
DOI	10.1007/s00477-021-02160-4
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: The influence of meteorological variables and lockdowns on COVID-19 cases in urban agglomerations of Indian cities

Chelani, Asha B. / Gautam, Sneha

Stochastic environmental research and risk assessment. 2022 Sept., v. 36, no. 9

2022

Abstract	Coronavirus has been identified as one of the deadliest diseases and the WHO has declared it a pandemic and a global health crisis. It has become a massive challenge for humanity. India is also facing its fierceness as it is highly infectious and mutating at a rapid rate. To control its spread, many interventions have been applied in India since the first reported case on January 30, 2020. Several studies have been conducted to assess the impact of climatic and weather conditions on its spread in the last one and half years span. As it is a well-established fact that temperature and humidity could trigger the onset of diseases such as influenza and respiratory disorders, the relationship of meteorological variables with the number of COVID-19 confirmed cases has been anticipated. The association of several meteorological variables has therefore been studied in the past with the number of COVID-19 confirmed cases. The conclusions in those studies are based on the data obtained at an early stage, and the inferences drawn based on those short time series studies may not be valid over a longer period. This study attempted to assess the influence of temperature, humidity, wind speed, dew point, previous day’s number of deaths, and government interventions on the number of COVID-19 confirmed cases in 18 districts of India. It is also attempted to identify the important predictors of the number of confirmed COVID-19 cases in those districts. The random forest model and the hybrid model obtained by modelling the random forest model's residuals are used to predict the response variable. It is observed that meteorological variables are useful only to some extent when used with the data on the number of the previous day’s deaths and lockdown information in predicting the number of COVID-19 cases. Partial lockdown is more important than complete or no lockdown in predicting the number of confirmed COVID-19 cases. Since the time span of the data in the study is reasonably large, the information is useful to policymakers in balancing the restriction activities and economic losses to individuals and the government.
Keywords	COVID-19 infection ; Orthocoronavirinae ; algorithms ; dewpoint ; humidity ; influenza ; models ; pandemic ; research ; risk assessment ; temperature ; time series analysis ; wind speed ; India
Language	English
Dates of publication	2022-09
Size	p. 2949-2960.
Publishing place	Springer Berlin Heidelberg
Document type	Article
ZDB-ID	1481263-0
ISSN	1436-3259 ; 1435-151X ; 1436-3240 ; 0931-1955
ISSN (online)	1436-3259 ; 1435-151X
ISSN	1436-3240 ; 0931-1955
DOI	10.1007/s00477-021-02160-4
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Lockdown during COVID-19 pandemic: A case study from Indian cities shows insignificant effects on persistent property of urban air quality.

Chelani, Asha / Gautam, Sneha

Geoscience frontiers

2021 Volume 13, Issue 6, Page(s) 101284

Abstract: The influence of reduction in emissions on the inherent temporal characteristics of ... ...

Abstract	The influence of reduction in emissions on the inherent temporal characteristics of PM
Language	English
Publishing date	2021-08-12
Publishing country	Netherlands
Document type	Journal Article
ISSN	2588-9192
ISSN (online)	2588-9192
DOI	10.1016/j.gsf.2021.101284
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Article ; Online: Integrated analytical hierarchy process-grey relational analysis approach for mechanical recycling scenarios of plastics waste in India.

Sharma, Radhika / Pardeshi, Sushma / Joseph, Jowin / Khan, Debishree / Chelani, Asha / Dhodapkar, Rita

Environmental science and pollution research international

2024 Volume 31, Issue 15, Page(s) 23106–23119

Abstract: Mechanical recycling is an indispensable tool for plastic waste (PW) recycling and has the highest share in the PW recycling sector in India. The transition to the circular economy of plastics (CEoP) needs a systemic perspective on the mechanical ... ...

Abstract	Mechanical recycling is an indispensable tool for plastic waste (PW) recycling and has the highest share in the PW recycling sector in India. The transition to the circular economy of plastics (CEoP) needs a systemic perspective on the mechanical recycling processes. Nevertheless, the assessment of multiple parameters influencing the mechanical recycling of PW is a complex decision-making problem for the development of triple-bottom-line mechanical recycling. A systemic perspective of various mechanical recycling scenarios was performed by employing a multi-criteria decision-making approach to examine the complexity of interlinked factors in the present investigation. Analytical hierarchy process (AHP) integrated with grey relational analysis (GRA) was used to evaluate the criteria that directly influence quality-oriented mechanical recycling. Data were collected by conducting semi-structured interviews using a framed questionnaire in stakeholder engagement with mechanical recyclers of PW. The first level hierarchy included economy, technical, resource consumption and environmental criteria. These criteria were further categorized into various significant indices such as quality of recyclate, recyclability, water and energy consumption during recycling. The results of the integrated grey relational analysis indicated that the technical parameters including quality of recyclate, resource efficiency, PW processing rate and recyclability have a significant influence on mechanical recycling. Based on AHP-GRA, scenario MR6, i.e. manufacturing of PET strap from recycled PET flakes, was ranked the optimal mechanical process amongst the various scenarios. MR6 was followed by Straps and Films at the second and third rank. The lowest ranking was observed for polymer blend recycling. These processes with higher ranks produced good quality recyclate with better efficiency and recyclability. Moreover, these processes consumed optimal resources during manufacturing. These processes also exhibited less maintenance cost, high production rate, low chemical consumption and waste generation as well as implemented pollution control practices.
MeSH term(s)	Plastics ; Analytic Hierarchy Process ; Recycling ; Polymers ; India ; Waste Management
Chemical Substances	Plastics ; Polymers
Language	English
Publishing date	2024-02-28
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1178791-0
ISSN	1614-7499 ; 0944-1344
ISSN (online)	1614-7499
ISSN	0944-1344
DOI	10.1007/s11356-024-32632-3
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Long-memory property in air pollutant concentrations

Chelani, Asha

Atmospheric research. 2016 May 01, v. 171

2016

Abstract: In the present paper, long-memory in air pollutant concentrations is reviewed and outcome of the past studies is analyzed to provide the possible mechanism behind temporal evolution of air pollutant concentrations. It is observed that almost all the ... ...

Abstract	In the present paper, long-memory in air pollutant concentrations is reviewed and outcome of the past studies is analyzed to provide the possible mechanism behind temporal evolution of air pollutant concentrations. It is observed that almost all the studies show air pollutant concentrations over time possess persistence up to a certain limit. Self-organized criticality of air pollution, multiplicative process of pollutant concentrations, and uniformity in emission sources leading to self-organized criticality are few of the phenomena behind the persistent property of air pollutant concentrations. The self-organized criticality of air pollution is linked to atmosphere's self-cleansing mechanism. This demonstrates that inspite of increasing anthropogenic emissions, self-organized criticality of air pollution is sustained and has low influence of human interventions. In the future, this property may, however, be perturbed due to continuous air pollution emissions, which may influence the accuracy in predictions.
Keywords	air pollutants ; air pollution ; emissions ; prediction
Language	English
Dates of publication	2016-0501
Size	p. 1-4.
Publishing place	Elsevier B.V.
Document type	Article
ISSN	0169-8095
DOI	10.1016/j.atmosres.2015.12.007
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Article: Optimal selection of “zero liquid discharge” (ZLD) system using “analytical hierarchy process” (AHP) and “grey relational analysis” (GRA)

Shende, Akshay D / Chelani, Asha B / Rao, N. N / Pophali, Girish R

Environment, development and sustainability. 2021 June, v. 23, no. 6

2021

Abstract: This article specifically presents three different zero liquid discharge (ZLD) options as “Desalination of industrial wastewater and associated rejects management” and deals with optimal selection of ZLD system using “analytical hierarchy process” and “ ... ...

Abstract	This article specifically presents three different zero liquid discharge (ZLD) options as “Desalination of industrial wastewater and associated rejects management” and deals with optimal selection of ZLD system using “analytical hierarchy process” and “grey relation analysis” (GRA). Commercially available ZLD systems, which differ from each other in some way or the other, were assessed for various factors. Hierarchy among the three factors, viz. economic, technical, and administrative criteria, was considered to arrive at the best treatment option. Each criterion again involved hierarchy of indices. The most suitable ZLD option was arrived at in two ways: 1) by comparing the commercially available treatment options and 2) by deriving the most suitable option based on the maximum beneficial unit operation and treatment process among all the options. A ZLD treatment system based on the combination of unit operation and processes of different treatment options was recommended since it provided maximum benefits. An assessment of annual expenditure on operation and maintenance of existing ZLD system revealed that there is an emergent need to develop more cost-effective techniques to make them environmentally and economically sustainable.
Keywords	cost effectiveness ; desalination ; economic sustainability ; environment ; industrial wastewater ; liquids
Language	English
Dates of publication	2021-06
Size	p. 8506-8523.
Publishing place	Springer Netherlands
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	1438730-x
ISSN	1387-585X
ISSN	1387-585X
DOI	10.1007/s10668-020-00979-5
Database	NAL-Catalogue (AGRICOLA)

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Article: Irregularity analysis of CO, NO2 and O 3 concentrations at traffic, commercial and low activity sites in Delhi

Chelani, Asha B

Stochastic environmental research and risk assessment. 2014 May, v. 28, no. 4

2014

Abstract: The irregularity analysis of exceedance time series of gaseous pollutants CO, NO₂and O₃is carried out using Shannon entropy and Fisher information measure. The data observed during 2007–2010 at three sites with different land-use activities in Delhi are ... ...

Abstract	The irregularity analysis of exceedance time series of gaseous pollutants CO, NO₂and O₃is carried out using Shannon entropy and Fisher information measure. The data observed during 2007–2010 at three sites with different land-use activities in Delhi are analyzed. CO and NO₂showed irregular behavior at both, low anthropogenic activity and commercial activity sites, whereas at traffic site both the pollutant concentrations showed regular behavior. The irregularity is attributed to the multiplicity in emission sources at low activity and commercial site and regular behavior is observed due to the uniformity and well defined source characteristics at the traffic site. O₃at three sites showed irregular behavior owing to its secondary nature. Fisher–Shannon information plane showed the grouping of three pollutants except CO and NO₂at traffic and O₃at low activity site suggesting the similar temporal characteristics of the pollutants even at the sites with different land-use activities.
Keywords	anthropogenic activities ; entropy ; land use ; nitrogen dioxide ; pollutants ; time series analysis ; traffic ; India
Language	English
Dates of publication	2014-05
Size	p. 921-925.
Publishing place	Springer-Verlag
Document type	Article
ZDB-ID	1481263-0
ISSN	1436-3259 ; 1436-3240 ; 0931-1955
ISSN (online)	1436-3259
ISSN	1436-3240 ; 0931-1955
DOI	10.1007/s00477-013-0791-1
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Prediction of daily maximum ground ozone concentration using support vector machine.

Chelani, Asha B

Environmental monitoring and assessment

2009 Volume 162, Issue 1-4, Page(s) 169–176

Abstract: The accurate predictions of ground ozone concentrations are required for proper management, control, and making public warning strategies. Due to the difficulties in handling phenomenological models that are based on complex chemical reactions of ozone ... ...

Abstract	The accurate predictions of ground ozone concentrations are required for proper management, control, and making public warning strategies. Due to the difficulties in handling phenomenological models that are based on complex chemical reactions of ozone production, neural network models gained popularity in the last decade. These models also have some limitations due to problems of overfitting, local minima, and tuning of network parameters. In this study, the predictions of daily maximum ozone concentrations are attempted using support vector machines (SVMs). The comparison between the accuracy of SVM and neural network predictions is performed to evaluate their performance. For this, the daily maximum ozone concentration data observed during 2002-2004 at a site in Delhi is utilized. The models are developed using the available meteorological parameters. The results indicated the promising performance of SVM over neural networks in predicting daily maximum ozone concentrations.
MeSH term(s)	Air Pollutants/analysis ; Models, Theoretical ; Ozone/analysis ; Regression Analysis
Chemical Substances	Air Pollutants ; Ozone (66H7ZZK23N)
Language	English
Publishing date	2009-02-25
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	782621-7
ISSN	1573-2959 ; 0167-6369
ISSN (online)	1573-2959
ISSN	0167-6369
DOI	10.1007/s10661-009-0785-0
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Persistence analysis of extreme CO, NO₂ and O₃ concentrations in ambient air of Delhi

Chelani, Asha B

Atmospheric research. 2012 May, v. 108

2012

Abstract: Persistence analysis of air pollutant concentration and corresponding exceedance time series is carried out to examine for temporal evolution. For this purpose, air pollutant concentrations, namely, CO, NO₂ and O₃ observed during 2000–2009 at a traffic ... ...

Abstract	Persistence analysis of air pollutant concentration and corresponding exceedance time series is carried out to examine for temporal evolution. For this purpose, air pollutant concentrations, namely, CO, NO₂ and O₃ observed during 2000–2009 at a traffic site in Delhi are analyzed using detrended fluctuation analysis. Two types of extreme values are analyzed; exceeded concentrations to a threshold provided by national pollution controlling agency and time interval between two exceedances. The time series of three pollutants is observed to possess persistence property whereas the extreme value time series of only primary pollutant concentrations is found to be persistent. Two time scaling regions are observed to be significant in extreme time series of CO and NO₂, mainly attributed to implementation of CNG in vehicles. The presence of persistence in three pollutant concentration time series is linked to the property of self-organized criticality. The observed persistence in the time interval between two exceeded levels is a matter of concern as persistent high concentrations can trigger health problems.
Keywords	air ; nitrogen dioxide ; ozone ; pollutants ; time series analysis ; traffic ; India
Language	English
Dates of publication	2012-05
Size	p. 128-134.
Publishing place	Elsevier B.V.
Document type	Article
ISSN	0169-8095
DOI	10.1016/j.atmosres.2012.02.001
Database	NAL-Catalogue (AGRICOLA)

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Article: Prediction of daily maximum ground ozone concentration using support vector machine

Chelani, Asha B

Environmental monitoring and assessment. 2010 Mar., v. 162, no. 1-4

2010

Abstract	The accurate predictions of ground ozone concentrations are required for proper management, control, and making public warning strategies. Due to the difficulties in handling phenomenological models that are based on complex chemical reactions of ozone production, neural network models gained popularity in the last decade. These models also have some limitations due to problems of overfitting, local minima, and tuning of network parameters. In this study, the predictions of daily maximum ozone concentrations are attempted using support vector machines (SVMs). The comparison between the accuracy of SVM and neural network predictions is performed to evaluate their performance. For this, the daily maximum ozone concentration data observed during 2002-2004 at a site in Delhi is utilized. The models are developed using the available meteorological parameters. The results indicated the promising performance of SVM over neural networks in predicting daily maximum ozone concentrations.
Keywords	chemical bases ; chemical reactions ; equipment ; meteorological parameters ; neural networks ; ozone ; prediction
Language	English
Dates of publication	2010-03
Size	p. 169-176.
Publisher	Springer Netherlands
Publishing place	Dordrecht
Document type	Article
ZDB-ID	782621-7
ISSN	1573-2959 ; 0167-6369
ISSN (online)	1573-2959
ISSN	0167-6369
DOI	10.1007/s10661-009-0785-0
Database	NAL-Catalogue (AGRICOLA)

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