scholarly journals Impact of Coronavirus (COVID-19) Outbreak on Society, Air Quality, and Economy in India: A Study of Three “P”s of Sustainability in India

2021 ◽  
Vol 13 (5) ◽  
pp. 2873
Author(s):  
Sayanti Kar ◽  
Indrajit Ghosh ◽  
Sebanti Show ◽  
Arunabh Sen ◽  
Tanya Gupta ◽  
...  
Keyword(s):  
Air Quality ◽  
Secondary Data ◽  
Sampling Technique ◽  
Ambient Air ◽  
Quality Parameters ◽  
Ambient Air Quality ◽  
Novel Coronavirus ◽  
Pm2.5 And Pm10 ◽  
Indian Stock Market ◽  
The Impact

The outbreak of novel coronavirus (COVID-19) pandemic forced affected countries to implement strict lockdown to contain the spread of this disease before the advent of the vaccine. This containment resulted in social and economic crisis globally. This study evaluated the impact of COVID-19 on three “P” s of sustainability (Planet, People, and Profit) in India. A comparative analysis was conducted by evaluating the available secondary data in different sectors during the pre-lockdown and lockdown period. Seven major air quality parameters: particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ammonia (NH3), carbon monoxide (CO), and ozone (O3) were studied in six states of India to review the ambient air quality status. Stratified random sampling technique was used in this study for collective portrayal of the country’s air quality. A drastic cutback of the level of PM2.5 and PM10 with significant increase of O3 was observed in the lockdown phase for most of the selected monitoring stations. A significant change in level of PM2.5 and PM10 was observed when t-test was performed in between the pre-lockdown and lockdown period. Improvement of ambient air quality was also observed considering the air quality index (AQI) during lockdown. The trend and volatility of two broad Indian stock market indices, SENSEX and NIFTY-50, were analyzed, and results showed that both the indices have recovered during the forty-day lockdown phase. The potential effects of the crisis on various sectors of Indian economy were assessed in this study, and a set of policy recommendations for these sectors were suggested.

Ambient Air Quality Monitoring Studies in Four Specific Location of Tamilnadu, India

2019 ◽  
pp. 677-683
Author(s):  
Mageshkumar P ◽  
Ramesh S ◽  
Angu Senthil K
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
High Volume ◽  
Ambient Air ◽  
Quality Parameters ◽  
Air Quality Index ◽  
Gaseous Pollutants ◽  
Ambient Air Quality ◽  
Air Sampler

A comprehensive study on the air quality was carried out in four locations namely, Tiruchengode Bus Stand, K.S.R College Campus, Pallipalayam Bus Stop and Erode Government Hospital to assess the prevailing quality of air. Ambient air sampling was carried out in four locations using a high volume air sampler and the mass concentrations of PM10, PM2.5, SO2, NOX and CO were measured. The analyzed quality parameters were compared with the values suggested by National Ambient Air Quality Standards (NAAQS). Air quality index was also calculated for the gaseous pollutants and for Particulate Matters. It was found that PM10 concentration exceeds the threshold limits in all the measured locations. The higher vehicular density is one of the main reasons for the higher concentrations of these gaseous pollutants. The air quality index results show that the selected locations come under moderate air pollution.

scholarly journals Assessing the impact of clean air action on air quality trends in Beijing using a machine learning technique

2019 ◽  
Vol 19 (17) ◽  
pp. 11303-11314 ◽  
Author(s):  
Tuan V. Vu ◽  
Zongbo Shi ◽  
Jing Cheng ◽  
Qiang Zhang ◽  
Kebin He ◽  
...  
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Action Plan ◽  
Ambient Air ◽  
Meteorological Conditions ◽  
Assessment Process ◽  
Pollutant Emissions ◽  
Ambient Air Quality ◽  
Clean Air ◽  
The Impact

Abstract. A 5-year Clean Air Action Plan was implemented in 2013 to reduce air pollutant emissions and improve ambient air quality in Beijing. Assessment of this action plan is an essential part of the decision-making process to review its efficacy and to develop new policies. Both statistical and chemical transport modelling have been previously applied to assess the efficacy of this action plan. However, inherent uncertainties in these methods mean that new and independent methods are required to support the assessment process. Here, we applied a machine-learning-based random forest technique to quantify the effectiveness of Beijing's action plan by decoupling the impact of meteorology on ambient air quality. Our results demonstrate that meteorological conditions have an important impact on the year-to-year variations in ambient air quality. Further analyses show that the PM2.5 mass concentration would have broken the target of the plan (2017 annual PM2.5<60 µg m−3) were it not for the meteorological conditions in winter 2017 favouring the dispersion of air pollutants. However, over the whole period (2013–2017), the primary emission controls required by the action plan have led to significant reductions in PM2.5, PM10, NO2, SO2, and CO from 2013 to 2017 of approximately 34 %, 24 %, 17 %, 68 %, and 33 %, respectively, after meteorological correction. The marked decrease in PM2.5 and SO2 is largely attributable to a reduction in coal combustion. Our results indicate that the action plan has been highly effective in reducing the primary pollution emissions and improving air quality in Beijing. The action plan offers a successful example for developing air quality policies in other regions of China and other developing countries.

scholarly journals Research on Air Quality Analysis Based on Cluster Methods

2021 ◽  
Vol 898 (1) ◽  
pp. 012024
Author(s):  
Zhaoni Li ◽  
Jian Zheng
Keyword(s):  
Air Quality ◽  
Ambient Air ◽  
Quality Analysis ◽  
Quality Data ◽  
Ambient Air Quality ◽  
Republic Of China ◽  
Pollution Levels ◽  
Analysis Process ◽  
Cluster Methods ◽  
The Impact

Abstract Research on air quality analysis is a hot field. Here we describe an analysis process based on cluster methods for the data of ambient air quality. In this paper, we use the process to cluster on the air quality data which from the National Urban Air Quality Report in December 2020 on the official website of the Ministry of Ecology and Environment of the People’s Republic of China. We find that cities in different clusters with different main pollutants and pollution levels. Ambient air quality analysis aims to provide guidance for reducing the impact of air pollution on health.

scholarly journals Assessing the impact of Eskom power plant emissions on ambient air quality over KwaZamokuhle

2019 ◽  
Vol 29 (1) ◽  
Author(s):  
Prince Chidhindi ◽  
Monray D Belelie ◽  
Roelof P Burger ◽  
Gabi Mkhatshwa ◽  
Stuart J Piketh
Keyword(s):  
Air Quality ◽  
Low Income ◽  
Power Plants ◽  
Dispersion Model ◽  
Ambient Air ◽  
Background Concentration ◽  
Monitoring Site ◽  
Ambient Air Quality ◽  
The Impact

Coal-fired power plants are considered a major source of criteria air pollutants. The existence of such activities close to densely populated areas has an impact on human health and more generally on the environment. The impact of a pollutant typically depends on its residence time and the existence of background concentration levels. This study evaluates the dispersion of PM2.5, SO2 and NOX emissions from Eskom power plants (Arnot, Hendrina, and Komati) located close to KwaZamokuhle Township. AERMOD was used to assess the contribution of each plant to the air quality of the township. This steady-state dispersion model was used to simulate surface concentrations (1-hour, 24-hour and annual average concentrations) on a 50km domain for 2015-2017. The modelled results together with data obtained from Eskom’s KwaZamokuhle monitoring site were used to estimate the extent to which these power plants contribute to the ambient air quality of KwaZamokuhle Township. The results confirm that the power plants do contribute to concentrations of PM2.5, SO2, and NOx in the ambient air of the township. However, based on a comparison between the modelled and monitored data, it was inferred that power plants are not the only significant source of these criteria pollutants. Evidence from temporal variations in the monitored data shows that domestic burning is likely the major contributor since the variability is more closely associated with burning habits. It is therefore likely that existing regulatory strategies that focus mostly on the industrial sector may not be successful in improving ambient air quality in low-income settlements like KwaZamokuhle.

scholarly journals Assessment of the effects of thermal renovation of detached houses. 2. Reduction the impact on the ambient air quality.

2014 ◽  
Vol XXXI (61 (3/I/14)) ◽  
pp. 197-215
Author(s):  
Robert Oleniacz ◽  
◽  
Magdalena Kasietczuk ◽  
Mateusz Rzeszutek
Keyword(s):  
Air Quality ◽  
Ambient Air ◽  
Ambient Air Quality ◽  
The Impact

scholarly journals Relationships between perceived health status and ambient air quality parameters in healthy Japanese: a panel study

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Motoyuki Nakao ◽  
Keiko Yamauchi ◽  
Satoshi Mitsuma ◽  
Hisamitsu Omori ◽  
Yoko Ishihara
Keyword(s):  
Health Status ◽  
Air Quality ◽  
Panel Study ◽  
Ambient Air ◽  
Perceived Health ◽  
Quality Parameters ◽  
Ambient Air Quality ◽  
Perceived Health Status

A Novel Approach to Predicting Combustion Emission Using Ambient Air Quality Parameters in Onshore Eastern Nigeria

2021 ◽  
Author(s):  
Osemanre Ossy Omion ◽  
Chioma Maduewesi ◽  
Emeke Chukwu
Keyword(s):  
Air Quality ◽  
Statistical Significance ◽  
Ambient Air ◽  
Quality Parameters ◽  
Gas Production ◽  
Linear Regression Method ◽  
Eastern Region ◽  
Ambient Air Quality ◽  
Gaseous Emission ◽  
Yearly Average

Abstract The paper aims to estimate the tCO2e from flare stack sites in the Eastern zone of Nigeria and review air monitoring done at the flare sites with the objective of establishing a model for gas tCO2e emission and gaseous pollutants. It focuses on the South-Eastern region of Nigeria where oil and gas production are being carried out (Imo and Abia states). It zero-in on the hydrocarbon processing and handling facilities (flowstation) and the gas flared volumes. The study was carried out using representative data from an onshore flowstation in Eastern Nigeria. The data consist of gas flared volumes from year 2013-2017 and ambient gaseous emission from air quality report done on the same location. Univariate regression and correlation using Excel were carried out on yearly average ambient air quality parameters (VOC, NOx, CO, SOx, CH4, SPM, NH3, H2S) to check the statistical significance of each parameter as an independent variable and calculated tCO2e as the dependent variable. Excel Muti-variate linear regression method was then used to generate a predictive model for tCO2e and gaseous emission parameters. It presented a relationship between the emission from flared gas and air quality index.

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