scholarly journals Pre-During-Post Lockdown Air Quality in Adyar, Chennai, India Amid COVID-19 Pandemic

2020 ◽  
Vol 72 (4) ◽  
pp. 110-117
Author(s):  
Monikandon Sukumaran ◽  
Kesavan Devarayan ◽  
Ramar Marimuthu ◽  
Sabariswaran Kandasamy
Keyword(s):  
Air Quality ◽  
Nitrogen Dioxide ◽  
Sulphur Dioxide ◽  
Tamil Nadu ◽  
Pollution Source ◽  
Quality Data ◽  
Pm 2.5 ◽  
Pollution Levels ◽  
The People ◽  
Temporary Control

The COVID-19 pandemic has shoved most of the countries to implement restrictions for transportation and all other social activities to minimize spread of disease to the people. India is the second most populated country in the world which has implemented a historical complete lockdown throughout the country from the last week of March to April 2020 with an extension up to the first week of May 2020. This lockdown has slowed down the pollution levels in most of the cities in India within the first few weeks of the lockdown. In this view, the present study discusses the air quality scenario of Chennai, one of the megacities of India, scientifically. With the aid of air quality data of the Tamil Nadu Pollution Control Board, India, for five parameters such as PM 2.5 and P.M 10, sulphur dioxide, nitrogen dioxide and air quality index, the authors correlated the pre-during-post lockdown air quality of Adyar, Chennai. The results indicated that the concentrations of particulate matter reduced to about 50 � 80 % during the lockdown compared to pre-lockdown. The concentrations of sulphur dioxide and nitrogen dioxide were decreased to 50% and 20%, respectively, within the first week of lockdown. Further the data were compared with the pollution data for the past two years (2018 and 2019). The present study gives insight on the reduction of pollution in proportion to the temporary control of pollution source at particular interval could rejuvenate the environment.

scholarly journals THE NATIONAL CAPITAL UNDER THE EFFECT OF SEVERE AIR POLLUTION – A CONCERN FOR COMMUNITY LIVING AND EXISTENCE

2019 ◽  
pp. 78-82
Author(s):  
Dr. Yashoda Tammineni
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Quality Index ◽  
Air Quality Index ◽  
Pm 2.5 ◽  
Pollution Levels ◽  
The People ◽  
National Capital ◽  
Pm 10 ◽  
National Emergency

It’s of great concern to observe that the capital of our country, Delhi is under the severe grip of air pollution since a couple of days sending most alarming indications even for a national emergency. The Air quality index (AQI) entered the "severe plus" or "emergency" category and the Pollution levels in Delhi peaked to a three-year high in the month of November this year. Alarmingly, the level of particulate matter (PM) in the air reached intolerable level and the real time AQI was as high as 999 at monitoring stations at many places in Delhi. The smog (smoke and fog) has reached such an intolerable state that the people are suffering from severe pulmonary disorders and the visual clearance has enormously reduced leading to road accidents and even effected the air trafficking. Until and unless the AQI comes down drastically general living conditions in Delhi seems to be next to impossible. KEYWORDS: Air quality index (AQI), PM 2.5 Pollution, PM 10 Pollution, Severe Smog, Pulmonary disorders

scholarly journals Understanding Public Response to Air Quality Using Tweet Analysis

2019 ◽  
Vol 5 (3) ◽  
pp. 205630511986765
Author(s):  
Supraja Gurajala ◽  
Suresh Dhaniyala ◽  
Jeanna N. Matthews
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Machine Learning Algorithms ◽  
Mitigation Measures ◽  
Quality Data ◽  
Public Health Issue ◽  
New Delhi ◽  
Public Response ◽  
Pollution Levels ◽  
Adverse Health Effects

Poor air quality is recognized as a major risk factor for human health globally. Critical to addressing this important public-health issue is the effective dissemination of air quality data, information about adverse health effects, and the necessary mitigation measures. However, recent studies have shown that even when public get data on air quality and understand its importance, people do not necessarily take actions to protect their health or exhibit pro-environmental behaviors to address the problem. Most existing studies on public attitude and response to air quality are based on offline studies, with a limited number of survey participants and over a limited number of geographical locations. For a larger survey size and a wider set of locations, we collected Twitter data for a period of nearly 2 years and analyzed these data for three major cities: Paris, London, and New Delhi. We identify the three hashtags in each city that best correlate the frequency of tweets with local air quality. Using tweets with these hashtags, we determined that people’s response to air quality across all three cities was nearly identical when considering relative changes in air pollution. Using machine-learning algorithms, we determined that health concerns dominated public response when air quality degraded, with the strongest increase in concern being in New Delhi, where pollution levels are the highest among the three cities studied. The public call for political solutions when air quality worsens is consistent with similar findings with offline surveys in other cities. We also conducted an unsupervised learning analysis to extract topics from tweets in Delhi and studied their evolution over time and with changing air quality. Our analysis helped extract relevant words or features associated with different air quality–related topics such as air pollution policy and health. Also, the topic modeling analysis revealed niche topics associated with sporadic air quality events, such as fireworks during festivals and the air quality impact on an outdoor sport event. Our approach shows that a tweet-based analysis can enable social scientists to probe and survey public response to events such as air quality in a timely fashion and help policy makers respond appropriately.

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 Evidence of air quality data misreporting in China: An impulse indicator saturation model comparison of local government-reported and U.S. embassy-reported PM2.5 concentrations (2015–2017)

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249063
Author(s):  
Jesse S. Turiel ◽  
Robert K. Kaufmann
Keyword(s):  
Air Quality ◽  
Local Government ◽  
Model Comparison ◽  
Quality Data ◽  
Random Chance ◽  
Pollution Levels ◽  
Reported Data ◽  
Impulse Indicator Saturation ◽  
Air Quality Data ◽  
Monitoring Stations

This paper analyzes hourly PM2.5 measurements from government-controlled and U.S. embassy-controlled monitoring stations in five Chinese cities between January 2015 and June 2017. We compare the two datasets with an impulse indicator saturation technique that identifies hours when the relation between Chinese and U.S. reported data diverges in a statistically significant fashion. These temporary divergences, or impulses, are 1) More frequent than expected by random chance; 2) More positive than expected by random chance; and 3) More likely to occur during hours when air pollution concentrations are high. In other words, relative to U.S.-controlled monitoring stations, government-controlled stations systematically under-report pollution levels when local air quality is poor. These results contrast with the findings of other recent studies, which argue that Chinese air quality data misreporting ended after a series of policy reforms beginning in 2012. Our findings provide evidence that local government misreporting did not end after 2012, but instead continued in a different manner. These results suggest that Chinese air quality data, while still useful, should not be taken entirely at face value.

scholarly journals Changes in air-pollution related behaviour measured by Google Trends Search Volume Index in response to reported air quality in Poland

2021 ◽  
Author(s):  
Wojciech Nazar ◽  
Katarzyna Plata-Nazar
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Winter Season ◽  
Google Trends ◽  
Volume Index ◽  
Quality Data ◽  
Coefficient Of Determination ◽  
Pollution Levels ◽  
Search Volume ◽  
Air Quality Data

Abstract Background Decreased air quality is connected to a higher number of hospital admissions and an increase in daily mortality rates. Thus, Poles’ behavioural response to sometimes elevated air pollution levels is vital. The aim of this study was to carry out analysis of changes in air-pollution related information seeking behaviour in response to nationwide reported air quality in Poland. Methods Google Trends Search Volume Index data was used to investigate Poles’ interest in air pollution-related keywords. PM10 and PM2.5 concentrations measured across Poland between 2016 and 2019 were collected from the Chief Inspectorate of Environmental Protection databases. Pearson Product-Moment Correlation and the R2 correlation coefficient of determination were used to measure spatial and seasonal correlations between reported air pollution levels and the popularity of search queries. Results The highest PM10 and PM2.5 concentrations were observed in southern voivodeships and during the winter season. Similar trends were observed for Poles’ interest in air-pollution related keywords. All R2 coefficient of determination values were > 0.5 and all correlations were statistically significant. Conclusion Poland’s air quality does not meet the World Health Organisation guidelines. Also, the air quality is lower in southern Poland and during the winter season. It appears that Poles are aware of this issue and search for daily air quality data in their location. Greater interest in air quality data in Poland strongly correlates with both higher regional and higher seasonal air pollution levels.

scholarly journals Trend of Particulate Matter PM 2.5 and PM 10 in Dhaka City

1970 ◽  
Vol 46 (3) ◽  
pp. 389-398 ◽  
Author(s):  
MA Rouf ◽  
M Nasiruddin ◽  
AMS Hossain ◽  
MS Islam
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Winter Season ◽  
Ambient Air ◽  
Quality Data ◽  
Dhaka City ◽  
Monsoon Period ◽  
Pm 2.5 ◽  
Pm 10

Dhaka City has been affecting with severe air pollution particularly by particulate matter. The ambient air quality data for particulate matter were collected during April 2002 to September 2005 at the Continuous Air Quality Monitoring Station (CAMS) located at Sangshad Bhaban, Dhaka. Data reveal that the pollution from particulate matter greatly varies with climatic condition. While the level comes down the limit value in the monsoon period (April-October), it goes beyond the limit during non-monsoon time (November-March). The latest data show that during monsoon period PM 10 concentration varies from 50 μg/m3 to 80 μg/m3 and PM 2.5 concentration from 20 μg/m3 to 60 μg/m3 and during non monsoon period PM 10 varies from 100 μg/m3 to 250 μg/m3 and PM 2.5 varies from 70 μg/m3 to 165 μg/m3. The seasonal variation clearly indicates the severe PM 10 pollution during the dry winter season and also sometime during post-monsoon season in Dhaka City. Keywords: Air pollution; PM 2.5; PM 10; Air quality DOI: http://dx.doi.org/10.3329/bjsir.v46i3.9049 BJSIR 2011; 46(3): 389-398

scholarly journals NO2 Concentration in Banepa Valley, Nepal

1970 ◽  
Vol 4 (1) ◽  
pp. 1-11
Author(s):  
Ahmad Kamruzzaman Majumder ◽  
V Krishna Murthy ◽  
Sanjay Nath Khanal ◽  
Dhiraj Giri
Keyword(s):  
Air Quality ◽  
Winter Season ◽  
Maximum Level ◽  
Ambient Air ◽  
World Health ◽  
Quality Data ◽  
Residential Areas ◽  
Pollution Levels ◽  
Air Sampler ◽  
Commercial Area

This study comprised of air quality monitoring during the day time at three municipalities of Banepa, Dhulikhel and Panauti(Known as Banepa Valley) in Kavre district of Nepal. The study was conducted in order to establish a baseline air quality data for those municipalities as the first time ever in the district. In each of those municipalities three air monitoring stations were established representing predominant industrial, commercial and residential areas. Nitrogen Dioxide (NO2) had been estimated from air sampling programme which spanned 7 months and a total of 126 days reflecting winter, premonsoon and monsoon seasons. Low Volume Air (LVA) Sampler and Personal air sampler were used for sampling. UV spectrophotometer was used for estimation of the NO2. The study found that during winter season the concentration of NO2 was more and among the areas commercial area found to be highest level pollution. The over all mean, minimum and maximum level of NO2 was found to be 24.62μg/m3, 11.26μg/m3, 91.20μg/m3 in the Banepa valley. The seasonal trend in pollution levels show that winter > pre-monsoon > monsoon. The pollution concentration trend noted among the areas was commercial > industrial > residential on almost all the occasions. This finding conclude that, most of the time NO2 level are below the National Ambient Air Quality Standards (NAAQS) and World Health Organization (WHO) guideline representing little risk at present in Banepa Valley however commercial area of Banepa is more polluted and is associated with higher NO2 concentration compared to other areas. Keywords: NO2, Nepal, Banepa, air quality, personal air sampler DOI: 10.3126/kuset.v4i1.2878 Kathmandu University Journal of Science, Engineering and Technology Vol.4, No.1, September 2008, pp 1-11

scholarly journals Environmental justice and air quality in Santiago de Chile

2015 ◽  
Vol 17 (3) ◽  
pp. 337-350 ◽  
Author(s):  
Richelle Rose Perez
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Environmental Justice ◽  
Fine Particles ◽  
Metropolitan Region ◽  
Quality Data ◽  
Policy Makers ◽  
Pollution Levels ◽  
Spatial Differences ◽  
Socioeconomic Data

<p><strong>Objective </strong>The metropolitan region in Santiago, Chile has an air quality problem.  However, the larger issue may lie in the inequities created by the distribution of the air pollution.</p><p><strong>Methods </strong>To assess the inequities created by the spatial differences in air pollution, the author analyzed fine particle pollution levels for 2008-2011 at monitoring stations throughout the region. The author also compared air quality data with socioeconomic data.</p><p><strong>Results </strong>The areas of the Santiago metropolitan region with the worst air quality have lower socioeconomic levels. Pollution in these areas reaches levels higher than the current Chilean 24 hour standard for fine particles. These areas also have longer time periods of unhealthy air and 21 % more days with unhealthy levels of air pollution.</p><p><strong>Discussion </strong>The differences in exposure to pollution create an inequality and environmental injustice among the socioeconomic groups in the metropolitan region. Chilean policymakers have the regulatory tools needed to improve environmental justice. However, they need to improve the implementation of these tools in order to achieve that goal: Chilean policy makers should consider local sources of air pollution in the most polluted municipalities; Government decision makers should make extra efforts to listen to the community and improve access to environmental information; Environmental justice advocates should involve stakeholders from the social justice movement and other related areas; Policy makers should track progress towards environmental justice by evaluating differences in health outcomes related to differential exposure to air pollution in different parts of the Santiago metropolitan area.</p>

scholarly journals What is the relationship between the coronavirus crisis and air pollution in Tunisia?

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Nihel Chekir ◽  
Yassine Ben Salem
Keyword(s):  
Air Quality ◽  
Sulfur Dioxide ◽  
Nitrogen Dioxide ◽  
Significant Drop ◽  
Industrial Activity ◽  
Substantial Impact ◽  
Social Distancing ◽  
Pollution Levels ◽  
Positive Side ◽  
Pollutant Concentrations

Abstract Since the beginning of 2020, the COVID-19 pandemic has generated horror and panic around the world. Nevertheless, this terrible crisis is having a positive side effect: it is lowering pollution levels. The outbreak of the coronavirus has caused many governments to impose measures to slow the spread of the virus within populations, such as limiting population displacement, requesting social distancing and the isolation of individuals at home, and reducing industrial activity. In this work, we investigated the effects of governmental measures taken to limit the spread of COVID-19 on the concentrations of air pollutants over four Tunisian cities (Tunis, Sousse, Sfax, and Tataouine). Data on the average daily levels of nitrogen dioxide, sulfur dioxide, carbon monoxide, and particulate matter during January, February, March, and April of 2020 were collected, treated, and analyzed for each city. Curves of average monthly pollutant concentrations from 1 January to 30 April for each city investigated showed that measures taken to reduce the spread of the virus had a substantial impact on emission levels: there were tremendous drops of 51% in NO2 and 52% in SO2 over Sfax City during March compared to those during January, while nitrogen dioxide and sulfur dioxide levels dropped by about 38% and 42%, respectively, over Tunis City and by around 20% for Sousse. During the four months investigated, almost all of the pollutant concentrations showed a significant drop from mid-March. On 12 March, the Tunisian government imposed some individual and collective measures to protect the population from the virus, such as social distancing, limiting transportation, shutting down schools and universities, and reducing industrial activity. A general lockdown was brought in later. Thus, restricting human and industrial activities appeared to affect the air quality in Tunisia, leading to a marked improvement in the air quality index. Graphic abstract

scholarly journals LONG TERM AIR QUALITY ANALYSIS IN REFERENCE TO THERMAL POWER PLANTS USING SATELLITE DATA IN SINGRAULI REGION, INDIA

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 829-834
Author(s):  
H. K. Romana ◽  
R. P. Singh ◽  
D. P. Shukla
Keyword(s):  
Carbon Dioxide ◽  
Air Quality ◽  
Nitrogen Dioxide ◽  
Sulphur Dioxide ◽  
Power Plants ◽  
Anthropogenic Activities ◽  
Thermal Power ◽  
Local Environment ◽  
Thermal Power Plants

Abstract. The exponentially growing population and related anthropogenic activities have led to modifications in local environment. The change in local environment, evolving pattern of land use, concentrations of greenhouse gases and aerosols alter the energy balance of our climate system. This alteration in climate is leading to premature deaths worldwide. This study analyses the air quality of Singrauli region, Madhya Pradesh, India for the past 15 years. Otherwise known as Urjanchal “the energy capital” of India has been declared as critically polluted by CPCB. The study provides an updated list of thermal power plants in the study area and their emission effects on the local environment. The pollutants analyzed in the study are carbon dioxide, methane, nitrogen dioxide, Sulphur dioxide and particulate matter. Long term remotely sensed data was obtained from NASA Giovanni for past 15 years. Statistical analysis is used to characterize seasonal and annual variations of trace gases in the study area. The study concluded that Methane, Carbon dioxide, Nitrogen dioxide and Sulphur dioxide are on an increasing trend with an average rate of 1.03, 0.99, 2.15 and 1.09 annually. Secondly, Methane &amp; SO2, PM2.5 &amp; NO2, PM10 &amp; NO2, CO2 &amp; Methane and PM2.5 &amp; PM10 have strong correlations with a 95% significance. Furthermore, Methane, SO2 and CO2 exhibit cyclic variation with change in season. The study also indicated that maximum aerosols present in the study area are a result of anthropogenic activities.

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