scholarly journals Identifying Air Pollution As a Major Threat to Newly Grown Ecotourism Spot in Baranti, Purulia, West Bengal, India

2021 ◽  
Vol 14 (4) ◽  
pp. 1895-1890
Author(s):  
Dibyendu Saha
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
West Bengal ◽  
Ambient Air ◽  
Sustainable Growth ◽  
Mean Values ◽  
Pm 2.5 ◽  
Lower Productivity ◽  
The Government ◽  
Pm 10

Air pollution is a notable worldwide warning to human health. Every year, air pollution is accountable for more than five million death, out of these 91% occur in lower-middle-income countries. In addition to this, various respiratory & cardiovascular diseases, lower productivity and increased mortality are also related to air pollution, that’s why it’s often called a silent or invisible killer. However, Ecotourism generates opportunities for tourists wishing to enjoy the natural environment without destructing or disturbing its habitats. It is increasingly considered instrumental in helping the local socio-economic sustainable development and also as a means for generating revenues with the object of preserving the local traditional culture and craft. Environmental ambient quality must be considered as a crucial aspect in the predetermining process of prospective tourists and tourism destinations. The present study site Baranti, in Raghunathpur subdivision of Purulia district, West Bengal, India is situated in a splendid location within Baranti Lake and Baranti Hill, both has emerged as a fast-grown ecotourism spot over the last 7-8 years. The present study was carried out through survey questionnaire method from May 2020 (01.05.2020) - November 2020 (30.11.2020) on different categories of respondents like local people, hotel-resort owners & staff, local businessmen and tourists and simultaneously during this period, the air quality was also measured in respect of temperature, humidity, PM 2.5, PM 10, particles and CO2 through Temtop M2000C Air Quality Monitor at the said site. In the observation, ambient air quality was measured at three hours intervals on a day every week and 10 readings were taken from each site at a distance of 10 meters apart and the mean values were considered for statistical analyses. It was found that average PM 2.5, PM 10 & CO2 in ambient air in the study site were 64.26 ug/m3, 89.43 ug/m3 & 701.66 respectively therefore unexpectedly the ambient air is not only polluted but also moderate to unhealthy in respect of the said parameters as judged by the yardstick of Air Quality Guideline Levels laid down by the WHO. A well-defined management plan is required for controlling and minimising the said pollution with the interference of the Government and other agencies for the sustainable growth and development of the said ecotourism spot.

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

Long-Term Exposure to Ambient Air Pollution and Myocardial Infarction-A systematic review and meta-analysis

2020 ◽  
Author(s):  
Wenning Fu ◽  
Li Zou ◽  
Hongbin Xu ◽  
Xiantao Zeng ◽  
Shijiao Yan ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Systematic Review ◽  
Air Pollution ◽  
Cohort Studies ◽  
Meta Analysis ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Pm 2.5 ◽  
Pm 10

Abstract Background and Objective: An increasing amount of epidemiological original studies suggested that long-term exposure to particulate matter (PM 2.5 and PM 10 ) could be associated with the risk of myocardial infarction(MI), but the results were inconsistent. We aimed to synthesized available cohort studies to identify the association between ambient air pollution (PM 2.5 and PM 10 ) and MI risk by a meta-analysis. Methods: PubMed and Embase were searched through September 2019 to identify studies that met predetermined inclusion criterion. Reference lists from retrieved articles were also reviewed. A random-effects model was used to calculate the pooled relative risk ( RR ) and 95% confidence intervals ( CI ). Results: Twenty-two cohort studies involving 6,567,314 participants and 865,98 patients with MI were included in this systematic review. The pooled results showed that higher levels of ambient air pollution (PM 2.5 and PM 10 ) exposure were significantly associated with the risk of MI. The pooled relative ratio ( RR) for each 10-μg/m 3 increment in PM 2.5 and PM 10 were 1.20 (95% CI : 1.11–1.29), and1.03 (95% CI :1.00-1.07) respectively. Exclusion of any single study did not materially alter the combined risk estimate. Conclusions: Integrated evidence from cohort studies supports the hypothesis that long-term exposure to PM 2.5 and PM 10 as a risk factor for MI.

scholarly journals Impact of Air Pollution on Lung Function among Preadolescent Children in Two Cities in Poland

2021 ◽  
Vol 10 (11) ◽  
pp. 2375
Author(s):  
Piotr Dąbrowiecki ◽  
Łukasz Adamkiewicz ◽  
Dominika Mucha ◽  
Piotr Oskar Czechowski ◽  
Mateusz Soliński ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Lung Function ◽  
Ambient Air ◽  
Forced Expiratory Volume ◽  
Ambient Air Pollution ◽  
Mean Values ◽  
Baltic Coast ◽  
Allergic Symptoms ◽  
The Baltic

Ambient air pollution impairs lung development in children, particularly in industrialized areas. The air quality in Zabrze, a city located in the Upper Silesian Industrial Region of Poland, is among the worst in Europe. We compared lung function and the frequency of respiratory or allergic symptoms between children living in Zabrze and those living in Gdynia, a city on the Baltic coast, which has the best long-term air quality in Poland. We enrolled children aged 9–15 years from both cities who were able to perform a spirometry. The following spirometry variables were measured for all participants: forced vital capacity (FVC), forced expiratory volume during the first second of expiration (FEV1), FEV1/FVC index, and peak expiratory flow (PEF). The frequencies of respiratory or allergic symptoms were taken from a survey completed by the participants’ parents. In total, 258 children from Gdynia and 512 children from Zabrze were examined. The mean values of FVC, FEV1, and PEF were significantly greater among children in Gdynia than those reported in Zabrze (p ≤ 0.032), and the frequencies of seasonal rhinorrhea (p = 0.015) or coughing episodes (p = 0.022) were significantly higher in Zabrze than in Gdynia. In conclusion, lung function was significantly impaired in children living in Zabrze, an area which is associated with poor air quality. Strategies to improve air quality in the Silesia region are urgently needed.

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 Data-driven regionalization for analyzing the spatiotemporal characteristic of air quality in China

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Sheng Li ◽  
Jiangtao Liu ◽  
Chao Wu
Keyword(s):  
Principal Component Analysis ◽  
Air Pollution ◽  
Cluster Analysis ◽  
Air Quality ◽  
Principal Component ◽  
Ambient Air ◽  
Component Analysis ◽  
Data Driven ◽  
Regional Collaboration ◽  
The Government

<p><strong>Abstract.</strong> With the development of urbanization and industrialization, the degradation of ambient air quality has become a serious issue that impacts human health and the environment; thus, it has attracted more attention from scholars. Usually, the mass concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3) and particulate matter with an aerodynamic diameter less than 10&amp;thinsp;&amp;mu;m and 2.5&amp;thinsp;&amp;mu;m (PM10 and PM2.5) are used to evaluate air quality. A commonly used data-driven regionalization framework for studying air quality issues, identifying areas with similar air pollution behavior and locating emission sources involves an incorporation of the principal component analysis (PCA) with cluster analysis (CA) methods. However, the traditional PCA does not consider spatial variations, which is a notable issue in geographic studies. This article focuses on extracting the local principal components (PCs) of air quality indicators based on a geographically weighted principal component analysis (GWPCA), which is superior to the PCA when considering spatial heterogeneity. Then, a spatial cluster analysis (SCA) is used to identify the areas with similar air pollution behavior based on the results of the GWPCA. The results are all visualized and show that the GWPCA has a higher explanatory ability than the traditional PCA. Our modified framework based on the GWPCA and SCA for assessing air quality can effectively guide environmentalists and geographers in evaluating and improving air quality from a new perspective. Furthermore, the visualization results can be used by city planners and the government for monitoring and managing air pollution. Finally, policy suggestions are recommended for mitigating air pollution via regional collaboration.</p>

Temporal Variation of Urban Ambient Air Quality in Nanchong, China

2013 ◽  
Vol 864-867 ◽  
pp. 953-957 ◽  
Author(s):  
You Ping Li ◽  
Hong Zhou ◽  
Hui Fang Liu
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Temporal Variation ◽  
Ambient Air ◽  
Urban Air Quality ◽  
Urban Air ◽  
Ambient Air Quality ◽  
Mean Values ◽  
June July ◽  
Mass Concentrations

The study applied 2008-2012 hourly mass concentrations of SO2, NO2and PM10and air pollution indexes (API) to discuss the temporal variation of urban air quality in Nanchong, a southwest city in China. The results showed that the total annual mean SO2, NO2and PM10concentrations during the 5 years were 0.045±0.004mg/m3, 0.035±0.005mg/m3, 0.061±0.001 mg/m3, respectively. And the annual mean concentrations and API values presented decreasing tendency, which were less than the annual second-level air quality limit except for NO2(0.042mg/m3) in 2008. In addition, the monthly mean values in spring and winter were higher than those in summer and fall, which the maximum appeared in December, January and February and the minimum appeared in June, July and August. The ratio of reaching standard presented increasing tendency, but PM10and SO2were the main contribution to air pollution in Nanchong.

scholarly journals Using Multi-Angle Imaging SpectroRadiometer Aerosol Mixture Properties for Air Quality Assessment in Mongolia

2018 ◽  
Vol 10 (8) ◽  
pp. 1317 ◽  
Author(s):  
Meredith Franklin ◽  
Khang Chau ◽  
Olga Kalashnikova ◽  
Michael Garay ◽  
Temuulen Enebish ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Capital City ◽  
World Health ◽  
Dust Particles ◽  
Support Vector ◽  
Daily Maximum ◽  
Pm 2.5 ◽  
Pm 10

Ulaanbaatar (UB), the capital city of Mongolia, has extremely poor wintertime air quality with fine particulate matter concentrations frequently exceeding 500 μg/m3, over 20 times the daily maximum guideline set by the World Health Organization. Intensive use of sulfur-rich coal for heating and cooking coupled with an atmospheric inversion amplified by the mid-continental Siberian anticyclone drive these high levels of air pollution. Ground-based air quality monitoring in Mongolia is sparse, making use of satellite observations of aerosol optical depth (AOD) instrumental for characterizing air pollution in the region. We harnessed data from the Multi-angle Imaging SpectroRadiometer (MISR) Version 23 (V23) aerosol product, which provides total column AOD and component-particle optical properties for 74 different aerosol mixtures at 4.4 km spatial resolution globally. To test the performance of the V23 product over Mongolia, we compared values of MISR AOD with spatially and temporally matched AOD from the Dalanzadgad AERONET site and find good agreement (correlation r = 0.845, and root-mean-square deviation RMSD = 0.071). Over UB, exploratory principal component analysis indicates that the 74 MISR AOD mixture profiles consisted primarily of small, spherical, non-absorbing aerosols in the wintertime, and contributions from medium and large dust particles in the summertime. Comparing several machine learning methods for relating the 74 MISR mixtures to ground-level pollutants, including particulate matter with aerodynamic diameters smaller than 2.5 μm ( PM 2.5 ) and 10 μm ( PM 10 ), as well as sulfur dioxide ( SO 2 ), a proxy for sulfate particles, we find that Support Vector Machine regression consistently has the highest predictive performance with median test R 2 for PM 2.5 , PM 10 , and SO 2 equal to 0.461, 0.063, and 0.508, respectively. These results indicate that the high-dimensional MISR AOD mixture set can provide reliable predictions of air pollution and can distinguish dominant particle types in the UB region.

scholarly journals Air Quality Assessment in the State of Kuwait during 2012 to 2017

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 678
Author(s):  
Adeeba Al-Hurban ◽  
Sawsan Khader ◽  
Ahmad Alsaber ◽  
Jiazhu Pan
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Meteorological Factors ◽  
Ambient Air ◽  
The State ◽  
Ambient Air Pollution ◽  
Northeast Monsoon ◽  
Residential Areas ◽  
Industrial Areas ◽  
The State Of Kuwait

This study aimed to examine the trend of ambient air pollution (i.e., ozone (O3), nitrogen monoxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOx), sulfur dioxide (SO2), carbon monoxide (CO), benzene (C6H6) and particulate matter with an aerodynamic diameter smaller than 10 microns (PM10), and non-methane hydrocarbons (NMHCs) at 10 monitoring stations located in the main residential and industrial areas in the State of Kuwait over 6 years (2012–2017). We found that the SO2 level in industrial areas (0.065 ppm) exceeded the allowable range of SO2 in residential areas (0.030 ppm). Air pollution variables were defined by the Environmental Public Authority of Kuwait (K-EPA). In this study, integrated statistical analysis was performed to compare an established air pollution database to Kuwait Ambient Air Quality Guidelines and to determine the association between pollutants and meteorological factors. All pollutants were positively correlated, with the exception of most pollutants and PM10 and O3. Meteorological factors, i.e., the ambient temperature, wind speed and humidity, were also significantly associated with the above pollutants. Spatial distribution mapping indicated that the PM10 level remained high during the southwest monsoon (the hot and dry season), while the CO level was high during the northeast monsoon (the wet season). The NO2 and O3 levels were high during the first intermonsoon season.

scholarly journals Functional ANOVA approaches for detecting changes in air pollution during the COVID-19 pandemic

2021 ◽  
Author(s):  
Christian Acal ◽  
Ana M. Aguilera ◽  
Annalina Sarra ◽  
Adelia Evangelista ◽  
Tonio Di Battista ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Functional Data ◽  
Central Italy ◽  
Principal Component ◽  
Functional Principal Component Analysis ◽  
Area Of Interest ◽  
Pm 10 ◽  
The Impact ◽  
Monitoring Stations

AbstractFaced with novel coronavirus outbreak, the most hard-hit countries adopted a lockdown strategy to contrast the spread of virus. Many studies have already documented that the COVID-19 control actions have resulted in improved air quality locally and around the world. Following these lines of research, we focus on air quality changes in the urban territory of Chieti-Pescara (Central Italy), identified as an area of criticality in terms of air pollution. Concentrations of $$\hbox {NO}_{{2}}$$ NO 2 , $$\hbox {PM}_{{10}}$$ PM 10 , $$\hbox {PM}_{2.5}$$ PM 2.5 and benzene are used to evaluate air pollution changes in this Region. Data were measured by several monitoring stations over two specific periods: from 1st February to 10 th March 2020 (before lockdown period) and from 11st March 2020 to 18 th April 2020 (during lockdown period). The impact of lockdown on air quality is assessed through functional data analysis. Our work makes an important contribution to the analysis of variance for functional data (FANOVA). Specifically, a novel approach based on multivariate functional principal component analysis is introduced to tackle the multivariate FANOVA problem for independent measures, which is reduced to test multivariate homogeneity on the vectors of the most explicative principal components scores. Results of the present study suggest that the level of each pollutant changed during the confinement. Additionally, the differences in the mean functions of all pollutants according to the location and type of monitoring stations (background vs traffic), are ascribable to the $$\hbox {PM}_{{10}}$$ PM 10 and benzene concentrations for pre-lockdown and during-lockdown tenure, respectively. FANOVA has proven to be beneficial to monitoring the evolution of air quality in both periods of time. This can help environmental protection agencies in drawing a more holistic picture of air quality status in the area of interest.

scholarly journals Air pollution and out-of-hospital cardiac arrest risk

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
L Moderato ◽  
D Lazzeroni ◽  
A Biagi ◽  
T Spezzano ◽  
B Matrone ◽  
...  
Keyword(s):  
Air Pollution ◽  
Cardiac Arrest ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
External Temperature ◽  
Pm 2.5 ◽  
Pm10 And Pm2.5 ◽  
Short Term Exposure ◽  
The Impact ◽  
Hospital Cardiac Arrest

Abstract Introduction Out-of-hospital cardiac arrest (OHCA) is a leading cause of death worldwide; it accounts for up to 50% of all cardiovascular deaths.It is well established that ambient air pollution triggers fatal and non-fatal cardiovascular events. However, the impact of air pollution on OHCA is still controversial. The objective of this study was to investigate the impact of short-term exposure to outdoor air pollutants on the incidence of OHCA in the urban area of Piacenza, Italy, one of the most polluted area in Europe. Methods From 01/01/2010 to 31/12/2017 day-by-day PM10 and PM2.5 levels, as well as climatic data, were extracted from Environmental Protection Agency (ARPA) local monitoring stations. OHCA were extracted from the prospective registry of Community-based automated external defibrillator Cardiac arrest “Progetto Vita”. OHCA data were included: audio recordings, event information and ECG tracings. Logistic regression analysis was used to estimate the association between the risk of OHC, expressed as odds ratios (OR), associated with the PM10 and PM2.5 levels. Results Mean PM10 levels were 33±29 μg/m3 and the safety threshold (50 μg/m3) recommended by both WHO and Italian legislation has been exceeded for 535 days (17.5%). Mean PM 5 levels were 33±29 μg/m3. During the follow-up period, 880 OHCA were recorded on 750 days; the remaining 2174 days without OHCA were used as control days. Mean age of OHCA patients was 76±15 years; male gender was prevalent (55% male vs 45% female; &lt;0.001). Concentration of PM10 and PM 2.5 were significantly higher on days with the occurrence of OHCA (PM10 levels: 37.7±22 μg/m3 vs 32.7±19 μg/m3; p&lt;0.001; PM 2.5 levels: 26±16 vs 22±15 p&lt;0.001). Risk of OHCA was significantly increased with the progressive increase of PM10 (OR: 1.009, 95% CI 1.004–1.015; p&lt;0.001) and PM2.5 levels (OR 1.012, 95% CI 1.007–1.017; p&lt;0.001). Interestingly, the above mentioned results remain independent even when correct for external temperature or season (PM 2.5 levels: p=0.01 – PM 10 levels: p=0.002), Moreover, dividing PM10 values in quintiles, a 1.9 fold higher risk of cardiac arrest has been showed in the highest quintile (Highest quintile cut-off: &lt;48μg/m3) Conclusions In large cohort of patients from a high pollution area, both PM10 and PM2.5 levels are associated with the risk of Out-of-hospital cardiac arrest. PM10 and PM2.5 levels and risk of OHCA Funding Acknowledgement Type of funding source: None

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