scholarly journals Analysis of Ambient Air Quality Based On Exceedance Factor and Air Quality Index for Siliguri City, West Bengal

2020 ◽  
pp. 236-246 ◽  
Author(s):  
Subham Roy ◽  
Nimai Singha
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
Ambient Air ◽  
Air Quality Index ◽  
National Standard ◽  
Pollution Level ◽  
Pm2.5 And Pm10 ◽  
The City ◽  
Exceedance Factor

Bad air is one of the key concerns for most of the urban centres today, and Siliguri is no exceptions to this. In order to assess the air quality of Siliguri, Exceedance factor (EF) method was applied based on the average annual concentration of the pollutants named as; NO2, SO2, PM2.5 and PM10 and it is found that PM2.5 and PM10 are the major pollutants that pose a severe threat for the city. After applying the EF method, it is found that the values of PM2.5 was between moderate to high pollution level and for PM10 it falls under high to critical pollution level. On the other hand, the concentration of NO2 and SO2 falls under moderate to low pollution level. Through trend analysis of the various pollutants, it is found that their concentration was varying in nature. In case of PM10, the trend shows high concentration which exceeds national standard; whereas PM2.5 shows its concentration near towards violating the national standard soon if not checked. In contrast, trends of NO2 and SO2 were recorded lower than the national standard. The present situation of ambient air of Siliguri was analyzed based on Air Quality Index which reveals that air quality of the city can be classified into two seasons, i.e. clean air period (from April to October) and polluted period (from November to March). Lastly, the annual trends of PM2.5 and PM10 were constructed as they are the major pollutants, and it shows their skewed nature during winter months which results in smog episodes. It unveils how critical the situation of air quality of Siliguri became especially during winter months which seek immediate attention. Thus the study tries to present a vivid scenario about the present air quality of Siliguri, which concludes with some of the suggestions to restrain the air quality.

scholarly journals Emission from Uyo Main Refuse Dumpsite and Potential Impact on Health

2020 ◽  
pp. 8-13
Author(s):  
S. A. Nta ◽  
M. J. Ayotamuno ◽  
A. H. Igoni ◽  
R. N. Okparanma
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
Ambient Air ◽  
Air Quality Index ◽  
Volatile Organic Carbon ◽  
Highly Sensitive ◽  
Volatile Organic ◽  
Landfill Emissions ◽  
Potential Impact ◽  
Pm2.5 And Pm10

This paper presents potential impact on health of emission from landfill site on Uyo village road, Uyo local government area of Akwa Ibom State, Nigeria. Three sampling points were assessed for particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), sulphur dioxide (SO2), carbon monoxide (CO), hydrogen sulphide H2S, ammonia (NH3), total volatile organic carbon (TVOC) and hydrogen cyanide (HCN) using highly sensitive digital portable meters. The data obtained were expressed in terms of an air quality index. Air quality index indicates that the ambient air can be described as unhealthy for sensitive groups for NO2, unhealthy for SO2 and PM2.5 and moderate for CO, respectively. H2S, NH3, TVOC, HCN, PM10 were not indicated in USEPA air quality standards. It recommended that stringent and proper landfill emissions management together with appropriate burning of wastes should be considered in the study area to ease the risks associated with these pollutants on public health.

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.

APPLICATION OF AIR QUALITY INDEX AND INVERSE DISTANCE WEIGHTING FOR MAPPING THE DISTRIBUTION OF AIR POLLUTION AT SEVERAL URBAN DISTRICTS OF HANOI CITY

2020 ◽  
Vol 65 (10) ◽  
pp. 189-200
Author(s):  
Khac Dang Vu ◽  
Anh Nguyen Thi Van
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Quality Index ◽  
Ambient Air ◽  
Inverse Distance Weighting ◽  
Air Quality Index ◽  
Pollution Level ◽  
Urban Districts ◽  
Distance Weighting ◽  
Inverse Distance

The air pollution level can be assessed using air quality index - AQI calculated from the concentration of some gases and particle matters which are measured at ambient air quality monitoring stations. The calculated AQI values are characterized by temporal continuity but spatial discontinuity. However, AQI values of each monitoring station is interpolated by the IDW (Inverse Distance Weighting) method in GIS which helps us to assess the air quality at a detailed and specific level for every location in the study area by establishing distribution maps of air pollution. The interpolation of AQI values for zoning air quality in several urban districts of Hanoi during the Winter (October, November, December 2019) shows that in general, the areas with a very bad level of air quality occupied an important surface in the Northwest of urban districts (on the territory of Bac Tu Liem, Ba Dinh, Tay Ho, Cau Giay) for last 3 months of the year. The areas with a bad level of air quality occupied a large surface in the Southeast in October and December, but its surface became narrow in November. But in November, areas having a bad level of air quality were expanded to the Southeast while they occupied only a small surface at the center of the study area in October and December. Although the distribution of each level vary in terms of coverage, their common pattern has been conserved during three months of Winter. The distribution map of air quality provides the complete picture of the air pollution situation and it helps to adequately evaluate this issue in the urban districts of Hanoi city.

scholarly journals Effect of the COVID-19 Lockdown on Ambient Air Quality in Major Cities of Nepal

2021 ◽  
Vol 11 (29) ◽  
Author(s):  
Bashu Dev Baral ◽  
Kapil Thapa
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
Positive Association ◽  
Ambient Air ◽  
Air Quality Index ◽  
Ambient Air Quality ◽  
Flight Operations ◽  
Financial Interests ◽  
Pm2.5 And Pm10 ◽  
Mean Concentration

Background. The Nepalese government announced a nationwide lockdown beginning on March 24, 2020 as an attempt to restrain the spread of COVID-19. The prohibition in flight operations and movement of vehicles, factory shutdowns and restriction in people's movement due to the lockdown led to a significant reduction in the amounts of pollutants degrading air quality in many countries. Objectives. The present study aimed to analyze changes in particulate matter (PM) emissions and the air quality index (AQI) of six cities in Nepal i.e., Damak, Simara, Kathmandu, Pokhara, Nepalgunj and Surkhet due to the nationwide lockdown in response to the COVID-19 outbreak. Methods. Daily PM concentrations of each of the six study cities from January 24 to September 21, 2020 were obtained from the World Air Quality Index project (https://aqicn.org) and analyzed using R Studio software. The drop percentage was calculated to determine the change in PM2.5 and PM10 concentration during different time periods. Independent sample Mann–Whitney U tests were performed to test the significance of differences in mean concentration for each site during the lockdown period (24 March–24 July 2020) and its corresponding period in 2019. Similarly, the significance of differences in mean concentrations between the lockdown period and the period immediately before lockdown (23 January–23 March) was also examined using the same test. Results. During the lockdown period, in overall Nepal, AQIPM2.5 and AQIPM10 were within the moderate zone for the maximum number of days. As a result of the lockdown, the highest immediate and final drop of PM2.5 was observed in Damak (26.37%) and Nepalgunj (80.86%), respectively. Similarly, the highest immediate drop of PM10 was observed in Surkhet (37.22%) and finally in Nepalgunj (81.14%). Analysis with the Mann–Whitney U test indicated that for both PM types, all sites showed a statistically significant (p < 0.05) difference in mean concentrations during lockdown and the corresponding period in 2019. Conclusions. The present study explored the positive association between vehicular movement and PM emissions, highlighting the need for alternative fuel sources to improve air quality and human health. Competing Interests. The authors declare no competing financial interests.

scholarly journals Does Air Quality Influence the Spread of the SARS - COV2 in Metropolitan Cities? - A Case Study from Urban India

2021 ◽  
Vol 16 (2) ◽  
pp. 628-648
Author(s):  
Souradip Basu ◽  
Rajdeep Das ◽  
Sohini Gupta ◽  
Sayak Ganguli
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
Quality Parameters ◽  
Air Pollutant ◽  
Air Quality Index ◽  
Pollution Level ◽  
Metropolitan Cities ◽  
The Government

COVID 19 pandemic has gradually established itself as the worst pandemic in the last hundred years around the world after initial outbreak in China, including India. To prevent the spread of the infection the Government implemented lockdown measure initially from 24th March to 14th April, 2020 which was later extended to 3rd May, 2020. This lockdown imposed restrictions in human activities, vehicular movements and industrial functioning; resulting in reduced pollution level in the cities. This study was initiated with the objective to identify the change in the air quality of seven megacities in India and to determine any correlation between the active COVID cases with the air quality parameters. Air quality dataset of the most common parameters (PM2.5, PM10, SO2, NO2, NH3, CO and Ozone) along with air quality index for 70 stations of seven megacities (Delhi, Mumbai, Kolkata, Bengaluru, Hyderabad, Chennai and Chandigarh) were analysed. Comparison was made between AQI of pre lockdown and during lockdown periods. The results obtained indicate sufficient improvement in air quality during the period of the lockdown. For the next part of the study active COVID cases during the lockdown were compared to the air quality change of that period. A significant correlation between active COVID case and change in the air quality was observed for Delhi and Kolkata with 0.51 and 0.64 R2 values respectively. A positive correlation was also observed between air pollutant parameters and incidents of COVID cases in this study. Thus from the analysis it was identified that air quality index improved considerably as a result of the nationwide lockdown however, there was no significant impact of this improvement on the infection rate of the prevailing pandemic.

scholarly journals Health Implications of Air Quality Index of Fine and Coarse Particulates During Outdoor Combustion of Biomass in the Niger Delta, Nigeria

2021 ◽  
pp. 21-26
Author(s):  
Glory Richard ◽  
Wisdom Ebiye Sawyer ◽  
Sylvester Chibueze Izah
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Niger Delta ◽  
Quality Index ◽  
Fine Particulate Matter ◽  
Ambient Air ◽  
Air Quality Index ◽  
World Health ◽  
Health Implications ◽  
Pm2.5 And Pm10

Rural dwellers in the Niger Delta commonly use biomass for cooking and other activities. This study investigated the air quality index of fine particulate matter 2.5 (PM2.5) and coarse particulate matter 10 (PM10) and its health implications during outdoor combustion of fuelwood in the Niger Delta, Nigeria. A mini-volume air sampler (model: AEROCET 531) was used to measure PM2.5, PM10, and total suspended particulate (TSP) in the study area. A bimonthly triplicate sampling was carried out at 3 distances in 4 different states spanning one Calendar year. The results showed that PM2.5, PM10, and TSP ranged from 19.85 – 27.95µg/m3, 55.66 – 80.59µg/m3, and 74.29 – 140.44µg/m3, respectively. There was statistical variation across the different months, locations and distances, and their interactions. The concentration of PM2.5 and PM10 occasionally exceeds the World Health Organization limits of 25µg/m3 and 50µg/m3 for 24-hourly average, respectively. The air quality index showed no contamination to slight contamination in both seasons. The air quality index indicates that the air is slightly contaminated at the emission source which decreased as distance away increased. Therefore, there is a need for the regulatory agencies to consider PM2.5 and PM10 in the monitoring of ambient air quality to forestall potential hazards associated with human exposure.

scholarly journals Forecasting of outdoor air quality index using adaptive Neuro Fuzzy Inference System

2022 ◽  
Author(s):  
Haripriyan Uthayakumar ◽  
Perarasu Thangavelu ◽  
Saravanathamizhan Ramanujam
Keyword(s):  
Air Quality ◽  
Fuzzy Inference System ◽  
Quality Index ◽  
Fuzzy Inference ◽  
Ambient Air ◽  
Air Quality Index ◽  
Quality Data ◽  
Pollution Level ◽  
Inference System ◽  
Neuro Fuzzy

Introduction: The estimation of air pollution level is well indicated by Air Quality Index (AQI), which tells how unhealthy the ambient air is and how polluted it can become in near future. Hence, the predictions or modeling of AQI is always of greater concern among researchers and this present study aims to develop such a model for forecasting the AQI. Materials and methods: A combination of Artificial Neural Network (ANN) and Fuzzy logic (FL) system, called Adaptive Neuro-Fuzzy Inference System (ANFIS) have been considered for model development. Daily air quality data (PM2.5 and PM10) and meteorological data (temperature and humidity) over a period of March 2020 to March 2021 were used as the input data and AQI as the output variable for the ANFIS model. The performances of models were evaluated based on Root Mean Square Error (RMSE), Regression coefficient (R2) and Average Absolute Relative Deviation (AARD). Results: A total of 100 datasets is split into training (70), testing (15) and simulation (15). Gaussian and Constant membership functions were employed for classifications and the final index consisted of 81 inference (IF/THEN) rules. The ANFIS Simulation result shows an R2 and RMSE value of 0.9872 and 0.0287 respectively. Conclusion: According to the results from this study, ANFIS based AQI is a comprehensive tool for classification of air quality and it is inclined to produce accurate results. Therefore, local authorities in air quality assessment and management schemes can apply these reliable and suitable results.

scholarly journals Analysis of Air Quality Index Distribution of PM10 and PM2.5 Concentrations in Ambient Air of Al-Hillah City, Iraq

2021 ◽  
Vol 1058 (1) ◽  
pp. 012014
Author(s):  
Ruqayah Ali Grmasha ◽  
Shahla N. A. Al-Azzawi ◽  
Osamah J. Al-sareji ◽  
Talal Alardhi ◽  
Mawada Abdellatif ◽  
...  
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
Ambient Air ◽  
Air Quality Index ◽  
Pm10 And Pm2.5 ◽  
Index Distribution

scholarly journals Implementation of dataflow programming based Fuzzy Logic algorithm for gas concentration index in around of Sidoarjo mudflow, Indonesia

2018 ◽  
Vol 154 ◽  
pp. 03012
Author(s):  
Edita Rosana Widasari ◽  
Barlian Henryranu Prasetio ◽  
Hurriyatul Fitriyah ◽  
Reza Hastuti
Keyword(s):  
Air Pollution ◽  
Fuzzy Logic ◽  
Air Quality ◽  
Quality Index ◽  
Methane Concentration ◽  
Air Quality Index ◽  
Pollution Level ◽  
Affected Area ◽  
Fuzzy Logic Algorithm ◽  
Dataflow Programming

Sidoarjo mudflow or known as Lapindo mudflow erupted since 2006. The Sidoarjo mudflow is located in Sidoarjo City, East Java, Indonesia. The mudflow-affected area has high air pollution level and high health risk. Therefore, in this paper was implemented a system that can categorize the level of air pollution into several categories. The air quality index can be categorized using fuzzy logic algorithm based on the concentration of air pollutant parameters in the mudflow-affected area. Furthermore, Dataflow programming is used to process the fuzzy logic algorithm. Based on the result, the measurement accuracy of the air quality index in the mudflow-affected area has an accuracy rate of 93.92% in Siring Barat, 93.34% in Mindi, and 95.96% in Jatirejo. The methane concentration is passes the standard quality even though the air quality index is safe. Hence, the area is indicated into Hazardous level. In addition, Mindi has highest and stable methane concentration. It means that Mindi has high-risk air pollution.

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