scholarly journals Air Quality Index: A Case of One-Day Monitoring in 253 Nigerian Urban and Suburban Towns

Author(s):  
Francis Olawale Abulude ◽  
I. A. Abulude ◽  
S. D. Oluwagbayide ◽  
S. D. Afolayan ◽  
D Ishaku

Abstract Government departments use the air quality index (AQI) to inform the public about how unhealthy the air is now or may become in the future. As the AQI increases, so do the health threats. It is a daily air quality index that is used to report on air quality. In addition, a measure of how air pollution impacts one's health over a limited period of time. The AQI was created to assist people in understanding how local air quality affects their health. Therefore the aim of the study was to assess one-day air quality of 253 towns in Nigeria, thereby determining the health threat in these towns. The data was collected from the Tutiempo Network's regular data set by the EPA Environmental Protection Agency. Data on all of the major pollutants (O3, PM2.5, PM10, CO, NO, SO2) was collected and statistical analysis was performed. Kura (Kano State), a town in northern Nigeria, recorded the highest level of 184, while Idiroko, a border town (Nigeria-Benin Republic) in Ogun State, had the least value of 41. Kura was portrayed as unhealthy, while Idiroko was portrayed as healthy, implying that Idiroko air poses little to no danger, while Kura air showed that certain people of the general public, as well as members of sensitive groups, could encounter more severe health effects.

2021 ◽  
Vol 8 (1) ◽  
pp. 4
Author(s):  
Francis Abulude ◽  
Ifeoluwa Abulude ◽  
Samuel Oluwagbayide ◽  
Segun Afolayan ◽  
Deborah Ishaku

Government departments use the air quality index (AQI) to inform the public about how unhealthy the air is now or may become in the future. As the AQI increases, so do health threats. In addition to reporting daily air quality, it is also a measure of how air pollution impacts one’s health over a limited period of time. The AQI was created to assist people in understanding how local air quality affects their health. Therefore, the aim of this study was to assess the air quality of one day of 253 towns in Nigeria, thereby determining the health threat in these towns. The data were collected from the Tutiempo Network’s regular dataset by the Environmental Protection Agency (EPA). Data on all of the major pollutants (O3, PM2.5, PM10, CO, NO, SO2) were collected and statistical analysis was performed. Kura (Kano State), a town in northern Nigeria, recorded the highest level of 184, while Idiroko, a border town (Nigeria–Benin Republic) in Ogun State, had the lowest value of 41. Kura was portrayed as unhealthy, while Idiroko was portrayed as healthy, implying that Idiroko air poses little to no danger, while Kura air showed that certain people of the general public, as well as members of sensitive groups, could encounter more severe health effects.


The surveys regarding air pollution shows that there has been a hasty growth due to the emission of fuels and exhaust gases from factories. The Air Quality Index (AQI) has been launched to note the contemporary status of the air quality. The intent of AQI is to aid every individual know how the regional air quality will make an impact on them. The Environmental Protection Agency assess the AQI for five major air pollutants namely Nitrogen dioxide (NO2), ground-level ozone (O3), particle pollution (PM10, PM2.5), carbon monoxide (CO), and sulphur dioxide (SO2). The intent of the project is to congregate real-time Air Quality Index from distinct monitoring stations across India, analysing the data and reporting on it. Collect the real-time data using the API key provided by Open Government Data (OGD) platform India. This is done by making use of Microsoft Business Intelligence (MSBI) and Power BI Tools to transform, analyse and visualize the data. This project can be utilized to develop various programs like Ozone today in Europe and in mobile applications which acts as an alert system that can protect people from air pollution.


Author(s):  
Mageshkumar P ◽  
Ramesh S ◽  
Angu Senthil K

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.


2018 ◽  
Vol 12 ◽  
pp. 117863021879286 ◽  
Author(s):  
Amit Kumar Gorai ◽  
Paul B Tchounwou ◽  
SS Biswal ◽  
Francis Tuluri

Rising concentration of air pollution and its associated health effects is rapidly increasing in India, and Delhi, being the capital city, has drawn our attention in recent years. This study was designed to analyze the spatial and temporal variations of particulate matter (PM2.5) concentrations in a mega city, Delhi. The daily PM2.5 concentrations monitored by the Central Pollution Control Board (CPCB), New Delhi during November 2016 to October 2017 in different locations distributed in the region of the study were used for the analysis. The descriptive statistics indicate that the spatial mean of monthly average PM2.5 concentrations ranged from 45.92 μg m−3 to 278.77 μg m−3. The maximum and minimum spatial variance observed in the months of March and September, respectively. The study also analyzed the PM2.5 air quality index (PM2.5—Air Quality Index (AQI)) for assessing the health impacts in the study area. The AQI value was determined according to the U.S. Environmental Protection Agency (EPA) system. The result suggests that most of the area had the moderate to very unhealthy category of PM2.5-AQI and that leads to severe breathing discomfort for people residing in the area. It was observed that the air quality level was worst during winter months (October to January).


Koneksi ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 366
Author(s):  
Nishya Gavrila ◽  
Farid Rusdi

On July 29, 2019, Jakarta's air quality was ranked first on the AirVisual.com website with the worst air quality statement in the world. According to AirVisual.com, Jakarta's Air Quality Index (AQI) stands at 188, which means the air quality in Jakarta is not healthy. On the same date, Detik.com and Kompas.com reported on the poor quality of Jakarta's air. The reason the author chose the latter is because based on the Alexa.com site, both news portals have the highest number of visitor readers in Indonesia. This study aims to determine and analyze Detik.com and Kompas.com in framing unhealthy air quality in Jakarta. The approach in this study uses a constructivist paradigm. by using Robert N. Entman's framing model that defines problems, diagnoses causes, makes moral judgment and recommendation treatment. From the results of this study, Detik.com further explained the response of Anies Baswedan regarding poor air quality in Jakarta, while on Kompas.com that poor air quality in Jakarta was a challenge for the government and the government could be convicted if it continued. Pada tanggal 29 Juli 2019, kualitas udara Jakarta menempati peringkat pertama di situs AirVisual.com dengan pernyataan kualitas udara terburuk di dunia. Menurut AirVisual.com, Air Quality Index (AQI) Jakarta berada pada angka angka 188, yang artinya kualitas udara di Jakarta tidak sehat. Pada tanggal yang sama Detik.com dan Kompas.com memberitakan tentang buruknya kualitas udara Jakarta. Alasan penulis memilih kedua tersebut karena berdasarkan situs Alexa.com, kedua portal berita tersebut memiliki jumlah pengunjung pembaca terbanyak di Indonesia. Penelitian ini bertujuan untuk mengetahui dan menganalisis Detik.com dan Kompas.com dalam membingkai kualitas udara di Jakarta yang tidak sehat.Pendekatan dalam penelitian ini memakai paradigma konstruktivis, dengan menggunakan framing model Robert N. Entman yakni define problems, diagnose cause, make moral judgement dan treatment recommendation. Dari hasil penelitian ini, Detik.com lebih menjelaskan tanggapan dari Anies Baswedan terkait buruknya kualitas udara Jakarta, sementara pada Kompas.com bahwa buruknya kualitas udara di Jakarta merupakan tantangan pemerintah dan pemerintah bisa dipidana jika terus dibiarkan.


Author(s):  
Joshua Anish S. Selwyn ◽  
Monali B. Kadam ◽  
Snigdha Thakur

Background: There is limited information describing the change on quality of air and solid waste generation if there is limited and efficient use of vehicles and the shutdown of industries producing hazardous air pollutants that have been achieved by the lockdown. Study assessed changes in the quality of air and solid waste generation due to Lockdown.Methods: It was an analytical study where the data is received from Maharashtra Pollution Control Board data for Mumbai during the period from December 2019 to July 2020. Analysis of Air pollutants like PM10, SO2, NO2, Air quality index, and solid waste generated are taken into consideration.Results: Findings of air quality data has been analysed from December to July. Where the mean air quality index before the lockdown was 251 which is very unhealthy and during lockdown was 62 which is moderate which is a 75% reduction in the pollutants and the solid waste generation before the lockdown was 6338.63 Metric tons per day which have been reduced to 4121.23 Metric tons per day which is a reduction of 34.98 %.Conclusions: This study provides information about how the environment would heal itself if there is a restriction on the use of vehicles and shutting down factories producing hazardous pollutants. This would provide the evidence for the Pollution Control Board to implement policy to improve air quality and solid waste generation, which would have a positive impact on human health and ecosystem.


Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5931
Author(s):  
Ekaterina Svertoka ◽  
Mihaela Bălănescu ◽  
George Suciu ◽  
Adrian Pasat ◽  
Alexandru Drosu

As medical technologies are continuously evolving, consumer involvement in health is also increasing significantly. The integration of the Internet of Things (IoT) concept in the health domain may improve the quality of healthcare through the use of wearable sensors and the acquisition of vital and environmental parameters. Currently, there is significant progress in developing new approaches to provide medical care and maintain the safety of the life of the population remotely and around the clock. Despite the standards for emissions of harmful substances into the atmosphere established by the legislation of different countries, the level of pollutants in the air often exceeds the permissible limits, which is a danger not only for the population but also for the environment as a whole. To control the situation an Air Quality Index (AQI) was introduced. For today, many works discuss AQI, however, most of them are aimed rather at studying the methodologies for calculating the index and comparing air quality in certain regions of different countries, rather than creating a system that will not only calculate the index in real-time but also make it publicly available and understandable to the population. Therefore we would like to present a decision support algorithm for a solution called “Environmental Sensing to Act for a Better Quality of Life: Smart Health” with the primary goal of ensuring the transformation of raw environmental data collected by special sensors (data which typically require scientific interpretation) into a form that can be easily understood by the average user; this is achieved through the proposed algorithm. The obtained result is a system that increases the self-awareness and self-adaptability of people in environmental monitoring by offering easy to read and understand suggestions. The algorithm considers three types of parameters (concentration of PM10 (particulate matter), PM2.5, and NO2) and four risk levels for each of them. The technical implementation is presented in a step-like procedure and includes all the details (such as calculating the Air Quality Index—AQI, for each parameter). The results are presented in a front-end where the average user can observe the results of the measurements and the suggestions for decision support. This paper presents a supporting decision algorithm, highlights the basic concept that was used in the development process, and discusses the result of the implementation of the proposed solution.


2020 ◽  
pp. 236-246 ◽  
Author(s):  
Subham Roy ◽  
Nimai Singha

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.


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