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Assessment of Air Quality Index in Annaba

Badjoudj Salem, Benselhoub Aissa, Narsis Souad, Dovbash Nadiia, Idres Abdelaziz, Benghadab Khadouja Marame, Boutarfa Fares, Bounouala Mohamed, Bellucci Stefano

Inżynieria Mineralna

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2023

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no. 2, vol. 1

341--350

EN

In recent years, the world has been witnessing serious ecological imbalances due to the catastrophic situation and the damage caused to the environment. Human activities as waste disposal, cement units, smelting, chemical industries etc., are the main causes of pollution. Air pollution directly affects the human living standards, pollutants requires regular control in view of their direct impact on health, such as nitrogen oxide, sulfur dioxide, ozone, and particulate matter. Algeria adopts international standards to monitor the levels of pollution recorded in Algerian cities and compare them with global levels. In this context, quantitative estimates of polluted waste resulting from some industrial activities have been conducted in order to determine the degree of its danger and the extent of its contribution to the deterioration of the air quality. The monitoring of pollutants allowed us to identify the benefits of comprehensive environmental assessment. We determined the air quality index in Annaba using various pollutants parameters (dust, ozone, nitrogen dioxide and sulfur dioxide). A ten-point scale ranking of the overall air quality index of pollution accepted in Algeria allows making the differentiated assessment of negative impacts of existing industrial agglomerations on the environment. However, the analysis performed on samples DC1 and DC2 with SEM (TESCAN model VEGA II) and BSE detector (Backscattered Electrons) shows that the particles sizes are estimated to range from hundreds of microns to a few microns, a different morphology and irregular shape. Our results will enable policy makers to appropriate measures to be taken, and which are based mainly on sensitizing economic operators to environmental issues in order to adopt an environmentally friendly industrial system.

PL

W ostatnich latach świat był świadkiem poważnych zaburzeń równowagi ekologicznej z powodu katastrofalnej sytuacji i szkód wyrządzonych środowisku. Działalność człowieka, taka jak usuwanie odpadów, cementownie, hutnictwo, przemysł chemiczny itp. są głównymi przyczynami zanieczyszczenia. Zanieczyszczenie powietrza bezpośrednio wpływa na standardy życia ludzi, zanieczyszczenia wymagają regularnej kontroli ze względu na ich bezpośredni wpływ na zdrowie, takie jak tlenek azotu, dwutlenek siarki, ozon i pył zawieszony. Algieria przyjmuje międzynarodowe standardy w celu monitorowania poziomów zanieczyszczeń rejestrowanych w algierskich miastach i porównywania ich z poziomami globalnymi. W tym kontekście przeprowadzono ilościowe szacunki zanieczyszczonych odpadów powstających w wyniku niektórych działań przemysłowych w celu określenia stopnia ich zagrożenia i zakresu ich wkładu w pogorszenie jakości powietrza. Monitorowanie zanieczyszczeń pozwoliło nam zidentyfikować korzyści płynące z kompleksowej oceny środowiska. Określiliśmy indeks jakości powietrza w Annabie, wykorzystując różne parametry zanieczyszczeń (pył, ozon, dwutlenek azotu i dwutlenek siarki). Dziesięciopunktowa skala rankingu ogólnego wskaźnika jakości powietrza zanieczyszczeń przyjętych w Algierii pozwala na zróżnicowaną ocenę negatywnego wpływu istniejących aglomeracji przemysłowych na środowisko. Jednak analiza przeprowadzona na próbkach DC1 i DC2 za pomocą SEM (TESCAN model VEGA II) i detektora BSE (Backscattered Electrons) pokazuje, że rozmiary cząstek szacuje się na od setek mikronów do kilku mikronów, o różnej morfologii i nieregularnym kształcie. Nasze wyniki umożliwią decydentom podjęcie odpowiednich środków, które opierają się głównie na uwrażliwieniu podmiotów gospodarczych na kwestie środowiskowe w celu przyjęcia przyjaznego dla środowiska systemu przemysłowego.

2

Analysis and Prediction for Air Quality Using Various Machine Learning Models

Dao To-Hieu, Dieu Vu Hoang, Nhat Hoang Van, Thu Nguyen Thi, Tran Duc-Tan, Trung Hoang Quang, Tran Duc-Nghia

Annals of Computer Science and Information Systems

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2022

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Vol. 33

89--94

EN

Air pollution has been a concern in recent years. Measuring the extent of pollution is important to know about the air quality. Previous research has used machine learning algorithms to forecast the Air Quality Index (AQI) in specific locations. Even though that research achieved quite reliable results, they still have some drawbacks that need to be taken into consideration, such as low accuracy or lack of data analysis.On a public dataset, we used Random Forest, XGBoost, and Neural Network to build a machine learning model for the purpose of making predictions about the air quality index (AQI) in a number of cities located in India. The performances of these models were evaluated by using their score errors, Root Mean Square Error (RMSE), and Coefficient Of Determination (R2). This paper demonstrates the analysis of air pollutants from the dataset, which is an effective way to enhance the model's performance.

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Patterns of relationship between PM10 from air monitoring quality station and AOT data from MODIS sensor onboard of Terra satellite

Suriya Winai, Chunpang Poramate, Laosuwan Teerawong

Przegląd Naukowy Inżynieria i Kształtowanie Środowiska

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2021

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Vol. 30, No. 2

236--249

EN

Thailand, especially in the northern region, often encounters the problem of having PM10 exceeding the normal standard level, which could do harm to people’s health. Mostly, such problem is caused by the burning of forest area and open area; this is clearly seen during January–April of every year. Also, the problem as mentioned is caused by the meteorological conditions and the terrains in the northern region that make it easy for PM10 to be accumulated. The aim of this study was to analyze the patterns of relationship between PM10 measured from the ground monitoring station and AOT data received from MODIS sensor onboard of Terra satellite in Phrae Province located in the northern region of Thailand. The method performed was by analyzing the correlation between PM10 data obtained from the ground monitoring station and the AOT data received from the MODIS sensor onboard of Terra satellite during January–April 2018. It was found from the study that the change of the intensity of PM10 and AOT in the climate was highly related; it appeared that the correlation coefficient (r) in January–April was 0.92, 0.91, 0.91 and 0.92, respectively. This research pointed out that during February– –April, the areas of Phrae Province had the level of PM10 that affected health. Besides, from the method in this research, it revealed AOT data received from MODIS sensor onboard of Terra satellite could be applied in order to follow up, monitor, and notify the spatial changes of PM10 efficiently.

4

Assessment of Ambient Air Quality of Mosul City/Iraq Via Air Quality Index

Shihab Abdulmuhsin S.

Journal of Ecological Engineering

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2021

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Vol. 22, nr 10

241--250

EN

The research aimed to assess air quality in Mosul city (Iraq) using air quality index (AQI). The data were collected at six monitoring sites using two stations, one fixed and the other is mobile type. The concentrations of CO, NO2, O3, SO2 and PM10 were measured. The daily AQI were calculated for each site and classified to AQI categories according to USEPA approach. The dominant AQI category at the public library site fluctuated between "Moderate" to "Unhealthy for Sensitive Groups". AQI undergoes seasonal variation with lower value at March. The results showed that PM10 is the main contributor for AQI determination in Mosul city with 93.8%. CO has no contribution to Mosul AQI. SO2, O3 and NO2 have little contribution to Mosul AQI with 0.8%, 2.7% and 2.7% respectively. The annual mean of AQI in the public library site/ Mosul city is 96 in the category "Moderate". The worst site was Mosul municipality (old location) with a dominant category "Unhealthy for Sensitive Groups".

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COVID-19: A spectio-temporal analysis of air quality status in coking coalfields of India due to nationwide lockdown in India

Singh Amarjeet, Singh Gurdeep

Journal of Sustainable Mining

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2020

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Vol. 19, iss. 4

243--253

EN

A novel infectious corona virus disease (COVID-19) was identified in the month of December 2019. It has now been announced as a worldwide pandemic by the World Health Organization. COVID-19 pandemic has positive impacts on the environmental pollutants. In present work, Coalfield areas of Jharia Coalfields (JCF), India have been taken as a case study to evaluate the effect of the lockdown on air quality at 10 locations. This study had been selected to estimate the reduction in concentration of pollutants likePM10, PM2.5, SO2, and NOx during 3 Seasons (summer, Post-Monsoon and winter season) in the year 2019 in comparison to the concentration during the lockdown period i.e. from April 2020 to June 2020. The study areas selected was as fire affected and non-fire affected areas of Jharia Coalfield to identify the contribution of pollutants in the mining area to establish the baseline concentration of Business as usual (BAU) vs. the lockdown condition. The average reduction in concentration of PM10, PM2.5, SO2 and NOx was observed as 18%, 14%, 22% and 26% respectively during the lockdown period in comparison with the annual average concentration. As observed, the AQI value at the selected monitoring sites in JCF was 1.5 times higher in comparison to the lockdown period. This study will provide the confidence to the regulatory body for strict implementation of the applicable air quality standard/policies in the mining areas. The study will also provide confidence to the regulatory body in making emission control strategies for improvement of environmental conditions and human health.