scholarly journals Impact of the COVID-19 Outbreak on Air Quality in Korea

Atmosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1137 ◽  
Author(s):  
Ji Hoon Seo ◽  
Hyun Woo Jeon ◽  
Ui Jae Sung ◽  
Jong-Ryeul Sohn
Keyword(s):  
Air Quality ◽  
Human Activity ◽  
Quality Index ◽  
Air Pollutant ◽  
Air Quality Index ◽  
Control Action ◽  
Quality Improvements ◽  
Social Distancing ◽  
Two Cities ◽  
Activity Restrictions

The COVID-19 pandemic has led countries to take action, which has included practicing social distancing or lockdown. Many cities are experiencing air quality improvements due to human activity restrictions. The purpose of this study was to compare the air quality between 2020 and the previous three years, focusing on the two cities (Seoul and Daegu) where coronavirus is spreading the fastest in Korea. Significant decreases in PM2.5, PM10, CO, and NO2 were observed in both cities. In particular, compared to the same period of 2017-2019, in March 2020, PM2.5 showed remarkable reductions of 36% and 30% in Seoul and Daegu, respectively. The effects of social distancing have maximized improvements in air quality due to reduced transboundary pollutants. The PM2.5/PM10 ratio was significantly reduced after social distancing, indicating that the contribution of traffic-related PM2.5 declined. Air quality improved overall from January to July, and the most noticeable drop in the air quality index (AQI) was observed in April. These findings indicate that relatively weak social distancing measures compared to a COVID-19 lockdown can help reduce air pollutant levels. At the same time, however, changes in air quality in the neighboring countries caused by COVID-19 control action are affecting Korea.

scholarly journals Regional Energy, CO2, and Economic and Air Quality Index Performances in China: A Meta-Frontier Approach

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2119 ◽  
Author(s):  
Ying Li ◽  
Yung-Ho Chiu ◽  
Liang Lu
Keyword(s):  
Particulate Matter ◽  
Energy Consumption ◽  
Air Quality ◽  
Quality Index ◽  
Air Pollutant ◽  
Air Quality Index ◽  
Significant Difference ◽  
Desirable Output ◽  
Reduce Emissions ◽  
Carbon Dioxide Co2

Rapid economic development has resulted in a significant increase in energy consumption and pollution such as carbon dioxide (CO2), particulate matter (PM2.5), particulate matter 10 (PM10), SO2, and NO2 emissions, which can cause cardiovascular and respiratory diseases. Therefore, to ensure a sustainable future, it is essential to improve economic efficiency and reduce emissions. Using a Meta-frontier Non-radial Directional Distance Function model, this study took energy consumption, the labor force, and fixed asset investments as the inputs, Gross domestic product (GDP) as the desirable output, and CO2 and the Air Quality Index (AQI) scores as the undesirable outputs to assess energy efficiency and air pollutant index efficiency scores in China from 2013–2016 and to identify the areas in which improvements was necessary. It was found that there was a large gap between the western and eastern cities in China. A comparison of the CO2 and AQI in 31 Chinese cities showed a significant difference in the CO2 emissions and AQI efficiency scores, with the lower scoring cities being mainly concentrated in China’s western region. It was therefore concluded that China needs to pay greater attention to the differences in the economic levels, stages of social development, and energy structures in the western cities when developing appropriately focused improvement plans.

scholarly journals Air Quality Index and Air Pollutant Concentration Prediction Based on Machine Learning Algorithms

2019 ◽  
Vol 9 (19) ◽  
pp. 4069 ◽  
Author(s):  
Huixiang Liu ◽  
Qing Li ◽  
Dongbing Yu ◽  
Yu Gu
Keyword(s):  
Machine Learning ◽  
Air Pollution ◽  
Air Quality ◽  
Regression Models ◽  
Quality Index ◽  
Air Pollutant ◽  
Air Quality Index ◽  
Machine Learning Algorithms ◽  
Coefficient Of Determination ◽  
Support Vector

Air pollution has become an important environmental issue in recent decades. Forecasts of air quality play an important role in warning people about and controlling air pollution. We used support vector regression (SVR) and random forest regression (RFR) to build regression models for predicting the Air Quality Index (AQI) in Beijing and the nitrogen oxides (NOX) concentration in an Italian city, based on two publicly available datasets. The root-mean-square error (RMSE), correlation coefficient (r), and coefficient of determination (R2) were used to evaluate the performance of the regression models. Experimental results showed that the SVR-based model performed better in the prediction of the AQI (RMSE = 7.666, R2 = 0.9776, and r = 0.9887), and the RFR-based model performed better in the prediction of the NOX concentration (RMSE = 83.6716, R2 = 0.8401, and r = 0.9180). This work also illustrates that combining machine learning with air quality prediction is an efficient and convenient way to solve some related environment problems.

scholarly journals Fuzzy Based Prediction Model for Air Quality Monitoring for Kampala City in East Africa

2021 ◽  
Vol 4 (3) ◽  
pp. 44
Author(s):  
Calorine Katushabe ◽  
Santhi Kumaran ◽  
Emmanuel Masabo
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Quality Index ◽  
Air Pollutant ◽  
Air Quality Index ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Pollutant Concentrations ◽  
Kampala City ◽  
Air Pollutant Concentrations

The quality of air affects lives and the environment at large. Poor air quality has claimed many lives and distorted the environment across the globe, and much more severely in African countries where air quality monitoring systems are scarce or even do not exist. Here in Africa, dirty air is brought about by the growth in industrialization, urbanization, flights, and road traffic. Air pollution remains such a silent killer, especially in Africa, and if not dealt with, it will continue to lead to health issues, such as heart conditions, stroke, and chronic respiratory organ unwellness, which later result in death. In this paper, the Kampala Air Quality Index prediction model based on the fuzzy logic inference system was designed to determine the air quality for Kampala city, according to the air pollutant concentrations (nitrogen dioxide, sulphur dioxide and fine particulate matter 2.5). It is observed that fuzzy logic algorithms are capable of determining the air quality index and therefore, can be used to predict and estimate the air quality index in real time, based on the given air pollutant concentrations. Hence, this can reduce the effects of air pollution on both humans and the environment.

scholarly journals Research on Influence Factors of Air Quality in the Host Area of the 24th Winter Olympic Games Based on Grey Relational Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Wei Wang ◽  
Yan Chen ◽  
Yuhan Xie ◽  
Lifeng Wu
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
Olympic Games ◽  
Air Quality Index ◽  
Added Value ◽  
Atmospheric Environment ◽  
Total Output ◽  
Winter Olympics ◽  
Two Cities ◽  
Winter Olympic Games

In recent years, the continuous development of the economy and science and technology of China has caused a certain degree of pollution to the atmospheric environment on which the people depend. The current air pollution problem is actively a concern by the government and all walks of life. Based on the 2015–2019 air quality indicators and some socioeconomic indicators, this paper uses the grey correlation analysis method to analyze the Beijing and Zhangjiakou cities that will host the Winter Olympics in 2022. The study found that the three factors most closely related to the Beijing Air Quality Index (AQI) are the permanent population (0.831), energy consumption (0.801), the number of motor vehicles (0.79), and the permanent population (0.916) and industrial added value (0.905). The total output value of agriculture, forestry, and animal husbandry and fishery (0.89) are the three factors most closely related to the air quality index (AQI) of Zhangjiakou City, and the permanent population is the common factor affecting the two cities. Considering that the factors that affect the air quality of the two cities are not exactly the same, this paper combines the development positioning of the two cities and their own characteristics, and puts forward specific suggestions and opinions on the different problems faced by the two cities. The aim is to promote the continuous improvement of air quality in the two cities to reach an excellent level through scientific and feasible air management programs before the opening of the 2022 Winter Olympic Games, and help the 2022 Winter Olympics to be held smoothly.

scholarly journals The Assessment of Air Pollutant Concentrations and Air Quality Index in Shiraz during 2011-2013

2016 ◽  
Vol 3 (3) ◽  
pp. 182-192 ◽  
Author(s):  
Monireh Majlesi Nasr ◽  
Mohammad Ansarizadeh ◽  
Mostafa Leili ◽  
◽  
◽  
...  
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
Air Pollutant ◽  
Air Quality Index ◽  
Pollutant Concentrations ◽  
Air Pollutant Concentrations

scholarly journals Modeling air quality index using optimized neuronal networks inspired by swarms

2020 ◽  
Vol 26 (6) ◽  
pp. 200469-0
Author(s):  
Dimple Pruthi ◽  
Rashmi Bhardwaj
Keyword(s):  
Air Quality ◽  
Fuzzy Inference System ◽  
Quality Index ◽  
Neuronal Networks ◽  
Fuzzy Inference ◽  
Air Pollutant ◽  
Air Quality Index ◽  
Inference System ◽  
Air Quality Prediction ◽  
Neuro Fuzzy

Air quality prediction is a significant field in environmental engineering, as air and water are essential for life on Earth. Nowadays, a common parameter used worldwide to measure air quality is termed as Air quality index. The parameter is measured based on the air pollutant concentration. The hybrid neuronal networks have been widely used for modeling air quality index. In the quest of optimizing the error in modeling air quality index, the existing adaptive neuro-fuzzy inference system is improved in this study using algorithms based on evolution and swarm movement. The model is based on the prominent air pollutants- nitrogen oxide, particulate matter of size equal to or less than 2.5microns (PM2.5), and sulphur dioxide. The proposed hybrid model using wavelet transform, particle swarm optimization, and adaptive neuro-fuzzy inference system accurately predicts the Air Quality Index and can be used in the public interest to take necessary precautions beforehand.

scholarly journals Impact of Open Burning Refuse on Air Quality: In the Case of “Hidar Sitaten” at Addis Ababa, Ethiopia

2020 ◽  
Vol 14 ◽  
pp. 117863022094320
Author(s):  
Tadesse Weyuma Bulto
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
Addis Ababa ◽  
Cultural Practice ◽  
Air Pollutant ◽  
Air Quality Index ◽  
Pollutant Concentration ◽  
Open Burning ◽  
Particulate Pollution ◽  
The Mean

Open burning of refuse is one of the key sources that causes high air pollution in Metropolitan cities. This paper identifies pollutant concentration of particulate matter (PM2.5) emission and air quality index categories with the peak hour interval on Hidar Sitaten day, and present analysis of air quality in Addis Ababa from August 2016 to November 2019. Daily records, with a 1-hour interval, of raw concentration of air pollutant and air quality index data, were obtained from the AirNow website of Addis Ababa central monitoring station. The data collected were analyzed using descriptive statistics of the mean air quality index and concentration of PM2.5. Accordingly, the study revealed that the peak hour for high pollutant concentration emission ranges between 8 pm to 11 pm hours, and the mean air quality index was more than a moderate level. Particularly, on Hidar Sitaten in 2019 at 9 pm the maximum concentration of PM2.5 was 8.6 times higher than WHO air quality guideline standard of daily allowance. The highest mean of air quality index and concentration of PM2.5 recorded was 112 and 44.2 µg/m3 on 21 November 2017, respectively, and it was found to be unhealthy for sensitive groups. This implies that the concentration of PM2.5 was harmful to people who are unusually sensitive to particulate pollution and have health problems. Therefore, public participation and strong regulations are needed on air quality management to strike a balance between a cultural practice of Hidar Sitaten and healthy air quality.

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.

Changes in Air Quality of the Yuxi City Urban Area

2014 ◽  
Vol 1021 ◽  
pp. 225-228
Author(s):  
Cheng Qiu ◽  
Hong Chen ◽  
Chun Li Ye ◽  
Yan Jun Yang ◽  
Chang Bing Ye
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Area ◽  
Health Problem ◽  
Quality Index ◽  
Quality Standards ◽  
Air Pollutant ◽  
Air Quality Index ◽  
Air Quality Standards

Air pollution causes health problem. The paper simply analyzed the changes of air quality in the Yuxi city urban area from 2006 to 2012. In the Yuxi city urban area between 2006 and 2012, SO2 levels increased about 43.9 percent; NO2 levels increased about 13.3 percent; PM10 levels in 2012 decreased about 1.5 percent. By evaluating the air quality in the Yuxi city urban area, the results showed that air quality index was the maximum in 2009, and the quality of the air in Yuxi became worse from 2006 to 2012, air pollution in 2009 was the heaviest between 2006 to 2012. After adopting P.R.C EPA air quality standards (GB3095-2012) in 2013, the first air pollutant in Yuxi is PM10, and then it is SO2 among SO2, NO2 and PM10.Much should beend done to reduce the amount of PM10 and SO2 released.

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