scholarly journals Investigating the impacts of air quality and weather indicators on the spread of SARS-COV-2 in Istanbul, Turkey

2021 ◽  
pp. 71-71
Author(s):  
Caner Taniş ◽  
Kadir Karakaya
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Meteorological Parameters ◽  
Positive Impact ◽  
Pearson Correlation ◽  
Quality Data ◽  
Hospital Discharges ◽  
Weather Parameters ◽  
The Impact ◽  
Quality Indexes

Background/aim: Air pollution is having a positive impact on the spread of the SARS-COV-2 virus. The effects of meteorological parameters on the spread of SARS-COV-2 are a matter of curiosity. The main purpose of this paper is to determine the association between air quality indexes (PM2.5, PM10, NO2, SO2, CO, and O3) and weather parameters (temperature, humidity, pressure, dew, wind speed) with the number of SARS-COV-2 cases, hospitalizations, hospital discharges. In this paper, we also focused on determining the impact of air pollution and weather parameters on the number of daily hospitalizations and daily discharges. Materials and methods: It is gleaned daily cases, hospitalizations, hospital discharges, meteorological, and air quality data in Istanbul from Turkey between July 15, 2020, and September 30, 2020. We performed the Pearson correlation analysis to evaluate the effects of meteorological parameters and air quality indexes on the variables related to SARS-COV-2. Results: It is determined a statistically significant positive relationship between air quality indexes such as CO, SO2, PM2.5, PM10, NO2, and the number of daily confirmed SARS-COV-2 cases. We also observed a negative association between weather parameters such as temperature and pressure and the number of daily confirmed SARS-COV-2 cases. Conclusion: Our study proposes that high air quality could reduce the number of SARS-COV-2 cases. The empirical findings of this paper might provide key input to prevent the spread of SARS-COV-2 across Turkey.

scholarly journals Scalable kernel-based SVM classification algorithm on imbalance air quality data for proficient healthcare

2021 ◽  
Author(s):  
Shwet Ketu ◽  
Pramod Kumar Mishra
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Class Imbalance ◽  
Imbalanced Data ◽  
Classification Algorithm ◽  
Quality Data ◽  
Pollution Level ◽  
Classification Problems ◽  
Chi Square ◽  
The Impact

AbstractIn the last decade, we have seen drastic changes in the air pollution level, which has become a critical environmental issue. It should be handled carefully towards making the solutions for proficient healthcare. Reducing the impact of air pollution on human health is possible only if the data is correctly classified. In numerous classification problems, we are facing the class imbalance issue. Learning from imbalanced data is always a challenging task for researchers, and from time to time, possible solutions have been developed by researchers. In this paper, we are focused on dealing with the imbalanced class distribution in a way that the classification algorithm will not compromise its performance. The proposed algorithm is based on the concept of the adjusting kernel scaling (AKS) method to deal with the multi-class imbalanced dataset. The kernel function's selection has been evaluated with the help of weighting criteria and the chi-square test. All the experimental evaluation has been performed on sensor-based Indian Central Pollution Control Board (CPCB) dataset. The proposed algorithm with the highest accuracy of 99.66% wins the race among all the classification algorithms i.e. Adaboost (59.72%), Multi-Layer Perceptron (95.71%), GaussianNB (80.87%), and SVM (96.92). The results of the proposed algorithm are also better than the existing literature methods. It is also clear from these results that our proposed algorithm is efficient for dealing with class imbalance problems along with enhanced performance. Thus, accurate classification of air quality through our proposed algorithm will be useful for improving the existing preventive policies and will also help in enhancing the capabilities of effective emergency response in the worst pollution situation.

Air Pollution and Seasonality Effects on Mode Choice in China

2017 ◽  
Vol 2634 (1) ◽  
pp. 101-109 ◽  
Author(s):  
Weibo Li ◽  
Maria Kamargianni
Keyword(s):  
Air Pollution ◽  
Developing Countries ◽  
Air Quality ◽  
Positive Impact ◽  
Mode Choice ◽  
Urban Transport ◽  
Modal Shift ◽  
Pollution Levels ◽  
Study Results ◽  
The Impact

A modal shift from motorized to nonmotorized vehicles is imperative to reduce air pollution in developing countries. Nevertheless, whether better air quality will improve the willingness to use nonmotorized transport remains unclear. If such a reciprocal effect could be identified, a sort of virtuous circle could be created (i.e., better air quality could result in higher nonmotorized transport demand, which in turn could further reduce air pollution). Developing countries may, therefore, be more incentivized to work on air pollution reduction from other sources to exploit the extra gains in urban transport. This study investigated the impact of air pollution on mode choices and whether nonmotorized transport was preferred when air quality was better. Revealed preference data about the mode choice behavior of the same individuals was collected during two seasons (summer and winter) with different air pollution levels. Two discrete mode choice models were developed (one for each season) to quantify and compare the impacts of different air pollution levels on mode choices. Trip and socioeconomic characteristics also were included in the model to identify changes in their impacts across seasons. Taiyuan, a Chinese city that operates a successful bikesharing scheme, was selected for a case study. The study results showed that air quality improvement had a significant, positive impact on nonmotorized transport use, which suggested that improvements in air quality and promotion of nonmotorized transport must be undertaken simultaneously because of their interdependence. The results of the study could act as a harbinger to policy makers and encourage them to design measures and policies that lead to sustainable travel behavior.

scholarly journals Basin-scale wind transport during the MILAGRO field campaign and comparison to climatology using cluster analysis

2007 ◽  
Vol 7 (5) ◽  
pp. 13035-13076 ◽  
Author(s):  
B. de Foy ◽  
J. D. Fast ◽  
S. J. Paech ◽  
D. Phillips ◽  
J. T. Walters ◽  
...  
Keyword(s):  
Air Pollution ◽  
Cluster Analysis ◽  
Air Quality ◽  
Mexico City ◽  
Atmospheric Chemistry ◽  
Quality Data ◽  
Field Campaign ◽  
Urban Impacts ◽  
Basin Scale ◽  
The Impact

Abstract. The MILAGRO field campaign was a multi-agency international collaborative project to evaluate the regional impacts of the Mexico City air pollution plume as a means of understanding urban impacts on the global climate. Mexico City lies on an elevated plateau with mountains on three sides and has complex mountain and surface-driven wind flows. This paper asks what the wind transport was in the basin during the field campaign and how representative it was of the climatology. Surface meteorology and air quality data, radiosoundings and radar wind profiler data were collected at sites in the basin and its vicinity. Cluster analysis is used to identify the dominant wind patterns both during the campaign and within the past 10 years of operational data from the warm dry season. Our analysis shows that March 2006 was representative of typical flow patterns experienced in the basin. Six episode types were identified for the basin scale circulation providing a way of interpreting atmospheric chemistry and particulate data collected during the campaign. Decoupling between surface winds and those aloft had a strong influence in leading to convection and poor air quality episodes. Hourly characterisation of wind circulation during the MILAGRO, MCMA-2003 and IMADA field campaigns will enable the comparisons of similar air pollution episodes and the evaluation of the impact of wind transport on measurements of the atmospheric chemistry taking place in the basin.

scholarly journals Population Aging Can Aggravate Air Pollution: Evidence from China

2018 ◽  
Vol 11 (2) ◽  
pp. 41
Author(s):  
Hui Shi
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Technological Innovation ◽  
Positive Impact ◽  
Population Aging ◽  
Household Consumption ◽  
Policy Recommendations ◽  
Fossil Energy ◽  
The Impact ◽  
The Relationship

Population, resources and environment have always attracted much attention from the society. Nowadays, pollution and population aging are urgent problems to be solved in China, and many scholars have found a strong correlation between pollution and aging. This paper constructs a KAYA model with aging variables, making an empirical analysis of the relationship between population aging and air pollution based on the panel data of 82 cities in China from 2011 to 2016. We found that population aging has a significant and positive impact on air pollution. 1% change of the population aging will lead to a 0.203% change in AQI. The deepening of China’s aging level will lead to ineffective improvement of air quality and even lead to more serious air pollution. Then we make the further analysis of the impact mechanism of population aging on air quality, the results show that population aging could have a positive impact on air pollution by improving labor productivity, promoting technological innovation, increasing fossil energy consumption and the household consumption, and changing the structure of household consumption. At last, in order to improve the air pollution under the background of population aging, we put forward the policy recommendations according to the conclusion of this paper.

scholarly journals Using an Internet of Behaviours to Study How Air Pollution Can Affect People’s Activities of Daily Living: A Case Study of Beijing, China

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5569
Author(s):  
Guangyuan Zhang ◽  
Stefan Poslad ◽  
Xiaoping Rui ◽  
Guangxia Yu ◽  
Yonglei Fan ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Activities Of Daily Living ◽  
Daily Living ◽  
Positive Impact ◽  
Sensor Data ◽  
Quality Data ◽  
Quantitative Evidence ◽  
Wide Range ◽  
Beijing China

This study aims to quantitatively model rather than to presuppose whether or not air pollution in Beijing (China) affects people’s activities of daily living (ADLs) based on an Internet of Behaviours (IoB), in which IoT sensor data can signal environmental events that can change human behaviour on mass. Peoples’ density distribution computed by call detail records (CDRs) and air quality data are used to build a fixed effect model (FEM) to analyse the influence of air pollution on four types of ADLs. The following four effects are discovered: Air pollution negatively impacts people going sightseeing in the afternoon; has a positive impact on people staying-in, in the morning and the middle of the day. Air pollution lowers people’s desire to go to restaurants for lunch, but far less so in the evening. As air quality worsens, people tend to decrease their walking and cycling and tend to travel more by bus or subway. We also find a monotonically decreasing nonlinear relationship between air quality index and the average CDR-based distance for each person of two citizen groups that go walking or cycling. Our key and novel contributions are that we first define IoB as a ubiquitous concept. Based on this, we propose a methodology to better understand the link between bad air pollution events and citizens’ activities of daily life. We applied this methodology in the first comprehensive study that provides quantitative evidence of the actual effect, not the presumed effect, that air pollution can significantly affect a wide range of citizens’ activities of daily living.

scholarly journals Study of the Effects of Air Pollutants on Human Health Based on Baidu Indices of Disease Symptoms and Air Quality Monitoring Data in Beijing, China

2019 ◽  
Vol 16 (6) ◽  
pp. 1014 ◽  
Author(s):  
Shaobo Zhong ◽  
Zhichen Yu ◽  
Wei Zhu
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Human Health ◽  
Air Pollutants ◽  
Pearson Correlation ◽  
Additive Model ◽  
Health Impact ◽  
Cerebrovascular Diseases ◽  
Relative Risks ◽  
The Impact

There is an increasing body of evidence showing the impact of air pollutants on human health such as on the respiratory, and cardio- and cerebrovascular systems. In China, as people begin to pay more attention to air quality, recent research focused on the quantitative assessment of the effects of air pollutants on human health. To assess the health effects of air pollutants and to construct an indicator placing emphasis on health impact, a generalized additive model was selected to assess the health burden caused by air pollution. We obtained Baidu indices (an evaluation indicator launched by Baidu Corporation to reflect the search popularity of keywords from its search engine) to assess daily query frequencies of 25 keywords considered associated with air pollution-related diseases. Moreover, we also calculated the daily concentrations of major air pollutants (including PM10, PM2.5, SO2, O3, NO2, and CO) and the daily air quality index (AQI) values, and three meteorological factors: daily mean wind level, daily mean air temperature, and daily mean relative humidity. These data cover the area of Beijing from 1 March 2015 to 30 April 2017. Through the analysis, we produced the relative risks (RRs) of the six main air pollutants for respiratory, and cardio- and cerebrovascular diseases. The results showed that O3 and NO2 have the highest health impact, followed by PM10 and PM2.5. The effects of any pollutant on cardiovascular diseases was consistently higher than on respiratory diseases. Furthermore, we evaluated the currently used AQI in China and proposed an RR-based index (health AQI, HAQI) that is intended for better indicating the effects of air pollutants on respiratory, and cardio- and cerebrovascular diseases than AQI. A higher Pearson correlation coefficient between HAQI and RRTotal than that between AQI and RRTotal endorsed our efforts.

scholarly journals SEASONAL AND SPATIAL VARIATION OF PM10 IN AN URBAN AREA FROM ROMANIA

2019 ◽  
Vol 6 (3-4) ◽  
pp. 7-14
Author(s):  
MARIANA CARMELIA BĂLĂNICĂ DRAGOMIR ◽  
CRISTIAN MUNTENIȚĂ ◽  
AUREL GABRIEL SIMIONESCU ◽  
DANIELA ECATERINA ZECA ◽  
IRYNA KRAMAR ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Area ◽  
Air Temperature ◽  
Atmospheric Pollution ◽  
Meteorological Parameters ◽  
Influence Factor ◽  
Dispersion Models ◽  
Research Results ◽  
The Impact

The cyclic variance of PM10 mass concentration in the urban area in the South-East of Romania has been analysed in the article. SE of Romania is considered to be a territory which has medium level of pollution for a period of last ten years, from 2009 to 2018. The spatial dispersion of PM10 concentration was obtained using the METI-LIS soft wear for each season. The objective of dispersion models is to evaluate how pollutant concentration is spread out taking into account the diffusion. The average measurements of PM10 and meteorological parameters as inputs has been used. An evident seasonal change of PM10 concentrations is observed in the article. In order to establish national measures for the improvement of the atmospheric pollution control it was analysed the mechanism of atmospheric pollution. It was observed that the air quality was overall better in spring and in summer in comparison to the other two periods. With regard to the seasonal variation characteristics of PM10 significant differences for the air quality registered in different months in the researched region were observed. The impact of air temperature on atmospheric pollution was insignificant in spring and autumn; moreover, precipitation was defined as an important influence factor upon the atmospheric pollution. The impact of precipitation on the possibility of atmospheric pollution was obviously different in the four seasons. The research results indicate the meteorological parameters that influence the air pollution become active during the cold seasonal days. It was shown that relative humidity and wind speed are the meteorological parameters that impact the PM10. It was found out that the probability of atmospheric pollution decreased with the increase of air temperature in summer. The research results also testify that the air pollution mapping could be enhanced using atmospheric dispersion models and in-situ measurements.

scholarly journals Basin-scale wind transport during the MILAGRO field campaign and comparison to climatology using cluster analysis

2008 ◽  
Vol 8 (5) ◽  
pp. 1209-1224 ◽  
Author(s):  
B. de Foy ◽  
J. D. Fast ◽  
S. J. Paech ◽  
D. Phillips ◽  
J. T. Walters ◽  
...  
Keyword(s):  
Air Pollution ◽  
Cluster Analysis ◽  
Air Quality ◽  
Mexico City ◽  
Atmospheric Chemistry ◽  
Quality Data ◽  
Field Campaign ◽  
Urban Impacts ◽  
Basin Scale ◽  
The Impact

Abstract. The MILAGRO field campaign was a multi-agency international collaborative project to evaluate the regional impacts of the Mexico City air pollution plume as a means of understanding urban impacts on the global climate. Mexico City lies on an elevated plateau with mountains on three sides and has complex mountain and surface-driven wind flows. This paper asks what the wind transport was in the basin during the field campaign and how representative it was of the climatology. Surface meteorology and air quality data, radiosondes and radar wind profiler data were collected at sites in the basin and its vicinity. Cluster analysis was used to identify the dominant wind patterns both during the campaign and within the past 10 years of operational data from the warm dry season. Our analysis shows that March 2006 was representative of typical flow patterns experienced in the basin. Six episode types were identified for the basin-scale circulation providing a way of interpreting atmospheric chemistry and particulate data collected during the campaign. Decoupling between surface winds and those aloft had a strong influence in leading to convection and poor air quality episodes. Hourly characterisation of wind circulation during the MILAGRO, MCMA-2003 and IMADA field campaigns enables the comparisons of similar air pollution episodes and the evaluation of the impact of wind transport on measurements of the atmospheric chemistry taking place in the basin.

scholarly journals Changes in the concentration of air pollutants before and after the COVID-19 blockade period and their correlation with vegetation coverage

2021 ◽  
Author(s):  
Manguo Zhou ◽  
Yanguo Huang ◽  
Guilan Li
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Vegetation Index ◽  
Pearson Correlation ◽  
Air Pollutant ◽  
Atmospheric Environment ◽  
Vegetation Coverage ◽  
Time Space ◽  
Climatic Environment ◽  
The Impact

AbstractIn order to control the spread of COVID-19, China had implemented strict lockdown measures. The closure of cities had had a huge impact on human production and consumption activities, which had greatly reduced population mobility. This article used air pollutant data from 341 cities in mainland China and divided these cities into seven major regions based on geographic conditions and climatic environment. The impact of urban blockade on air quality during COVID-19 was studied from the perspectives of time, space, and season. In addition, this article used Normalized Difference Vegetation Index (NDVI) to systematically analyze the characteristics of air pollution in the country and used the Pearson correlation coefficient to explore the relationship between NDVI and the air pollutant concentrations during the COVID-19 period. Then, linear regression was used to find the quantitative relationship between NDVI and AQI, and the fitting effect of the model was found to be significant through t test. Finally, some countermeasures were proposed based on the analysis results, and suggestions were provided for improving air quality. This paper has drawn the following conclusions: (1) the concentration of pollutants varied greatly in different regions, and the causes of their pollution sources were also different. The region with the largest decline in AQI was the Northeast China (60.01%), while the AQI in the southwest China had the smallest change range, and its value had increased by 1.72%. In addition, after the implementation of the city blockade, the concentration of NO2 in different regions dropped the most, but the increase in O3 was more obvious. (2) Higher vegetation coverage would have a beneficial impact on the atmospheric environment. Areas with higher NDVI values have relatively low AQI. There is a negative correlation between NDVI and AQI, and an average increase of 0.1 in NDVI will reduce AQI by 3.75 (95% confidence interval). In the case of less human intervention, the higher the vegetation coverage, the lower the local pollutant concentration will be. Therefore, the degree of vegetation coverage would have a direct or indirect impact on air pollution.

THE IMPACT OF METEOROLOGICAL PARAMETERS ON SULPHURIC AIR POLLUTION IN KOHTLA-JÄRVE

Oil Shale ◽  
2011 ◽  
Vol 28 (2) ◽  
pp. 337
Author(s):  
J PAVLENKOVA ◽  
M KAASIK ◽  
E-S KERNER ◽  
A LOOT ◽  
R OTS
Keyword(s):  
Air Pollution ◽  
Meteorological Parameters ◽  
The Impact
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