scholarly journals Time Series Modeling of Air Pollution and Its Association with Season and Climate Variables in Istanbul, Turkey

2020 ◽  
Author(s):  
hazem al-najjar ◽  
Nadia Al-Rousan ◽  
Ismail A. Elhaty
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Feature Selection ◽  
Wind Speed ◽  
Air Pollutants ◽  
Time Series Modeling ◽  
Climate Variables ◽  
Different Seasons ◽  
The Impact

Abstract Air pollution depends on seasons, wind speed, temperature, wind direction and air pressure. The effect of different seasons on air pollution is not fully addressed in the reported works. The current study investigated the impact of season on air pollutants including SO2, PM10, NO, NOX, and O3 using NARX method. In the applied methodology, a feature selection was used with each pollutant to find the most important season(s). Afterward, six models are designed based on the feature selection to show the impact of seasons in finding the concentration of pollutants. A case study is conducted on Esenyurt which is one of the most populated and industrialized places in Istanbul to validate the proposed framework. The performance of using all of the designed models with different pollutants showed that using season effect led to improving the performance of predictor and generating high R2 and low error functions.

scholarly journals Time series modeling of air pollution and its association with season and climate variables in istanbul, turkey

2020 ◽  
Author(s):  
hazem al-najjar ◽  
Nadia Al-Rousan ◽  
Ismail A. Elhaty
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Feature Selection ◽  
Air Pollutants ◽  
Time Series Modeling ◽  
Climate Variables ◽  
Different Seasons ◽  
The Impact ◽  
Nonlinear Autoregressive

Abstract Air pollution depends on seasons, wind speed, temperature, wind direction and air pressure. The effect of different seasons on air pollution is not fully addressed in the reported works. The current study investigated the impact of season on air pollutants including SO2, PM10, NO, NOX, and O3 using Nonlinear AutoregRessive network with eXogenous inputs (NARX) method. In the applied methodology, a feature selection was used with each pollutant to find the most important season(s). Afterward, six models are designed based on the feature selection to show the impact of seasons in finding the concentration of pollutants. A case study is conducted on Esenyurt which is one of the most populated and industrialized places in Istanbul to validate the proposed framework. The performance of using all of the designed models with different pollutants showed that using season effect led to improving the performance of predictor and generating high R2 and low error functions.

scholarly journals Time series modeling of air pollution and its association with season and climate variables in istanbul, turkey

2020 ◽  
Author(s):  
hazem al-najjar ◽  
Nadia Al-Rousan ◽  
Ismail A. Elhaty
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Feature Selection ◽  
Air Pollutants ◽  
Time Series Modeling ◽  
Climate Variables ◽  
Different Seasons ◽  
The Impact ◽  
Nonlinear Autoregressive

Abstract Air pollution depends on seasons, wind speed, temperature, wind direction and air pressure. The effect of different seasons on air pollution is not fully addressed in the reported works. The current study investigated the impact of season on air pollutants including SO2, PM10, NO, NOX, and O3 using Nonlinear AutoregRessive network with eXogenous inputs (NARX) method. In the applied methodology, a feature selection was used with each pollutant to find the most important season(s). Afterward, six models are designed based on the feature selection to show the impact of seasons in finding the concentration of pollutants. A case study is conducted on Esenyurt which is one of the most populated and industrialized places in Istanbul to validate the proposed framework. The performance of using all of the designed models with different pollutants showed that using season effect led to improving the performance of predictor and generating high R2 and low error functions.

scholarly journals Time series modeling of air pollution and its association with season and climate variables in istanbul, turkey

2020 ◽  
Author(s):  
hazem al-najjar ◽  
Nadia Al-Rousan ◽  
Ismail A. Elhaty
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Feature Selection ◽  
Air Pollutants ◽  
Time Series Modeling ◽  
Climate Variables ◽  
Different Seasons ◽  
The Impact ◽  
Nonlinear Autoregressive

Abstract Air pollution depends on seasons, wind speed, temperature, wind direction and air pressure. The effect of different seasons on air pollution is not fully addressed in the reported works. The current study investigated the impact of season on air pollutants including SO2, PM10, NO, NOX, and O3 using Nonlinear AutoregRessive network with eXogenous inputs (NARX) method. In the applied methodology, a feature selection was used with each pollutant to find the most important season(s). Afterward, six models are designed based on the feature selection to show the impact of seasons in finding the concentration of pollutants. A case study is conducted on Esenyurt which is one of the most populated and industrialized places in Istanbul to validate the proposed framework. The performance of using all of the designed models with different pollutants showed that using season effect led to improving the performance of predictor and generating high R2 and low error functions.

scholarly journals The modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rui Zhang ◽  
Yujie Meng ◽  
Hejia Song ◽  
Ran Niu ◽  
Yu Wang ◽  
...  
Keyword(s):  
Air Pollution ◽  
High Temperature ◽  
Air Pollutants ◽  
Meteorological Data ◽  
Effect Of Temperature ◽  
Distributed Lag ◽  
Modification Effect ◽  
Incidence Risk ◽  
The Impact ◽  
The Relationship

Abstract Background Although exposure to air pollution has been linked to many health issues, few studies have quantified the modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China. Methods The data of daily incidence of influenza and the relevant meteorological data and air pollution data in Ningbo from 2014 to 2017 were retrieved. Low, medium and high temperature layers were stratified by the daily mean temperature with 25th and 75th percentiles. The potential modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo was investigated through analyzing the effects of air pollutants stratified by temperature stratum using distributed lag non-linear model (DLNM). Stratified analysis by sex and age were also conducted. Results Overall, a 10 μg/m3 increment of O3, PM2.5, PM10 and NO2 could increase the incidence risk of influenza with the cumulative relative risk of 1.028 (95% CI 1.007, 1.050), 1.061 (95% CI 1.004, 1.122), 1.043 (95% CI 1.003, 1.085), and 1.118 (95% CI 1.028, 1.216), respectively. Male and aged 7–17 years were more sensitive to air pollutants. Through the temperature stratification analysis, we found that temperature could modify the impacts of air pollution on daily incidence of influenza with high temperature exacerbating the impact of air pollutants. At high temperature layer, male and the groups aged 0–6 years and 18–64 years were more sensitive to air pollution. Conclusion Temperature modified the relationship between air pollution and daily incidence of influenza and high temperature would exacerbate the effects of air pollutants in Ningbo.

scholarly journals Relationship between preterm birth and air pollution in Santos, Sao Paulo, Brazil

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M E L Brandao ◽  
B A L F Braga ◽  
M L C Martins ◽  
P L A A Pereira
Keyword(s):  
Air Pollution ◽  
Preterm Birth ◽  
Air Pollutants ◽  
First Trimester ◽  
Sao Paulo ◽  
São Paulo ◽  
Air Humidity ◽  
Relative Air Humidity ◽  
The Impact ◽  
Fourth Quartile

Abstract Santos is a seaboard Brazilian city recognized by its port activity where the road and rail infrastructure along with the large transportation operation, displays an important factor to contribute with all kinds of toxic and air pollutants. Recent studies have suggested associations between air pollution and various birth outcomes. Pollutant gases such as NOx, O3 and particulate matter PM2,5, PM10 have been cited as factors involved in such outcomes. The present study aims to assess the relationship between atmospheric pollutants and perinatal outcomes in the city of Santos from Jan. 2012 to Dec. 2015. Cross-sectional study that analyzed 10.319 singleton births in an area set with 2 km radius of the monitoring stations. Birth weight and information on mother and pregnancy were obtained at the Brazilian “Born Alive National Information System”. Daily records of air pollutants (PM10, PM2.5, NO2 and O3), temperature and relative air humidity, for the study period, were obtained from São Paulo State Environmental Agency (CETESB). Associations between preterm birth and air pollutants mean levels at each gestational trimester were investigated using multiple logistic regression model controlled by the variables: infant sex, type of delivery, maternal education. prenatal care, and number of previous live births, temperature and relative air humidity. NO2 e PM2,5 was not associated with preterm birth. O3 was significantly associated in the first trimester in the fourth quartile (OR = 1,47 CI 95% 1,05; 2,07). PM10 was significantly associated in the first trimester for the fourth quartile (OR = 1,28 CI 95% 1,00; 1,64), second trimester for the second quartile (OR = 1,37 CI 95% 1,07; 1,77). Conclusions the results shows evidence that maternal exposure to air pollution especially during the first trimester of pregnancy may contribute to preterm birth. Further actions are needed towards controlling air pollution are strongly recommended for promoting early-life health. Key messages This is the first research of this kind that was made in Santos. It brings important evidence of the impact in the life of the population, especially those whose is not even born yet. It can be used as a resource to guide public policies in health, especially the guidelines that dictate the concentration of air pollutants and air quality.

scholarly journals Cause-and-effect relationships between air pollution and health conditions in population

2020 ◽  
Vol 5 (4) ◽  
pp. 230-234
Author(s):  
I. I. Berezin ◽  
Yu. Yu. Eliseev ◽  
A. K. Sergeev
Keyword(s):  
Air Pollution ◽  
Allergic Rhinitis ◽  
Bronchial Asthma ◽  
Respiratory System ◽  
Air Pollutants ◽  
Preventive Measures ◽  
Industrial City ◽  
Cause And Effect ◽  
The Impact

Objectives to reveal cause-and-effect relationships in the system "air pollution morbidity of the population" in a large industrial city. Material and methods.The dynamics of the pollutants concentration, such as formaldehyde and benzopyrene, through the period of 20152017 was analyzed in relation to the indicators of the morbidity of the respiratory system in the population of Samara. In particular, the study focused on the ratio of allergic rhinitis and asthma cases and the concentration of the formaldehyde and benzopyrene. Results.The incidence of respiratory diseases and the general morbidity increased both among children (by 46.7%) and adults (by 11.4%). There was the causal correlation between the effect of benzopyrene on the development of allergic rhinitis and bronchial asthma in children(r = 0.57 and r = 0.76) and in adults (r = 0.45 and r = 0.51) in Samara. The significant differences between the level of the pollutants and the frequency of the respiratory system diseases were registered in children and adults in different areas of Samara. Discussion.As a result of the increase of the maximum allowable concentration (MAC) of formaldehyde in atmospheric air, this pollutant has now ceased to be a priority. The revealed negative correlations point to the absence of an adverse effect of formaldehyde on the development of allergic rhinitis and bronchial asthma in both children and adults in Samara. Conclusion.According to the results of the study, the preventive measures aimed at reducing the impact of main air pollutants on the health of children and adults in Samara were suggested. Their implementation is possible by the immediate informing of the executive authorities to ensure they can make timely management decisions to improve the quality of the environment.

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