Statistical analysis of wind circulation and air pollution in urban Trabzon

Demirci, Emrullah; Çuhadaroğlu, Burhan

doi:10.1016/s0378-7788(99)00002-x

Cited by 37 publications

(20 citation statements)

References 1 publication

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“…Adequate ventilation was reported to be a major factor in improving IAQ (Daisey et al 2003;Zuraimi et al 2007). This study did not investigate some factors such as geographical and metrological factors (e.g., wind direction and speed) which were known to be important to explain outdoor pollutant levels (Demirci and Cuhadaroglu 2000) The reason why so many preschools (83 out of 100) refused to participate was unclear. But some principals complained that these types of survey often lead to enforced regulation later.…”

Section: Discussionmentioning

confidence: 99%

Indoor air quality differences between urban and rural preschools in Korea

Yoon

Lee

Park

2010

Environ Sci Pollut Res

118

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We confirmed that pollutants in indoor and urban settings were higher than those in outdoor and rural areas, respectively. Preschool children are expected to spend more time inside preschool facilities and therefore to be more exposed to pollutants. As far as we know, preschool IAQ is different from elementary school or higher school IAQ. Also, they are more vulnerable than higher-grade children. We found that the indoor and urban concentration profiles of the studied pollutants in preschools were higher than those in outdoor and rural areas. We believe that our findings may be useful for understanding the potential health effects of exposure and intervention studies in preschools.

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Section: Discussionmentioning

confidence: 99%

Indoor air quality differences between urban and rural preschools in Korea

Yoon

Lee

Park

2010

Environ Sci Pollut Res

118

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“…As with other crowded urban areas in Turkey, the outdoor air quality in urban Elazığ has deteriorated due to air pollution. The main causes of air pollution in Turkish residential areas are low quality coal and fuel-oil consumption, as well as also exhaust gases emitted by transportation vehicles (Demirci and Cuhadaroglu 2000).…”

Section: Introductionmentioning

confidence: 99%

“…Their results indicated that there is a moderate and weak level of relation between the SO 2 level and the meteorological factors in Trabzon city. In their other study, Demirci and Cuhadaroglu (2000) considered wind circulation and air pollution by taking into account wind directions with the same statistical code. They found that there is a weak relationship between wind speeds blowing from different directions and pollutant concentrations.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of relationship between meteorological parameters and air pollutant concentrations during winter season in Elazığ, Turkey

Akpınar

Öztop

Akpınar

2007

Environ Monit Assess

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In recent years, due to the rapid increase in population density, building density and energy consumption, the outdoor air quality has deteriorated in the crowded urban areas of Turkey. Elaziğ city, which is located in the east Anatolia region of Turkey, is also influenced by air pollutants. In the present study, relationship between monitored air pollutant concentrations such as SO2 and the total suspended particles (TSP) data and meteorological factors such as wind speed, temperature, relative humidity, solar radiation and atmospheric pressure was investigated in months of October, November, December, January, February, and March during the period of 3 years (2003, 2004 and 2005) for Elaziğ city. According to the results of linear and non-linear regression analysis, it was found that there is a moderate and weak level of relation between the air pollutant concentrations and the meteorological factors in Elaziğ city. The correlation between the previous day's SO2, TSP concentrations and actual concentrations of these pollutants on that day was investigated and the coefficient of determination R2 was found to be 0.64 and 0.54, respectively. The statistical models of SO2 and TSP including all of meteorological parameters gave R2 of 0.20 and 0.12, respectively. Further, in order to develop this model, previous day's SO2 and TSP concentrations were added to the equations. The new model for SO2 and TSP was improved considerably with R2 = 0.74 and 0.61, respectively.

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“…However, the concentrations of air pollutants usually vary randomly and are correlated with several factors such as types of fuels consumed, geographical and topographical peculiarities, town planning and meteorological factors, etc. (Demirci & Cuhadaroglu, 2000). Air quality management and information systems are required to control air pollutants and provide proper actions, controlling strategies and a better and safe environment for future generation (Bhanarkar, Goyal, Sivacoumar, & Chalapati Rao, 2005;Kurt, Gulbagci, Karaca, & Alagha, 2008;Lumbreras, ValdTs, Borge, & Rodriguez, 2008).…”

Section: Introductionmentioning

confidence: 99%

Unsupervised system to classify SO2 pollutant concentrations in Salamanca, Mexico

Barrón-Adame

Cortina-Januchs

Vega-Corona

et al. 2012

Expert Systems with Applications

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Keywords:Air pollution Meteorological variables Artificial neural networks Self-Organizing Maps (SOM) Clustering Salamanca is cataloged as one of the most polluted cities in Mexico. In order to observe the behavior and clarify the influence of wind parameters on the Sulphur Dioxide (S0 2 ) concentrations a Self-Organizing Maps (SOM) Neural Network have been implemented at three monitoring locations for the period from January 1 to December 31, 2006. The maximum and minimum daily values of S0 2 concentrations measured during the year of 2006 were correlated with the wind parameters of the same period. The main advantages of the SOM Neural Network is that it allows to integrate data from different sensors and provide readily interpretation results. Especially, it is powerful mapping and classification tool, which others information in an easier way and facilitates the task of establishing an order of priority between the distinguished groups of concentrations depending on their need for further research or remediation actions in subsequent management steps. For each monitoring location, SOM classifications were evaluated with respect to pollution levels established by Health Authorities. The classification system can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction.

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Statistical analysis of wind circulation and air pollution in urban Trabzon

Cited by 37 publications

References 1 publication

Indoor air quality differences between urban and rural preschools in Korea

Indoor air quality differences between urban and rural preschools in Korea

Evaluation of relationship between meteorological parameters and air pollutant concentrations during winter season in Elazığ, Turkey

Unsupervised system to classify SO2 pollutant concentrations in Salamanca, Mexico

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