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RISS 인기검색어
- 검색키워드
- 저자 : Mohammad K. Younes (검색결과 3 건)
- 무료
- 기관 내 무료
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Integration of Traffic Management and an Artificial Intelligence to Evaluate Urban Air Quality
Mohammad K. Younes,Ghassan Sulaiman,Ali Al-Mashni 한국대기환경학회 2020 Asian Journal of Atmospheric Environment (AJAE) Vol.14 No.3
Emissions from motor vehicles are the primary source of air pollution, especially in congested urban centres. However, through effective traffic management, it has been found that the level of pollution can be significantly reduced, facilitating the mobility of urban arterials. This study aims to quantify the extent of traffic emissions and to identify the influence of traffic management to improve air quality and reducing traffic emissions. An Adaptive Neuro-Fuzzy Inference System (ANFIS) model was developed to estimate the extent of traffic emissions(NO2 and PM10) at certain intersections. Then, a traffic management simulation software was also used to simulate traffic and to build a traffic improvement scenario at these intersections. This was followed by measuring the improvement in air quality due to traffic management modification, analysed using the developed ANFIS model. The results showed that reducing the delay at certain intersections may reduce NO2 and PM10 significantly. The proposed hybrid model increased the forecasting accuracy and improved the perception between the relationship between traffic characteristics and pollutant emissions. Additionally, it facilitates the work of city planners and helps decision making regarding urban air quality.
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Ghassan Sulaiman,Mohammad K. Younes,Ghassan A. Al-Dulaimi 대한환경공학회 2018 Environmental Engineering Research Vol.23 No.1
Air quality and pollution have recently become a major concern; vehicle emissions significantly pollute the air, especially in large and crowded cities. There are various factors that affect vehicle emissions; this research aims to find the most influential factors affecting CO₂ and NOx emissions using Adaptive Neural Fuzzy Inference System (ANFIS) as well as a systematic approach. The modified ANFIS (MANFIS) was developed to enhance modelling and Root Mean Square Error was used to evaluate the model performance. The results show that percentages of CO₂ from trucks represent the best input combination to model. While for NOx modelling, the best pair combination is the vehicle delay and percentage of heavy trucks. However, the final MANFIS structure involves two inputs, three membership functions and nine rules. For CO₂ modelling the triangular membership function is the best, while for NOx the membership function is two-sided Gaussian.
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Methane Oxidation in Landfill Cover Soils: A Review
Mohammed F.M. Abushammala,Noor Ezlin Ahmad Basri,Dani Irwan,Mohammad K. Younes 한국대기환경학회 2014 Asian Journal of Atmospheric Environment (AJAE) Vol.8 No.1
Migration of methane (CH4) gas from landfills to thesurrounding environment negatively affects bothhumankind and the environment. It is thereforeessential to develop management techniques toreduce CH4 emissions from landfills to minimize globalwarming and to reduce the human risks associatedwith CH4 gas migration. Oxidation of CH4 in landfillcover soil is the most important strategy for CH4emissions mitigation. CH4 oxidation occurs naturallyin landfill cover soils due to the abundance of methanotrophicbacteria. However, the activities of thesebacteria are influenced by several controlling factors. This study attempts to review the important issuesassociated with the CH4 oxidation process in landfillcover soils. The CH4 oxidation process is highly sensitiveto environmental factors and cover soil properties. The comparison of various biotic system techniquesindicated that each technique has uniqueadvantages and disadvantages, and the choice ofthe best technique for a specific application dependson economic constraints, treatment efficiency andlandfill operations.
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