پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 161 |
| تعداد شمارهها | 6,532 |
| تعداد مقالات | 70,501 |
| تعداد مشاهده مقاله | 124,097,410 |
| تعداد دریافت فایل اصل مقاله | 97,205,165 |
Contribution of Predictive Statistics in the Evaluation of Correlations between Air Pollutants and Traffic Intensity in the City of Kénitra | ||
| Pollution | ||
| دوره 11، شماره 1، بهمن 2024، صفحه 134-146 اصل مقاله (2.02 M) | ||
| نوع مقاله: Original Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/poll.2024.376596.2374 | ||
| نویسندگان | ||
| Mouhsine Hadine1؛ Jamal Mabrouki* 2؛ Najat Qisse2؛ Khadija El-Moustaqim3؛ Yassine El Yousfi4 | ||
| 1Laboratory of applied geophysics, geotechnics, geology of the engineer and the environment, Mohammed V University in Rabat. Mohammadia School of Engineers (EMI), B.P. 765, Agdal, Rabat, Morocco | ||
| 2Laboratory of Spectroscopy, Molecular Modeling, Materials, Nanomaterial, Water and Environment, CERNE2D, Faculty of Science, Mohammed V University in Rabat, Rabat, Morocco | ||
| 3Improvement and Valuation of Plant Resources, Faculty of Sciences, Ibn Tofaïl University—KENITRA-University Campus, Kenitra 14000, Morocco | ||
| 4Applied Sciences Laboratory LSA, Environmental Management and Civil Engineering GEGC Research Team, ENSAH, Abdelmalek Essaadi University, Tetouan 93030, Morocco | ||
| چکیده | ||
| In recent years, the problem of air pollution has become increasingly important in the field of the environment. That is why our research focuses on the air quality of this coastal city. It seems essential to carry out a diagnosis for this city. We have rigorously chosen eight sites based on their diverse conditions. The selected and targeted parameters are the following: Total suspended particulate (TSP), lead (Pb), cadmium (Cd), nitrogen dioxide (NO2), sulfur dioxide (SO2), and traffic intensity, which represent the explanatory variables and the explained variable respectively. In addition to the evaluation of the concentration of each pollutant in the study area, we analyzed the correlations between the exogenous variables and the endogenous variable. The results obtained suggest that, according to the coefficient table, the TSP and heavy metals such as Pb and Cd do not seem to play a decisive role in explaining the intensity of traffic because their significant values exceed 5%. On the other hand, nitrogen dioxide and sulfur dioxide showed values significantly below the significance level of 5%, i.e., 0.005 and 0.018, respectively. These factors could provide an explanation for the intensity of traffic. However, the standard error results of these two variables have changed the meaning of their correlation, indicating that only nitrogen dioxide is positively evolving in the same direction as traffic intensity. Nitrogen dioxide exhibits a strong correlation with traffic intensity. NO2 could therefore be considered an indicator of traffic-related urban air pollution. The advantage of this analysis and interpretation methodology lies in its ability to provide a predictive and preventive tool to identify specific measures to reduce air pollution. | ||
| کلیدواژهها | ||
| Air Quality؛ Traffic Intensity؛ Multiple Linear Regression (MLR)؛ Correlation؛ Kénitra | ||
| مراجع | ||
|
Afnor. (1991). Gas analysis. Air quality (vol 1). Pp 178-179. Afnor. (1996). Air quality environment. pp 35-38 Arkkelin, D. (2014). Using SPSS to Understand Research and Data Analysis. Psychology Curricular Materials Bard, D. (2017). Acting locally on air pollution, Environ. Risques Santé, 16(4), 332-333, Bencheikh, I., Mabrouki, J., Azoulay, K., et al. (2020).Predictive analytics and optimization of wastewater treatment efficiency using statistic approach. In : Big Data and Networks Technologies 3. Springer International Publishing: 310-319. Bobbia, M., Pernelet, V., & Roth, C. (2001). L’intégration des informations indirectes à la cartographie géostatistique des polluants. Poll Atmos 2001 ; 170 : 251-62. Cihan, S., Ashish, T., & Vassil, N.A. (2006). Grid Enablement of the Danish Eulerian Air Pollution Model, Lecture Notes in Computer Science, High Performance Computing and Communications, Dodge, Y., & Rousson, V. (2004). Analysis of applied regression. Collection: Eco sup, Dunod ; 56-62, 280. Eddine, S. S., Drissi, L. B., Mejjad, N., Mabrouki, J., & Romanov, A. A. (2024). Machine learning models application for spatiotemporal patterns of particulate matter prediction and forecasting over Morocco in north of Africa. Atmospheric Pollution Research, 15(9) : 102239. Ennasri, F. Z., Mabrouki, J., Hadine, M., & Slaoui, M. (2024). Evaluation and Modeling of Air Pollution in the City of Casablanca, Morocco. In Technical and Technological Solutions Towards a Sustainable Society and Circular Economy: 357-365. Fabienne, C., Corneau, M., & Cousineau, M.M. (2010). Guide d’introduction au logiciel SPSS. CRI-1600 G : Initiation aux méthodes quantitatives. Certificat de criminologie. Faculté de l’éducation permanente. Pages 66-70 Falissard, B. (1998). Comprendre et utiliser les statistiques dans les sciences de la vie. Paris : Masson, 1998 : pages 65-9. Fattah, G., Elouardi, M., Benchrifa, M., Ghrissi, F., & Mabrouki, J. (2023). Modeling of the coagulation system for treatment of real water rejects. In Advanced technology for smart environment and energy : 161-171. Fattah, G., Mabrouki, J., Ghrissi, F., Azrour, M., & Abrouki, Y. (2022). Multi-sensor system and internet of things (IoT) technologies for air pollution monitoring. In Futuristic research trends and applications of Internet of Things . CRC Press: 101-116. Garth, A. (2008). Analyzing data using SPSS. Sheffield Hallam University. Ghizlane, F., Mabrouki, J., Ghrissi, F., & Azrour, M. (2022). Proposal for a high-resolution particulate matter (PM10 and PM2. 5) capture system, comparable with hybrid system-based internet of things: case of quarries in the western rif, Morocco. Pollution, 8(1) : 169-180. Gitte, B. H., Jørgen Brandt, J. H., Christensen, L. M., Frohn, C. G., Kaj, M. H., & Martin, S. (2005). Impacts of Climate Change on Air Pollution Levels in the Northern Hemisphere with Special Focus on Europe and the Arctic. NATO Science for Peace and Security Series C: Environmental Security, Air Pollution Modeling and Its Application XIX, ISO standard 6767 (1990). Ambient air — Determination of the mass concentration of Sulphur dioxide, Tetrachloromercurate (TMC) and pararosaniline method, International Organization for Standardization. Jasrai, L. (2020). Data analysis using SPSS. Sage Publications Pvt Kampa, M., & Castanas, E. (2008). Human health effects of air pollution, Environ. Pollut., 151(2), 362–367, doi: 10.1016/j.envpol.2007.06.012. Katz, M., and al. (1970). Measuring air pollutants: A guide to choosing methods. World Health Organization, Geneva. 130 pp. Kelly, F.J., Fussell, J.C. (2012). Size, source and chemical composition as determinants of toxicity attributable to ambient particulate matter. Atmos. Environ. 60, 504–526 Labreuche, J. (2010). Les différents types de variables, leurs représentations graphiques et paramètres descriptifs. Sang Thrombose Vaisseaux 2010 ; 22 : 536-43. Levesque, R. (2007). SPSS programming and data management: A guide for SPSS and SAS users. Mejjad, N., Sbai, S. E., Laissaoui, A., Benchrif, A., Aouidi, S. E., & Mabrouki, J. (2024). Air Pollution Research in African Countries: A Bibliometric Visualization and Analysis Using Dimensions. Ai and Scopus Databases. In Advanced Technology for Smart Environment and Energy : 53-66. Nafstad, P., Haheim, L.L., Oftedal, B., Gram, F., Holme, I., Hjermann, I., & Leren, P. (2003). Lung cancer and air pollution: a 27 years follow-up of 16 209 Norwegian men. Thorax 2003; 58:1071-1076. Nyberg, F., Gustavsson, P., Järup, L., Bellander, T., Berglind, N., Jakobsson, R., & Pershagen, G. (2000). Urban air pollution and lung cancer in Stocklom. Epidemiology, 11: 487-495. Rodriguez, J. A., & Hrbek, J. (1999). Interaction of sulfur with well-defined metal and oxide surfaces: Unraveling the mysteries behind catalyst poisoning and desulfurization. Acc. Chem. Res., 32(9), 719–728, doi:10.1021/ar9801191, Sbai, S. E., Mejjad, N., & Mabrouki, J. (2024). Oxidation Flow Reactor for Simulating and Accelerating Atmospheric Secondary Aerosol Formation. In Technical and Technological Solutions Towards a Sustainable Society and Circular Economy: 543-555. Sleiman, H. (2016). Air pollution: blood lead and road traffic in Beirut. 2268-3798 Stadlober, E., Hörmann, S., & Pfeiler, B. (2008). Quality and performance of a PM10 daily forecasting model. Atmospheric Environment 42 (6), pages 1098– 1109. Tam, P. S., Kittrell, J. R., & Eldridge, J.W. (1990). Desulfurization of fuel oil by oxidation and extraction. 1. Enhancement of extraction oil yield, Ind. Eng. Chem. Res., 29(3), 321–324, doi:10.1021/ie00099a002, Tenenhaus, M. (2007). Statistique 2ème édition : Méthodes pour décrire, expliquer et prévoir », Collection : Management Sup Dunod pp 38-42, 696 pages. Vorhies, B. (2017). SPSS Statistics to Predict Customer Behavior [Webinar]. Data Science Central | ||
|
آمار تعداد مشاهده مقاله: 159 تعداد دریافت فایل اصل مقاله: 168 |
||