Prediction of fine particulate matter in low-emission zones using a modified numerical method for a system of ordinary differential equations

• Autorzy: Asenov Asen , Georgiev Ivan , Pencheva Velizara , Mineva Kremena

Identyfikatory

DOI

10.20858/tp.2022.17.3.17

• Języki publikacji: EN

Abstrakty

EN

Currently, many European cities have severely exceeded the EU air quality standards and are struggling with high concentrations of fine particulate matter PM10 and PM2.5 in the air, with road transport often being one of the major polluters. One of the forms for correction of the problem that many cities in the EU are currently using is the construction of low-emission zones. For the prediction of PM10 and PM2.5, a modified numerical method for a system of ordinary differential equations has been proposed. In the right part of this system, in addition to the main trend and the periodicity of PM10 and PM2.5, their correlation is taken into account. Against the background of the best solution obtained, a forecast is made fo the emission levels in a period of one week in the town of Ruse.

Słowa kluczowe

EN

low-emission zone; PM10; PM2.5; prediction

PL

strefa niskiej emisji; PM10; PM2.5; prognoza

• Wydawca: Wydawnictwo Politechniki Śląskiej
• Czasopismo: Transport Problems
• Rocznik: 2022
• Tom: T. 17, z. 3
• Strony: 197--210
• Opis fizyczny: Bibliogr. 16 poz.

Twórcy

autor

Asenov Asen

• University of Ruse, Department of Transport; 8 Studentska St., 7017 Ruse, Bulgaria

• https://orcid.org/0000-0002-9770-0403

autor

Georgiev Ivan

• University of Ruse, Department of Applied Mathematics and Statistics; 8 Studentska St. 7017 Ruse, Bulgaria

• https://orcid.org/0000-0001-6275-6557

autor

Pencheva Velizara

• University of Ruse, Department of Transport, 8 Studentska St., 7017 Ruse, Bulgaria

• https://orcid.org/0000-0002-9809-4759

autor

Mineva Kremena

• University of Ruse, Department of Transport, 8 Studentska St., 7017 Ruse, Bulgaria

• https://orcid.org/0000-0002-6068-2934

Bibliografia

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).