IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i12p2146-d843188.html
   My bibliography  Save this article

Innovative Digital Stochastic Methods for Multidimensional Sensitivity Analysis in Air Pollution Modelling

Author

Listed:
  • Venelin Todorov

    (Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
    Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria)

  • Ivan Dimov

    (Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria)

Abstract

Nowadays, much of the world has a regional air pollution strategy to limit and decrease the pollution levels across governmental borders and control their impact on human health and ecological systems. Environmental protection is among the leading priorities worldwide. Many challenges in this research area exist since it is a painful subject for society and a fundamental topic for the healthcare system. Sensitivity analysis has a fundamental role during the process of validating a large-scale air pollution computational models to ensure their accuracy and reliability. We apply the best available stochastic algorithms for multidimensional sensitivity analysis of the UNI-DEM model, which plays a key role in the management of the many self-governed systems and data that form the basis for forecasting and analyzing the consequences of possible climate change. We develop two new highly convergent digital sequences with special generating matrices, which show significant improvement over the best available existing stochastic methods for measuring the sensitivity indices of the digital ecosystem. The results obtained through sensitivity analysis will play an extremely important multi-sided role.

Suggested Citation

  • Venelin Todorov & Ivan Dimov, 2022. "Innovative Digital Stochastic Methods for Multidimensional Sensitivity Analysis in Air Pollution Modelling," Mathematics, MDPI, vol. 10(12), pages 1-14, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:12:p:2146-:d:843188
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/12/2146/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/12/2146/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stefka Fidanova & Petar Zhivkov & Olympia Roeva, 2022. "InterCriteria Analysis Applied on Air Pollution Influence on Morbidity," Mathematics, MDPI, vol. 10(7), pages 1-8, April.
    2. Iooss, Bertrand & Van Dorpe, François & Devictor, Nicolas, 2006. "Response surfaces and sensitivity analyses for an environmental model of dose calculations," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1241-1251.
    3. Jacques, Julien & Lavergne, Christian & Devictor, Nicolas, 2006. "Sensitivity analysis in presence of model uncertainty and correlated inputs," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1126-1134.
    4. Karaivanova, Aneta & Dimov, Ivan, 1998. "Error analysis of an adaptive Monte Carlo method for numerical integration," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 47(2), pages 201-213.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu Yang & Mengmeng Suo & Shunqian Gao & Hongzan Jiao, 2022. "Construction of an Ecological Network Based on an Integrated Approach and Circuit Theory: A Case Study of Panzhou in Guizhou Province," Sustainability, MDPI, vol. 14(15), pages 1-29, July.
    2. Dimosthenis Kotsopoulos, 2022. "Organizational Energy Conservation Matters in the Anthropocene," Energies, MDPI, vol. 15(21), pages 1-30, November.
    3. Yilong Li & Yu-Ting Tang & May Tan-Mullins & Christopher D. Ives, 2023. "Exploring the Potential Opportunities of China’s Environmental Agenda, Ecological Civilization, on Global Sustainable Development," Sustainability, MDPI, vol. 15(6), pages 1-25, March.
    4. Aknur Temireyeva & Khabiba Zhunussova & Madiyar Aidabulov & Christos Venetis & Yerbol Sarbassov & Dhawal Shah, 2022. "Greenhouse Gas Emissions-Based Development and Characterization of Optimal Scenarios for Municipal Solid and Sewage Sludge Waste Management in Astana City," Sustainability, MDPI, vol. 14(23), pages 1-12, November.
    5. Ying Chen & Qi Da & Weizhang Liang & Peng Xiao & Bing Dai & Guoyan Zhao, 2022. "Bagged Ensemble of Gaussian Process Classifiers for Assessing Rockburst Damage Potential with an Imbalanced Dataset," Mathematics, MDPI, vol. 10(18), pages 1-22, September.
    6. Nurulkamal Masseran & Muhammad Aslam Mohd Safari, 2022. "Statistical Modeling on the Severity of Unhealthy Air Pollution Events in Malaysia," Mathematics, MDPI, vol. 10(16), pages 1-15, August.
    7. Yuan Liu & Wangyang Yu & Cong Gao & Minsi Chen, 2022. "An Auto-Extraction Framework for CEP Rules Based on the Two-Layer LSTM Attention Mechanism: A Case Study on City Air Pollution Forecasting," Energies, MDPI, vol. 15(16), pages 1-16, August.
    8. Ioannis S. Triantafyllou, 2022. "Signature-Based Analysis of the Weighted- r -within-Consecutive- k -out-of- n : F Systems," Mathematics, MDPI, vol. 10(15), pages 1-13, July.
    9. Anderson Palmeira & Éder Pereira & Paulo Ferreira & Luisa Maria Diele-Viegas & Davidson Martins Moreira, 2022. "Long-Term Correlations and Cross-Correlations in Meteorological Variables and Air Pollution in a Coastal Urban Region," Sustainability, MDPI, vol. 14(21), pages 1-12, November.
    10. Luca Adami & Marco Schiavon, 2022. "A Quali-Quantitative Comparison between In Situ and Ex Situ Waste-to-Energy Processes in Terms of Local and Global Impacts," Resources, MDPI, vol. 11(10), pages 1-11, October.
    11. Riccardo Fontana & Marco Marzola & Mattia Buratto & Giulia Trioschi & Anna Caproni & Chiara Nordi & Cesare Buffone & Beatrice Bandera & Luciano Vogli & Peggy Marconi, 2022. "Analysis of Civil Environments Cleaning Services—Microbiological and LCA Analysis after Traditional and Sustainable Procedures," Sustainability, MDPI, vol. 15(1), pages 1-19, December.
    12. Leslier Valenzuela-Fernández & Manuel Escobar-Farfán, 2022. "Zero-Waste Management and Sustainable Consumption: A Comprehensive Bibliometric Mapping Analysis," Sustainability, MDPI, vol. 14(23), pages 1-24, December.
    13. Wancheng Xie & Andrew Chapman & Taihua Yan, 2023. "Do Environmental Regulations Facilitate a Low-Carbon Transformation in China’s Resource-Based Cities?," IJERPH, MDPI, vol. 20(5), pages 1-23, March.
    14. Kaimeng Li & Shuang Gao & Yuantao Liao & Ke Luo & Shaojian Wang, 2022. "The Impact of Development Zones on China’s Urbanization from the Perspectives of the Population, Land, and the Economy," Land, MDPI, vol. 11(10), pages 1-16, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Venelin Todorov & Slavi Georgiev & Ivan Georgiev & Snezhinka Zaharieva & Ivan Dimov, 2023. "Optimizing Air Pollution Modeling with a Highly-Convergent Quasi-Monte Carlo Method: A Case Study on the UNI-DEM Framework," Mathematics, MDPI, vol. 11(13), pages 1-14, June.
    2. Dimov, I. & Georgieva, R., 2010. "Monte Carlo algorithms for evaluating Sobol’ sensitivity indices," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(3), pages 506-514.
    3. Labopin-Richard T. & Gamboa F. & Garivier A. & Iooss B., 2016. "Bregman superquantiles. Estimation methods and applications," Dependence Modeling, De Gruyter, vol. 4(1), pages 1-33, March.
    4. Iooss, Bertrand & Ribatet, Mathieu, 2009. "Global sensitivity analysis of computer models with functional inputs," Reliability Engineering and System Safety, Elsevier, vol. 94(7), pages 1194-1204.
    5. Auder, Benjamin & De Crecy, Agnès & Iooss, Bertrand & Marquès, Michel, 2012. "Screening and metamodeling of computer experiments with functional outputs. Application to thermal–hydraulic computations," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 122-131.
    6. Broto, Baptiste & Bachoc, François & Depecker, Marine & Martinez, Jean-Marc, 2019. "Sensitivity indices for independent groups of variables," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 163(C), pages 19-31.
    7. López-Benito, Alfredo & Bolado-Lavín, Ricardo, 2017. "A case study on global sensitivity analysis with dependent inputs: The natural gas transmission model," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 11-21.
    8. Mara, Thierry A. & Tarantola, Stefano, 2012. "Variance-based sensitivity indices for models with dependent inputs," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 115-121.
    9. Deman, G. & Kerrou, J. & Benabderrahmane, H. & Perrochet, P., 2015. "Sensitivity analysis of groundwater lifetime expectancy to hydro-dispersive parameters: The case of ANDRA Meuse/Haute-Marne site," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 276-286.
    10. Blagojević, Nikola & Didier, Max & Stojadinović, Božidar, 2022. "Quantifying component importance for disaster resilience of communities with interdependent civil infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    11. Rogeau, A. & Girard, R. & Kariniotakis, G., 2017. "A generic GIS-based method for small Pumped Hydro Energy Storage (PHES) potential evaluation at large scale," Applied Energy, Elsevier, vol. 197(C), pages 241-253.
    12. Salacinska, K. & El Serafy, G.Y. & Los, F.J. & Blauw, A., 2010. "Sensitivity analysis of the two dimensional application of the Generic Ecological Model (GEM) to algal bloom prediction in the North Sea," Ecological Modelling, Elsevier, vol. 221(2), pages 178-190.
    13. Zio, E. & Pedroni, N., 2009. "Functional failure analysis of a thermal–hydraulic passive system by means of Line Sampling," Reliability Engineering and System Safety, Elsevier, vol. 94(11), pages 1764-1781.
    14. Marrel, Amandine & Iooss, Bertrand & Van Dorpe, François & Volkova, Elena, 2008. "An efficient methodology for modeling complex computer codes with Gaussian processes," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4731-4744, June.
    15. Haro Sandoval, Eduardo & Anstett-Collin, Floriane & Basset, Michel, 2012. "Sensitivity study of dynamic systems using polynomial chaos," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 15-26.
    16. Alrefaei, Mahmoud H. & Abdul-Rahman, Houssam M., 2008. "An adaptive Monte Carlo integration algorithm with general division approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(1), pages 49-59.
    17. Marrel, Amandine & Iooss, Bertrand & Laurent, Béatrice & Roustant, Olivier, 2009. "Calculations of Sobol indices for the Gaussian process metamodel," Reliability Engineering and System Safety, Elsevier, vol. 94(3), pages 742-751.
    18. Lin, Yan-Hui & Yam, Richard C.M., 2017. "Uncertainty importance measures of dependent transition rates for transient and steady state probabilities," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 402-409.
    19. Marie Hermant & Olivier Blanchard & Guillaume Perouel & Guillaume Boulanger & Mathilde Merlo & Virginie Desvignes, 2018. "Environmental Exposure of the Adult French Population to Permethrin," Risk Analysis, John Wiley & Sons, vol. 38(4), pages 853-865, April.
    20. Mirko Ginocchi & Ferdinanda Ponci & Antonello Monti, 2021. "Sensitivity Analysis and Power Systems: Can We Bridge the Gap? A Review and a Guide to Getting Started," Energies, MDPI, vol. 14(24), pages 1-59, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:12:p:2146-:d:843188. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.