{"doi":"10.15587/1729-4061.2019.175892","title":"Improvement of the model of forecasting heavy metals of exhaust gases of motor vehicles in the soil","abstract":null,"journal":"Eastern-European Journal of Enterprise Technologies","year":2019,"id":684878,"datarank":0.48283137373023016,"base_score":3.2188758248682006,"endowment":3.2188758248682006,"self_citation_contribution":0.48283137373023016,"citation_network_contribution":0.0,"self_endowment_contribution":0.48283137373023016,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":24,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1789337,"name":"Vasyl Melnyk","orcid":"0000-0002-5793-5486","position":1,"is_corresponding":false},{"id":1789339,"name":"Bogdan Dolishnii","orcid":"0000-0002-4591-5381","position":2,"is_corresponding":false},{"id":1789341,"name":"Volodymyr Korohodskyi","orcid":"0000-0002-1605-4631","position":3,"is_corresponding":false},{"id":1789343,"name":"Igor Prunko","orcid":"0000-0002-0242-614X","position":4,"is_corresponding":false},{"id":1789345,"name":"Liudmyla Kryshtopa","orcid":"0000-0002-5274-0217","position":5,"is_corresponding":false},{"id":1789347,"name":"Ihor Zakhara","orcid":"0000-0001-6214-6548","position":6,"is_corresponding":false},{"id":1789350,"name":"Tetiana Voitsekhivska","orcid":"0000-0001-7967-4953","position":7,"is_corresponding":false},{"id":1789336,"name":"Sviatoslav Kryshtopa","orcid":"0000-0001-7899-8817","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Improvement of the model of forecasting heavy metals of exhaust gases of motor vehicles in the soil","abstract":"Consideration of the problem of modeling the penetration of heavy metals of exhaust gases of automobile engines is carried out for the soil with permeability coefficient cp and diffusion coefficient D. As a result of mathematical modeling, an exponential equation is obtained, the input variables for which are the surface concentration of harmful components c, permeability coefficient cp, diffusion coefficient D and soil depth l. The output variables for the obtained exponential equation is the concentration of harmful components C1 at a depth l.According to the obtained equation, the depth of penetration of heavy metals into the soil – l is theoretically investigated, depending on the surface concentration с1˂с2 and at constant ratio cp/D. As a result, the penetration depth of heavy metals increases, which is due to an increase in the driving force of the diffusion process. Having studied the effect of an increase in the cp/D ratio on the penetration depth of heavy metals into the soil at constant surface concentrations c1 and c2, a decrease in their penetration depth is found, which is due to a decrease in the diffusion process.The obtained theoretical results are confirmed by experimental studies of the depth of penetration of heavy metals – exhaust gases of the ZMZ-511.10 petrol engine into the soil. It is found that the content of heavy metals in the soil at an arbitrary depth corresponds to theoretical calculations, and the discrepancy is within the measurement error. When measuring the lead concentration, the discrepancy is within 12.5–15 %, zinc 5.5–7.5 %, manganese 8.5–11 %. So, the concentrations of heavy metals, measured at arbitrary depths, are 0.1 and 0.2 m for lead; 0.1, 0.2 and 0.3 m for zinc; 0.1; 0.2 and 0.25 m for manganese. This indicates the validity of the results obtained by the exponential equation. Therefore, the proposed model provides high accuracy in determining the concentration of heavy metals in the soil and can be used for forecasting their penetration depth if the surface concentration is known","is_dataset_classified":null,"base_score":3.2188758248682006,"endowment":3.2188758248682006,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"26207759","pmcid":null,"openalex_id":"https://openalex.org/W2978628615","authors":[],"funders":[],"total_grants":0,"fwci":1.2008,"citation_percentile":0.79195963,"influential_citations":0,"citation_trend":[{"year":2020,"count":5},{"year":2021,"count":4},{"year":2022,"count":3},{"year":2023,"count":5},{"year":2024,"count":1},{"year":2025,"count":6}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"http://journals.uran.ua/eejet/article/download/175892/176989","host_type":"journal"},{"url":"http://journals.uran.ua/eejet/article/download/175892/176989","host_type":"publisher"},{"url":"https://doi.org/10.15587/1729-4061.2019.175892","host_type":"journal"},{"url":"https://doaj.org/article/949fb4e809de4ad5bcf34436a16f9895","host_type":"repository"},{"url":"https://zenodo.org/record/3463122","host_type":"repository"}],"fields_of_study":["Technical Engine Diagnostics and Monitoring","Aerospace, Electronics, Mathematical Modeling","Environmental and Industrial Safety"],"mesh_terms":[],"keywords":["Penetration (warfare)","Penetration depth","Exponential function","Exponential decay","Diffusion","Soil water","Exhaust gas","Chemistry","Soil science","Analytical Chemistry (journal)","Materials science","Environmental science","Environmental chemistry","Thermodynamics","Physics","Mathematics","road transport","fuel","petrol","exhaust gases","heavy metals","soil","pollution forecasting"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Life in Land"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-18T15:14:52.558793Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}