Investigation of VOC Series Collected in a Refinery and Their Classification Based on Statistical Features
In the context of the increased pollution from different sources and its significant negative effect on the population’s health and environment, the article presents a comprehensive analysis of the data series formed by the concentrations of the volatile organic compounds (VOCs) collected in three z...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/14/24/11921 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846105983606063104 |
|---|---|
| author | Alina Bărbulescu Sebastian-Barbu Barbeş Lucica Barbeş Cristian Ștefan Dumitriu |
| author_facet | Alina Bărbulescu Sebastian-Barbu Barbeş Lucica Barbeş Cristian Ștefan Dumitriu |
| author_sort | Alina Bărbulescu |
| collection | DOAJ |
| description | In the context of the increased pollution from different sources and its significant negative effect on the population’s health and environment, the article presents a comprehensive analysis of the data series formed by the concentrations of the volatile organic compounds (VOCs) collected in three zones—storage areas in the reservoir park—of a refinery complex in Romania during the maintenance period. Statistical analyses, including parametric and nonparametric tests, were performed to assess the correlation between the studied series and to group them based on some common features. The series were clustered using the raw data, and the series features were extracted after the statistical analysis. The results indicate that the series are not correlated and do not follow the same distribution even though the study zone is not large. The sites’ classification based on statistical features is shown to be more relevant from the viewpoint of the emissions level than that provided using the raw series. The Principal Component Analysis (PCA) indicates that the features with the highest contribution on the first two components are maximum, standard deviation, autocorrelation, and partial autocorrelation for Zone 1; average, maximum, minimum, and partial autocorrelation for Zone 2; and skewness, average, maximum, and standard deviation for Zone 3. The study’s novelty is two-fold. First, it provides the results of the study performed during the maintenance period of the storage tanks, which was insufficiently investigated in the literature. Secondly, since complete data series are not generally available to the large public, clustering them based on their features provides a clear image of pollution levels and the sites where actions should be taken to reduce it. This investigation offers essential insights that can serve as a background for developing effective air pollutant monitoring strategies and mitigation measures by understanding the emission patterns and identifying the factors that influence VOC levels during the maintenance of storage tanks for highly volatile petroleum products. |
| format | Article |
| id | doaj-art-44ed9a35a4b4410c82fc29706d7ed44f |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-44ed9a35a4b4410c82fc29706d7ed44f2024-12-27T14:08:46ZengMDPI AGApplied Sciences2076-34172024-12-0114241192110.3390/app142411921Investigation of VOC Series Collected in a Refinery and Their Classification Based on Statistical FeaturesAlina Bărbulescu0Sebastian-Barbu Barbeş1Lucica Barbeş2Cristian Ștefan Dumitriu3Department of Civil Engineering, Transilvania University of Brașov, 5 Turnului Str., 500152 Braşov, RomaniaDoctoral School of Civil Engineering, Technical University of Civil Engineering of Bucharest, 122-124 Lacul Tei Bvd., 020396 Bucharest, RomaniaDepartment of Chemistry and Chemical Engineering, Ovidius University of Constanța, 124 Mamaia Bvd., 900527 Constanta, RomaniaFaculty of Mechanical Engineering and Robotics in Constructions, Technical University of Civil Engineering Bucharest, 59 Calea Plevnei, 010223 Bucharest, RomaniaIn the context of the increased pollution from different sources and its significant negative effect on the population’s health and environment, the article presents a comprehensive analysis of the data series formed by the concentrations of the volatile organic compounds (VOCs) collected in three zones—storage areas in the reservoir park—of a refinery complex in Romania during the maintenance period. Statistical analyses, including parametric and nonparametric tests, were performed to assess the correlation between the studied series and to group them based on some common features. The series were clustered using the raw data, and the series features were extracted after the statistical analysis. The results indicate that the series are not correlated and do not follow the same distribution even though the study zone is not large. The sites’ classification based on statistical features is shown to be more relevant from the viewpoint of the emissions level than that provided using the raw series. The Principal Component Analysis (PCA) indicates that the features with the highest contribution on the first two components are maximum, standard deviation, autocorrelation, and partial autocorrelation for Zone 1; average, maximum, minimum, and partial autocorrelation for Zone 2; and skewness, average, maximum, and standard deviation for Zone 3. The study’s novelty is two-fold. First, it provides the results of the study performed during the maintenance period of the storage tanks, which was insufficiently investigated in the literature. Secondly, since complete data series are not generally available to the large public, clustering them based on their features provides a clear image of pollution levels and the sites where actions should be taken to reduce it. This investigation offers essential insights that can serve as a background for developing effective air pollutant monitoring strategies and mitigation measures by understanding the emission patterns and identifying the factors that influence VOC levels during the maintenance of storage tanks for highly volatile petroleum products.https://www.mdpi.com/2076-3417/14/24/11921VOCsstatistical analysisfeaturesclassification |
| spellingShingle | Alina Bărbulescu Sebastian-Barbu Barbeş Lucica Barbeş Cristian Ștefan Dumitriu Investigation of VOC Series Collected in a Refinery and Their Classification Based on Statistical Features Applied Sciences VOCs statistical analysis features classification |
| title | Investigation of VOC Series Collected in a Refinery and Their Classification Based on Statistical Features |
| title_full | Investigation of VOC Series Collected in a Refinery and Their Classification Based on Statistical Features |
| title_fullStr | Investigation of VOC Series Collected in a Refinery and Their Classification Based on Statistical Features |
| title_full_unstemmed | Investigation of VOC Series Collected in a Refinery and Their Classification Based on Statistical Features |
| title_short | Investigation of VOC Series Collected in a Refinery and Their Classification Based on Statistical Features |
| title_sort | investigation of voc series collected in a refinery and their classification based on statistical features |
| topic | VOCs statistical analysis features classification |
| url | https://www.mdpi.com/2076-3417/14/24/11921 |
| work_keys_str_mv | AT alinabarbulescu investigationofvocseriescollectedinarefineryandtheirclassificationbasedonstatisticalfeatures AT sebastianbarbubarbes investigationofvocseriescollectedinarefineryandtheirclassificationbasedonstatisticalfeatures AT lucicabarbes investigationofvocseriescollectedinarefineryandtheirclassificationbasedonstatisticalfeatures AT cristianstefandumitriu investigationofvocseriescollectedinarefineryandtheirclassificationbasedonstatisticalfeatures |