{"title":"利用突出淡水微藻对荧蒽进行生物处理:微藻的生理反应和生物去除过程的人工神经网络模型。","authors":"Samaneh Torbati, Behrouz Atashbar Kangarloei, Zahra Asalpisheh","doi":"10.1080/15226514.2023.2288900","DOIUrl":null,"url":null,"abstract":"<p><p>Due to the intensified industrial activities and other anthropogenic actions, contamination of polycyclic aromatic hydrocarbons (PAHs) has been growing at an alarming rate, turning in to a serious environmental concern. Bioremediation, as an eco-friendly and sustainable removal technology, can be used by organisms to reduce the resulting contaminations. In the present study, the ability of <i>Tetradesmus obliquus</i> to remove of fluoranthene (FLA) was evaluated. It was confirmed that FLA removal efficiency was managed by various environmental parameters and pH was found to be one of the most important influencial factors. The reusability of the algae in long-term repetitive operations confirmed the occurrence of biodegradation along with other natural attenuation and 10 intermediate compounds were identified in the FLA biodegradation pathway by GC-MS. As a result of physiological assays, induced antioxidant enzymes activities and augmentation of phenol and flavonoids contents, after the treatment of the microalgae by a high concentration of FLA, confirmed the ability of the microalgae to upregulate its antioxidant defense system in response to the toxic effects of FLA. An artificial neural network (ANN) model was then developed to predict FLA biodegradation efficiency and the appropriate predictive performance of ANN was confirmed by comparing the experimental FLA removal efficiency with its predicted amounts (R<sup>2</sup> = 0.99).</p>","PeriodicalId":14235,"journal":{"name":"International Journal of Phytoremediation","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fluoranthene biotreatment using prominent freshwater microalgae: physiological responses of microalgae and artificial neural network modeling of the bioremoval process.\",\"authors\":\"Samaneh Torbati, Behrouz Atashbar Kangarloei, Zahra Asalpisheh\",\"doi\":\"10.1080/15226514.2023.2288900\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Due to the intensified industrial activities and other anthropogenic actions, contamination of polycyclic aromatic hydrocarbons (PAHs) has been growing at an alarming rate, turning in to a serious environmental concern. Bioremediation, as an eco-friendly and sustainable removal technology, can be used by organisms to reduce the resulting contaminations. In the present study, the ability of <i>Tetradesmus obliquus</i> to remove of fluoranthene (FLA) was evaluated. It was confirmed that FLA removal efficiency was managed by various environmental parameters and pH was found to be one of the most important influencial factors. The reusability of the algae in long-term repetitive operations confirmed the occurrence of biodegradation along with other natural attenuation and 10 intermediate compounds were identified in the FLA biodegradation pathway by GC-MS. As a result of physiological assays, induced antioxidant enzymes activities and augmentation of phenol and flavonoids contents, after the treatment of the microalgae by a high concentration of FLA, confirmed the ability of the microalgae to upregulate its antioxidant defense system in response to the toxic effects of FLA. An artificial neural network (ANN) model was then developed to predict FLA biodegradation efficiency and the appropriate predictive performance of ANN was confirmed by comparing the experimental FLA removal efficiency with its predicted amounts (R<sup>2</sup> = 0.99).</p>\",\"PeriodicalId\":14235,\"journal\":{\"name\":\"International Journal of Phytoremediation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Phytoremediation\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1080/15226514.2023.2288900\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/12/12 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Phytoremediation","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1080/15226514.2023.2288900","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/12/12 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Fluoranthene biotreatment using prominent freshwater microalgae: physiological responses of microalgae and artificial neural network modeling of the bioremoval process.
Due to the intensified industrial activities and other anthropogenic actions, contamination of polycyclic aromatic hydrocarbons (PAHs) has been growing at an alarming rate, turning in to a serious environmental concern. Bioremediation, as an eco-friendly and sustainable removal technology, can be used by organisms to reduce the resulting contaminations. In the present study, the ability of Tetradesmus obliquus to remove of fluoranthene (FLA) was evaluated. It was confirmed that FLA removal efficiency was managed by various environmental parameters and pH was found to be one of the most important influencial factors. The reusability of the algae in long-term repetitive operations confirmed the occurrence of biodegradation along with other natural attenuation and 10 intermediate compounds were identified in the FLA biodegradation pathway by GC-MS. As a result of physiological assays, induced antioxidant enzymes activities and augmentation of phenol and flavonoids contents, after the treatment of the microalgae by a high concentration of FLA, confirmed the ability of the microalgae to upregulate its antioxidant defense system in response to the toxic effects of FLA. An artificial neural network (ANN) model was then developed to predict FLA biodegradation efficiency and the appropriate predictive performance of ANN was confirmed by comparing the experimental FLA removal efficiency with its predicted amounts (R2 = 0.99).
期刊介绍:
The International Journal of Phytoremediation (IJP) is the first journal devoted to the publication of laboratory and field research describing the use of plant systems to solve environmental problems by enabling the remediation of soil, water, and air quality and by restoring ecosystem services in managed landscapes. Traditional phytoremediation has largely focused on soil and groundwater clean-up of hazardous contaminants. Phytotechnology expands this umbrella to include many of the natural resource management challenges we face in cities, on farms, and other landscapes more integrated with daily public activities. Wetlands that treat wastewater, rain gardens that treat stormwater, poplar tree plantings that contain pollutants, urban tree canopies that treat air pollution, and specialized plants that treat decommissioned mine sites are just a few examples of phytotechnologies.