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Wang LJ, Han W, Lou TT, Ma LL, Xiao YB, Xu Z, Chen ML, Cheng YH, Ding L. An iron-based metal-organic framework as a novel dispersive solid-phase extraction sorbent for the efficient adsorption of tetrabromobisphenol A from environmental water samples. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:343-352. [PMID: 36594622 DOI: 10.1039/d2ay01287a] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
For environmental safety, it is important to establish a simple, rapid, and sensitive method for emerging pollutants. Here, a dispersive solid-phase extraction (d-SPE) method based on an iron-based metal-organic framework (Fe-MIL-88-NH2) combined with high-performance liquid chromatography (HPLC) was developed for tetrabromobisphenol A (TBBPA) in water samples. Fe-MIL-88-NH2 was synthesized using a solvothermal method and completely characterized. Fe-MIL-88-NH2 had good water stability and gave a maximum adsorption capacity of 40.97 mg g-1 for TBBPA. The adsorption of TBBPA on Fe-MIL-88-NH2 followed Langmuir adsorption models and a pseudo-second-order kinetic model. The bromine ion and the hydroxyl group of TBBPA could form strong hydrogen bond interactions with the amino protons around the cavity of Fe-MIL-88-NH2, which was in accord with the molecular simulation calculations. Furthermore, several important d-SPE parameters were optimized, such as the amount of materials, extraction time, pH, ionic strength, elution solvent type, and volume. The established method showed good linearity in the concentration range of 0.005-100 μg g-1 (r2 ≥ 0.9996). This method's limits of detection (LOD) and quantification (LOQ) were 0.001 μg g-1 and 0.005 μg g-1, respectively. The recoveries in spiked water samples ranged from 87.5% to 104.9%. The proposed method was applied successfully to detect TBBPA in environmental water samples.
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Affiliation(s)
- Ling-Juan Wang
- School of Food Science and Bioengineering, Changsha University of Science & Technology, Changsha 410114, China.
| | - Wei Han
- Technical Center for Animal, Plant, Foodstuffs and Industrial Product Safety, Tianjin Customs, Tianjin 300457, China
| | - Ting-Ting Lou
- Technical Center for Animal, Plant, Foodstuffs and Industrial Product Safety, Tianjin Customs, Tianjin 300457, China
| | - Lin-Lin Ma
- School of Food Science and Bioengineering, Changsha University of Science & Technology, Changsha 410114, China.
| | - Ya-Bing Xiao
- Technical Center for Animal, Plant, Foodstuffs and Industrial Product Safety, Tianjin Customs, Tianjin 300457, China
| | - Zhou Xu
- School of Food Science and Bioengineering, Changsha University of Science & Technology, Changsha 410114, China.
| | - Mao-Long Chen
- School of Food Science and Bioengineering, Changsha University of Science & Technology, Changsha 410114, China.
| | - Yun-Hui Cheng
- School of Food Science and Bioengineering, Changsha University of Science & Technology, Changsha 410114, China.
| | - Li Ding
- School of Food Science and Bioengineering, Changsha University of Science & Technology, Changsha 410114, China.
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Adeleye AS, Xue J, Zhao Y, Taylor AA, Zenobio JE, Sun Y, Han Z, Salawu OA, Zhu Y. Abundance, fate, and effects of pharmaceuticals and personal care products in aquatic environments. JOURNAL OF HAZARDOUS MATERIALS 2022; 424:127284. [PMID: 34655870 DOI: 10.1016/j.jhazmat.2021.127284] [Citation(s) in RCA: 103] [Impact Index Per Article: 51.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 09/06/2021] [Accepted: 09/16/2021] [Indexed: 06/13/2023]
Abstract
Pharmaceuticals and personal care products (PPCPs) are found in wastewater, and thus, the environment. In this study, current knowledge about the occurrence and fate of PPCPs in aquatic systems-including wastewater treatment plants (WWTPs) and natural waters around the world-is critically reviewed to inform the state of the science and highlight existing knowledge gaps. Excretion by humans is the primary route of PPCPs entry into municipal wastewater systems, but significant contributions also occur through emissions from hospitals, PPCPs manufacturers, and agriculture. Abundance of PPCPs in raw wastewater is influenced by several factors, including the population density and demography served by WWTPs, presence of hospitals and drugs manufacturers in the sewershed, disease burden of the population served, local regulations, and climatic conditions. Based on the data obtained from WWTPs, analgesics, antibiotics, and stimulants (e.g., caffeine) are the most abundant PPCPs in raw wastewater. In conventional WWTPs, most removal of PPCPs occurs during secondary treatment, and overall removal exceeds 90% for treatable PPCPs. Regardless, the total PPCP mass discharged with effluent by an average WWTP into receiving waters (7.35-20,160 g/day) is still considerable, because potential adverse effects of some PPCPs (such as ibuprofen) on aquatic organisms occur within measured concentrations found in surface waters.
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Affiliation(s)
- Adeyemi S Adeleye
- Department of Civil and Environmental Engineering, University of California, Irvine, CA 92697-2175, USA.
| | - Jie Xue
- Department of Civil and Environmental Engineering, University of California, Irvine, CA 92697-2175, USA
| | - Yixin Zhao
- Department of Civil and Environmental Engineering, University of California, Irvine, CA 92697-2175, USA
| | - Alicia A Taylor
- Ecological and Biological Sciences Practice, Exponent, Inc., Oakland, CA 94612, USA
| | - Jenny E Zenobio
- Department of Civil and Environmental Engineering, University of California, Irvine, CA 92697-2175, USA
| | - Yian Sun
- Department of Civil and Environmental Engineering, University of California, Irvine, CA 92697-2175, USA; Water-Energy Nexus Center, University of California, Irvine, CA 92697-2175, USA
| | - Ziwei Han
- Department of Civil and Environmental Engineering, University of California, Irvine, CA 92697-2175, USA
| | - Omobayo A Salawu
- Department of Civil and Environmental Engineering, University of California, Irvine, CA 92697-2175, USA
| | - Yurong Zhu
- Department of Chemical and Biomolecular Engineering, University of California, Irvine, CA 92697-2580, USA
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Favela KA, Hartnett MJ, Janssen JA, Vickers DW, Schaub AJ, Spidle HA, Pickens KS. Nontargeted Analysis of Face Masks: Comparison of Manual Curation to Automated GCxGC Processing Tools. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:860-871. [PMID: 33395529 DOI: 10.1021/jasms.0c00318] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Masks constructed of a variety of materials are in widespread use due to the COVID-19 pandemic, and people are exposed to chemicals inherent in the masks through inhalation. This work aims to survey commonly available mask materials to provide an overview of potential exposure. A total of 19 mask materials were analyzed using a nontargeted analysis two-dimensional gas chromatography (GCxGC)-mass spectrometric (MS) workflow. Traditionally, there has been a lack of GCxGC-MS automated high-throughput screening methods, resulting in trade-offs with throughput and thoroughness. This work addresses the gap by introducing new machine learning software tools for high-throughput screening (Floodlight) and subsequent pattern analysis (Searchlight). A recursive workflow for chemical prioritization suitable for both manual curation and machine learning is introduced as a means of controlling the level of effort and equalizing sample loading while retaining key chemical signatures. Manual curation and machine learning were comparable with the mask materials clustering into three groups. The majority of the chemical signatures could be characterized by chemical class in seven categories: organophosphorus, long chain amides, polyethylene terephthalate oligomers, n-alkanes, olefins, branched alkanes and long-chain organic acids, alcohols, and aldehydes. The olefin, branched alkane, and organophosphorus components were primary contributors to clustering, with the other chemical classes having a significant degree of heterogeneity within the three clusters. Machine learning provided a means of rapidly extracting the key signatures of interest in agreement with the more traditional time-consuming and tedious manual curation process. Some identified signatures associated with plastics and flame retardants are potential toxins, warranting future study to understand the mask exposure route and potential health effects.
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Affiliation(s)
- Kristin A Favela
- Southwest Research Institute, Chemistry and Chemical Engineering, 6220 Culebra Road, San Antonio, Texas 78228, United States
| | - Michael J Hartnett
- Southwest Research Institute, Intelligent Systems, 6220 Culebra Road, San Antonio, Texas 78228, United States
| | - Jake A Janssen
- Southwest Research Institute, Intelligent Systems, 6220 Culebra Road, San Antonio, Texas 78228, United States
| | - David W Vickers
- Southwest Research Institute, Intelligent Systems, 6220 Culebra Road, San Antonio, Texas 78228, United States
| | - Andrew J Schaub
- Southwest Research Institute, Intelligent Systems, 6220 Culebra Road, San Antonio, Texas 78228, United States
| | - Heath A Spidle
- Southwest Research Institute, Intelligent Systems, 6220 Culebra Road, San Antonio, Texas 78228, United States
| | - Keith S Pickens
- Southwest Research Institute, Space Science and Engineering, 6220 Culebra Road, San Antonio, Texas 78228, United States
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