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Ashraf M, Siddiqui MT, Galodha A, Anees S, Lall B, Chakma S, Ahammad SZ. Pharmaceuticals and personal care product modelling: Unleashing artificial intelligence and machine learning capabilities and impact on one health and sustainable development goals. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 955:176999. [PMID: 39427916 DOI: 10.1016/j.scitotenv.2024.176999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Revised: 10/13/2024] [Accepted: 10/15/2024] [Indexed: 10/22/2024]
Abstract
The presence of pharmaceutical and personal care products (PPCPs) in the environment poses a significant threat to environmental resources, given their potential risks to ecosystems and human health, even in trace amounts. While mathematical modelling offers a comprehensive approach to understanding the fate and transport of PPCPs in the environment, such studies have garnered less attention compared to field and laboratory investigations. This review examines the current state of modelling PPCPs, focusing on their sources, fate and transport mechanisms, and interactions within the whole ecosystem. Emphasis is placed on critically evaluating and discussing the underlying principles, ongoing advancements, and applications of diverse multimedia models across geographically distinct regions. Furthermore, the review underscores the imperative of ensuring data quality, strategically planning monitoring initiatives, and leveraging cutting-edge modelling techniques in the quest for a more holistic understanding of PPCP dynamics. It also ventures into prospective developments, particularly the integration of Artificial Intelligence (AI) and Machine Learning (ML) methodologies, to enhance the precision and predictive capabilities of PPCP models. In addition, the broader implications of PPCP modelling on sustainability development goals (SDG) and the One Health approach are also discussed. GIS-based modelling offers a cost-effective approach for incorporating time-variable parameters, enabling a spatially explicit analysis of contaminant fate. Swin-Transformer model enhanced with Normalization Attention Modules demonstrated strong groundwater level estimation with an R2 of 82 %. Meanwhile, integrating Interferometric Synthetic Aperture Radar (InSAR) time-series with gravity recovery and climate experiment (GRACE) data has been pivotal for assessing water-mass changes in the Indo-Gangetic basin, enhancing PPCP fate and transport modelling accuracy, though ongoing refinement is necessary for a comprehensive understanding of PPCP dynamics. The review aims to establish a framework for the future development of a comprehensive PPCP modelling approach, aiding researchers and policymakers in effectively managing water resources impacted by increasing PPCP levels.
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Affiliation(s)
- Maliha Ashraf
- School of Interdisciplinary Research, Indian Institute of Technology, Delhi, New Delhi 110016, India
| | - Mohammad Tahir Siddiqui
- Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, Delhi, New Delhi 110016, India
| | - Abhinav Galodha
- School of Interdisciplinary Research, Indian Institute of Technology, Delhi, New Delhi 110016, India
| | - Sanya Anees
- Department of Electronics and Communication Engineering, Netaji Subash University of Technology (NSUT), New Delhi 110078, India.
| | - Brejesh Lall
- Bharti School of Telecommunication Technology and Management, Indian Institute of Technology, Delhi, New Delhi e110016, India
| | - Sumedha Chakma
- Department of Civil Engineering, Indian Institute of Technology, Delhi, New Delhi 110016, India.
| | - Shaikh Ziauddin Ahammad
- Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, Delhi, New Delhi 110016, India.
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Wan Y, Chen S, Liu J, Jin L. Brownfield-related studies in the context of climate change: A comprehensive review and future prospects. Heliyon 2024; 10:e25784. [PMID: 38420456 PMCID: PMC10900957 DOI: 10.1016/j.heliyon.2024.e25784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 01/23/2024] [Accepted: 02/02/2024] [Indexed: 03/02/2024] Open
Abstract
The global climate change events are expected to augment the vulnerability of persistent organic pollutants within the global brownfield areas to a certain extent, consequently heightening the risk crises faced by these brownfields amidst the backdrop of global environmental changes. However, studies addressing brownfield risks from the perspective of climate change have received limited attention. Nonetheless, the detrimental consequences of brownfield risks are intrinsically linked to strategies for mitigating and adapting to sustainable urban development, emphasizing the critical importance of their far-reaching implications. This relevance extends to concerns about environmental quality, safety, health risks, and the efficacy of chosen regeneration strategies, including potential secondary pollution risks. This comprehensive review systematically surveys pertinent articles published between 1998 and 2023. A selective analysis was conducted on 133 articles chosen for their thematic relevance. The findings reveal that: (1) Under the backdrop of the climate change process, brownfield restoration is necessitated to provide scientific and precise guidance. The integration of brownfield considerations with the dynamics of climate change has progressively evolved into a unified framework, gradually shaping a research paradigm characterized by "comprehensive + multi-scale + quantitative" methodologies; (2) Research themes coalesce into five prominent clusters: "Aggregation of Brownfield Problem Analysis", "Precision Enhancement of Brownfield Identification through Information Technology", "Diversification of Brownfield Reutilization Assessment", "Process-Oriented Approaches to Brownfield Restoration Strategies", and "Expansion of Ecological Service Functions in Brownfield Contexts"; (3) Application methodologies encompass five key facets: "Temporal and Spatial Distribution Patterns of Pollutants", "Mechanisms and Correlations of Pollution Effects", "Evaluation of Pollution Risks", "Assessment of Brownfield Restoration Strategies", and "Integration of Brownfield Regeneration with Spatial Planning". Future brownfield research from the climate change perspective is poised to reflect characteristics such as "High-Precision Prediction, Comprehensive Dimensionality, Full-Cycle Evaluation, Low-Risk Exposure, and Commitment to Sustainable Development".
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Affiliation(s)
- Yunshan Wan
- China Architecture Design & Research Group, China
| | - Shuo Chen
- College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China
| | - Jiaqi Liu
- China Construction Engineering Design & Research Institute Co., Ltd., China
| | - Lin Jin
- Interdisciplinary Program in Landscape Architecture, Seoul National University, Seoul, Republic of Korea
- Integrated Major in Smart City Global Convergence, Seoul National University, Seoul, Republic of Korea
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Feng Z, Yang Z, Yang S, Xiong H, Ning Y, Wang C, Li Y. Current status and future challenges of chlorobenzenes pollution in soil and groundwater (CBsPSG) in the twenty-first century: a bibliometric analysis. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:111748-111765. [PMID: 37843707 DOI: 10.1007/s11356-023-29956-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 09/14/2023] [Indexed: 10/17/2023]
Abstract
The global industrial structure had undertaken significant changes since the twenty-first century, making a severe problem of chlorobenzene pollution in soil and groundwater (CBsPSG). CBsPSG receives increasing attention due to the high toxicity, persistence, and bioaccumulation of chlorobenzenes. To date, despite the gravity of this issue, no bibliometric analysis (BA) of CBsPSG does exist. This study fills up the gap by conducting a BA of 395 articles related to CBsPSG from the Web of Science Core Collection database using CiteSpace. Based on a comprehensive analysis of various aspects, including time-related, related disciplines, keywords, journal contribution, author productivity, and institute and country distribution, the status, development, and hotspots of research in the field were shown visually and statistically. Moreover, this study has also delved into the environmental behavior and remediation techniques of CBsPSG. In addition, four challenges (unequal research development, insufficient cooperation, deeply mechanism research, and developing new technologies) have been identified, and corresponding suggestions have been proposed for the future development of research in the field. Afterwards, the limitations of BA were discussed. This work provides a powerful insight into CBsPSG, enabling to quickly identify the hotspot and direction of future studies by relevant researchers.
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Affiliation(s)
- Zhi Feng
- School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
| | - Zhe Yang
- School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
| | - Sen Yang
- School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
| | - Hanxiang Xiong
- School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
| | - Yu Ning
- School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
| | - Changxiang Wang
- School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
| | - Yilian Li
- School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China.
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Hou Y, Li Y, Tao H, Cao H, Liao X, Liu X. Three-dimensional distribution characteristics of multiple pollutants in the soil at a steelworks mega-site based on multi-source information. JOURNAL OF HAZARDOUS MATERIALS 2023; 448:130934. [PMID: 36860071 DOI: 10.1016/j.jhazmat.2023.130934] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 01/26/2023] [Accepted: 02/01/2023] [Indexed: 06/18/2023]
Abstract
Soil pollution at steelworks mega-sites has become a severe environmental issue worldwide. However, due to the complex production processes and hydrogeology, the soil pollution distribution at steelworks is still unclear. This study scientifically cognized the distribution characteristics of polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), and heavy metals (HMs) at a steelworks mega-site based on multi-source information. Specifically, firstly, 3D distribution and spatial autocorrelation of pollutants were obtained by interpolation model and local indicators of spatial associations (LISA), respectively. Secondly, the characteristics of horizontal distribution, vertical distribution, and spatial autocorrelations of pollutants were identified by combining multi-source information such as production processes, soil layers, and properties of pollutants. Horizontal distribution showed that soil pollution in steelworks mainly occurred in the front end of the steel process chain. Over 47% of PAHs and VOCs pollution area were distributed in coking plants and over 69% of HMs in stockyards. Vertical distribution indicated that HMs, PAHs, and VOCs were enriched in the fill, silt, and clay layers, respectively. Spatial autocorrelation of pollutants was positively correlated with their mobility. This study clarified the soil pollution characteristics at steelworks mega-sites, which can support the investigation and remediation of steelworks mega-sites.
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Affiliation(s)
- Yixuan Hou
- Anhui Province Key Laboratory of Polar Environment and Global Change, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China; Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Beijing Key Laboratory of Environmental Damage Assessment and Remediation, Beijing 100101, China
| | - You Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Beijing Key Laboratory of Environmental Damage Assessment and Remediation, Beijing 100101, China
| | - Huan Tao
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Beijing Key Laboratory of Environmental Damage Assessment and Remediation, Beijing 100101, China
| | - Hongying Cao
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Beijing Key Laboratory of Environmental Damage Assessment and Remediation, Beijing 100101, China
| | - Xiaoyong Liao
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Beijing Key Laboratory of Environmental Damage Assessment and Remediation, Beijing 100101, China.
| | - Xiaodong Liu
- Anhui Province Key Laboratory of Polar Environment and Global Change, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China; CAS Key Laboratory of Crust-Mantle Materials and Environments, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China.
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He T, Li Y, Huang Y, He E, Li Y, Qu L, Ding F, Jin R, Han M, Yuan L, Xue W, Qu R, Zheng W, Xie Y, Liu X, Zhao L, Liu M. Simulation and risk assessment of arsenic by Hydrus-3D and CalTOX in a typical brownfield site. JOURNAL OF HAZARDOUS MATERIALS 2023; 448:130892. [PMID: 36758430 DOI: 10.1016/j.jhazmat.2023.130892] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 12/24/2022] [Accepted: 01/26/2023] [Indexed: 06/18/2023]
Abstract
Accurate quantification of arsenic migration and accumulation in brownfield site is critical for environmental management and soil remediation. However, the researches simulating arsenic in brownfield site in China are limited due to sparse data and complex migration behaviors. In this study, we simulated historic arsenic contamination using Hydrus-3D in an abandoned brownfield site in Hebei, China, from 1972 to 2019. Atmospheric discharge, wastewater leakage, solid waste discharge and tank leakage were calculated according to the factory processes for model simulation. Based on the results of Hydrus-3D, we assessed health risk of arsenic in this site. The results showed that total arsenic input to the soil surface from 4 pathways was 24.6 tons, the solid waste discharge was the highest contributor. The accumulation process mainly occurred in the unsaturated zone due to clay and silty clay absorbed arsenic and thus slow down the migration process. While in the saturation zone, abundant groundwater promoted migration of arsenic, resulting in widespread distribution of contaminated area. The model results represented good performance between simulated and measured values. Sensitivity analysis indicated that adsorption constant and water conductivity were the most influential parameters. Heath risk assessment showed that arsenic contamination continues to threaten resident health.
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Affiliation(s)
- Tianhao He
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Ye Li
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China.
| | - Ye Huang
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Erkai He
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Yan Li
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Liangyu Qu
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Fangfang Ding
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Ruihe Jin
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Mingzhe Han
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Lina Yuan
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Weizhen Xue
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ruijuan Qu
- State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing 210023, Jiangsu, China
| | - Wang Zheng
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China
| | - Yunfeng Xie
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China
| | - Xingmei Liu
- College of Environmental Natural Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Ling Zhao
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Min Liu
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China.
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Yuan J, Chen Z, Ding S, Zhang Q, Jia Y. Application of an environmental multimedia modeling system for health risk assessment: Key influencing factors and uncertainties research. INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT 2021; 17:877-886. [PMID: 33410257 DOI: 10.1002/ieam.4387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 11/03/2020] [Accepted: 12/30/2020] [Indexed: 06/12/2023]
Abstract
In this paper, an environmental multimedia modeling system (EMMS) that combines a risk assessment with a Monte Carlo method (MCM) was used to explore the interaction between groundwater and surface water with respect to chemical exposure and risk. The EMMS-MCM simulations incorporated several key influencing factors that are inherent in traditional predictions of subsurface and surface-water interactions, including soil permeability coefficients and parameters such as hydraulic conductivity, density, recharge, layers, and depth. These influencing factors are generally associated with the largest sources of uncertainty in modeling and pose significant challenges to water management and to the optimal allocation of water resources. A case study involving benzene at the Trail Road landfill site located in the Ottawa-Carlton area of Canada is presented to illustrate the use of the EMMS-MCM approach. The model results are verified by comparisons to the results of groundwater and surface-water investigations in the landfill. The EMMS-MCM results are evaluated using a risk quotient (RQ) risk assessment method to quantify environmental risk. The EMMS-MCM simulations can be used to support hazardous field work and contribute to environmental management by predicting the possible consequences of hazardous chemical contaminations in surface waters and groundwater. The integration of the EMMS-MCM and RQ approaches represents an appropriate tool for the accurate assessment of long-term pollutant risks and environmental management of surface- and groundwater resources. Integr Environ Assess Manag 2021;17:877-886. © 2021 SETAC.
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Affiliation(s)
- Jing Yuan
- Green Intelligence Environmental School, Yangtze Normal University, Chong Qing, China
- University of Alberta, Edmonton, Alberta, Canada
- Department of Building, Civil, and Environmental Engineering, Concordia University, Montreal, Quebec, Canada
| | - Zhi Chen
- Department of Building, Civil, and Environmental Engineering, Concordia University, Montreal, Quebec, Canada
| | - Shimin Ding
- Green Intelligence Environmental School, Yangtze Normal University, Chong Qing, China
| | - Qianfeng Zhang
- Institute of Energy and Environment, Anhui University of Technology, Ma'anshan, Anhui, China
| | - Yong Jia
- Institute of Energy and Environment, Anhui University of Technology, Ma'anshan, Anhui, China
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Na G, Liang Y, Li R, Gao H, Jin S. Flux of Polynuclear Aromatic Compounds (PAHs) from the Atmosphere and from Reindeer/Bird Feces to Arctic Soils in Ny-Ålesund (Svalbard). ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2021; 81:166-181. [PMID: 34019116 DOI: 10.1007/s00244-021-00851-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 04/19/2021] [Indexed: 06/12/2023]
Abstract
Atmospheric, soil, and feces samples were collected in Ny-Ålesund during July 2015. The concentrations, distributions, congener profiles, and contaminant migration levels were analyzed for 16 polycyclic aromatic hydrocarbons (PAHs) identified by the United States Environmental Protection Agency (US EPA) as priority contaminants (16 PAHs). Mean concentrations in the gas and particle phases were 37.8 ng m-3 and 2.9 ng m-3, respectively, and mean concentrations in soil and reindeer/bird feces were 329.1 ng g-1 and 720.7 ng g-1, respectively, on a dry weight (d.w.) basis. In more than three phases, naphthalene and phenanthrene dominated the concentrations of the 16 total PAHs (Σ16PAH) and the concentration of PAHs in the gas phase was much higher than in the particle phase. The main sources of local PAHs may be coal combustion and air-surface exchange. There was a volatilization tendency from soil to air for 2-4 ring PAHs, and exchange fluxes were ~ 105 times greater than the deposition fluxes of 5-6 ring PAHs. The underground migration of PAHs was investigated in Ny-Ålesund; the results showed flux values of ~ 0.07% from the initial PAH concentrations.
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Affiliation(s)
- Guangshui Na
- College of Marine Ecology and Environment, Shanghai Ocean University, Shanghai, 201306, China.
- National Marine Environmental Monitoring Center, Dalian, 116023, China.
- Hainan Tropical Ocean University, Sanya, 572022, China.
| | - Yuyuan Liang
- College of Marine Ecology and Environment, Shanghai Ocean University, Shanghai, 201306, China
- National Marine Environmental Monitoring Center, Dalian, 116023, China
| | - Ruijing Li
- National Marine Environmental Monitoring Center, Dalian, 116023, China
| | - Hui Gao
- National Marine Environmental Monitoring Center, Dalian, 116023, China
| | - Shuaichen Jin
- National Marine Environmental Monitoring Center, Dalian, 116023, China
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Yuan J, Sun Y, Jia Y, Zhang Q. Thermodynamic Properties Investigation of Process Volatile Organic Compounds (VOCs) and Its Transport Impact Factor in Oil Sands Management. NANOMATERIALS 2021; 11:nano11030709. [PMID: 33799857 PMCID: PMC7998836 DOI: 10.3390/nano11030709] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 02/20/2021] [Accepted: 03/05/2021] [Indexed: 11/16/2022]
Abstract
This paper presents a new approach for the determination of volatile organic compounds (VOCs) characteristics and their migration influencing factors in oil sands management processes and reveals the relationship between different asphaltene content and different solvents. Specifically, thermodynamic (i.e., partitioning coefficients, Kr, specific retention volume, Vg, the activity coefficients, γ and enthalpy of solution, ΔH0) and their impact factors are discussed. Gas-liquid chromatography (GLC) experimental measurements were used as the test data. A range of solvents (nC5, iC5, nC6, nC7, and Toluene) has been tested in different asphalt contents (0, 2.56, 9.93, 36.86, 53.67 wt%). There are temperatures in the range of 333.2–393.2 K (with 10 K increase) were conducted, respectively. The dynamics properties of asphalt mixture are calculated, and the relation between dynamics properties of asphalt mixture and absolute temperature, asphalt content and solvent type is discussed. The results show that within the acceptable error range, partitioning coefficients, Kr, specific retention volume, Vg, and enthalpy of solution, ΔH0 and other thermodynamic properties have a good tendency to predict, they decrease with the increase in asphaltene content and temperature and increase with the increase in solute carbon number.
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Affiliation(s)
- Jing Yuan
- Department of Civil Engineering, Tongling University, No. 4, Cui Hu Road 1335, Tongling District, Tongling 244000, China;
- Donadeo Innovation Centre of Engineering, University of Alberta, 9211-116 Street NW, Edmonton, AB T6G 1H9, Canada
- CanmetENERGY Devon Research Centre, Natural Resources Canada, 1 Oil Patch Drive, Devon, AB T9G 1A8, Canada
- Correspondence:
| | - Yuyong Sun
- Department of Civil Engineering, Tongling University, No. 4, Cui Hu Road 1335, Tongling District, Tongling 244000, China;
| | - Yong Jia
- Institute of Molecular Engineering and Applied Chemistry, Anhui University of Technology, Ma’anshan 243002, China; (Y.J.); (Q.Z.)
| | - Qianfeng Zhang
- Institute of Molecular Engineering and Applied Chemistry, Anhui University of Technology, Ma’anshan 243002, China; (Y.J.); (Q.Z.)
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