Volatile organic compounds (VOCs) contamination may occur in subsurface soil due to various reasons and pose great threat to people. Petroleum hydrocarbon compound (PHC) is a typical kind of VOC, which can readily biodegrade in an aerobic environment. The biodegradation of vapor-phase PHC in the vadose zone consumes oxygen in the soil, which leads to the change in aerobic and anaerobic zones but has not been studied by the existing analytical models. In this study, a one-dimensional analytical model is developed to simulate the transient diffusion and oxygen-limited biodegradation of PHC vapor in homogeneous soil. Laplace transformation and Laplace inversion of the Talbot method are adopted to derive the solution. At any given time, the thickness of aerobic zone is determined by the dichotomy method. The analytical model is verified against numerical simulation and experimental results first and parametric study is then conducted. The transient migration of PHC vapor can be divided into three stages including the pure aerobic zone stage (Stage I), aerobic-anaerobic zones co-existence stage (Stage II), and steady-state stage (Stage III). The proposed analytical model should be adopted to accommodate scenarios where the transient effect is significant (Stage II), including high source concentration, deep contaminant source, high biodegradation capacity, and high water saturation. The applicability of this model to determine the breakthrough time for better vapor intrusion assessment is also evaluated. Lower first-order biodegradation rate, higher source concentration, and shallower source depth all lead to smaller breakthrough time.
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http://dx.doi.org/10.1016/j.chemosphere.2022.134522 | DOI Listing |
JAMA Netw Open
January 2025
Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston.
Importance: Cardiovascular disease (CVD) and cancer are the leading causes of mortality in the US. Large-scale population-based and mechanistic studies support a direct effect of CVD on accelerated tumor growth and spread, specifically in breast cancer.
Objective: To assess whether individuals presenting with advanced breast cancers are more likely to have prevalent CVD compared with those with early-stage breast cancers at the time of diagnosis.
Anal Chem
January 2025
Laboratorio de Investigación y Desarrollo en Métodos Analíticos (LIDMA), Facultad de Ciencias Exactas, Universidad Nacional de La Plata (UNLP), Calle 49 y 115 (B1900AJL), La Plata 1900, Argentina.
A new strategy is proposed for second-order data fusion based on the simultaneous modeling of two data sets using the multivariate curve resolution-alternating least-squares (MCR-ALS) model, applying a new constraint during the ALS stage, called "Proportionality of Scores". This approach allows for the fusion of data from different sources, without requiring common dimensionality, and enables the application of specific constraints to each data set. This strategy was applied to the determination of five pharmaceutical contaminants (naproxen, danofloxacin, ofloxacin, sarafloxacin, and enoxacin) in environmental water samples, by fusing two sets of excitation-emission fluorescence matrices, measured before and after photochemical derivatization.
View Article and Find Full Text PDFClin Chem Lab Med
January 2025
70777 TUBITAK National Metrology Institute (TUBITAK UME), Kocaeli, Türkiye.
Objectives: An analytical protocol based on isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS), which includes a peptide-based calibration strategy, was developed and validated for the determination of cardiac troponin I (cTnI) levels in clinical samples. Additionally, the developed method was compared with a protein-based calibration strategy, using cTnI serving as a model for low-abundant proteins. The aim is to evaluate new approaches for protein quantification in complex matrices, supporting the metrology community in implementing new methods and developing fit-for-purpose SI- traceable peptide or protein primary calibrators.
View Article and Find Full Text PDFEnviron Sci Process Impacts
January 2025
College of Environment, Zhejiang University of Technology, Hangzhou, 310014, P. R. China.
The nano-self-assembly of natural organic matter (NOM) profoundly influences the occurrence and fate of NOM and pollutants in large-scale complex environments. Machine learning (ML) offers a promising and robust tool for interpreting and predicting the processes, structures and environmental effects of NOM self-assembly. This review seeks to provide a tutorial-like compilation of data source determination, algorithm selection, model construction, interpretability analyses, applications and challenges for big-data-based ML aiming at elucidating NOM self-assembly mechanisms in environments.
View Article and Find Full Text PDFLangmuir
January 2025
Department of Physical Chemistry and Materials Science, Budapest University of Technology and Economics, Műegyetem rkp. 3, 1111 Budapest, Hungary.
During the experimental formation of sol-gel coatings, the colloid dispersions go through a drying process, and the structure of the coatings is formed as a result of complex chemical, colloidal, and capillary interactions. While computer simulations provide guidelines to tune and even design the nanomaterials synthesis, simulations of coating structure formation are hitherto unknown in the literature. Based on real experiments, we establish here a ReaxFF reactive force field-based molecular dynamics simulation protocol in order to investigate and determine the role of the experimental conditions on the pore structure formation in the coatings.
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