Biochar-derived dissolved organic carbon (BDOC), as a highly activated carbonaceous fraction of biochar, significantly affects the environmental effect of biochar. This study systematically investigated the differences in the properties of BDOC produced at 300-750 °C in three atmosphere types (including N and CO flows and air limitation) as well as their quantitative relationship with biochar properties. The results showed that BDOC in biochar pyrolyzed in air limitation (0.19-2.88 mg/g) was more than that pyrolyzed in N (0.06-1.63 mg/g) and CO flows (0.07-1.74 mg/g) at 450-750 °C. The aliphaticity, humification, molecular weight, and polarity of BDOC strongly depended on the atmosphere types as well as the pyrolysis temperatures. BDOC produced in air limitation contained more humic-like substances (0.65-0.89) and less fulvic-like substances (0.11-0.35) than that produced in N and CO flows. The multiple linear regression of the exponential form of biochar properties (H and O contents, H/C and (O+N)/C) could be used to quantitatively predict the bulk content and organic component contents of BDOC. Additionally, self-organizing maps could effectively visualize the categories of fluorescence intensity and components of BDOC from different pyrolysis atmospheres and temperatures. This study highlights that pyrolysis atmosphere types are a crucial factor controlling the BDOC properties, and some characteristics of BDOC can be quantitatively evaluated based on the properties of biochar.
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http://dx.doi.org/10.3390/molecules28052247 | DOI Listing |
Anal Chem
January 2025
Key Laboratory of Nondestructive Test (Ministry of Education), Nanchang Hangkong University, Nanchang 330063, China.
Off-axis integrated cavity output spectroscopy (OA-ICOS) allows the laser to be reflected multiple times inside the cavity, increasing the effective absorption path length and thus improving sensitivity. However, OA-ICOS systems are affected by various types of noise, and traditional filtering methods offer low processing efficiency and perform limited feature extraction. Deep learning models enable us to extract important features from large-scale, complex spectral data and analyze them efficiently and accurately.
View Article and Find Full Text PDFPLoS One
January 2025
School of Environmental Engineering, Yellow River Conservancy Technical Institute, Kaifeng Key Laboratory of Food Composition and Quality Assessment, Kaifeng, China.
Antibiotic resistance is a critical global public health issue. The gut microbiome acts as a reservoir for numerous antibiotic resistance genes (ARGs), which influence both existing and future microbial populations within a community or ecosystem. However, the differences in ARG expression between fresh and composted feces remain poorly understood.
View Article and Find Full Text PDFJ Prosthodont
January 2025
Prosthodontist, Implant Dentistry Associates of Arlington, Arlington, Texas, USA.
Purpose: The purpose of this study was to analyze gingival fibroblast proliferation on additively manufactured polymethylmethacrylate (PMMA) groups with different surface characteristics namely no treatment group (NTG) and customized 250 µm diameter porosity (AM-250G) group.
Materials And Methods: 3D-printed NTG was compared for its influence on growth of cells to a additively manufactured surface with porosity (AM-250G). For each group (NTG, AM-250G) 20 samples of material were tested.
PLoS One
January 2025
Department of Environmental Health, Qingdao Municipal Center for Disease Control and Prevention, Qingdao Institute of Disease Prevention, Qingdao, Shandong, China.
Background: It is crucial to comprehend the interplay between air pollution and meteorological conditions in relation to population health within the framework of "dual-carbon" targets. The purpose of this study was to investigate the impact of intricate environmental factors, encompassing both meteorological conditions and atmospheric pollutants, on respiratory disease (RD) mortality in Qingdao, a representative coastal city in China.
Methods: The RD mortality cases were collected from the Chronic Disease Surveillance Monitoring System in Qingdao during Jan 1st, 2014 and Dec 31st, 2020.
PLoS One
January 2025
Department of Economics, University Carlos III, Getafe, Spain.
Climate change is a spatial and temporarily non-uniform phenomenon that requires understanding its evolution to better evaluate its potential societal and economic impact. The value added of this paper lies in introducing a quantitative methodology grounded in the trend analysis of temperature distribution quantiles to analyze climate change heterogeneity (CCH). By converting these quantiles into time series objects, the methodology empowers the definition and measurement of various relevant concepts in climate change analysis (warming, warming typology, warming amplification and warming acceleration) in a straightforward and robust testable linear regression format.
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