In-situ biodegradation of volatile organic compounds in landfill by sewage sludge modified waste-char

2020 ◽  
Vol 105 ◽  
pp. 317-327 ◽  
Author(s):  
Linbo Qin ◽  
Zhe Xu ◽  
Lei Liu ◽  
Haijun Lu ◽  
Yong Wan ◽  
...  
2003 ◽  
Author(s):  
Michael Loren Thomas ◽  
Robert Clark Hughes ◽  
Ara S Kooser ◽  
Lucas K McGrath ◽  
Clifford Kuofei Ho ◽  
...  

2018 ◽  
Vol 254 ◽  
pp. 597-602 ◽  
Author(s):  
Felix Y.H. Kutsanedzie ◽  
Lin Hao ◽  
Song Yan ◽  
Qin Ouyang ◽  
Quansheng Chen

2020 ◽  
Vol MA2020-01 (28) ◽  
pp. 2153-2153
Author(s):  
Binayak Ojha ◽  
Divyashree Narayana ◽  
Margarita Aleksandrova ◽  
Heinz Kohler ◽  
Matthias Schwotzer ◽  
...  

Metabolites ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 361
Author(s):  
Carolyn L. Fisher ◽  
Pamela D. Lane ◽  
Marion Russell ◽  
Randy Maddalena ◽  
Todd W. Lane

Microalgae produce specific chemicals indicative of stress and/or death. The aim of this study was to perform non-destructive monitoring of algal culture systems, in the presence and absence of grazers, to identify potential biomarkers of incipient pond crashes. Here, we report ten volatile organic compounds (VOCs) that are robustly generated by the marine alga, Microchloropsis salina, in the presence and/or absence of the marine grazer, Brachionus plicatilis. We cultured M. salina with and without B. plicatilis and collected in situ volatile headspace samples using thermal desorption tubes over the course of several days. Data from four experiments were aggregated, deconvoluted, and chromatographically aligned to determine VOCs with tentative identifications made via mass spectral library matching. VOCs generated by algae in the presence of actively grazing rotifers were confirmed via pure analytical standards to be pentane, 3-pentanone, 3-methylhexane, and 2-methylfuran. Six other VOCs were less specifically associated with grazing but were still commonly observed between the four replicate experiments. Through this work, we identified four biomarkers of rotifer grazing that indicate algal stress/death. This will aid machine learning algorithms to chemically define and diagnose algal mass production cultures and save algae cultures from imminent crash to make biofuel an alternative energy possibility.


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