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Modeling sulfate removal by inhibited mesophilic mixed anaerobic communities using a statistical approach

Overview of attention for article published in Water Research, May 2013
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Title
Modeling sulfate removal by inhibited mesophilic mixed anaerobic communities using a statistical approach
Published in
Water Research, May 2013
DOI 10.1016/j.watres.2013.01.045
Pubmed ID
Authors

Chungman Moon, Rajesh Singh, Subba Rao Chaganti, Jerald A. Lalman

Abstract

Optimizing sulfate removal by a mixed anaerobic mesophilic culture fed glucose, linoleic acid (LA) and sulfate under several pH conditions was performed using a three factor three level Box-Behnken design (BBD). Based on the BBD approach, a statistical model was developed to predict the residual sulfate concentration. The LA concentration, initial pH and the COD/SO4(2-) ratio were the three experimental factors under consideration. Increasing the COD/SO4(2-) ratio increased the quantity of sulfate removed. The COD/SO4(2-) ratio showed the largest effect on reducing the sulfate level. Significant interactions between the three experimental factors were confirmed by the surface plots, interaction plot and ANOVA. An analysis of residuals verified accuracy of the model. Acetate and H2 production was dominant in cultures with the pH set at 6.0 and 6.75 and fed LA. After 168 h, butyrate and H2S were associated with the largest quantity of sulfate removed. At a D-optimality value of 1.0, a minimum response (residual sulfate concentration) of 36.2 mg L(-1) was recorded at 1500 mg L(-1) LA with a COD/SO4(2-) ratio of 2.18 and a pH set at 6.0. Based on the conditions under consideration, the model provided a useful approach for predicting the residual sulfate concentration in inhibited mixed anaerobic cultures.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 26%
Researcher 7 17%
Student > Doctoral Student 5 12%
Professor 5 12%
Professor > Associate Professor 4 10%
Other 8 19%
Unknown 2 5%
Readers by discipline Count As %
Environmental Science 11 26%
Engineering 9 21%
Biochemistry, Genetics and Molecular Biology 4 10%
Chemical Engineering 2 5%
Agricultural and Biological Sciences 2 5%
Other 4 10%
Unknown 10 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 February 2013.
All research outputs
#10,721,873
of 12,091,208 outputs
Outputs from Water Research
#4,574
of 5,486 outputs
Outputs of similar age
#246,675
of 291,889 outputs
Outputs of similar age from Water Research
#20
of 55 outputs
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So far Altmetric has tracked 5,486 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.