Heterogeneity and spatial distribution of bacterial background contamination in pulp and process water of a paper mill View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2012-12

AUTHORS

K. Milferstedt, J. -J. Godon, R. Escudié, S. Prasse, C. Neyret, N. Bernet

ABSTRACT

Identifying the source and the distribution of bacterial contaminant communities in water circuits of industrial applications is critical even when the process may not show signs of acute biofouling. The endemic contamination of facilities can cause adverse effects on process runability but may be masked by the observed daily variability. The distribution of background communities of bacterial contaminants may therefore be critical in the development of new site-specific antifouling strategies. In a paper mill as one example for a full-scale production process, bacterial contaminants in process water and pulp suspensions were mapped using molecular fingerprints at representative locations throughout the plant. These ecological data were analyzed in the process-engineering context of pulp and water flow in the facilities. Dispersal limits within the plant environment led to the presence of distinct groups of contaminant communities in the primary units of the plant, despite high flows of water and paper pulp between units. In the paper machine circuit, community profiles were more homogeneous than in the other primary units. The variability between sampled communities in each primary unit was used to identify a possible point source of microbial contamination, in this case a storage silo for reused pulp. Part of the contamination problem in the paper mill is likely related to indirect effects of microbial activity under the local conditions in the silo rather than to the direct presence of accumulated microbial biomass. More... »

PAGES

1751-1759

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10295-012-1196-8

DOI

http://dx.doi.org/10.1007/s10295-012-1196-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1020755666

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23007958


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