Carbon supplementation and bioaugmentation to improve denitrifying
woodchip bioreactor performance under cold conditions
Abstract
Cold temperatures limit nitrate-N load reductions of woodchip
bioreactors in higher-latitude climates. This two-year, on-farm
(Willmar, Minnesota, USA) study was conducted to determine whether
field-scale nitrate-N removal of woodchip bioreactors can be improved by
the addition of cold-adapted, locally isolated bacterial denitrifying
strains (bioaugmentation) or dosing with a carbon (C) source
(biostimulation). In Spring 2017, biostimulation removed 66% of the
nitrate-N load, compared to 21% and 18% for bioaugmentation and
control, respectively. The biostimulation nitrate-N removal rate (NRR)
was also significantly greater, 15.0 g N m-1 d-1, versus 5.8 and 4.4 g N
m-1 d-1, for bioaugmentation and control, respectively. Bioclogging of
the biostimulation beds limited dosing for the remainder of the
experiment; NRR was greater for biostimulation in Fall 2017, but in
Spring 2018 there were no differences among treatments. Carbon dosing
did not increase outflow dissolved organic C concentration. The
abundance of one of the inoculated strains, Cellulomonas sp. strain
WB94, increased over time, while another, Microvirgula aerodenitrificans
strain BE2.4, increased briefly, returning to background levels after 42
days. Eleven days after inoculation in Spring 2017, outflow nitrate-N
concentrations of bioaugmentation were sporadically reduced compared to
the control for two weeks but were insignificant over the study period.
The study suggests that biostimulation and bioaugmentation are promising
technologies to enhance nitrate removal during cold conditions. A means
of controlling bioclogging is needed for biostimulation, and improved
means of inoculation and maintaining abundance of introduced strains is
needed for bioaugmentation. In conclusion, biostimulation showed greater
potential than bioaugmentation for increasing nitrate removal in a
woodchip bioreactor, whereas both methods need improvement before
implementation at the field scale.