Nitrous oxide and nitrate in the Grand River, Ontario: Sources, production pathways and predictability
Rosamond, Madeline Simone
MetadataShow full item record
The increased use of synthetic nitrogen fertilizers since the early 1900s has resulted in greater food production but also problems with nitrogen pollution in freshwaters. Nitrate (NO3-) is a common pollutant in rivers and groundwater in agricultural watersheds; the drinking water limit in Canada is 10 mg N/L. Microbial processing of NO3- and ammonium (NH4+) can produce nitrous oxide (N2O), a potent greenhouse gas responsible for about 5% of the greenhouse effect. Rivers provide a complex environment, where a variety of redox conditions, available substrates and microbial populations can co-exist on small spatial and temporal scales. Therefore, many questions remain about N cycling in river environments. N2O is produced during anoxic microbial NO3- or NO2- reduction to N2 (denitrification) and oxic microbial NH4+ oxidation to NO3- (nitrification). A significant portion (~25%) of global anthropogenic N2O is produced in rivers and estuaries, but mechanisms are not clear and predictability is poor. The United Nations Intergovernmental Panel on Climate Change (IPCC) provides default equations for calculating N2O emission estimates, in which annual NO3- loading to rivers is positively linearly related to N2O emissions. However, it is unclear how sound these linear relationships are and if measured N2O emissions are similar to IPCC estimates. The Grand River watershed is the largest in southern Ontario. Nutrient discharge to the Grand River is high due to extensive agriculture and high urban populations. The river often has a hypoxic water column due to high community respiration in summer. However, although nitrogen pollution is significant, N cycling is not well understood in the river. This thesis shows that NO3- and NH4+ do not typically change on the diel scale, with the exception of two sites downstream of wastewater treatment plants (WWTPs). However, N2O concentration changes dramatically. N2O concentrations are higher at night and lower during the day for most sites, but are reversed at very low-nutrient sites. N2O is therefore a sensitive indicator of changes in N cycling that may not be evident from NO3- and NH4+ concentrations or stable isotope ratios. Additionally, this work shows the importance of having a sampling design that captures diel variability in N2O. Previous work in rivers and streams worldwide focused on the appropriate N2O:NO3- ratio used to predict N2O emissions. In contrast, this thesis shows that there is a significant but very weak relationship between instantaneous N2O emissions and NO3- concentrations. However, there is a much stronger negative exponential relationship between DO and N2O. Annual N2O emissions tripled between 2006 and 2007 but NO3- masses in the river were only 10% higher, likely because river levels were lower and anoxia more prevalent in 2007. This research suggests that the IPCC needs a new conceptual model for N2O-NO3- relationships in rivers. N2O is produced in rivers, partially due to microbial processing of NO3- and NH4+ from WWTP effluent. However, WWTP effluent may also include dissolved N2O and CH4 but this previously had not been directly quantified. It was also unclear if stable isotopic ratios of NH4+, NO3-, N2O and CH4 in WWTP effluent were distinct from river sources and could be used for effluent tracing. N2O emissions from three WWTPs in the Grand River Watershed were measured over 24 hours in summer and winter. N2O emissions were similar to direct emissions from WWTPs but CH4 emissions were about an order of magnitude lower than direct WWTP emissions. This is a previously-ignored source of N2O and CH4 to the atmosphere. While stable isotopic ranges of NO3- and NH4+ were not always distinct from river sources, δ15N-N2O, δ18O-N2O and δ13C-CH4 were distinct, making them potentially useful tracers of WWTP effluent in rivers. N2O isotopic signatures may help determine production and removal processes in rivers, but isotopic effects of the major production pathway, denitrification, have not been characterized for river sediments. This was addressed by preparing anoxic laboratory incubations of river sediment from two sites (non-urban and urban) in the Grand River and measuring stable isotopic effects of N2O production via denitrification. Stable isotopic fractionations were similar to published values but, surprisingly, strongly negatively correlated to production rate, even though NO3- substrate was plentiful. This novel finding suggests that N2O reduction resulting in isotopic effects is more prevalent in high-substrate systems than previously thought, and that N2O reduction may be inhibited by high NO3- or NO2- or by lags in N2O reductase activity in high N2O-production incubations. This could explain why N2O emissions from the Grand River are lower than predicted by IPCC equations, which assume that N2O:(N2O+N2) ratios produced by denitrification are constant. Concern about NO3- export to freshwater lakes and to oceans is growing, but the role of large, eutrophic rivers in removing watershed NO3- loading via denitrification and biotic assimilation is not clear. To understand how much NO3- the Grand River receives, and how much it removes annually, a NO3- isotope mass balance for the Grand River was created. The river denitrified between 0.5% and 17% of incoming NO3-, less than the 50% suggested by the IPCC. This is surprising, as the river is well mixed, has moderate to high NO3- concentrations, experiences hypoxia (promoting denitrification), and has extensive biomass (biofilm and macrophytes) that assimilate N. However, the river’s short residence time (~3 days not counting reservoirs), organic carbon-poor sediment and mineralization of organic matter could contribute to low denitrification rates. These findings suggest that denitrification rates in rivers worldwide could be lower than previously estimated. Although error was high, most δ15N-NO3- values for losses were in the expected range for denitrification and most δ15N-NO3- values for gains were within ranges from tributaries, WWTP effluent and groundwater measured in the watershed. The model suggests that 68% to 83% of N loads to the watershed are lost before entering the Grand River, and 13% is exported to Lake Erie, leaving 5 to 19% lost in the Grand River from a combination of denitrification, assimilation and storage. These findings suggest that large rivers are much less efficient in denitrification than other locations in watersheds such as small streams, ponds, groundwater and riparian zones. They also indicate that agricultural NO3- loading is much higher than WWTP effluent, suggesting that N management strategies should focus on agricultural runoff and groundwater. Given that N2O:NO3- relationships are weak and non-linear in the Grand River, a new conceptual model for N2O:NO3- relationships is presented. First, the Grand River dataset was supplemented with data from high-oxygen streams in southern Ontario. Regression tree analysis shows a weak relationship between NO3- and N2O in these streams with no other factors (temperature, DO, NH4+, TP, DOC, etc.) improving fit. A conceptual model was then created, which posits that N2O emission variability (between and within sites) increases with NO3- concentration when NO3- concentrations are above the threshold for NO3- limitation. The global dataset does not dispute this model, though a NO3- threshold was not clear. The lack of sites with both high NO3- and high N2O may indicate a paucity of research on eutrophic sites. Alternatively, high NO3- may indicate oxic conditions (i.e. little to no denitrification to remove it) which are incompatible with very high N2O emissions. In this case, the conceptual model can be modified such that N2O variability decreases when NO3- > ~ 4 mg N/L. The work also shows that low DO consistently results in high N2O emissions but high temperatures result in a very large range of N2O emissions. This approach allows N2O emissions, which have very high variability and are difficult to predict, to be constrained to likely ranges.