Peter A. Turner

Indirect nitrous oxide emissions from streams within the US Corn Belt scale with stream order.

Significance N2O emissions from riverine systems are poorly constrained, giving rise to highly uncertain indirect emission factors that are used in bottom-up inventories. Using a non–steady-state flow-through chamber system, N2O fluxes were measured across a stream order gradient within the US Corn Belt. The results show that N2O emissions scale with the Strahler stream order. This information was used to estimate riverine emissions at the local and regional scales and demonstrates that previous bottom-up inventories based on the Intergovernmental Panel on Climate Change default values have significantly underestimated these indirect emissions. N2O is an important greenhouse gas and the primary stratospheric ozone depleting substance. Its deleterious effects on the environment have prompted appeals to regulate emissions from agriculture, which represents the primary anthropogenic source in the global N2O budget. Successful implementation of mitigation strategies requires robust bottom-up inventories that are based on emission factors (EFs), simulation models, or a combination of the two. Top-down emission estimates, based on tall-tower and aircraft observations, indicate that bottom-up inventories severely underestimate regional and continental scale N2O emissions, implying that EFs may be biased low. Here, we measured N2O emissions from streams within the US Corn Belt using a chamber-based approach and analyzed the data as a function of Strahler stream order (S). N2O fluxes from headwater streams often exceeded 29 nmol N2O-N m−2⋅s−1 and decreased exponentially as a function of S. This relation was used to scale up riverine emissions and to assess the differences between bottom-up and top-down emission inventories at the local to regional scale. We found that the Intergovernmental Panel on Climate Change (IPCC) indirect EF for rivers (EF5r) is underestimated up to ninefold in southern Minnesota, which translates to a total tier 1 agricultural underestimation of N2O emissions by 40%. We show that accounting for zero-order streams as potential N2O hotspots can more than double the agricultural budget. Applying the same analysis to the US Corn Belt demonstrates that the IPCC EF5r underestimation explains the large differences observed between top-down and bottom-up emission estimates.

Isoprene emissions and impacts over an ecological transition region in the U.S. Upper Midwest inferred from tall tower measurements

We present 1 year of in situ proton transfer reaction mass spectrometer (PTR-MS) measurements of isoprene and its oxidation products methyl vinyl ketone (MVK) and methacrolein (MACR) from a 244 m tall tower in the U.S. Upper Midwest, located at an ecological transition between isoprene-emitting deciduous forest and predominantly non-isoprene-emitting agricultural landscapes. We find that anthropogenic interferences (or anthropogenic isoprene) contribute on average 22% of the PTR-MS m/z 69 signal during summer daytime, whereas MVK + MACR interferences (m/z 71) are minor (7%). After removing these interferences, the observed isoprene and MVK + MACR abundances show pronounced seasonal cycles, reaching summertime maxima of >2500 pptv (1 h mean). The tall tower is impacted both by nearby and more distant regional isoprene sources, with daytime enhancements of isoprene (but little MVK + MACR) under southwest winds and enhancements of MVK + MACR (but little isoprene) at other times. We find that the GEOS-Chem atmospheric model with the MEGANv2.1 (Model of Emissions of Gases and Aerosols from Nature version 2.1) biogenic inventory can reproduce the isoprene observations to within model uncertainty given improved land cover and temperature estimates. However, a 60% low model bias in MVK + MACR cannot be resolved, even across diverse model assumptions for NOx emissions, chemistry, atmospheric mixing, dry deposition, land cover, and potential measurement interferences. This implies that, while isoprene emissions in the immediate vicinity of the tall tower are adequately captured, they are underestimated across the broader region. We show that this region experiences a strong seasonal shift between VOC-limited chemistry during the spring and fall and NOx-limited or transitional chemistry during the summer, driven by the spatiotemporal distribution of isoprene emissions. Isoprenes role in causing these chemical shifts is likely underestimated due to the underprediction of its regional emissions.

Partitioning N2O emissions within the U.S. Corn Belt using an inverse modeling approach

Nitrous oxide (N2O) emissions within the US Corn Belt have been previously estimated to be 200–900% larger than predictions from emission inventories, implying that one or more source categories in bottom-up approaches are underestimated. Here we interpret hourly N2O concentrations measured during 2010 and 2011 at a tall tower using a time-inverted transport model and a scale factor Bayesian inverse method to simultaneously constrain direct and indirect agricultural emissions. The optimization revealed that both agricultural source categories were underestimated by the Intergovernmental Panel on Climate Change (IPCC) inventory approach. However, the magnitude of the discrepancies differed substantially, ranging from 42 to 58% and from 200 to 525% for direct and indirect components, respectively. Optimized agricultural N2O budgets for the Corn Belt were 319 ± 184 (total), 188 ± 66 (direct), and 131 ± 118 Gg N yr−1 (indirect) in 2010, versus 471 ± 326, 198 ± 80, and 273 ± 246 Gg N yr−1 in 2011. We attribute the interannual differences to varying moisture conditions, with increased precipitation in 2011 amplifying emissions. We found that indirect emissions represented 41–58% of the total agricultural budget, a considerably larger portion than the 25–30% predicted in bottom-up inventories, further highlighting the need for improved constraints on this source category. These findings further support the hypothesis that indirect emissions are presently underestimated in bottom-up inventories. Based on our results, we suggest an indirect emission factor for runoff and leaching ranging from 0.014 to 0.035 for the Corn Belt, which represents an upward adjustment of 1.9–4.6 times relative to the IPCC and is in agreement with recent bottom-up field studies.

Regional‐scale controls on dissolved nitrous oxide in the Upper Mississippi River

The U.S. Corn Belt is one of the most intensive agricultural regions of the world and is drained by the Upper Mississippi River (UMR), which forms one of the largest drainage basins in the U.S. While the effects of agricultural nitrate (NO3−) on water quality in the UMR have been well documented, its impact on the production of nitrous oxide (N2O) has not been reported. Using a novel equilibration technique, we present the largest data set of freshwater dissolved N2O concentrations (0.7 to 6 times saturation) and examine the controls on its variability over a 350 km reach of the UMR. Driven by a supersaturated water column, the UMR was an important atmospheric N2O source (+68 mg N2O N m−2 yr−1) that varies nonlinearly with the NO3− concentration. Our analyses indicated that a projected doubling of the NO3− concentration by 2050 would cause dissolved N2O concentrations and emissions to increase by about 40%.

Nitrous oxide emissions are enhanced in a warmer and wetter world

Significance N2O has 300 times the global warming potential of CO2 on a 100-y timescale, and is of major importance for stratospheric ozone depletion. The climate sensitivity of N2O emissions is poorly known, which makes it difficult to project how changing fertilizer use and climate will impact radiative forcing and the ozone layer. Here, atmospheric inverse analyses reveal that direct and indirect N2O emissions from the US Corn Belt are highly sensitive to perturbations in temperature and precipitation. We combine top-down constraints on these emissions with a land surface model to evaluate the climate feedback on N2O emissions. Our results show that, as the world becomes warmer and wetter, such feedbacks will pose a major challenge to N2O mitigation efforts. Nitrous oxide (N2O) has a global warming potential that is 300 times that of carbon dioxide on a 100-y timescale, and is of major importance for stratospheric ozone depletion. The climate sensitivity of N2O emissions is poorly known, which makes it difficult to project how changing fertilizer use and climate will impact radiative forcing and the ozone layer. Analysis of 6 y of hourly N2O mixing ratios from a very tall tower within the US Corn Belt—one of the most intensive agricultural regions of the world—combined with inverse modeling, shows large interannual variability in N2O emissions (316 Gg N2O-N⋅y−1 to 585 Gg N2O-N⋅y−1). This implies that the regional emission factor is highly sensitive to climate. In the warmest year and spring (2012) of the observational period, the emission factor was 7.5%, nearly double that of previous reports. Indirect emissions associated with runoff and leaching dominated the interannual variability of total emissions. Under current trends in climate and anthropogenic N use, we project a strong positive feedback to warmer and wetter conditions and unabated growth of regional N2O emissions that will exceed 600 Gg N2O-N⋅y−1, on average, by 2050. This increasing emission trend in the US Corn Belt may represent a harbinger of intensifying N2O emissions from other agricultural regions. Such feedbacks will pose a major challenge to the Paris Agreement, which requires large N2O emission mitigation efforts to achieve its goals.

A geostatistical approach to identify and mitigate agricultural nitrous oxide emission hotspots.

Anthropogenic emissions of nitrous oxide (N2O), a trace gas with severe environmental costs, are greatest from agricultural soils amended with nitrogen (N) fertilizer. However, accurate N2O emission estimates at fine spatial scales are made difficult by their high variability, which represents a critical challenge for the management of N2O emissions. Here, static chamber measurements (n=60) and soil samples (n=129) were collected at approximately weekly intervals (n=6) for 42-d immediately following the application of N in a southern Minnesota cornfield (15.6-ha), typical of the systems prevalent throughout the U.S. Corn Belt. These data were integrated into a geostatistical model that resolved N2O emissions at a high spatial resolution (1-m). Field-scale N2O emissions exhibited a high degree of spatial variability, and were partitioned into three classes of emission strength: hotspots, intermediate, and coldspots. Rates of emission from hotspots were 2-fold greater than non-hotspot locations. Consequently, 36% of the field-scale emissions could be attributed to hotspots, despite representing only 21% of the total field area. Variations in elevation caused hotspots to develop in predictable locations, which were prone to nutrient and moisture accumulation caused by terrain focusing. Because these features are relatively static, our data and analyses indicate that targeted management of hotspots could efficiently reduce field-scale emissions by as much 17%, a significant benefit considering the deleterious effects of atmospheric N2O.

A Modeling Study of Direct and Indirect N2O Emissions From a Representative Catchment in the U.S. Corn Belt

Indirect nitrous oxide (N2O) emissions from drainage ditches and headwater streams are poorly constrained. Few studies have monitored stream N2O emissions and fewer modeling studies have been conducted to simulate stream N2O emissions. In this study, we developed direct and indirect N2O emission modules and a corresponding calibration module for use in the Soil and Water Assessment Tool (SWAT) model, and implemented the expanded SWAT model (termed SWAT-N2O) to a representative fourthstream-order catchment (210 km) and six first-order stream catchments (0.22–1.83 km) in southeastern Minnesota. We simulated the spatial and temporal fluctuations of the indirect emissions from streams, identified emission ‘‘hot spots’’ and ‘‘hot moments,’’ and diagnosed the correlations between direct and indirect emissions. We showed that zero-order streams and first-order streams could contribute 0.034–0.066 and 0.011 nmol N2O m 22 s (expressed on the basis of unit catchment area) to the total surface emissions, respectively. Emissions from zero-order and first-order streams equal 24–41% of direct emissions from soil, which may explain the emission gap between calculations using top-down and bottom-up methods. Clear spatial patterns were identified for both direct and indirect emissions and their spatial variations were negatively correlated. Our results suggest that the IPCC N2O emission factor for streams in the Corn Belt should be increased by 3.2–5.7 times. Increasing precipitation and streamflow in the Corn Belt may potentially increase frequencies of soil anoxic conditions and nitrate leaching to streams, and subsequently increase N2O emissions from both soils and streams.