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Article

Measuring N2O Emissions from Multiple Sources Using a Backward Lagrangian Stochastic Model

1
Department of Agronomy, Purdue University, West Lafayette, IN 47907, USA
2
Department of Earth, Atmospheric and Planetary Sciences, Purdue University, West Lafayette, IN 47907, USA
*
Author to whom correspondence should be addressed.
Atmosphere 2020, 11(12), 1277; https://doi.org/10.3390/atmos11121277
Received: 28 September 2020 / Revised: 21 November 2020 / Accepted: 24 November 2020 / Published: 26 November 2020
(This article belongs to the Special Issue Atmospheric Trace Gas Source Detection and Quantification)
Nitrous oxide (N2O) emissions from agricultural soil are substantially influenced by nitrogen (N) and field management practices. While routinely soil chambers have been used to measure emissions from small plots, measuring field-scale emissions with micrometeorological methods has been limited. This study implemented a backward Lagrangian stochastic (bLS) technique to simultaneously and near-continuously measure N2O emissions from four adjacent fields of approximately 1 ha each. A scanning open-path Fourier-transform infrared spectrometer (OP-FTIR), edge-of-field gas sampling and measurement, locally measured turbulence, and bLS emissions modeling were integrated to measure N2O emissions from four adjacent fields of maize production using different management in 2015. The maize N management treatments consisted of 220 kg NH3-N ha−1 applied either as one application in the fall after harvest or spring before planting or split between fall after harvest and spring before planting. The field preparation treatments evaluated were no-till (NT) and chisel plow (ChP). This study showed that the OP-FTIR plus bLS method had a minimum detection limit (MDL) of ±1.2 µg m−2 s−1 (3σ) for multi-source flux measurements. The average N2O emission of the four treatments ranged from 0.1 to 2.3 µg m−2 s−1 over the study period of 01 May to 11 June after the spring fertilizer application. The management of the full-N rate applied in the fall led to higher N2O emissions than the split-N rates applied in the fall and spring. Based on the same N application, the ChP practice tended to increase N2O emissions compared with NT. Advection of N2O from adjacent fields influenced the estimated emissions; uncertainty (1σ) in emissions was 0.5 ± 0.3 µg m−2 s−1 if the field of interest received a clean measured upwind background air, but increased to 1.1 ± 0.5 µg m−2 s−1 if all upwind sources were advecting N2O over the field of interest. Moreover, higher short-period emission rates (e.g., half-hour) were observed in this study by a factor of 1.5~7 than other micrometeorological studies measuring N2O-N loss from the N-fertilized cereal cropping system. This increment was attributed to the increase in N fertilizer input and soil temperature during the measurement. We concluded that this method could make near-continuous “simultaneous” flux comparisons between treatments, but further studies are needed to address the discrepancies in the presented values with other comparable N2O flux studies. View Full-Text
Keywords: N2O; a backward Lagrangian stochastic (bLS) dispersion technique; open-path Fourier-transform infrared spectrometer (OP-FTIR); multiple emission sources N2O; a backward Lagrangian stochastic (bLS) dispersion technique; open-path Fourier-transform infrared spectrometer (OP-FTIR); multiple emission sources
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MDPI and ACS Style

Lin, C.-H.; Grant, R.H.; Johnston, C.T. Measuring N2O Emissions from Multiple Sources Using a Backward Lagrangian Stochastic Model. Atmosphere 2020, 11, 1277. https://doi.org/10.3390/atmos11121277

AMA Style

Lin C-H, Grant RH, Johnston CT. Measuring N2O Emissions from Multiple Sources Using a Backward Lagrangian Stochastic Model. Atmosphere. 2020; 11(12):1277. https://doi.org/10.3390/atmos11121277

Chicago/Turabian Style

Lin, Cheng-Hsien, Richard H. Grant, and Cliff T. Johnston 2020. "Measuring N2O Emissions from Multiple Sources Using a Backward Lagrangian Stochastic Model" Atmosphere 11, no. 12: 1277. https://doi.org/10.3390/atmos11121277

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