Abstract
Atmospheric nitrous oxide (N2O) contributes to global warming and stratospheric ozone depletion, so reducing uncertainty in estimates of emissions from different sources is important for climate policy. In this study, we simulate atmospheric N2O using an atmospheric chemistry-transport model (ACTM), and the results are first compared with the in situ measurements. Five combinations of known (a priori) N2O emissions due to natural soil, agricultural land, other human activities, and sea–air exchange are used. The N2O lifetime is 127.6 ± 4.0 yr in the control ACTM simulation (range indicates interannual variability). Regional N2O emissions are optimized using Bayesian inverse modeling for 84 partitions of the globe at monthly intervals, using measurements at 42 sites around the world covering 1997–2019. The best estimated global land and ocean emissions are 12.99 ± 0.22 TgN yr−1 and 2.74 ± 0.27 TgN yr−1, respectively, for 2000–2009, and 14.30 ± 0.20 TgN yr−1 and 2.91 ± 0.27 TgN yr−1, respectively, for 2010–2019. On regional scales, we find that the most recent ocean emission estimation, with lower emissions in the Southern Ocean regions, fits better with that predicted by the inversions. Marginally higher (lower) emissions than the inventory/model for the tropical (extratropical) land regions are estimated and validated using independent aircraft observations. Global land and ocean emission variabilities show a statistically significant correlation with El Niño Southern Oscillation (ENSO). Analysis of regional land emissions shows increases over America (Temperate North, Central, and Tropical), Central Africa, and Asia (South, East, and Southeast) between the 2000s and 2010s. Only Europe as a whole recorded a slight decrease in N2O emissions due to the chemical industry. Our inversions suggest revisions to seasonal emission variations for three of the 15 land regions (East Asia, Temperate North America, and Central Africa), and the Southern Ocean region. The terrestrial ecosystem model (Vegetation Integrative SImulator for Trace Gases) can simulate annual total emissions in agreement with the observed N2O growth rate since 1978, but the lag-time scales of N2O emissions from nitrogen fertilizer application may need to be revised.
Highlights
Nitrous oxide (N2O) emissions cause 300 times more warming over 100 years than equal emissions of carbon dioxide (CO2), and N2O has the 3rd largest increase in radiative forcing from 1750-2019 (Etminan et al 2016; IPCC 2013)
We have conducted forward transport modeling of atmospheric N2O (1971-2020) by MIROC4-atmospheric chemistry-transport model (ACTM), and inverse modelling to estimate N2O emissions over the globe using the measurements of National Oceanic and Atmospheric Administration (NOAA), AGAGE and NIES at 42 sites and MIROC4662 ACTM simulations
The MIROC4-ACTM simulations are compared with the 663 long-term (1978-2019) records of N2O at a few sites of AGAGE and NOAA, which led us to conclude that global N2O emissions from ocean and land surfaces are fairly well developed in the recent years for simulating the atmospheric burden of N2O. The lifetime of N2O in MIROC4-ACTM control transport simulation is estimated to be 127.6±4.0 yr for 1990-2019, but it has sensitivity to the model transport
Summary
Nitrous oxide (N2O) emissions cause 300 times more warming over 100 years than equal emissions of carbon dioxide (CO2), and N2O has the 3rd largest increase in radiative forcing from 1750-2019 (Etminan et al 2016; IPCC 2013). Atmospheric N2O averaged 327.5±2.9 ppb from 2010-2019 (https://gml.noaa.gov/ccgg/trends_n2o), a 21% increase from the pre-industrial level due to an increase in anthropogenic activities (Crippa et al 2020; Ishijima et al 2007) Of this 21% N2O increase, 18% has occurred since 1900 with large scale application of nitrogen fertiliser. No study has been conducted to elucidate the roles of these factors on the estimated emission in a single modelling system, in order to disentangle the roles of selecting a priori emissions, and processes in forward149 running ACTMs. An emission assessment framework using multi-model inversion provides only the range of uncertainty arising from their own choices of transport, chemistry and emissions, but does not elucidate the sources of uncertainty. The study significantly differs from the MIROC4-ACTM inversion used in Thompson et al (2019), for the choices of large number of a priori emission scenarios, input parameter selection for the inverse model and ACTM transport sensitivity simulations.
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