Global partitioning of NOx sources using satellite observations: Relative roles of fossil fuel combustion, biomass burning and soil emissions

Abstract

We use space-based observations of NO2 columns from the Global Ozone Monitoring Experiment (GOME) to derive monthly top-down NOx emissions for 2000 via inverse modeling with the GEOS-CHEM chemical transport model. Top-down NOx sources are partitioned among fuel combustion (fossil fuel and biofuel), biomass burning and soils by exploiting the spatio-temporal distribution of remotely sensed fires and a priori information on the location of regions dominated by fuel combustion. The top-down inventory is combined with an a priori inventory to obtain an optimized a posteriori estimate of the relative roles of NOx sources. The resulting a posteriori fuel combustion inventory (25.6 TgN year(-1)) agrees closely with the a priori (25.4 TgN year(-1)), and errors are reduced by a factor of 2, from +/- 80% to +/- 40%. Regionally, the largest differences are found over Japan and South Africa, where a posteriori estimates are 25% larger than a priori. A posteriori fuel combustion emissions are aseasonal, with the exception of East Asia and Europe where winter emissions are 30-40% larger relative to summer emissions, consistent with increased energy use during winter for heating. Global a posteriori biomass burning emissions in 2000 resulted in 5.8 TgN (compared to 5.9 TgN year(-1) in the a priori), with Africa accounting for half of this total. A posteriori biomass burning emissions over Southeast Asia/India are decreased by 46% relative to a priori; but over North equatorial Africa they are increased by 50%. A posteriori estimates of soil emissions (8.9 TgN year(-1)) are 68% larger than a priori (5.3 TgN year(-1)). The a posteriori inventory displays the largest soil emissions over tropical savanna/woodland ecosystems (Africa), as well as over agricultural regions in the western U.S. (Great Plains), southern Europe (Spain, Greece, Turkey), and Asia (North China Plain and North India), consistent with field measurements. Emissions over these regions are highest during summer at mid-latitudes and during the rainy season in the Tropics. We estimate that 2.5-4.5 TgN year(-1) are emitted from N-fertilized soils, at the upper end of previous estimates. Soil and biomass burning emissions account for 22% and 14% of global surface NOx emissions, respectively. We infer a significant role for soil NOx emissions at northern mid-latitudes during summer, where they account for nearly half that of the fuel combustion source, a doubling relative to the a priori. The contribution of soil emissions to background ozone is thus likely to be underestimated by the current generation of chemical transport models.

Tropospheric emissions: Monitoring of pollution (TEMPO)

“…Soil NO x Jaeglé et al [43] have performed top-down (satellite) partitioning among NO x sources, including fuel combustion (fossil fuel and biofuel), biomass burning and soils. These are combined with bottom-up inventories to provide much improved a posteriori inventories of NO x sources and their relative importance.…”

Intercomparison of SCIAMACHY and OMI tropospheric NO2 columns: Observing the diurnal evolution of chemistry and emissions from space

“…But for most of the rural Southeast, observed NO 2 is lower at 1000 LT than at 1330 LT. We hypothesize that the opposite diurnal variation between the observed (0. emissions (dependent on soil temperature) are strongest in the afternoon [Ludwig et al, 2001], and there is evidence that these emissions are significantly underestimated in the model [Jaeglé et al, 2005]. Furthermore, Park et al [2007] found strong biomass burning activity throughout the Southeast and GEOS-Chem does not take into account the diurnal cycle of fires (see next section).…”

“…Data sets of tropospheric NO 2 columns retrieved from the Global Ozone Monitoring Experiment (GOME), the Scanning Imaging Absorption Chartography (SCIAMACHY) and the Ozone Monitoring Experiment (OMI) now span more than 10 years (1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006) and have been used for trend studies van der A et al, 2006a]. GOME and SCIAMACHY tropospheric NO 2 data has been used to estimate surface emissions of NO x [Martin et al, 2003;Jaeglé et al, 2004Jaeglé et al, , 2005Müller and Stavrakou, 2005;Bertram et al, 2005;Toenges-Schüller et al, 2006;Konovalov et al, 2006;Martin et al, 2006;Kim et al, 2006] and lightning NO x production [Boersma et al, 2005;Beirle et al, 2006;Martin et al, 2007].…”

The Dawn of Geostationary Air Quality Monitoring: Case Studies From Seoul and Los Angeles

“…These data have been useful for understanding global (e.g., Martin et al, 2003;Jaegl et al, 2005), regional (e.g., Duncan et al, 2016;Travis et al, 2016) and local air quality (e.g., Zhu et al, 2017) over daily (e.g., Valin et al, 2014;de Foy et al, 2016), seasonal (e.g., Russell et al, 2010), interannual, and decadal time periods (van der et al, 2008;De Smedt et al, 2015). However, the relatively coarse spatial resolutions and single daily observation times have substantially limited these applications, particularly within the air quality management community which needs to be able to distinguish temporal profiles of emissions from different source sectors and identify specific physical processes to justify regulatory decisions.…”