Figure 2. Monthly multiyear (2013-2018) mean CrIS NH3. Data are gridded to 0.1° × 0.1° with oversampling (see text for details). Grey grids, limited to Scotland, have < 10 observations.
3 The GEOS-Chem chemical transport model
We use the GEOS-Chem CTM version 12.1.0 (https://doi.org/10.5281/zenodo.1553349) to derive UK NH3 emissions from IASI and CrIS. The model is driven with NASA GEOS-FP assimilated meteorology from the Global Modeling and Assimilation Office (GMAO). Model simulations are conducted on a horizontal grid at 0.25° × 0.3125° (~25 km latitude × ~31 km longitude) nested over western Europe (32.75-61.25°N, 15°W-40°E). The model extends over 47 vertical layers from the Earth’s surface to 0.01 hPa. Dynamic (3-hourly) boundary conditions are from a global GEOS-Chem simulation at 4° × 5°.
Anthropogenic emissions over the UK, including from agriculture, are updated in GEOS-Chem to include gridded emissions from the NAEI for 2016 (Ricardo, 2018a). These are annual totals on a 1 km × 1 km grid available at https://naei.beis.gov.uk/data/map-uk-das (last accessed August 2019). The agricultural NH3 emissions incorporated in the NAEI are calculated at coarser resolution (5 km) than the NAEI with the nitrogen balance models of Webb & Misselbrook (2004) for livestock sources and Misselbrook et al. (2006) for fertilizer sources. These models are driven with 30-year mean meteorology for 1981-2010, so the NH3 emissions represent a climatological mean (Ricardo, 2019a). Other anthropogenic NH3 emissions in the NAEI are typically calculated as the product of emission and activity factors representative of the year of interest and mapped to the 1 km NAEI emissions grid (Ricardo, 2018b). Mainlaind Europe anthropogenic emissions for 2016 are updated with the gridded (0.1° × 0.1°) product provided by the European Monitoring and Evaluation Programme (EMEP) (http://www.ceip.at/new_emep-grid/01_grid_data; last accessed September 2019. Now at https://www.ceip.at/the-emep-grid/gridded-emissions).
Temporal variability of annual NAEI and EMEP NH3emissions is represented in GEOS-Chem with gridded monthly scaling factors and spatially uniform diurnal scaling factors. Monthly scaling factors are from the Generation of European Emission Data for Episodes (GENEMIS) project detailed in Friedrich (2000). These lead to peak NH3 emissions in April. Hourly scaling factors are from Zhu et al. (2015) calculated using information about the dependence of NH3 on aerodynamic resistance, surface temperature and Henry’s law. As a result of these, 30% of NH3 is emitted at midday (noon-2pm LST) coincident with the CrIS overpass and 20% in the morning (9am-noon LST) coincident with the IASI overpass. Natural NH3 sources are from inventories already in GEOS-Chem. These include natural emissions from soils and the ocean from the Global Emissions InitiAtive (GEIA) inventory (Bouwman et al., 1997) and inland and coastal seabird emissions from the Riddick et al. (2012) inventory. We halve the GEIA inventory emissions, as in Paulot et al. (2014), informed by a 50% overestimate identified by Simpson et al. (1999).
NH3 is a semi-volatile acid buffer that neutralizes acidic sulfate and nitrate aerosols, so its abundance depends on the abundance of these acidic aerosols. Sulfate forms from oxidation of SO2 and nitrates from aerosol uptake of nitric acid formed from oxidation of NOx. The version of the NAEI we use includes outdated mapping of the location of ships and no vertical or temporal information for aircraft emissions. To address these issues, we separate ship and aircraft emissions from other sources in the lumped “Other Transport and Mobile Machinery” category of the NAEI emissions inventory and replace ship emissions with updated estimates that use geospatial information from the automatic identification system (Ricardo, 2017). We convert the NAEI aircraft emissions to monthly estimates and distribute these vertically up to 1 km (the altitude limit of the NAEI emissions) by deriving vertical and temporal scaling factors from the global Aviation Emissions Inventory version 2.0 (AEIv2) used in GEOS-Chem (Stettler et al., 2011). Above 1 km, the AEIv2 emissions are used. The existing temporal scaling factors in GEOS-Chem that are applied to NAEI SO2 and NOx emissions lead to peak emissions in winter, due to an increase in energy demand. SO2 is emitted in the model as 95% SO2and 5% sulfate, using sulfate-to-SO2 emission ratios for Europe reported by Chin et al. (2000). NAEI emissions are gridded to a uniform 0.1° × 0.1° grid for input to the Harmonized Emissions Component (HEMCO) processing package version 2.1.010 (Keller et al., 2014) that maps all emissions to the model grid and applies relevant scaling factors.
The model includes detailed coupled gas- and aerosol-phase chemistry. Sulfate aerosols are formed in the model from oxidation of SO2 in the gas phase by OH and in the aqueous phase in clouds by ozone and hydrogen peroxide (Park et al., 2004). Partitioning of NH3 between the gas and acidic aerosol phase is determined dynamically with the thermodynamic equilibrium model ISORROPIA-II (Fountoukis & Nenes, 2007). Wet and dry deposition, terminal sinks of NH3, are represented with a standard resistances-in-series scheme for dry deposition (Wesely, 1989) and, for wet deposition, includes scavenging in and below clouds (Amos et al., 2012).
We use network site measurements of trace gases and aerosols to evaluate model accuracy at reproducing surface concentrations of NH3, SO2, and sulfate. These include 2 rural sites (Auchencorth Moss in Scotland, Chilbolton Observatory in southern England) that form part of the EMEP network and the mostly rural UK Eutrophying and Acidifying Atmospheric Pollutants (UKEAP) network. The 2 EMEP sites include hourly measurements from Monitor for AeRosols and Gases in Air (MARGA) instruments (Stieger et al., 2017; ten Brink et al., 2007; Twigg et al., 2015; Walker et al., 2019). The UKEAP network includes monthly measurements from low-cost denuder filter sampling packs (Tang et al., 2018). In 2016, there were 30 sites for SO2 and sulfate and 51 for NH3. The MARGA data are from the EMEP Chemical Coordinating Centre EBAS database (http://ebas.nilu.no/; last accessed February 2020) (Tørseth et al., 2012) and the UKEAP data are from the UK-AIR data archive (https://uk-air.defra.gov.uk/data/data-availability; last accessed November 2020).
To ensure consistency between the model and observations, the model is sampled from the lowest to the top model layer during the satellite overpass times of 08-11 LST for use with IASI and 12-15 LST for use with CrIS, and as monthly 24-hour means in the lowest model layer for comparison to the surface observations. The model is sampled in March-September 2016 following a 2-month spin-up for chemical initialization.
4 UK bottom-up emissions of NH3
Figure 3 shows the spatial distribution of annual UK NH3emissions for 2016 from the NAEI. Table 1 gives the breakdown by sector. Annual emissions for 2016 total 298 Gg, mostly (84%) from agriculture. Natural emissions of 21.6 Gg (7% of the total) are consistent with annual total natural emissions in GEOS-Chem of 21.8 Gg. According to GEOS-Chem, these include soils, vegetation and the ocean (together 18.7 Gg) and seabirds (3.10 Gg). NAEI anthropogenic NH3emissions total 276 Gg, 21 Gg less than the UNECE Gothenburg protocol emissions ceiling of 297 Gg (UNECE, 2019). The NAEI version we implement in GEOS-Chem and evaluate against top-down estimates was released in 2018. Two NAEI versions have been released since. Reported differences in NH3 emissions across these versions for consistent years is minor, just 1-3% (Ricardo, 2019b; 2020).
The spatial patterns in Figure 3 coincide with farming activities that dominate NH3 emissions according to the modelling study by Hellsten et al. (2008). They used the same Webb & Misselbrook (2004) nitrogen balance model as the NAEI to identify regionally dominant farming activities. The agricultural sources that dominate NH3 emissions include sheep farming along the Welsh border where emissions are low, and large sources like pig and poultry farming and fertilizer use in east England and dairy and beef cattle farming in west England and Northern Ireland. Hellsten et al. (2008) used agricultural activity data for 2000. Detailed geospatial farming activity data is confidential and publicly available data are limited to decadal maps of farming activities in England for 2000 and 2010 and annual regional and national statistics. The decadal maps suggest that locations of intensive crop and livestock farming in England are relatively unchanged (DEFRA, 2016b; a). The regional statistics document large changes in the number of livestock and the amount of nitrogen fertilizer used from 2000 to 2016 that would affect trends in emissions. In general, livestock numbers in the UK have declined by 20% for sheep, 11% for dairy and beef cattle, and 25% for pigs (DEFRA, 2020b). Poultry, specifically table chickens, have increased by 10% in the UK, with the largest increase of 42% in Northern Ireland (DEFRA, 2020b). Nitrogen-based fertilizer usage, a dominant NH3 source in east England (Hellsten et al., 2008), declined by 19% in the UK, though the relative proportion of urea-based fertilizer has increased (Ricardo, 2020). Regional changes in nitrogen-based fertilizers range from a 3% increase in Scotland to a 37% decrease in Northern Ireland (AIC, 2020).