Nitrogen compounds

The NOx(= NO2+ NO) family is one of the key players in the formation of the O3in the tropo-

sphere, and during pollution episodes causes photochemical smog and contributes to acid rain. It has a relatively short lifetime; consequently, it is generally restricted to emission sources, both natural and anthropogenic (mainly fossil fuel combustion). The seasonal cycle of NOx near

the surface is controlled by the seasonality of anthropogenic emissions (especially in the North hemisphere) and biomass emissions (especially in the South Hemisphere). As a result, NOx

is more sensitive to errors in emissions than other pollutants, and errors in NOx emissions can

4.5. MODEL EVALUATION

Figure 4.9: Time series of NO2(top) and NOx(bottom) daily mean concentration averaged over all the rural EMEP

and EANET stations, respectively, used in µg m−3. Observations are in a solid red line and model data in a solid black line. Bars show the 25th-75th quartile interval for observations (orange bars) and for model simulation (grey bars).

Figure 4.9 shows the time series of NO2 and NOx daily mean concentrations over 21 and 10

ground-monitoring stations from the EMEP and EANET network, respectively. In both cases, the model is able to successfully reproduce the seasonal cycle of NO2 and NOx. However, a

positive bias is found during the summertime for NO2in Europe (Figure 4.9 top panel). Such a

result could be explained by the limitation on the anthropogenic emissions that are constant dur- ing the whole year. Because of that, the model cannot reproduce the decrease on anthropogenic emissions during the summertime leading to higher concentrations. Daily profiles show that the model tends to be too high at nighttime (not shown). This result may be due to the lack of the heterogeneous formation of HNO3through N2O5hydrolysis, an important sink of NO2at night

(Badia and Jorba, 2014). In addition, the current model does not consider secondary aerosol formation for the present exercise, which might result in an atmosphere that is too oxidising (overestimation of OH radicals), and in combination with the nocturnal chemistry this may lead

4.5. MODEL EVALUATION

to an accumulation of NO2in the surface layers. However, a slight underestimation is observed

between 9-18 UTC. Looking at the annual time series of NOxin the Asian network (Figure 4.9

bottom), we observed that the model is not able to reproduce NOxvalues, with a sizeable nega-

tive bias during the summer. This underestimation could be attributed to an underestimation in the emissions inventories which do not capture the extreme increase of anthropogenic emissions over Asia during the last decade (Akimoto, 2003; Richter et al., 2005), as was the case for CO.

Concerning the spatial statistics (see Figure 4.10 ), the model’s skills are lower in some regions such as Iberian Peninsula and most of the stations in Japan, with poor correlations. Best perfor- mance is seen in central EU and Japan stations that are not in the main island. In general there is a negative bias in most of the stations for these two regions.

Figure 4.10: NO2 (top) NOx(bottom) and spatial distribution of mean bias (MB, %) (left panel) , correlation (r)

(middle panel) and root mean square error (RMSE, µg m−3) (right panel) at all rural EMEP and EANET, respectively, stations used

Comparison of modelled and observed vertical profiles of NOX, HNO3 and PAN are presented

in Figure 4.11 for several regions over US, China, Hawaii and Japan (see Table 4.5 for more de- tail). As we explain in Section 4.3.2, these observational vertical profiles are not from the same year as the model simulation (see Table 4.5 for more detail), however, the qualitative patterns may provide insights on the model skills to reproduce the chemistry involved. Figure 4.11 (first column) shows that vertical profiles of NOX are in a very good agreement with the observed

values. The model has a tendency to overestimate values near the surface, it is likely that NOX

emissions used in this study are higher than the real emissions during these campaigns period. Another reason for these higher values over island locations (Japan and Hawaii) could be that emissions in the surface are spread throughout the entire model grid box while the measure-

4.5. MODEL EVALUATION

ments might measure in the clean marine boundary layer. In the middle and upper troposphere the model well reproduces the concentrations with a slight of underestimation in most of the locations. Note that NOxlightning emissions are not included in this simulation, explaining part

of this underestimation especially in the upper troposphere.

PAN is the principal tropospheric reservoir species for NOx with important implications for the

tropospheric O3production and of the main atmospheric oxidant, OH (Singh and Hanst, 1981).

PAN is mainly formed in the boundary layer by oxidation of non-methane volatile organic com- pounds (NMVOCs) in the presence of NOx. NMVOCs and NOx have both natural and anthro-

pogenic sources. Rapid convection can transport PAN to middle and upper troposphere and enables the long-range transport of NOx away from the urban and polluted areas, where it can

produce O3and OH remotely. Some features of vertical profiles are well-captured by the model,

although the model largely overpredicts PAN concentrations (see Figure 4.11, second column). Higher concentrations at the surface to middle atmosphere are found in Japan, China, Boul- der and Churchill, which present a high positive bias in the vertical profile, possibly explained by an overestimation in biogenic and anthropogenic NOx emissions in this area at the surface-

level. Another possibility for this overestimation of the modelled PAN might be attributed by a too long lifetime of calculated PAN. At most sites, PAN model concentrations tend to increase with altitude, reaching its maximum mixing ratios around 6km, and above that level it starts to decrease. This behaviour explains the long thermal decomposition time of PAN (lifetime of approximately a month) and the slow loss by photolysis in the cold middle-upper troposphere. Fischer et al. (2014), presents a sensitivity of PAN to different emission types. It shows that most of the northern hemisphere and Japan is more sensitive to anthropogenic emissions and south hemisphere and the west coast of the USA to biogenic emissions, both contributing to 70-90% PAN concentrations.

HNO3 is mainly produced by the reactions of NO2with OH and by the hydrolysis of N2O5 on

aerosols (we do not account for this reaction in this simulation), and then it is removed by wet and dry deposition. HNO3 is the main sink of NOx chemistry. In general, the modelled and

observed nitric acid concentrations are in good agreement throughout the troposphere, although the model reveals a tendency to overestimate HNO3concentrations, which is more pronounced

in USA regions. In the regions of Hawaii, Japan and China the model overestimates HNO3

in the lower-middle troposphere (up to 5km) and underestimates it in the upper troposphere (above 6km). Overestimation of HNO3in the troposphere is a common problem in global mod-

els (Hauglustaine et al., 1998; Bey et al., 2001b; Park et al., 2004; Folberth et al., 2006). One possible reason for this overestimation is that the scavenging from the convective precipitation is underestimated. Hence, HNO3concentrations are highly sensitive to the parameterization of

wet deposition.

4.5. MODEL EVALUATION

Figure 4.11: Comparison of modelled (black lines) and observed (red lines) vertical profiles of NOX (first column),

4.5. MODEL EVALUATION

Figure 4.12 presents the wet deposition fluxes of HNO3in comparison with nitrate observations

for three different networks located in Europe, USA and Asia. Satisfactory agreement is found in the HNO3 wet deposition with correlations 0.63 in Europe, 0.80 in USA and 0.52 in Asia.

There is a tendency to underestimate in most of the stations, principally in Asia and Europe. Part of this underestimation is because we are comparing nitric acid (gas) with nitrate (nitric acid + particulate nitrate) concentrations. However, this tendency to underestimate is consistent with the higher values of HNO3seen at lower and middle troposphere.

Figure 4.12: Scatter plots of the simulated HNO3 versus nitrate measurements for three networks: Europe (left

panel), USA (middle panel) and Asia (right panel). Dashed lines have slopes equal to 2 resp. 0.5. The dotted line is the result of the linear regression fitting through the origin.

Seasonally modelled VTC of NO2 ((no averaging kernel application) are calculated here and

compared with SCIAMACHY satellite data in Figure 4.13. The model is in good agreement with the observations, capturing higher NO2 over the most polluted regions, such as Europe,

USA and Eastern Asia. The phase in the seasonal cycle of the NO2columns is well-performed

by the model. During the whole year, the model tends to underestimate NO2 VTCs in big

cities, especially during the colder months, and overestimate them in rural regions. The largest differences are seen for eastern China suggesting an underestimation in the emission inventory for this area. Biomass burning cycle is captured remarkably well by the model, with higher NO2

VTC in central Africa during DJF and NO2 VTC in South America in the JJA. Over the sea,

the model concentrations are in very good agreement, with only small differences (± 0.5 1e15 molec/cm2).