The TAGGING model described here see also is written as a submodel of the Modular Earth Submodel System (MESSy), which comprises a standard interface to couple different processes, a simple coding standard and a set of different submodels . The TAGGING submodel is implemented in MESSy2 and consists of two parts, the submodel interface layer (SMIL) and the submodel core layer (SMCL). The SMIL part is mainly important for data management, defining and handling the tracers (using the TRACER submodel described in ), and the diagnostic output fields using the CHANNEL submodel . The coupling for the necessary input fields are also handled via the CHANNEL submodel. These input fields comprise, for example, lightning NOx emissions, and chemical production/loss rates from the chemical solver MECCA (Module Efficiently Calculating the Chemistry of the Atmosphere; ).

The TAGGING submodel is implemented in EMAC and MECO(n) (MESSyfied ECHAM and the Consortium for Small-Scale Modelling model COSMO nested n times). While EMAC uses ECHAM5 as a global circulation model, MECO(n) consists of COSMO/MESSy as a regional-scale model with EMAC as the driving model , which are coupled online. The SMCL of the TAGGING submodel is independent of the base model and consists mainly of the code needed to solve the relevant equations. A detailed description of the TAGGING submodel, including individual subroutines of the SMIL and the SMCL, are provided in the supplement. The model set-up is identical to that of . A detailed list of applied submodels can be found in the supplement of p. 42, therein. Table  describes only those submodels that are of direct relevance for the TAGGING submodel. An evaluation of the model configurations of EMAC and MECO(n) with respect to the chemical composition of the atmosphere can be found in and .

The objective of the tagging scheme is to determine the contribution of emissions from various sectors. Here, we discriminate between 10 different sources: four anthropogenic: non-traffic anthropogenic (industry, energy, households), road traffic, ships, and air traffic; five natural sources: lightning, emissions from biogenic sources including soils, decomposition of N2O, decomposition of CH4, stratospheric ozone production by photolysis of O2; and a mixed class: biomass burning (see Table ).

We use a configuration of the chemical scheme MECCA , which consists of 72 species. We only tag a reduced set of species, which resemble the main species and families for tropospheric chemistry, in order to limit the required memory. Besides CO, O3, peroxyacytyl nitrate (PAN), HO2, and OH, two families are considered: NOy and NMHC, which include all chemically active nitrogen compounds (15) and hydrocarbons (42) (see the Supplement for more details). All together, the tagging scheme consists of 7 species times 10 emission sectors, thus 70 tagged tracers. For each tracer initialisation, transport (except for OH and HO2), emissions, dry and wet deposition, and chemical conversion has to be deduced from the base model (Fig. ). The tagging scheme utilises the EMAC submodels, e.g. for tracer transport, for emissions computed online during the simulation, and for emissions prescribed by inventories (Table ; for details see the Supplement), such as industry, road traffic, etc. (Fig. , middle column). It further obtains information on online emissions (lightning, soils), dry and wet deposition, background tracers and reaction rates (left column). This information is processed in tagging core routines (right column).

Here, we concentrate on the TAGGING submodel (Fig. , right column). For the initialisation of the tagged tracers two options are available. First, the variables can be initialised from files, or second the tagged tracers can be initialised according to their key characteristics. In this case, the tagged stratospheric ozone is initialised by the ozone field above the tropopause and all other tagged ozone fields are zero above the tropopause and vice versa. Below the tropopause, all but the tagged stratospheric ozone tracer, obtain one-ninth of the tropospheric ozone concentration.

At each time step during the simulation, the online emissions (soil emissions) are added to the respectively tagged tracer (Table ). The emission rate is obtained by recording the concentration of NOx before and after the calculation of online emissions. The tagged lighting NOy tracer obtains the same lightning emissions as the chemical NO tracer, which is provided by the lightning submodel LNOX . Dry and wet deposition is treated as a bulk process. Changes in the concentration of all relevant chemical species are calculated in a practical and simple manner, by the difference in the respective concentrations before and after dry and wet deposition is calculated. This tendency of the concentration is provided to the tagging submodel and distributed among the tagged species according to their relative contribution to the total concentration.

The core of the tagging submodel is the distribution of the chemical tendencies to the tagged tracers as introduced in Sect. . Therefore, the individual production and loss terms have to be determined adequately to calculate concentration changes via Eq. (). Here, we consider effective ozone production and loss terms according to . This implies that a family is considered for ozone (see Supplement for more details), which includes all fast exchanges between ozone and other chemical species. The ozone production basically requires splitting up an oxygen molecule. For the identification of ozone production and loss reactions, we apply the tool ProdLoss (see Supplement for more detailed information), which identifies the effective production and loss reactions for a family in the selected chemical mechanism. This family for effective ozone is hereafter referred to as ozone for simplicity. This results in two ozone production terms, which are applied to any tagged ozone field with the exception of stratospheric ozone. This is Reaction () and the combination of reactions of the type (see Supplement for more detailed information) NO+RO2⟶NO2+RO with reaction rate PR2. The production and loss terms of these tagged ozone fields are then PO3tag=12PR1NOytagNOy+HO2tagHO2+12PR2NOytagNOy+NMHCtagNMHC,DO3tag=12PR3OHtagOH+O3tagO3+12PR4HO2tagHO2+O3tagO3+12PR5NOytagNOy+O3tagO3+12PR6NMHCtagNMHC+O3tagO3+PR7O3tagO3, with “tag” denoting one of the 10 source tags and with the reaction rates PR3, PR4, PR5, PR6, PR7 referring to the reactions OH+O3⟶HO2+O2HO2+O3⟶OH+2O2Effective ozoneloss viaNOyRO2+O3⟶RO+2O2OH+O3⟶HO2+O2

The tagged species NOy, CO, NMHC, and PAN are treated similarly and will be discussed here only briefly, while more detailed information is provided in the supplement. Figure  sketches the principal relations between the tagged species. Methane (not tagged) is depleted and the chemical products are then tagged as “NMHC from methane”. The species in the NMHC family are eventually transformed into CO and further into CO2. The decomposition of N2O (not tagged) constitutes a source for “stratospheric NOy”. Reactions between NOy and NMHCs form PAN (not included in NOy). PAN is an important species, which can be transported over long distances before it thermally decomposes .

HOx chemistry (Fig.  and Table ) and the calculation of the individual contributions to the concentrations of OH and HO2 is much more complex; hence, we discuss it here in more detail. The main source of OH is the reaction of H2O with O(1D). The chemical reactions between OH and HO2 involve species such as CO, CH4, NOy, and NMHC. Losses of HOx are the formation of H2O2 and HNO3, which are soluble and can be easily rained out.

Since the lifetime of both OH and HO2 is short, we assume steady state for the contributions. We refer to the main HOx reactions, for which the production and loss rates are calculated in and provided by the MECCA submodel (see also Table ).

The steady-state assumption for the contributions to the OH and HO2 concentrations, i.e. OHtag and HO2tag, implies that the individual production terms equal the individual loss terms: POHtag=LOHtag,PHO2tag=LHO2tag. Again the more complex part of the tagging chemistry is to derive the production and loss terms. Using the reactions in Table  and the approach from , we obtain for the production and loss of OHtag: POHtag=P1OHO3tagO3+12P2OHHO2tagHO2+O3tagO3+12P3OHNOytagNOy+HO2tagHO2,LOHtag=L1OH12OHtagOH+COtagCO+L2OHOHtagOH+L3OH12OHtagOH+O3tagO3+L4OH12OHtagOH+NMHCtagNMHC+L5OH12OHtagOH+HO2tagHO2+L6OH12OHtagOH+NOytagNOy.

This set of equations includes the assumption that exchanges within a family are fast enough to achieve equally distributed tags among family members. For example, concerning P1OH, the contribution of one source to O(1D) equals that of O3, i.e. O(1D)tagO(1D)=O3tagO3.

Similarly, we derive the individual production and loss terms for HO2:

PHO2tag=P1HO212OHtagOH+COtagCO+P2HO212OHtagOH+O3tagO3+P3HO212NMHCtagNMHC+NOytagNOy,

LHO2tag=L1HO212HO2tagHO2+O3tagO3+L2HO212HO2tagHO2+NOytagNOy+L3HO212HO2tagHO2+OHtagOH+L4HO212HO2tagHO2+NMHCtagNMHC+L5HO2HO2tagHO2. Now the Eqs. () and () can be written as 0=Atag-LOHOHtagOH+POHHO2tagHO2,0=Btag+PHO2OHtagOH-LHO2HO2tagHO2, with Atag=P1OHO3tagO3+12P2OHO3tagO3+12P3OHNOytagNOy-12L1OHCOtagCO-12L3OHO3tagO3-12L4OHNMHCtagNMHC-12L6OHNOytagNOy,Btag=12P1HO2COtagCO+12P2HO2O3tagO3+12P3HO2NMHCtagNMHC+12P3HO2NOytagNOy-12L1HO2O3tagO3-12L2HO2NOytagNOy-12L4HO2NMHCtagNMHC,POH=12P2OH+P3OH-L5OH,LOH=12L1OH+2L2OH+L3OH+L4OH+L5OH+L6OH,PHO2=12P1HO2+P2HO2,LHO2=12L1HO2+L2HO2+L3HO2+L4HO2+2L5HO2. The Eqs. () and () can easily be solved resulting in OHtag=AtagLHO2+BtagPOHLOHLHO2-POHPHO2OH,HO2tag=AtagPHO2+BtagLOHLOHLHO2-POHPHO2HO2.

The quantity Atag (Btag) represents the contribution of chemical tracers (tagged and non-tagged, other than OH and HO2) to the net OH production (net HO2 production). The terms LOH and POH are primarily contributions to OH loss and production rates, which depend on the contribution to OH (OHtag) and HO2 (HO2tag), respectively. Only the reaction of OH with HO2 forming water vapour and molecular oxygen constitutes an exception, since the loss of OH is dependent on both OH and HO2 (L5OH). Therefore, it also contributes to POH (see Eq. ), the last term in Eq. (), which depends on HO2. Note that in this case it does not lead to a production but destruction of OH.

The 6-year annual average contributions of the 10 emission sectors to the ozone concentration are shown in Fig. . We compare these results with an earlier model version, which only tags NOy and ozone Fig. 5b therein, and to earlier similar studies by and . This comparison aims at verifying that the implementation of the TAGGING mechanism is correct by comparing contribution patterns and magnitudes. We have to keep in mind that the approach is conceptually different from earlier studies and takes into account all ozone precursor emissions and not only NOy. Hence, the individual contributions have to be smaller and no agreement can be expected, except for pattern and magnitude. The only direct intercomparison can be performed for the stratospheric ozone mixed into the troposphere, since this process is independent from any precursors. Here , , , and (hereafter denoted as LD00, L05, G07, and E12, respectively) estimated a 5–40 % contribution from stratospheric ozone to tropospheric ozone in the Southern Hemisphere and mostly systematically lower values of 10–25 % in the Northern Hemisphere, while tropical values are below 10 % (Table ). Our simulation also shows a minimum of the stratospheric ozone mixing ratios in the tropics and lower mixing ratios in the Southern Hemisphere compared to the Northern Hemisphere. The mixing ratios for January and July are very similar to those of not shown.

Ozone formed from lightning NOx (Fig. ) shows a maximum in the tropics and upper troposphere and larger contributions in the Southern Hemisphere than in the Northern Hemisphere, which is in agreement with G07 and LD00. The maximum contribution from lightning is around 25–30 % and thus lower than G07 (40 %) and LD00 (50 %), because here we regard the ozone production of all precursors, whereas in G07 and LD00 only NOx as a precursor is considered (see above).

Agreement between the studies LD00, G07, E12, and our work can also be found with respect to the contribution of anthropogenic emissions to tropospheric ozone. These emissions (here: anthropogenic non-traffic, road traffic, shipping, and aviation) predominantly contribute by 30–50 % in the Northern Hemisphere. The ozone contribution from biomass burning peaks in the lower tropical troposphere with values of around 10–15 %, which compares well with G07 and LD00 (20 %). Around 15 % of the tropospheric ozone originates from methane, which reacts with OH and contributes to NMHC compounds and eventually to CO and CO2.

Figure  shows the contribution of the individual emission sectors to the tropospheric budgets of NOy, CO, NMHC, PAN, and O3. Lightning and non-traffic anthropogenic emissions show the largest contributions to NOy. The emitted NOy from lightning and aviation remains much longer in the atmosphere compared to a surface source, such as non-traffic anthropogenic NOy, since lightning and aviation emit mainly in the upper troposphere. Aviation, shipping, and biomass burning have approximately the same contribution.

The different emission sectors have very different emission characteristics. Some are only emitting NOy, such as lightning, or NOy and NMHCs, such as most anthropogenic sources. This is well reflected in the budgets (Fig. ). Since NOy is required to form PAN, the decomposition of PAN also produces NOy and NMHCs with the original tag, e.g. the lightning tag. This is fully consistent with the chosen tagging approach and leads to minor contributions of non-CO and non-NMHC emitting emission sectors to the CO and NMHC budgets (lightning, stratosphere, aviation). For example, NOx emitted by road traffic may react with hydrocarbons from, e.g., biogenic emissions to form PAN, which is then transported over longer distances. When decomposed after being transported over a long distance, the products obtain tags from both sources. Hence, hydrocarbons, which may not have been emitted by road traffic, obtain in this process a road traffic tag. The reasoning behind this is that only the PAN formation allowed for the long-range transport of either species and hence both emission sources have affected this. While this case is a wanted tagging effect, other situations may lead to unwanted side effects or even unphysical effects (see discussion in Sect.  for more details). The formation of PAN and hence contributions to PAN (Fig. , second row) requires both NOy and NMHCs. None of the 10 emission sectors has a large contribution from both; hence, the contributions of each of the 10 sectors to PAN are almost equally distributed around 10 %. One exception is methane, which contributes largely to NMHC concentrations but not to NOy. In addition, the NMHCs from methane are predominantly occurring in areas with low NOy background, which reduces the impact on PAN. The contribution to tropospheric ozone (Fig. , second row) reflects the distribution presented in Fig. , with major contributions from lightning, stratosphere, anthropogenic non-traffic emissions, and methane.

In this section, we present the effects of a surface source (shipping) and a higher-altitude atmospheric source (aviation) on their contribution to the HOx concentrations. We have chosen the Mediterranean Sea for shipping, since it includes areas in the middle of the Sea on the one hand, as well as areas that are largely affected by other sources, e.g. in southern France (Marseilles) and Italy (harbour areas such as Genoa, Fig. ), on the other hand.

We have identified four areas (A–D) with different chemical characteristics (Table , see also Fig. ): highly polluted areas with high concentrations of NO2 (A and B) and with a large (some) impact from shipping in region A (B); a more remote area with some impact from shipping on NOx and O3 (C), and a more remote area with a larger values of shipping ozone (D).

Large NOx concentrations in the background (A and B) impact the chemistry and net production efficiencies; i.e. the ozone enhancement per NOx is decreasing with increasing NOx concentrations e.g.. The Reaction (), which transforms HO2 into OH, in principle increases (decreases) the OH (HO2) concentration in the region where large amounts of shipping NOx is present. However, this reaction only dominates the OH to HO2 ratio if enough ozone is available for the HOx production. In region A, the very low ozone concentration due to ozone titration by NOx limits the availability of OH and the contribution of shipping NOx to OH is even negative. Region B is less polluted than region A and has lower values of shipping NOx and therefore Reaction () dominates the OH and HO2 contributions from shipping, leading to positive contributions to OH and negative to HO2. The tagged shipping ozone is larger in area D compared to A and B (not shown). This leads to a larger contribution to OH via the main production reaction of H2O with O(1D), where the O(1D) originates from the tagged ozone (see also Table ). The close coupling of OH with HO2 also enhances the tagged HO2 especially in region D. These processes then lead to a complex picture. It shows negative contributions to OH in region A, mainly due to low ozone concentration limiting the OH availability, which is even more pronounced by shipping emissions. The shipping contribution to HO2 in the polluted areas A and B are negative mainly driven by the Reaction (). Large positive contributions of shipping to OH and moderate negative contributions to HO2 are found in region C, resulting from a combination of effects from Reaction () and the main OH production resulting from tagged shipping ozone, whereas in region D moderate positive contributions of shipping to OH and large negative contributions to HO2 are found. Overall, the contributions from shipping emissions to the OH and HO2 concentrations show a complex picture, which results from variations in both the background concentrations and shipping concentrations. The impact of an enhanced horizontal resolution is discussed for the same situation in Sect. .

Figure  shows annual mean contributions of aviation NOx emissions to OH (left) and HO2 (right). The air traffic contribution to OH peaks at around 10–20 fmol mol-1 at the main flight altitude. At the surface, there are other secondary peaks, basically at the locations of the airports. summarised the work of and in their Fig. 10 and showed four atmospheric regions, which are affected differently by air traffic. In the first region (RNOy in their paper), which is mainly the air traffic corridor, Reaction () controls the chemical impact from air traffic emissions. This implies that air traffic largely contributes to OH and negatively contributes to RHO2 as shown in Fig. . The region north of RNOy is called RHO2 and the aviation impact is largely controlled by the reaction of O3 with HO2 (see Table ). Hence, this reaction leads to a reduction in HO2 without affecting the OH concentration in a similar manner. The region RO3 is located in the lower troposphere and away from the major flight corridor. Here, a significant contribution from air traffic to ozone is found, but not so much to NOy (not shown). The region is controlled by an increase in ozone. Hence, it leads to a general increase in HOx via the reaction of H2O with O(1D) (see Table ). This comparison shows that the OH and HO2 contributions from aviation, calculated here, are consistent with the chemical regimes identified in previous studies.

A more detailed view on this tagging mechanism is feasible by applying it to a Lagrangian framework . Within the EU-Project REACT4C (Reducing Emissions from Aviation by Changing Trajectories for the benefit of Climate), the HOx tagging mechanism was implemented in the same EMAC model version, including a Lagrangian transport algorithm. Aviation-like pulse emissions of NOx were released at selected points in the atmosphere, and trajectories with these emissions were tagged so that reactions with the background can be determined in detail. Note that aviation is not emitting CO and NMHCs in our simulation; hence, the equations look simplified in as the values for COtag and NMHCtag are zero (see Sect. ). Figure  shows the temporal development of several NOx-related species (top and middle) as well as ozone production and loss terms (bottom) for a pulse emission at 45∘ W, 50∘ N and 300 hPa. The NOx emission induces net production of O3tag see Eq. 10 in, mainly via Reaction () and enhanced HOxtag as calculated via Eqs. () and (). NOx reacts with OH and forms HNO3, which eventually leads to washout and a reduction of NOytag within a few weeks. When NOxtag is no longer available for O3 production, O3tag is subsequently depleted. We denote the chemical regime, where enough NOx is available to produce larger amounts of ozone with RegNOx and the following regime as RegO3 (see also Fig. ). Regarding the destruction of CH4tag, these two regimes are also characterising the two different depletion pathways. First, as long as sufficient NOxtag is available, CH4tag is reduced because of an increase of OHtag via reaction () (NOx-driven CH4 destruction). Second, when NOxtag is removed, OHtag is mainly produced via photolysis of O3tag and the subsequent Reaction P1OH (H2O + O1D → 2OH). The tagged OH and HO2 are far lower in the RegO3 regime compared to the RegNOx regime (Fig. , middle); consequently, the gradient in the O3-driven CH4 destruction is not as steep. However, due to the longer time period, it dominates the total amount of methane destruction in this case, which can be seen from a budget analysis for the chemical regimes RegNOx (blue bars) and RegO3 (red bars) given in Fig. . Note that the trajectory is transported into polar night around day 5, which leads to a reduction of OH and HO2 and a reduction of the photochemical activity. This example shows a reasonable temporal behaviour of the tagged species and it further shows how combining the tagging methodology and a Lagrangian transport algorithm results in a powerful tool, facilitating a detailed analysis of particular processes.

By applying the MECO(n) system , we have increased the horizontal resolution over Europe by roughly a factor of 5, from a resolution of roughly 200 km times 300 km in EMAC to 50 km times 50 km in the nested grid. Figure  shows the contributions of the individual emission sectors to the tropospheric ozone column as a mean over Europe for the coarse resolution (top) and the finer resolution (bottom). Clearly, the individual contributions are very similar in terms of mean values and the seasonal cycle. The finer-resolution simulation shows finer-resolved structures in the horizontal (not shown), which, however, do not largely affect the large-scale budgets.

As an example of the effects of finer resolution, we present OH and HO2 contributions from shipping over the Mediterranean Sea, as discussed in Sect.  and Fig. . The OH enhancement along shipping routes is much more visible in the finer-resolved case (Fig. , lower left) compared to the lower resolution (upper left). The structures for the OH and HO2 contributions are again similar: A positive contribution to the OH concentration in the area of shipping emissions (B–D) and a decrease in the contribution to OH and HO2 where background NOx is largely enhanced (region A).

The comparison of the coarser and finer resolution clearly shows that the tagging scheme is stable in its behaviour. Naturally, the finer resolution enables more detailed and finer-resolved chemical changes due to emissions to be quantified, but basic structures are reproduced in either resolution. This implies that, depending on the underlying research question, either model can be used.

We performed an additional global simulation with EMAC where we reduced the road traffic emissions by 5 %. The simulation set-up hence follows . This means that the chemical composition and the ozone productivity is different from the base simulation, which leads to a roughly 2–3 % reduction in the tagged road traffic ozone (not shown). Generally, a reduction of surface NOx emissions is increasing the ozone productivity and consequently a 5 % reduction in emissions is expected to lead to significantly less than a 5 % reduction in road traffic ozone, which is consistent with our results. Figure  shows the relative change in tropospheric ozone induced by the road traffic emission reduction of 5 %. The total ozone change of 0.08 % (black bar) is a consequence of the reduction of the contribution of road traffic to the tropospheric total ozone by 0.16 % and other compensating effects. In total, this leads to a factor of 2 difference between the total ozone change and the road traffic ozone change. The compensating effects are resulting from larger net ozone production rates for the shipping emission sector and other anthropogenic non-traffic emission sectors. This leads to a larger contribution of the anthropogenic non-traffic (dark blue bar) and the (other than road traffic) traffic emission sectors (green bar) to total ozone by 0.04 and 0.06 %, respectively. Other non-anthropogenic sectors (red bar) , i.e. natural emission, reduce this compensation.

The ratio of 2 between the reduction in total ozone and road traffic indicates that a calculation of the road traffic contribution to tropospheric ozone using the perturbation method, i.e. difference between two simulations with changing emissions, underestimates this contribution by exactly this factor of 2. Other studies have shown slightly larger factors, e.g. a factor of 3 for biomass burning NOx emissions and a factor of 5 for road traffic NOx emissions (Grewe et al., 2012). Here, a smaller factor can be expected, since emissions other than NOx and their impact on ozone are tagged, which reduces the effects from road traffic emission changes. Further, this factor largely depends on the chemical state of the atmosphere, which differ between the simulations. Hence, a direct intercomparison is not possible; however, the results are plausible.