7.4.4 Global Tropospheric Ozone
22.214.171.124 Present-Day Budgets of Ozone and its Precursors
Tropospheric ozone is (after CO2 and CH4) the third most important contributor to greenhouse radiative forcing. Trends over the 20th century are discussed in Chapter 2. Ozone is produced in the troposphere by photochemical oxidation of CO, CH4 and non-methane VOCs (NMVOCs) in the presence of NOx. Stratosphere-troposphere exchange (STE) is another source of ozone to the troposphere. Loss of tropospheric ozone takes place through chemical reactions and dry deposition. Understanding of tropospheric ozone and its relationship to sources requires three-dimensional tropospheric chemistry models that describe the complex nonlinear chemistry involved and its coupling to transport.
The past decade has seen considerable development in global models of tropospheric ozone, and the current generation of models can reproduce most climatological features of ozone observations. The TAR reported global tropospheric ozone budgets from 11 models in the 1996 to 2000 literature. Table 7.9 presents an update to the post-2000 literature, including a recent intercomparison of 25 models (Stevenson et al., 2006). Models concur that chemical production and loss are the principal terms in the global budget. Although STE is only a minor term in the global budget, it delivers ozone to the upper troposphere where its lifetime is particularly long (about one month, limited by transport to the lower troposphere) and where it is of most importance from a radiative forcing perspective.
The post-2000 model budgets in Table 7.9 show major differences relative to the older generation TAR models: on average a 34% weaker STE, a 35% stronger chemical production, a 10% larger tropospheric ozone burden, a 16% higher deposition velocity and a 10% shorter chemical lifetime. It is now well established that many of the older studies overestimated STE, as observational constraints in the lower stratosphere impose an STE ozone flux of 540 ± 140 Tg yr–1 (Gettelman et al., 1997; Olsen et al., 2001). Overestimation of the STE flux appears to be most serious in models using assimilated meteorological data, due to the effect of assimilation on vertical motions (Douglass et al., 2003; Schoeberl et al., 2003; Tan et al., 2004; Van Noije et al., 2004). The newer models correct for this effect by using dynamic flux boundary conditions in the tropopause region (McLinden et al., 2000) or by relaxing model results to observed climatology (Horowitz et al., 2003). Such corrections, although matching the global STE flux constraints, may still induce errors in the location of the transport (Hudman et al., 2004) with implications for the degree of stratospheric influence on tropospheric concentrations (Fusco and Logan, 2003).
Table 7.9. Global budgets of tropospheric ozone (Tg yr–1) for the present-day atmospherea.
|Reference ||Modelb ||Stratosphere-Troposphere Exchange ||Chemical Productionc ||Chemical Lossc ||Dry Deposition ||Burden (Tg) ||Lifetimed (days) |
|TARe ||11 models ||770 ± 400 ||3420 ± 770 ||3470 ± 520 ||770 ± 180 ||300 ± 30 ||24 ± 2 |
|Lelieveld and Dentener (2000) ||TM3 ||570 ||3310 ||3170 ||710 ||350 ||33 |
|Bey et al. (2001) ||GEOS-Chem ||470 ||4900 ||4300 ||1070 ||320 ||22 |
|Sudo et al. (2002b) ||CHASER ||593 ||4895 ||4498 ||990 ||322 ||25 |
|Horowitz et al. (2003) ||MOZART-2 ||340 ||5260 ||4750 ||860 ||360 ||23 |
|Von Kuhlmann et al. (2003) ||MATCH-MPIC ||540 ||4560 ||4290 ||820 ||290 ||21 |
|Shindell et al. (2003) ||GISS ||417 ||NRf ||NR ||1470 ||349 ||NR |
|Hauglustaine et al. (2004) ||LMDz-INCA ||523 ||4486 ||3918 ||1090 ||296 ||28 |
|Park et al. (2004) ||UMD-CTM ||480 ||NR ||NR ||1290 ||340 ||NR |
|Rotman et al. (2004) ||IMPACT ||660 ||NR ||NR ||830 ||NR ||NR |
|Wong et al. (2004) ||SUNY/UiO GCCM ||600 ||NR ||NR ||1100 ||376 ||NR |
|Stevenson et al. (2004) ||STOCHEM ||395 ||4980 ||4420 ||950 ||273 ||19 |
|Wild et al. (2004) ||FRSGC/UCI ||520 ||4090 ||3850 ||760 ||283 ||22 |
|Folberth et al. (2006) ||LMDz-INCA ||715 ||4436 ||3890 ||1261 ||303 ||28 |
|Stevenson et al. (2006) ||25 models ||520 ± 200 ||5060 ± 570 ||4560 ± 720 ||1010 ± 220 ||340 ± 40 ||22 ± 2 |
The faster chemical production and loss of ozone in the current generation of models could reflect improved treatment of NMVOC sources and chemistry (Houweling et al., 1998), ultraviolet (UV) actinic fluxes (Bey et al., 2001) and deep convection (Horowitz et al., 2003), as well as higher NOx emissions (Stevenson et al., 2006). Subtracting ozone chemical production and loss terms in Table 7.9 indicates that the current generation of models has net production of ozone in the troposphere, while the TAR models had net loss, reflecting the decrease in STE. Net production is not a useful quantity in analysing the ozone budget because (1) it represents only a small residual between production and loss and (2) it reflects a balance between STE and dry deposition, both of which are usually parametrized in models.
Detailed budgets of ozone precursors were presented in the TAR. The most important precursors are CH4 and NOx (Wang et al., 1998; Grenfell et al., 2003; Dentener et al., 2005). Methane is in general not simulated explicitly in ozone models and is instead constrained from observations. Nitrogen oxides are explicitly simulated and proper representation of sources and chemistry is critical for the ozone simulation. The lightning source is particularly uncertain (Nesbitt et al., 2000; Tie et al., 2002), yet is of great importance because of the high production efficiency of ozone in the tropical upper troposphere. The range of the global lightning NOx source presently used in models (3–7 TgN yr–1) is adjusted to match atmospheric observations of ozone and NOx, although large model uncertainties in deep convection and lightning vertical distributions detract from the strength of this constraint. Process-based models tend to predict higher lightning emissions (5–20 TgN yr–1; Price et al., 1997).
Other significant precursors for tropospheric ozone are CO and NMVOCs, the most important of which is biogenic isoprene. Satellite measurements of CO from the Measurements of Pollution in the Troposphere (MOPITT) instrument launched in 1999 (Edwards et al., 2004) have provided important new constraints for CO emissions, pointing in particular to an underestimate of Asian sources in current inventories (Kasibhatla et al., 2002; Arellano et al., 2004; Heald et al., 2004; Petron et al., 2004), as confirmed also by aircraft observations of Asian outflow (Palmer et al., 2003a; Allen et al., 2004). Satellite measurements of formaldehyde columns from the GOME instrument (Chance et al., 2000) have been used to place independent constraints on isoprene emissions and indicate values generally consistent with current inventories, although with significant regional discrepancies (Palmer et al., 2003b; Shim et al., 2005).
A few recent studies have examined the effect of aerosols on global tropospheric ozone involving both heterogeneous chemistry and perturbations to actinic fluxes. Jacob (2000) reviewed the heterogeneous chemistry involved. Hydrolysis of dinitrogen pentoxide (N2O5) in aerosols is a well-known sink for NOx, but other processes involving reactive uptake of the hydroperoxyl radical (HO2), NO2 and ozone itself could also be significant. Martin et al. (2003b) find that including these processes along with effects of aerosols on UV radiation in a global Chemical Transport Model (CTM) reduced ozone production rates by 6% globally, with larger effects over aerosol source regions.
Although the current generation of tropospheric ozone models is generally successful in describing the principal features of the present-day global ozone distribution, there is much less confidence in the ability to reproduce the changes in ozone associated with perturbations of emissions or climate. There are major discrepancies with observed long-term trends in ozone concentrations over the 20th century (Hauglustaine and Brasseur, 2001; Mickley et al., 2001; Shindell and Favulegi, 2002; Shindell et al., 2003; Lamarque et al., 2005c), including after 1970 when the reliability of observed ozone trends is high (Fusco and Logan, 2003). Resolving these discrepancies is needed to establish confidence in the models.