2.1. Model Description
 The GEOS-CHEM global three-dimensional (3-D) model of tropospheric chemistry [Bey et al., 2001a] is used here to relate sources of CO to atmospheric concentrations and constitutes the forward model in the inverse analysis (section 3). A recent application of GEOS-CHEM to the global simulation of CO, including evaluation with the ensemble of NOAA/CMDL observations, is presented by B. N. Duncan et al. (Model study of the variability and trends in carbon monoxide (1988–1997): 1. Model formulation, evaluation, and sensitivity, submitted to Journal of Geophysical Research, 2003, hereinafter referred to as Duncan et al., submitted manuscript, 2003). The model version used here (v4.33, available at http://www-as.harvard.edu/chemistry/trop/geos/index.html) has a horizontal resolution of 2° latitude ×2.5° longitude and has 48 vertical levels ranging from the surface to the mesosphere, 20 of which are below 12 km. The model is driven by GEOS-3 assimilated meteorological data from the Goddard Earth Observing System (GEOS) of the NASA Data Assimilation Office. The 3-D meteorological data are updated every 6 hours; mixing depths and surface fields are updated every 3 hours.
 Gridded CO emission inventories for fossil fuel, biofuel, and biomass burning in East Asia during the TRACE-P period [Streets et al., 2003; Heald et al., 2003a] are used as a priori by the model. The Streets et al.  inventory describes anthropogenic fossil fuel and biofuel emissions for the year 2000. Fossil fuel emissions are from residential coal and oil (both used for cooking and heating), transportation, and industry. Biofuel emissions (heating and cooking) are from wood, agricultural residues, and dung. We do not account for seasonal variability of any anthropogenic emissions because the TRACE-P sampling period is relatively short (March–April) and emissions are then near their annual mean value. Streets et al.  provide detailed error estimates associated with their national emissions from Asia, representing important information for the inverse model analysis. Fossil and biofuel emissions for the rest of the world are taken from Duncan et al. (submitted manuscript, 2003) and Yevich and Logan , respectively.
 We use daily biomass burning CO emissions for the TRACE-P period from Heald et al. . This inventory uses firecount data from the AVHRR satellite instrument [Stroppiana et al., 2000] to constrain daily variability. It applies this variability to the biomass burning emission inventory of CO from Duncan et al. , which includes interannual and seasonal variability derived from TOMS, ATSR, and AVHRR satellite observations. Global biomass burning emissions during TRACE-P were mainly from Southeast Asia and India and were approximately the same as the climatological average for February–April [Heald et al., 2003]. Biomass burning emissions in eastern Asia during TRACE-P represent ≃75% of the annual total for that region and represent typically >50% of the global mean biomass burning emissions during February–April.
 In addition to direct emissions of CO there is a large chemical source from the oxidation of CH4 and NMVOCs, which is treated here following the approach of Duncan et al. (submitted manuscript, 2003). Anthropogenic and biomass burning NMVOCs are in general coemitted with CO; following Duncan et al. (submitted manuscript, 2003), we model them here as direct sources of CO and correspondingly increase the primary emissions of CO by 20% (fossil fuel) and 10% (biofuel and biomass burning). Additional sources of CO in the model include CH4 (850 Tg CO/yr) and biogenic NMVOCs with contributions from isoprene (175 Tg CO/yr), methanol (85 Tg CO/yr), monoterpenes (70 Tg CO/yr), and acetone (25 Tg CO/yr). Further details on these sources can be found in the work of Duncan et al. (submitted manuscript, 2003). Oxidation of CH4 by OH largely determined the chemical source of CO; emissions of shorter-lived biogenic NMVOCs are low during March–April and contribute only a few percent to the TRACE-P measurements.
 The main sink for CO is oxidation by OH. We use prescribed monthly mean OH concentration fields calculated from a full-chemistry simulation conducted with GEOS-CHEM v4.33. The corresponding lifetime of methylchloroform (CH3CCl3), a proxy for the global mean OH concentration, is 6.3 years; this is consistent with the best estimate of 5.99−0.71+0.95 years by Prinn et al.  from CH3CCl3 measurements. A detailed discussion of the factors affecting the CH3CCl3 lifetime in GEOS-CHEM is presented by Martin et al. . Although adjustment of CO sources in the inverse model analysis should modify OH, the effect is inconsequential for inverting Asian sources using the TRACE-P observations, which are only a few days downwind of the sources. Correction to OH is effectively taken into account in the inversion through the adjustment of the CO source from “rest of the world” (section 4). The assumption of fixed OH linearises the inverse problem [Pétron et al., 2002]. In the forward model we “tag” CO produced by different sources from different geographic regions (Figure 2, Table 1). The Jacobian matrix K for the inversion (section 3.1), relating individual annual mean sources of CO to the resulting atmospheric concentrations, can then be readily calculated by dividing a particular tagged member by its respective annual emission.
Table 1. Annual A Priori Sources of CO (Tg CO yr−1) for the Inverse Model Analysis
|Region||Biofuelsa (BF)||Fossil Fuela (FF)||Biomass Burninga (BB)||Methane Biogenic NMVOCs|
|China (CH)||45±35||64 ± 50||19 ± 9|| |
|Korea (KR)||4 ± 2||5 ± 2||0.3 ± 0.1|| |
|Japan (JP)||2 ± 0.4||7 ± 1||0.8 ± 0.4|| |
|India (IN)||38 ± 38||16 ± 16||39 ± 19|| |
|Southeast Asia (SEA)||26 ± 26||17 ± 17||82 ± 41|| |
|Rest of World (RW)||70 ± 35||273 ± 96||340 ± 170|| |
|TOTAL||185 ± 68||382 ± 110||481 ± 176||1205 ± 301|
 A number of previous GEOS-CHEM model studies have evaluated the simulation of CO with surface and aircraft observations in different regions of the world [Bey et al., 2001a, 2001b; Fiore et al., 2002; Li et al., 2002; Martin et al., 2003; Kasibhatla et al., 2002; Duncan et al., submitted manuscript, 2003]. These studies used earlier versions of GEOS-CHEM, with different CO sources and OH concentrations, so that results are not strictly comparable. The global underestimate of CO reported in the original version of GEOS-CHEM [Bey et al., 2001a] has since been corrected by better accounting of NMVOC precursors and of various factors acting to reduce OH [Martin et al., 2003; Duncan et al., submitted manuscript, 2003]. The most recent global evaluation (Duncan et al., submitted manuscript, 2003) indicates no bias in the simulation of the CO background, and this appears to hold also for v4.33 used here [Heald et al., 2003]. However, both (Duncan et al., submitted manuscript, 2003) and Heald et al.  used an anthropogenic Chinese source of CO that is 20% higher than the Streets et al.  inventory used here.
 The timing of TRACE-P (February–April) was chosen to coincide with the strongest outflow from Asia to the Pacific, driven by frequent wave cyclones and associated cold fronts and warm conveyor belts [Yienger et al., 2000; Bey et al., 2001b], and to encompass the biomass burning season in Southeast Asia which peaks typically in March [Duncan et al., 2003]. Anthropogenic emissions are largely aseasonal. TRACE-P was conducted early in the growing season so the source of CO from biogenic emissions represents only a few percent of the total measured outflow of CO from Asia.
2.2. TRACE-P Measurements of CO
 Diode laser spectroscopic measurements of CO were taken during TRACE-P using the Differential Absorption CO Measurement (DACOM instrument) [Sachse et al., 1987]. CO was measured at a frequency of 1 Hz with an estimated 1-s precision of 1%. We use here the 1-min average data and further average it over the GEOS-CHEM 2 × 2.5° grid along the flight tracks; for the purpose of our analyses these subsequent values are what we use as observations. Accuracy of the 1-min averaged data is ≃2% and is dominated by the accuracy of the NOAA/CMDL calibration standards (Paul Novelli, NOAA/CMDL, personal communication, 2003). Altitude ranges for the DC-8 and P3-B aircraft flight tracks are 0–12 km and 0–10 km, respectively.
 The GEOS-CHEM global 3-D simulations of CO and tagged CO tracers were initialised in January 2000 and conducted for 16 months (through April 2001). The 14-month simulation before the start of TRACE-P effectively removes the influence from initial conditions. We sample the model fields along TRACE-P flight tracks and compare with the observations averaged over the 2 × 2.5° model grid. We remove the influence of stratospheric air using the criterion O3 > 100 ppb; we verified that this does not remove any pollution plumes (O3 was occasionally above 100 ppb in Chinese urban plumes but not when averaged over the 2 × 2.5° grid). We also ignore data east of 150°E, which are mainly from transit flights (Figure 1). The data used for the inversion include all flights between 27 February and 3 April 2001.
2.3. Evaluation of Model With A Priori Sources
 Before proceeding with the inversion we first examine the ability of the a priori sources, as described in section 2.1, to simulate the TRACE-P measurements of CO (section 2.2). A general statistical comparison of model results with observations is shown in Figure 3. The model is on average 23 ppb too low; this discrepancy is driven by the high tail of the distribution (CO > 200 ppb), representing strong boundary layer outflow from Asia. The frequency distribution of differences at model and observations shows an approximate Gaussian distribution with a 13 ppb negative bias in the median. Major pollution plumes in the observations (CO > 500 ppb) are not well captured by the model.
Figure 3. Statistical comparison of simulated and observed CO from TRACE-P, for the model with a priori sources (left panels) and a posteriori sources (right panels). The observations have been averaged over the 2 × 2.5° model grid. Data influenced by the stratosphere (O3 > 100 ppb) or away from the western Pacific rim (longitudes >150°E) are excluded from the comparison. Top: frequency distributions of simulated (solid) and observed (dotted) CO. Bottom: frequency distribution of the difference between simulated and observed CO.
Download figure to PowerPoint
 A more detailed evaluation of the model with observations is shown in Figure 4 by the modeled and observed latitudinal gradients at different altitudes from 0 to 12 km. The model has a negative bias in the boundary layer which increases with latitude, reaching 80 ppb (30% of the mean total CO) between 30 and 40°N. We attribute this negative bias to an underestimate of Chinese anthropogenic emissions, as discussed below. Above the boundary layer the negative model bias is less, and largely disappears south of 30°N or above 6 km. The concentration of CO in the free troposphere is relatively more sensitive to biomass burning and to sources outside of Asia [Liu et al., 2003].
Figure 4. Latitudinal gradients of measured and modeled CO concentrations over the TRACE-P domain on a 2 × 2.5° grid. Observations (circles) are averaged over the altitude range shown in the figure, and over 5° latitude bins. Vertical bars denote 1-σ values about the mean. The model is sampled along the TRACE-P flight tracks for the flight days, and values are averaged across the same latitude and altitude ranges as the observations. Model values are shown for the simulations with a priori (triangles) and a posteriori (squares) sources. Data influenced by the stratosphere (O3 > 100 ppb) or away from the western Pacific rim (longitudes >150°E) have been excluded from the comparison. Numbers inset at the top of each panel refer to the number of observations used to compute the mean statistics.
Download figure to PowerPoint