Regional CO Pollution in China Simulated by the High-Resolution Nested-Grid GEOS-Chem Model

1 An updated version of the nested-grid GEOS-Chem model is developed allowing for higher 2 horizontal (0.5 o x 0.667 o ) and vertical resolution as compared to global models. CO transport 3 over a heavily polluted region, the Beijing-Tianjin-Hebei (BTH) city cluster in China, and the 4 pattern of outflow from East China in summertime are investigated. Comparison of the 5 nested-grid with global models indicates that the fine-resolution nested-grid model is capable of 6 resolving individual cities with high associated emission intensities. The nested-grid model 7 indicates the presence of a high CO column density over the Sichuan Basin in summer, 8 attributable to the low-level stationary vortex associated with the Basin’s topographical features. 9 The nested-grid model provides good agreement also with measurements from a suburban 10 monitoring site in Beijing during summer 2005. Tagged CO simulation results suggest that 11 regional emissions make significant contributions to elevated CO levels over Beijing on polluted 12 days and that the southeastward moving cyclones bringing northwest winds to Beijing are the key 13 meteorological mechanisms responsible for dispersion of pollution over Beijing in summer. 14 Overall CO fluxes to the NW Pacific from Asia are found to decrease by a factor of 3-4 from 15 spring to summer. Much of the seasonal change is driven by decreasing fluxes from India and 16 Southeast Asia in summer, while fluxes from East China are only 30% lower in summer than in 17 spring. Compared to spring, summertime outflow from Chinese source regions is strongest at 18 higher latitudes (north of 35 o N). The deeper convection in summer transporting CO to higher 19 altitudes where export is more efficient is largely responsible for enhanced export in summer.


Introduction 22
Chemical transport models are effective in simulating the combined influences physical and 23 chemical processes affecting the distribution of a key chemical species in the Earth's atmosphere. 24 The domain of an atmospheric model varies from hundreds of meters to thousands of kilometers 25 (Seinfeld and Pandis, 1998). Global climate change or stratospheric ozone depletion is simulated 26 over a global scale domain and over periods ranging from months to hundreds of years and 27 beyond. Specific air pollution issues such as acid deposition and long-range transport of 28 particulates and ozone are simulated over synoptic to global-scale domains over periods of days 29 to months. Urban air pollution is simulated over micro-to mesoscale domains over periods 30 ranging from hours to days. It's difficult to simulate the variation of species concentrations at 31 scales smaller than the model resolution. For example, a global scale model that treats the entire 32 area as one computational cell of uniform chemical composition cannot describe the spatial 33 variations in pollution levels across the two adjacent large Chinese cities of Beijing and Tianjin . 34 The diffusion equation in regional atmospheric models needs side boundary conditions in 35 the x, y, and z directions, whereas global models simulate the Earth's atmosphere as a whole. It is 36 difficult to obtain exact values of tracer concentrations for all points of the side boundaries as a 37 function of time. Boundary conditions, especially at the upwind boundaries, continue to affect 38 model predictions throughout the simulation. Song et al. (2008) used the simulation results of a 39 global chemistry model, the Real-time Air Quality Modeling System (RAQMS), to provide 40 dynamic lateral boundary conditions for regional air quality simulations using the Models-3 41 resolution of the meteorological fields is degraded to 2º x 2.5º longitude or 4º latitude x 5º 114 longitude due to computational limitations. Details of the degradation process are provided by 115 Wang et al. (2004a). Compared to the global GEOS-Chem model, the nested-grid GEOS-Chem 116 model retains a generic high horizontal resolution over the nested regional domain. 117 The GEOS-5 meteorology uses an advection code different from that of GEOS-3, partly 118 because different vertical coordinates were used in the two versions of GEOS assimilated 119 meteorology. Lateral boundary conditions for the nested-grid model were added in the GEOS-5 120 advection code following the same methodology of Wang et al. (2004a). The nested regional 121 domain (70 o E-150 o E, 11 o S-55 o N; c.f. Fig. 1 in Wang et al., 2004a) includes all of China, its 122 neighboring countries (stretching from Pakistan in the west to Japan in the east and from 123 Indonesia in the south to Mongolia in the north), and a significant portion of the northwestern 124 Pacific. The high resolution regional domain is nested into a global domain treated with a 125 resolution of 4°x 5°. The outermost grids at the lateral boundaries of the high-resolution 126 nested-grid domain were used to delineate a buffer zone separating low and high-resolution 127 portions of the model (Wang et al., 2004a). To provide boundary conditions for the regional 128 model, the global assimilation was run at the spatial resolution of 4 degrees latitude by 5 degrees 129 longitude. The tracer mixing ratios for the buffer zone grids were saved for every three hours 130 consistent with the temporal resolution of the meteorology data. The archived, time-varying 131 boundary conditions were used to drive high-resolution nested-grid model runs. 132

CO Simulations with different resolutions 133
A CO-only simulation was conducted using the global model with its higher resolution 134 nested-grid for summer 2005 with specified OH fields derived from a global coupled 135 NO x -VOCs-O 3 -aerosol simulation (Wang et al., 2004a In this section, we examine the differences relating to the higher spatial resolution available 147 in the nested-grid regional domain by comparing high-resolution nested-grid model outputs with 148 the intermediate-resolution global simulation. Since the simulations with different resolutions 149 adopted the same OH fields, differences in modeling CO may be entirely attributed to the higher 150 resolution specification of sources and to differences in the treatment of transport as simulated 151 using the one-way nested formulation. 152

CO Emissions 153
Anthropogenic emissions of CO from the combustion of fossil fuel and biofuel over the 154 nested East Asia domain were taken from Zhang et al. (2009) for the year 2006. For China, the 155 inventory was based upon the studies of Streets et al. (2006), which improved estimations for 156 emissions from Chinese industrial sources that had been underestimated in the inventory 157 developed earlier in support of the TRACE-P aircraft mission (Streets et al., 2003). The updated 158 inventory was downloaded from http://mic.greenresource.cn/intex-b2006 at 0.5° X 0.5° 159 resolution. The 0.5°x0.5° gridded emission inventory was degraded into 4°x5°, 2°x2.5°, 160 0.5°x0.667° using spatial averaging. 161 For emissions associated with fossil fuels over the rest of the world, we adopted inventories 162 reported by Duncan et al. (2003). Emissions due to the combustion of biofuel and the burning of 163 biomass were taken from Yevich and Logan (2003) and Duncan et al. (2003), respectively. These 164 emissions were defined with respect to a 1° X 1° grid. The 1° X 1° emissions data sets were 165 regridded to match the 4° X 5°, 2° X 2.5°, 0.5° X 0.667° model resolutions. 166 The spatial distribution of composite CO emissions over the nested domain is presented in 167 illustrating a clear contrast with surrounding grids that have relatively low CO. At 2°x2.5°211 resolution, however, emissions from these cities are smeared out to a larger area, resulting in 212 lower concentrations in cities, compensated by higher concentrations in surrounding grids. 213

Differences between urban and suburban grids 214
We examine in this section the extent to which the nested-grid model with its current The monthly mean mixing ratios of CO during three months (July, August, and September) 235 in 2005 are summarized in Table 1, including both observations and model results for comparison. 236 The data are represented as daily (24hr)  Beijing grid and the suburban DL grid are 39% and 11% lower than the observations. The 251 underestimates of daily mean mixing ratios by the model may be partly due to underestimates of 252 CO emissions as inventory estimates for Chinese CO emissions are still uncertain (Zhang et al., 253 2009). More importantly, the six monitoring sites within the urban grid are all located within a 10 254 km range of the city center, while the urban emissions as simulated in the nested-grid model, 255 even given its relative high applied resolution (0.5° x 0.667°) are much more diluted. 256

A Case Study: Summertime CO variations in Beijing 257
To investigate the meteorological factors responsible for the alternations between heavy 258 pollution days and clean days in the BTH region in summertime, we first compared the modeled 259 and observed time series of CO mixing ratios and related meteorological parameters for Jul 2005 260 at the DL site. The reason for focusing on the suburban DL site rather than on the urban site is 261 because the resolution limitation of the nested-grid model made it impossible to simulate the very 262 high CO levels at the urban site as indicated above. 263

Day-to-day variations in CO and meteorology 264
Time series of CO daily mixing ratios observed at the urban site and the suburban DL site 265 are summarized in Fig. 4a. As discussed, the DL site was readily impacted by plumes with high 266 levels of CO from the urban grid during the daytime, resulting in high temporal correlations 267 between CO observations at the two sites (r = 0.82). Given the nested-grid model resolution, it 268 was difficult for the model to simulate the exact timing and locations of the urban plume. 269 Therefore, when we compared the daily CO levels between modeled results and observations at 270 the DL site, we excluded the impact of urban plumes by filtering out the observations with 271 hourly-mean CO mixing ratios greater than 1300 ppbv. The daily mean CO mixing ratios from 272 the model were based on hourly model outputs sampled in the same way as with the observations. 273 were also tagged as they make important contributions to Asian outflow of CO to the NW Pacific 305 as discussed in the next section. The tagged regions of emissions are indicated in Fig. 5. Detailed 306 methodology of the tagged CO simulation was described in Wang et al. (2004a). 307 Table 2 summarizes the percentage contributions of individual CO tracers to total CO 308 simulated at the DL site for each month. Emissions from the two Beijing grids (i.e., the urban 309 grid and the suburban DL grid, denoted as BJ in the table) were referred to as local emissions in 310 our study, while emissions from all the other tagged Chinese regions were regarded as regional 311 emissions. We found that local emissions make up an average about 46% of CO mixing ratios at 312 the DL site in summer. The regional emissions from the tagged Tianjin-Hebei region make up the 313 second largest contribution, accounting for an average of 17% for CO at DL. The temporal 314 correlation between the tagged BJ tracer (representing local emissions) and the TH tracer is 0.52. 315 The tagged SH tracer was also found to correlate well with the BJ tracer, although the 316 contribution from the SH tracer is much smaller. 317 For air quality regulators, an important question is how to reduce pollutant concentrations on 318 days with bad air quality. On those days, the relative contributions from local and regional 319 emissions may differ from their mean contributions. Therefore, we now turn our attention to the 320 contributions of tagged tracers on individual days. Figure 6 presents the day-to-day variations in 321 mixing ratios of individual tagged tracers for July 2005. Most days, the BJ tracer makes the 322 biggest contribution , but its relative importance becomes smaller on high pollution days with 323 high mixing ratios of CO. For example, during the high pollution period between 6 July and 8 324 July, the BJ tracer accounted for only 35%-40% of the total CO, while the influence from 325 regional emissions was much higher, with the TH tracer and the SH tracer accounting for about 326 35% and 20%, respectively, during the period. On relatively clean days (5 Jul and 28-29 Jul), the 327 BJ tracer (70-75%) and the global background made the biggest contributions. The tagged CO 328 simulation indicates that during periods of heavy pollution the Beijing, Tianjin-Hebei, Shandong, 329 and Hebei regions were particularly important source regions. 330

Meteorological Conditions 331
To investigate the meteorological conditions controlling the differces between heavily 332 polluted and relatively clean days in summer, we chose 1-4 July as a representative period. The 333 mixing ratios of CO observed at the DL site were relatively low on 1 July, rose to a high level on 334 the second day and peaked on 3 July, followed by a rapid drop on 4 July. During this period of 4 335 days, the observed variations in CO mixing ratios differed by about a factor of three. The model 336 reproduced well the sequence of variations, although it failed to reproduce the exact magnitude of 337 the very high and very low mixing ratios of CO on 3 July and 4 July, respectively. 338 Beijing. The Beijing area was not strongly influenced by either the low-pressure system to the 344 northwest or the high-pressure system to the southeast. A weak high-pressure system was located 345 over the North China Plain, and the atmosphere was relatively static over Beijing on 3 July, with 346 surface wind speeds below 1 m/s. The static conditions favored accumulation of the regional CO 347 emissions from the heavily polluted Tianjin-Hebei area and local Beijing emissions, resulting in 348 rapid rises in CO mixing ratios. The low-pressure system strengthened on 3 and 4 July and 349 moved toward the southeast. By 4 July, the low-pressure center was to the east of Beijing, with 350 the associated strong northwesterly winds bringing relatively clean air to Beijing with CO levels 351 over Beijing dropping accordingly. The meteorological setting for Jul 2 to 4 is consistent with the 352 general description of the sawtooth cycles of PM 2.5 levels over Beijing, as reported by Jia et, al. 353 (2008). They suggested that the passage of synoptic systems from the north is the key 354 meteorological mechanism resulting in the dilution and removal of pollution from Beijing. 355

China Outflow 356
The monsoonal circulation over East Asia is characterized by a general outflow of surface 357 air from the continent in winter compensated by a maritime inflow in summer. Many previous 358 studies have used CO as a tracer to examine the patterns and mechanisms of Asian outflow to the 359 Pacific, and much of the attention has thus far been paid to springtime (Liu et al., 2003;Fuelburg 360 et al., 2003;Liang et al., 2004). Liu et al. (2003) found that the major process responsible for the 361 export of Asian anthropogenic pollution to the western Pacific during spring is frontal lifting to 362 the free troposphere (FT) ahead of southeastward-moving cold fronts and transport in the 363 boundary layer (BL) behind the cold front. Orographic lifting over central and eastern China 364 combines with the cold fronts to promote the transport of Chinese pollution to the FT. In this 365 section, the outflow pattern in summertime is discussed and compared with that in spring. The 366 analysis focuses on CO emitted from the geographical regions in Asia as defined in the tagged 367 CO simulation described above (c.f. Fig. 5). The domain adopted to evaluate the export fluxes is 368 defined by 80°-140°E longitude, 10°-50°N latitude, and 0-12 km altitude. The regions of SH, TH, 369 and BJ are combined here into the North China (NC) region. 370 larger by a factor of 2-3 than the fluxes in summertime, consistent with the seasonality suggested 376 by Liu et al. (2003) for the export of Asian anthropogenic CO to the NW Pacific. CO originating 377 from India and Southeast Asia accounts for about 60% of the total fluxes in spring. The fraction 378 from these sources drops to 30% in summer. Seasonal biomass burning over India and Southeast 379 Asia is responsible for the large export of CO from the two regions in spring. The seasonal 380 variability in outflow from East China is relatively small, with summertime outflow only 30% 381 lower than that in springtime. Emissions of CO from East China are responsible for about 40% of 382 the total outflow of CO from Asia in spring, with the fraction increasing to 70%-80% in summer. 383 Table 3 summarizes the export efficiency of CO emitted from the tagged source regions in 384 springtime (MAM) and summertime (JJA). The export efficiency of CO, evaluated separately for 385 the north-south (northward as positive) and east-west (eastward as positive) directions, is defined 386 as the ratio of the net export through the lateral boundaries to the total emissions from the source 387 region. From the table, we can see that in both seasons the major export pathway is in the EW 388 direction for all source regions. It has been suggested in many previous studies that CO emitted 389 over Asia is transferred eastward through a two-step process (Liu et al., 2003;Wang et al., 2004;390 Fuelburg et al., 2003;Liang et al., 2004). First, it is lifted through vertical motions of the 391 atmosphere (e.g, by fronts or convection) from the near-surface regions to higher altitudes. 392 Subsequently, it is captured by strong westerlies that prevail in the free troposphere. Among the 393 regions listed in Table 3, SC has the highest EW export efficiency because its location in the 394 lower latitude with abundant solar radiation is conducive to stronger vertical motions of the lower 395 atmosphere, resulting in efficient lifting of CO to the free troposphere. NEC has the highest NS 396 export efficiency because of its location near the northern boundary. The EW export efficiency is 397 higher in summer and so is the efficiency for NS export. The total export efficiency ranges from 398 0.45 (NC) to 0.65 (SC) in spring and from 0.66 (NC) to 0.89 (SX) in summer. The deeper 399 convection in summer bringing CO to higher altitudes with more efficient export is the important 400 factor for higer export efficiency in summer. 401 Compared with springtime, summertime outflow from all the tagged Chinese source regions is 404 strongest at higher latitudes (north of 35°N). Inflow (i.e., negative fluxes) prevails through the whole 405 troposphere south of 25°N in summer. This suggests that in summer, CO emitted from the surface is 406 first transported northward by maritime inflow associated with the summer monsoon before being 407 lifted to the free troposphere by deep convection and carried eastward by the strong westerlies. 408 Northward transport is most significant for CO from SC, for which emissions are from south of 30°N, 409 whereas outflow is confined to north of 35°N. Convection is expected to be stronger in summer than 410 in spring, resulting in more efficient lifting and subsequently, stronger outflow in the free troposphere. 411 In summer, the eastward fluxes of Chinese CO all take the common pathway confined to north of 412 35°N in the free troposphere, regardless of the latitudes from which emissions originated. In contrast, 413 outflow in springtime is strongest over the same latitudes of emissions. For example, outflow from SC 414 in springtime is strongest at 25°N, while that from NC is strongest at 40°N. The nested-grid model was used to analyze the day-to-day variations in CO at a suburban site 433 near Beijing in summertime. The model was found to reproduce well the observed variations in 434 temperature and surface pressure but was found to overestimate wind speeds. Since the suburban 435 site is under the strong influence of Beijing urban emissions, overestimates in wind speeds by the 436 model result in more rapid dilution and greater export of local emissions out of the grid, leading 437 to underestimates of CO mixing ratios of the model. Tagged CO simulation results suggest that 438 regional emissions from Tianjin, Shandong, and Hebei make significant contributions to elevated 439 levels of CO over Beijing on polluted days. During these days, as much as 50% of CO in Beijing 440 was associated with emissions from the three regions. We found that the southeastward moving 441 cyclones that bring northwest winds to Beijing are the key meteorological mechanism 442 responsible for dispersion of pollution over Beijing in summer. 443 The overall fluxes of CO to the NW Pacific from Asia are found to decrease by a factor of 444 3-4 from spring to summer, consistent with the seasonality suggested by other studies (Liu et al., 445 2004 spring, increasing to 70-80% in summer. We found that the major export pathway for Asian CO is 450 in the EW direction in both spring and summer. Compared with springtime, summertime outflow 451 from all the tagged Chinese source regions is strongest at higher latitudes (north of 35°N). This 452 suggests that in summer, CO emitted from the surface is transported first northward by maritime 453 inflow associated with the summer monsoon before being lifted to the free troposphere by deep 454 convections and carried eastward by the strong westerlies. The export efficiency of CO is greater 455 in summer than in spring. The deeper convection in summer bringing CO to higher altitudes with 456 more efficient export is the important factor for higher export efficiency in summer. The analysis 457 suggests that despite the maritime inflow at lower latitudes in summer, summertime outflow of 458 CO from East Asia, which takes the pathway more north and toward higher altitudes, is important 459 for the global atmosphere. 460