• Draxler, R. R., and G. D. Hess, 2004: Description of the HYSPLIT_4 modeling system. NOAA Tech. Memo. ERL ARL-224, 28 pp. [Available online at http://www.arl.noaa.gov/documents/reports/arl-224.pdf].

    • Search Google Scholar
    • Export Citation
  • Fernald, F. G., 1984: Analysis of atmospheric lidar observations: Some comments. Appl. Opt., 23 , 652653.

  • Hagler, G. S., and Coauthors, 2006: Source areas and chemical composition of fine particulate matter in the Pearl River Delta region of China. Atmos. Environ., 40 , 38023815.

    • Search Google Scholar
    • Export Citation
  • Hess, M., P. Koepke, and I. Schult, 1998: Optical properties of aerosols and clouds: The software package OPAC. Bull. Amer. Meteor. Soc., 79 , 831844.

    • Search Google Scholar
    • Export Citation
  • Hua, W., and Coauthors, 2008: Atmospheric hydrogen peroxide and organic hydroperoxides during PRIDE-PRD’06, China: Their concentration, formation mechanism and contribution to secondary aerosols. Atmos. Chem. Phys. Discuss., 8 , 1048110530.

    • Search Google Scholar
    • Export Citation
  • Nishizawa, T., H. Okamoto, N. Sugimoto, I. Matsui, and A. Shimizu, 2007: An algorithm that retrieves aerosol properties from dual-wavelength polarization lidar measurements. J. Geophys. Res., 112 , D06212. doi:10.1029/2006JD007435.

    • Search Google Scholar
    • Export Citation
  • Nishizawa, T., H. Okamoto, T. Takemura, N. Sugimoto, I. Matsui, and A. Shimizu, 2008: Aerosol retrieval from two-wavelength backscatter and one-wavelength polarization lidar measurement taken during the MR01K02 cruise of the R/V Mirai and evaluation of a global aerosol transport model. J. Geophys. Res., 113 , D21201. doi:10.1029/2007JD009640.

    • Search Google Scholar
    • Export Citation
  • Sasano, Y., A. Shigematu, H. Shimizu, N. Takeuchi, and M. Okuda, 1982: On the relationship between the aerosol layer height and the mixed layer height determined by laser radar observations. J. Meteor. Soc. Japan, 60 , 889895.

    • Search Google Scholar
    • Export Citation
  • Shao, M., X. Tang, Y. Zhang, and W. Li, 2006: City clusters in China: Air and surface water pollution. Front. Ecol. Environ., 4 , 353361.

    • Search Google Scholar
    • Export Citation
  • Shimizu, A., and Coauthors, 2004: Continuous observations of Asian dust and other aerosols by polarization lidars in China and Japan during ACE-Asia. J. Geophys. Res., 109 , D19S17. doi:10.1029/2002JD003253.

    • Search Google Scholar
    • Export Citation
  • Smirnov, A., B. N. Holben, Y. J. Kaufman, O. Dubovik, T. F. Eck, I. Slutsker, C. Pietras, and R. N. Halthore, 2002: Optical properties of atmospheric aerosol in maritime environments. J. Atmos. Sci., 59 , 501523.

    • Search Google Scholar
    • Export Citation
  • Sugimoto, N., I. Matsui, A. Shimizu, I. Uno, K. Asai, T. Endoh, and T. Nakajima, 2002: Observation of dust and anthropogenic aerosol plumes in the northwest Pacific with a two-wavelength polarization lidar on board the research vessel Mirai. Geophys. Res. Lett., 29 , 1901. doi:10.1029/2002GL015112.

    • Search Google Scholar
    • Export Citation
  • Sugimoto, N., and Coauthors, 2006: Network observations of Asian dust and air pollution aerosols using two-wavelength polarization lidars. Proc. 23rd Int. Laser Radar Conf., Nara, Japan, Int. Assoc. Meteor. Atmos. Physics, 851–854. [Available online at http://www.gi.alaska.edu/ftp/foch/ILRC23_Proc/ILRC23/6P-1.pdf].

    • Search Google Scholar
    • Export Citation
  • Uno, I., and Coauthors, 2003: Regional chemical weather forecasting system CFORS; Model descriptions and analysis of surface observations at Japanese island stations during the ACE-Asia experiment. J. Geophys. Res., 108 , 8668. doi:10.1029/2002JD002845.

    • Search Google Scholar
    • Export Citation
  • Winker, D. M., W. H. Hunt, and M. J. McGill, 2007: Initial performance assessment of CALIOP. Geophys. Res. Lett., 34 , L19803. doi:10.1029/2007GL030135.

    • Search Google Scholar
    • Export Citation
  • Zhang, J., T. Wang, W. L. Chameides, C. Cardelino, J. Kwok, D. R. Blake, A. Ding, and K. L. So, 2007: Ozone production and hydrocarbon reactivity in Hong Kong, southern China. Atmos. Chem. Phys., 7 , 557573.

    • Search Google Scholar
    • Export Citation
  • Zhang, Y. H., M. Hu, L. J. Zhong, A. Wiedensohler, S. C. Liu, M. O. Andreae, W. Wang, and S. J. Fan, 2008: Regional integrated experiments on air quality over Pearl River Delta 2004 (PRIDE-PRD2004): Overview. Atmos. Environ., 42 , 61576173.

    • Search Google Scholar
    • Export Citation
  • View in gallery

    Time–height indications of (top) the ATBC at 532 nm and (bottom) the total depolarization ratio at 532 nm observed with the lidar at the Guangdong Environmental Protection Bureau (Guangzhou urban site) in July 2006.

  • View in gallery

    Extinction coefficients for (top) total aerosols, (middle) water-soluble aerosols, and (bottom) sea salt derived with the two-wavelength algorithm. Circles indicate layers of elevated aerosols.

  • View in gallery

    Surface meteorological parameters at the Guangzhou urban site for July 2006.

  • View in gallery

    PBL height, cloud-base height, and total aerosol optical depth from 120 m to the height indicated in the ordinate for (top) the whole period and (middle) 20–23 Jul. (bottom) As in the middle panel, but with extinction coefficient plotted instead of optical depth. The daytime is indicated in the middle and bottom panels with horizontal red lines. A layer of elevated aerosols and a sudden increase of the aerosol extinction coefficient in the PBL are indicated with a circle and an arrow, respectively, in the bottom panel.

  • View in gallery

    Temporal variation of (top) elemental carbon and (bottom) relative humidity observed at the Guangzhou urban site from 20 to 23 Jul 2006.

  • View in gallery

    Extinction coefficient at 532 nm derived from CALIPSO level-1B data for 0211 LT 23 Jul 2006.

  • View in gallery

    (left) Back trajectories calculated with the NOAA HYSPLIT model ending at 1000 m above ground level at 0400, 1000, 1600, and 2200 UTC 22 Jul and 0400, 1000, and 1600 UTC 23 Jul. (middle) As in left panel, but ending at 500 m above ground level. (right) The trajectories ending at 500 m above ground level at 1600 UTC 20 Jul, 0400 and 1600 UTC 21 Jul, 0400 and 1600 UTC 22 Jul, 0400 and 1600 UTC 23 Jul, 0400 and 1600 UTC 24 Jul, 0400 and 1600 UTC 25 Jul, and 0400 UTC 26 Jul.

  • View in gallery

    (left) Map of cities where APIs are reported from MEP, and (right) the API of 10 cities during the PRD campaign.

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Continuous Observations of Aerosol Profiles with a Two-Wavelength Mie-Scattering Lidar in Guangzhou in PRD2006

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  • * National Institute for Environmental Studies, Tsukuba, Japan
  • | + College of Environmental Sciences and Engineering, Peking University, Beijing, China
  • | # Advanced Environmental Monitoring Research Center, Department of Environmental Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, South Korea
  • | @ Guangdong Provincial Environmental Monitoring Center, Guangdong, China
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Abstract

Continuous lidar observation was performed in Guangzhou, China, in the Pearl River Delta (PRD) observation campaign in July 2006 (PRD2006), using a two-wavelength Mie-scattering lidar (532 and 1064 nm) with a depolarization measurement channel at 532 nm. The profiles of the extinction coefficients at 532 nm were derived using the two-wavelength method. The planetary boundary layer (PBL) height and the cloud-base height were derived from the signals at 1064 nm. Two air pollution episodes occurred during the campaign, one on 10–12 July and the other on 22–24 July. Two events with a typhoon-driven flow of northern air occurred on 15 and 25 July. Elevated aerosol layers were observed at 1 km above ground level on 12 July and on 22 and 23 July. This layer was also observed by the lidar aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) at 0200 LT 23 July 2006 near Guangzhou. The distribution observed by CALIPSO and trajectory analysis revealed that the layer was probably generated within the PRD region. The time–height indication of the ground-based lidar suggested that aerosols in the elevated layer were transported to the ground by convection when the PBL height reached the elevated layer. The surface concentration of elemental carbon also exhibited a corresponding increase. The air pollution index at Guangzhou, Shaoguan, Changsha, and other cities indicated temporal variations, implying the regional transport of air pollution in the typhoon episodes. Trajectory analysis indicated that an air mass from the north arrived after 24 July in the air pollution episode of 22–25 July 2006.

Corresponding author address: Tomoaki Nishizawa, Atmospheric Environment Division, National Institute for Environmental Studies, Tsukuba, Ibaraki 305-0052, Japan. Email: nisizawa@nies.go.jp

Abstract

Continuous lidar observation was performed in Guangzhou, China, in the Pearl River Delta (PRD) observation campaign in July 2006 (PRD2006), using a two-wavelength Mie-scattering lidar (532 and 1064 nm) with a depolarization measurement channel at 532 nm. The profiles of the extinction coefficients at 532 nm were derived using the two-wavelength method. The planetary boundary layer (PBL) height and the cloud-base height were derived from the signals at 1064 nm. Two air pollution episodes occurred during the campaign, one on 10–12 July and the other on 22–24 July. Two events with a typhoon-driven flow of northern air occurred on 15 and 25 July. Elevated aerosol layers were observed at 1 km above ground level on 12 July and on 22 and 23 July. This layer was also observed by the lidar aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) at 0200 LT 23 July 2006 near Guangzhou. The distribution observed by CALIPSO and trajectory analysis revealed that the layer was probably generated within the PRD region. The time–height indication of the ground-based lidar suggested that aerosols in the elevated layer were transported to the ground by convection when the PBL height reached the elevated layer. The surface concentration of elemental carbon also exhibited a corresponding increase. The air pollution index at Guangzhou, Shaoguan, Changsha, and other cities indicated temporal variations, implying the regional transport of air pollution in the typhoon episodes. Trajectory analysis indicated that an air mass from the north arrived after 24 July in the air pollution episode of 22–25 July 2006.

Corresponding author address: Tomoaki Nishizawa, Atmospheric Environment Division, National Institute for Environmental Studies, Tsukuba, Ibaraki 305-0052, Japan. Email: nisizawa@nies.go.jp

1. Introduction

The Pearl River Delta (PRD) area is a megacity area in China that has heavy air pollution (e.g., Hagler et al. 2006; Shao et al. 2006; Zhang et al. 2007). Comprehensive observational experiments were conducted in the PRD in October of 2004 (Zhang et al. 2008) and July of 2006 (PRD2006; e.g., see Hua et al. 2008). We conducted continuous observation with a two-wavelength (1064 and 532 nm) polarization (532 nm) lidar in the PRD campaign in July of 2006. In this paper, we discuss air pollution phenomena during the campaign using the lidar data, surface meteorological data, data of the spaceborne Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO; Winker et al. 2007), the air pollution index (API) for Guangzhou, China, and surrounding cities, and back trajectories calculated with the National Oceanic and Atmospheric Administration (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Model (see online at http://www.arl.noaa.gov/HYSPLIT.php; Draxler and Hess 2004).

2. Observations and data analysis methods

The lidar was installed on the top of the Guangdong Environmental Protection Bureau building (23.134°N, 113.264°E, 50 m above sea level). The lidar instrument is similar to that reported in our previous papers (Sugimoto et al. 2002, 2006). It has three channels and measures the backscattering at 1064 and 532 nm and the depolarization at 532 nm. The depolarization ratio, which is a parameter sensitive to nonsphericity of the scatterers, is useful in identifying mineral dust aerosols and in discriminating between water and ice clouds.

The lidar was operated continuously from 1 July to 6 August. The lidar profiles averaged for 5 min were recorded every 15 min; thus, 96 profiles were recorded per day. The height resolution was 6 m, and the profiles were recorded up to 24-km height. The surface meteorological parameters were observed at the same location by Sun Yet-sen University.

The lidar data were analyzed to derive extinction coefficient profiles using both Fernald’s method (Fernald 1984) assuming the lidar ratio value (Shimizu et al. 2004) and the two-wavelength methods assuming the optical characteristics for water solubles, sea salt, and mineral dust (Nishizawa et al. 2007). Details about the two-wavelength methods are presented in the appendix. The results of the two methods were consistent. The difference was less than 10% and was explained by the difference in the lidar ratio values used in Fernald’s method and the aerosol models used in the two-wavelength method.

The planetary boundary layer (PBL) height and the cloud-base height were derived from the 1064-nm signals. We used the gradient of the attenuated backscattering coefficient (ATBC) to detect the top of the PBL. Because the density of aerosols is high in the PBL, the gradient of the backscattering signal decreases rapidly at the top of the PBL (Sasano et al. 1982). We defined the PBL height as the height at which the gradient of the ATBC at 1064 nm has a minimum. However, the backscattering signal increases rapidly at the cloud base because the scattering of clouds is much larger than that of aerosols. We defined cloud-base height as the height at which the increase of the ATBC exceeds 4 × 10−8 m−1 sr−1 per 1 m and the value of the ATBC exceeds 5 × 10−6 m−1 sr−1.

The Chemical Weather Forecasting System (CFORS) model (Uno et al. 2003) was operated at the National Institute for Environmental Studies in the forecast mode, using numerical weather forecast data from the Japan Meteorological Agency as the boundary data.

The extinction coefficient was derived from CALIPSO level-1 data using the forward Fernald’s method with the assumption of different lidar ratios for clouds and aerosols. The API data were taken from the Ministry of Environmental Protection (MEP) of the People’s Republic of China Web site (http://datacenter.mep.gov.cn/). We also used the NOAA HYSPLIT model to calculate back trajectories.

3. Results and discussion

Time–height indications of the ATBC and the total depolarization ratio are presented in Fig. 1. The two rainy periods (15–16 and 27–28 July 2006) were associated with the typhoons that passed over Taiwan. The depolarization ratio was low throughout the observation period. Air pollution events are clearly seen in the extinction coefficient plot in Fig. 2, and the total aerosol extinction coefficient and the extinction coefficients for water-soluble aerosols and sea salt are indicated. We used the two-wavelength method here (Nishizawa et al. 2007). We did not use data before 7 July because of a problem with the 1064-nm detector. The two-wavelength algorithm considers two aerosol models: the mixture of water solubles and sea salt, and the mixture of water solubles and dust. These two models are switched, depending on the total depolarization ratio values. In this study, the depolarization ratio was low throughout the observation period, and no dust was detected. Aerosols were classified mostly as water soluble (Fig. 2). Two air pollution episodes occurred, one on 12 July 2006 and the other on 22–24 July 2006. The surface meteorological parameters (Fig. 3) indicate that the variation was very symmetrical for the two typhoon events. The wind direction changed to the northwest on 13 July for the first typhoon and on 24 July for the second one. The wind direction changed again to the southeast on 17 and 27 July, and then rain started. The air pollution periods corresponded to the weak southeasterly period before the start of the relatively strong northwesterly period associated with the typhoons.

Layers of elevated aerosols were observed at 1-km height on 12 July and on 22–23 July (denoted by a circle in Fig. 2). Relative humidity is generally higher near the top of the PBL because of adiabatic cooling by convection, and the aerosol extinction coefficient is generally high because of the hygroscopic growth of aerosols. However, the increase of the extinction coefficient was very large on 22 and 23 July, as compared with that on 20 July. In addition, distinct differences in vertical structure of the extinction coefficient were observed: the extinction coefficient was high near the PBL top on 20 July but high throughout the whole PBL on 22 and 23 July. Therefore, it is reasonable to assume that the layers of elevated aerosols mixed into the PBL. To demonstrate the details of the PBL structure and aerosol distribution, Fig. 4 presents the PBL height, cloud-base height, and aerosol optical depth (AOD) above 120 m. The period from 20 to 23 July is expanded in the middle and bottom panels. The extinction coefficient is plotted instead of AOD in the bottom panel. On 20 July, the height with a certain AOD value (e.g., 0.3) increased as the PBL height increased, indicating that the aerosols in the PBL were diluted. However, on 22 and 23 July, a constant AOD height started decreasing at about 0900–1000 LT, and a corresponding aerosol layer appeared in the extinction coefficient plot. This result suggests an elevated aerosol layer in the nighttime; the layer was taken into the PBL when the PBL height reached the aerosol layer. The mornings of 22 and 23 July were cloudy, and the aerosol layers above the clouds were not seen clearly. However, a layer of elevated aerosols was observed (bottom panel of Fig. 4) at 1-km height from 2100 LT 22 July to 0300 LT 23 July (denoted by a circle in the figure). Also, a sudden increase of the aerosol extinction coefficient in the PBL was observed at 1000 LT 23 July (denoted by an arrow in the figure). A similar pattern was observed on 22 July, but the aerosol layer was not clear because of the clouds.

Figure 5 plots the concentration of elemental carbon and relative humidity measured on the surface at the Guangzhou urban site (Verma et al. 2009, manuscript submitted to J. Geophys. Res.). The concentration of elemental carbon decreased in the daytime, corresponding to the increase of the PBL height on 20 July 2006. An increase of concentration was observed at 1000 LT 23 July, corresponding to the aerosol structure in Fig. 4. The relative humidity was high in the nighttime and low in the daytime, indicating no correlation with the increase of elemental carbon. The existence of aerosol layers above the boundary layer in the morning may provide an explanation for the increase of elemental carbon.

We used the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on CALIPSO for data to confirm the existence of aerosol layers. A satellite path over the PRD region at 1820 UTC 22 July (0220 LT 23 July) fortunately passed approximately 70 km east of Guangzhou. We derived the extinction coefficient at 532 nm from the CALIPSO level-1B (version 2.01) data, using the forward Fernald’s method with a variable lidar ratio. We set the boundary condition at an altitude of 20 km and used different lidar ratios for clouds (S1 = 20 sr) and aerosols (S1 = 50 sr). In this case, clouds existed only above 8 km, and therefore we switched the lidar ratio at 8 km (Fig. 6). Because of clouds at 16-km height, data were missing at latitudes from 25.4° to 27.2°.

The elevated aerosol layer was observed at 1-km height at a latitude of 23° (Fig. 6). An elevated aerosol layer was evident above the PRD region at 0220 LT 23 July, and it is probable that the layer observed by the ground-based lidar was a part of this layer.

Figure 7 depicts the back trajectories calculated with the NOAA HYSPLIT model starting from heights of 1000 and 500 m at the Guangzhou urban site. The duration of the trajectories was 48 h. The results indicate that a 48-h back trajectory from 1200 LT 22 July to 0000 LT 24 July stayed mostly within 200 km of Guangzhou. The trajectories and the aerosol distribution pattern observed by CALIPSO (Fig. 6) suggest that the elevated layer was generated in the PRD area and was not transported from long range.

The back trajectories starting after 1200 LT 25 July 2006 (right panel of Fig. 7) indicate that the air mass came from the north. Of interest is that the trajectories exhibited loops from 0000 LT 24 July to 0000 LT 25 July. The change in the direction of the airmass flow is consistent with the surface wind data presented in Fig. 3.

The regional feature of the distribution of air pollution can be seen in the plot of API of Guangzhou and surrounding cities. Figure 8 depicts the API of 10 cities during the PRD campaign, as well as a map indicating the locations of the cities. The API is separately defined for daily averaged particles with diameter of <10 μm (PM10), sulfur dioxide, and nitrogen dioxide concentrations, and the largest value is reported as the API with the name of the dominant pollutant, which is PM10 in most cases. The conversion from PM10 to API is not linear: PM10 of 0.05, 0.15, 0.35, 0.42, 0.5, and 0.6 (mg m−3) corresponds to API = 50, 100, 200, 300, 400, and 500, respectively. A detailed description can be found on the MEP Web site.

Figure 8 presents the correlation and time lag between the temporal variations of API of different cities. For the peak of API on 25 July 2006, preceding peaks were apparent in Shaoguan and Changsha, China, and other cities. This result is consistent with the trajectory analysis. However, a correlation between temporal variations does not necessarily mean that pollutants are actually transported. It is also possible that only meteorological situations are correlated and that pollutants are from local sources. Analysis with a high-resolution regional chemical transport model with a detailed emission inventory will be necessary to quantitatively evaluate the actual flow of air pollutants.

4. Conclusions

We used continuous lidar observation data to analyze the general situation regarding air pollution during the PRD2006 campaign (July 2006). We observed both the regional features associated with typhoons (on 10–12 and 22–24 July 2006) and the accumulation of air pollution within the PRD area (on 22–23 July 2006).

An elevated aerosol layer remaining above the boundary layer was observed at 1-km height with both the ground-based lidar and the spaceborne lidar CALIPSO in the early morning of 23 July 2006. The aerosol extinction coefficient in the PBL observed with the ground-based lidar indicated a sudden increase at 1000 LT 23 July 2006. This result suggests that aerosols (and pollutants) uplifting and staying during the nighttime are taken into the PBL again the next day as the boundary layer grows. The surface measurement of elemental carbon concentration revealed a corresponding increase on the morning of 23 July. Concentrations of organic carbon and sulfate indicated an even larger increase at the same timing, but we did not analyze their diurnal variation in this study, because it is much more complicated to understand the temporal variations of secondary aerosols. This work suggests that air pollution was accumulated three dimensionally and that the structure of the aerosol layer is important to the understanding of the diurnal variation of pollutants.

Acknowledgments

This work was partly supported by the China National Basic Research and Development Program (2002CB410801). The CALIPSO data were obtained from the National Aeronautics and Space Administration Langley Research Center Atmospheric Sciences Data Center.

REFERENCES

  • Draxler, R. R., and G. D. Hess, 2004: Description of the HYSPLIT_4 modeling system. NOAA Tech. Memo. ERL ARL-224, 28 pp. [Available online at http://www.arl.noaa.gov/documents/reports/arl-224.pdf].

    • Search Google Scholar
    • Export Citation
  • Fernald, F. G., 1984: Analysis of atmospheric lidar observations: Some comments. Appl. Opt., 23 , 652653.

  • Hagler, G. S., and Coauthors, 2006: Source areas and chemical composition of fine particulate matter in the Pearl River Delta region of China. Atmos. Environ., 40 , 38023815.

    • Search Google Scholar
    • Export Citation
  • Hess, M., P. Koepke, and I. Schult, 1998: Optical properties of aerosols and clouds: The software package OPAC. Bull. Amer. Meteor. Soc., 79 , 831844.

    • Search Google Scholar
    • Export Citation
  • Hua, W., and Coauthors, 2008: Atmospheric hydrogen peroxide and organic hydroperoxides during PRIDE-PRD’06, China: Their concentration, formation mechanism and contribution to secondary aerosols. Atmos. Chem. Phys. Discuss., 8 , 1048110530.

    • Search Google Scholar
    • Export Citation
  • Nishizawa, T., H. Okamoto, N. Sugimoto, I. Matsui, and A. Shimizu, 2007: An algorithm that retrieves aerosol properties from dual-wavelength polarization lidar measurements. J. Geophys. Res., 112 , D06212. doi:10.1029/2006JD007435.

    • Search Google Scholar
    • Export Citation
  • Nishizawa, T., H. Okamoto, T. Takemura, N. Sugimoto, I. Matsui, and A. Shimizu, 2008: Aerosol retrieval from two-wavelength backscatter and one-wavelength polarization lidar measurement taken during the MR01K02 cruise of the R/V Mirai and evaluation of a global aerosol transport model. J. Geophys. Res., 113 , D21201. doi:10.1029/2007JD009640.

    • Search Google Scholar
    • Export Citation
  • Sasano, Y., A. Shigematu, H. Shimizu, N. Takeuchi, and M. Okuda, 1982: On the relationship between the aerosol layer height and the mixed layer height determined by laser radar observations. J. Meteor. Soc. Japan, 60 , 889895.

    • Search Google Scholar
    • Export Citation
  • Shao, M., X. Tang, Y. Zhang, and W. Li, 2006: City clusters in China: Air and surface water pollution. Front. Ecol. Environ., 4 , 353361.

    • Search Google Scholar
    • Export Citation
  • Shimizu, A., and Coauthors, 2004: Continuous observations of Asian dust and other aerosols by polarization lidars in China and Japan during ACE-Asia. J. Geophys. Res., 109 , D19S17. doi:10.1029/2002JD003253.

    • Search Google Scholar
    • Export Citation
  • Smirnov, A., B. N. Holben, Y. J. Kaufman, O. Dubovik, T. F. Eck, I. Slutsker, C. Pietras, and R. N. Halthore, 2002: Optical properties of atmospheric aerosol in maritime environments. J. Atmos. Sci., 59 , 501523.

    • Search Google Scholar
    • Export Citation
  • Sugimoto, N., I. Matsui, A. Shimizu, I. Uno, K. Asai, T. Endoh, and T. Nakajima, 2002: Observation of dust and anthropogenic aerosol plumes in the northwest Pacific with a two-wavelength polarization lidar on board the research vessel Mirai. Geophys. Res. Lett., 29 , 1901. doi:10.1029/2002GL015112.

    • Search Google Scholar
    • Export Citation
  • Sugimoto, N., and Coauthors, 2006: Network observations of Asian dust and air pollution aerosols using two-wavelength polarization lidars. Proc. 23rd Int. Laser Radar Conf., Nara, Japan, Int. Assoc. Meteor. Atmos. Physics, 851–854. [Available online at http://www.gi.alaska.edu/ftp/foch/ILRC23_Proc/ILRC23/6P-1.pdf].

    • Search Google Scholar
    • Export Citation
  • Uno, I., and Coauthors, 2003: Regional chemical weather forecasting system CFORS; Model descriptions and analysis of surface observations at Japanese island stations during the ACE-Asia experiment. J. Geophys. Res., 108 , 8668. doi:10.1029/2002JD002845.

    • Search Google Scholar
    • Export Citation
  • Winker, D. M., W. H. Hunt, and M. J. McGill, 2007: Initial performance assessment of CALIOP. Geophys. Res. Lett., 34 , L19803. doi:10.1029/2007GL030135.

    • Search Google Scholar
    • Export Citation
  • Zhang, J., T. Wang, W. L. Chameides, C. Cardelino, J. Kwok, D. R. Blake, A. Ding, and K. L. So, 2007: Ozone production and hydrocarbon reactivity in Hong Kong, southern China. Atmos. Chem. Phys., 7 , 557573.

    • Search Google Scholar
    • Export Citation
  • Zhang, Y. H., M. Hu, L. J. Zhong, A. Wiedensohler, S. C. Liu, M. O. Andreae, W. Wang, and S. J. Fan, 2008: Regional integrated experiments on air quality over Pearl River Delta 2004 (PRIDE-PRD2004): Overview. Atmos. Environ., 42 , 61576173.

    • Search Google Scholar
    • Export Citation

APPENDIX

Two-Wavelength Methods

The forward and backward algorithms (Nishizawa et al. 2007) were used. Three assumptions are made in these algorithms. First, the volume-size distribution of aerosols is bimodal with peaks of lognormal shape. Second, two types of aerosol models are assumed: sea salt and dust models. The sea salt (dust) model consists of water-soluble (water soluble) components in the accumulation-mode region and a sea salt (dust) component with mode radii in the coarse-mode region. Third, the shape of each of the aerosol components is spherical; their mode radii, standard deviations, and refractive indexes are prescribed based on Smirnov et al. (2002) and Hess et al. (1998). The forward (backward) algorithm retrieves extinction coefficients for each aerosol component at each layer starting from the lowest (highest) layer and ending at the highest (lowest) layer. At each layer, the algorithms retrieve the extinction coefficients for the two aerosol components in each aerosol model that best reproduce βobs at the two wavelengths and select one of the two aerosol models using the measured total depolarization ratio. The backward algorithm is used for lidar data under clear-sky conditions, and the forward algorithm is used for lidar data under cloudy conditions.

The relative errors in extinction for water-soluble, sea salt, and dust particles are smaller than 20% for the backward algorithm, and 50%, 30%, and 10% for the forward one when the measurement uncertainty is ±5%. The errors for both the algorithms increase linearly as the measurement uncertainty increases. The potential uncertainties regarding the algorithm assumptions (e.g., variability of size distributions and refractive indexes for water-soluble particles, sea salt, and dust, and nonsphericity of dust) are about 50% in extinction for each aerosol component (Nishizawa et al. 2007, 2008).

Fig. 1.
Fig. 1.

Time–height indications of (top) the ATBC at 532 nm and (bottom) the total depolarization ratio at 532 nm observed with the lidar at the Guangdong Environmental Protection Bureau (Guangzhou urban site) in July 2006.

Citation: Journal of Applied Meteorology and Climatology 48, 9; 10.1175/2009JAMC2089.1

Fig. 2.
Fig. 2.

Extinction coefficients for (top) total aerosols, (middle) water-soluble aerosols, and (bottom) sea salt derived with the two-wavelength algorithm. Circles indicate layers of elevated aerosols.

Citation: Journal of Applied Meteorology and Climatology 48, 9; 10.1175/2009JAMC2089.1

Fig. 3.
Fig. 3.

Surface meteorological parameters at the Guangzhou urban site for July 2006.

Citation: Journal of Applied Meteorology and Climatology 48, 9; 10.1175/2009JAMC2089.1

Fig. 4.
Fig. 4.

PBL height, cloud-base height, and total aerosol optical depth from 120 m to the height indicated in the ordinate for (top) the whole period and (middle) 20–23 Jul. (bottom) As in the middle panel, but with extinction coefficient plotted instead of optical depth. The daytime is indicated in the middle and bottom panels with horizontal red lines. A layer of elevated aerosols and a sudden increase of the aerosol extinction coefficient in the PBL are indicated with a circle and an arrow, respectively, in the bottom panel.

Citation: Journal of Applied Meteorology and Climatology 48, 9; 10.1175/2009JAMC2089.1

Fig. 5.
Fig. 5.

Temporal variation of (top) elemental carbon and (bottom) relative humidity observed at the Guangzhou urban site from 20 to 23 Jul 2006.

Citation: Journal of Applied Meteorology and Climatology 48, 9; 10.1175/2009JAMC2089.1

Fig. 6.
Fig. 6.

Extinction coefficient at 532 nm derived from CALIPSO level-1B data for 0211 LT 23 Jul 2006.

Citation: Journal of Applied Meteorology and Climatology 48, 9; 10.1175/2009JAMC2089.1

Fig. 7.
Fig. 7.

(left) Back trajectories calculated with the NOAA HYSPLIT model ending at 1000 m above ground level at 0400, 1000, 1600, and 2200 UTC 22 Jul and 0400, 1000, and 1600 UTC 23 Jul. (middle) As in left panel, but ending at 500 m above ground level. (right) The trajectories ending at 500 m above ground level at 1600 UTC 20 Jul, 0400 and 1600 UTC 21 Jul, 0400 and 1600 UTC 22 Jul, 0400 and 1600 UTC 23 Jul, 0400 and 1600 UTC 24 Jul, 0400 and 1600 UTC 25 Jul, and 0400 UTC 26 Jul.

Citation: Journal of Applied Meteorology and Climatology 48, 9; 10.1175/2009JAMC2089.1

Fig. 8.
Fig. 8.

(left) Map of cities where APIs are reported from MEP, and (right) the API of 10 cities during the PRD campaign.

Citation: Journal of Applied Meteorology and Climatology 48, 9; 10.1175/2009JAMC2089.1

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