Scattering properties of the atmospheric aerosol in Beijing, China

Atmospheric Research 101 (2011) 799–808

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Atmospheric Research j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / a t m o s

Scattering properties of the atmospheric aerosol in Beijing, China Xiujuan Zhao ⁎, Xiaoling Zhang, Weiwei Pu, Wei Meng, Xiaofeng Xu Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing 100089, China

a r t i c l e

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Article history: Received 28 July 2010 Received in revised form 20 May 2011 Accepted 20 May 2011 Keywords: Aerosol scattering coefficient Seasonal and diurnal variation Mass scattering efficiency Fog and haze

a b s t r a c t Measurements of aerosol scattering coefficient (σsp) and PM2.5 concentration obtained during June 2008 to May 2009 at urban, suburban, and rural sites in Beijing area. The mean value of σsp during measurement period was 301 ± 307, 263 ± 263, 182 ± 201 Mm − 1 at Baolian (BL: urban site), Changping (CP: suburban site) and Shangdianzi (SDZ: rural site), respectively. The seasonal and diurnal patterns of σsp were analyzed with the measurement data. The σsp showed different seasonal and diurnal patterns at these three sites. The seasonal fluctuations inσsp in urban area were mostly influenced by seasonal variability in both emissions and meteorological conditions, while the seasonal wind patterns seemed to dominate the σsp in the suburban and rural areas. The diurnal activity of σsp generally showed a bimodal, trimodal and a unimodal pattern at BL, CP and SDZ sites, respectively. The diurnal variation of boundary layer height companying with source activity was mainly dominated the diurnal variation of σsp at urban and suburban sites. The mountain-valley breeze and boundary layer growth in SDZ region mostly dominated the diurnal variation of σsp. The mass scattering efficiency of PM2.5 was estimated at BL and SDZ, which showed a decreasing trend from urban to rural site with different seasonal variation at two sites. During fog and haze episodes, the lower northeasterly winds could result in significant spatial difference in σsp, while the σsp was spatially uniform under the influence of stronger southerly winds. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Atmospheric aerosols influence the earth's radiation balance directly through scattering and absorption of incoming solar radiation and outgoing terrestrial radiation (Charlson et al., 1992). The perturbation of the earth's radiative balance resulting from the scattering and absorption caused by anthropogenic aerosols has been termed direct aerosol radiative forcing and has been estimated globally to be similar in magnitude but opposite in sign to global greenhouse gas forcing (Houghton et al., 1996). However, the distribution of aerosols is quite patchy and depends on the presence of aerosol sources (Vrekoussis et al., 2005). From the model results, there are 34% of PM2.5 in Beijing urban have regional sources (Streets et al., 2007). Due to spatial and temporal differences in aerosol ⁎ Corresponding author. E-mail address: [email protected] (X. Zhao). 0169-8095/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.atmosres.2011.05.010

properties, it is necessary to measure aerosol properties in different scale to determine aerosol radiative forcing. Beijing, one of the largest cities in the world, is a metropolis with a population of over 14 million people in northern China. Beijing is situated at the northern tip of the roughly triangular North China Plain, which opens to the south and east of the city. The city is shielded by mountains to the north, northwest and west with elevations between 1000 and 3500 m a.s.l. and has heavily industrialized areas from the southwest to east (Streets et al., 2007). With the rapid economic development, population expansion and urbanization over the past 30 years, Beijing has been experiencing severe air pollution problem, especially aerosol pollution. PM10 is reported to be the major air pollutant and the PM2.5 is also high in Beijing's urban atmosphere (Zhao et al., 2007; Chan and Yao, 2008). The decrease of visibility is one of the most notable effects of aerosol. The visibilities showed significant decreasing trends during 1973–2007 in Beijing,

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especially since the middle of 1990s (Chang et al., 2009). Results from the previous studies indicate that aerosol scattering coefficient (σsp) is about 5–10 times higher than aerosol absorption coefficients in Beijing (Bergin et al., 2001; Yan et al., 2008; Garland et al., 2009; He et al., 2009). The σsp plays an important role in the visibility reduction in Beijing area. The measurement results in June 1999 in Beijing indicated that the submicron aerosol was responsible for about 80% of the light scattering at 532 nm (Bergin et al., 2001). The seasonal and diurnal variation of σsp has been investigated in different sites. The σsp in summer was higher than that in winter, showed peaks in the late morning and minimum in the evening at a urban site (He et al., 2009). At a rural site, low values of σsp in winter and highest in fall, with peak during the night and minimum in early afternoon (Yan et al., 2008). Garland et al. (2009) conducted measurements of aerosol optical properties at a suburban site ~30 km south of Beijing during 11 August to 9 September 2006 and found that the σsp was generally higher when the air mass come from south of Beijing than that originated in the north. Many observation studies have been carried out based on measurement at one single site, but simultaneous measurement of aerosol optical properties at different sites in Beijing were rarely reported. In this work, 1-year in site measurements of σsp and PM2.5 concentration were carried out at three sites in Beijing urban, suburban and rural area, respectively. The comparison of seasonal and diurnal variation of scattering coefficients between three sites is reported. The influence of meteorological conditions especially the wind direction on the behavior of σsp is investigated. The seasonal variation of mass scattering efficiency (αsp) of PM2.5 and the influence of wind pattern to spatial distribution of σsp during haze episodes are analyzed. This work expands the study we made in 2009, in which we provided a detailed discussion of the meteorological influences on the concentration of PM2.5 in urban and rural areas (Zhao et al., 2009). 2. Experimental 2.1. Site descriptions The measurements presented in this study were conducted at three sites in Beijing (Fig.1). The urban station BL (39 °56′N, 116 °17′E, 75.0 m a.s.l.) is located in the Baolian Sports Park, between the third and fourth Ring Roads in the western urban area of Beijing. The regions surrounding this site are mostly residential districts without obvious point sources of aerosol particles. About 30 m west to this station, a one-way street was opened in 2007. The traffic emissions during the morning and evening rush hours have inevitable impact on the aerosol density over this region near the street. The suburban station CP (40 °13′N, 116 °13′E, 74.1 m a.s.l) is located in the Beijing Changping Meteorological Bureau, about 40 km northwest to Beijing downtown. Changping district is one of suburban districts and lies in the north part of Beijing. The CP station is located in the northwest part of Changping district and is about 500 m away from a busy highway to the west direction. The other surrounding regions are mostly residential buildings lower than 20 m. Mountains to the north, northwest and west are about 5 km away from

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Fig. 1. Image map of three measurement sites.

CP station. The local aerosol sources are mainly the heavy traffic together with the re-suspension of material available on the ground. The rural station SDZ (40 °39′N, 117 °07′E, 293.9 m a.s.l.) is one of the regional Global Atmosphere Watch (GAW) stations in China. This station is located in the northern part of the North China Plain and in the Miyun County of Beijing, about 100 km northeast of the urban area of Beijing and 55 km northeast of the Miyun Township, respectively. The major local economical activities within Miyun County are farming and fruit growing, which means that there are only minimal natural and anthropogenic pollution sources within a 30 km range surrounding the SDZ site (Yan et al., 2008). SDZ is situated on the south slope of a hill surrounded by mountains in every direction except the southwest. Due to the valley topography, the prevailing winds at SDZ are from the east–northeast and the west– southwest. Polluted air masses from urban areas and satellite towns of Beijing, and even those regions in south of Beijing at North China Plain, can therefore be easily transported to SDZ by southwesterly winds, while relatively clean air masses arrive from other wind directions (Lin et al., 2008 ; Zhao et al., 2009). 2.2. Instruments and measurements σsp and PM2.5 concentration were measured continuously from June 2008 to May 2009 at BL and SDZ. The measurement at CP began from June 2008 and stopped at the end of January 2009 due to the re-establishment of the experiment building. The observed data of σsp at BL from June to August 2008 was not used in this work due to the low quality of data. The same integrating nephelometer (Model M9003, EcoTech, Australia) was used to monitor the aerosol scattering coefficients at three sites. This instrument used LEDs as the light source at a wavelength of 525 nm. The scattering integration angle is from 10° to 170°, and no size-selective inlet was used. A background (zero) check was done automatically at midnight

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by pumping in particle-free air everyday and a weekly span check was performed manually by the operator using particle-free HFCR134a gas recommended by the manufacturer. The relative humidity (RH) in the cell of the instrument was controlled below 60% by an automatic heating inlet provided by the manufacturer to prevent liquid particles going into the optical cell. This heating inlet could cause evaporation of volatile inorganic species (such as nitrate) and volatile organic matters. The averaging time was set to 5 min, and subsequently processed to hourly means. The PM2.5 concentration was simultaneously measured by using two types of instruments R&P model 1400a and GRIMM model 180. The R&P model 1400a Tapered Element Oscillating Microbalance (TEOM) instrument with a 2.5 μm cyclone inlet, an inlet humidity control system, and a dedicated sampling line is used to obtain fine particulate mass concentrations at BL and SDZ stations. Each one is housed in an air-conditioned room and is operated at 26 °C with a hydrophobic filter material to reduce the humidity of the incoming sampled air. The sample stream is preheated to 50 °C before entering the mass transducer, and hence semivolatiles such as ammonium nitrate and water are not measured. The filter loading percentage and flow rates of TEOM are checked once a week, and the filter is replaced when the filter loading percentage is greater than 30%. At CP, a GRIMM model 180 monitor with a dehumidification system in the inlet stream (GRIMM Aerosol Technik GmbH & Co. KG, Germany) is used to measure the PM2.5 concentration. The technical performance for obtaining continuous PM size and mass data in routine sampling had been proved with observation campaigns. The PM2.5 mass concentration measured with GRIMM is generally higher than that obtained with TEOM (Grimm and Eatough, 2009). The comparison of hourly average PM2.5 concentrations simultaneously monitored by GRIMM and TEOM at SDZ in February 2010 is presented in Fig. 2. The good liner relationship can be found between GRIMM and TEOM PM2.5 concentrations. The concentrations of PM2.5 obtained with the GRIMM was slightly higher than that obtained with TEOM because of the loss of semi-volatile ammonium nitrate and organic material from the heated filter of the TEOM monitor (Grimm and Eatough,

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2009). In this work, the PM2.5 concentration was mainly used to explain the variation of σsp, thus the slight divergence between two instruments could be accepted. The PM2.5 concentrations were recorded as 5-min averages at these three sites. The meteorological data, including wind speed and direction, temperature, relative humidity, etc., are obtained at CP and SDZ meteorology station near the sample site with a resolution of 1 h. For BL station, the meteorological data are obtained at the Haidian meteorology station, approximately 4 km to the north. The Haidian station is part of the measurement network run by the Beijing Meteorology Bureau and uses standard measurement equipment and methods.

3. Results and discussion 3.1. Seasonal variability of aerosol scattering coefficient The seasonal average and annual mean values (based on hourly data) of σsp are presented in Table 1. In order to investigate the seasonal variation characteristics of σsp, the measurement data has been divided in four parts according four season in Bejing area. The summer time is the period from June to August, the autumn from September to November of 2008, the winter from December 2008 to February 2009 and the spring from March to May of 2009. The annual mean value of σsp at BL, CP and SDZ was 301 ± 287, 263 ± 264 and 182 ± 203 Mm − 1, respectively. The annual mean result at BL was similar to the value of 288 ± 282 Mm − 1 obtained in Beijing urban area in 2005–2006 (He et al., 2009). The value of 313 ± 276 Mm − 1 at CP was lower than Garland et al. (2009) result (361 ± 295 Mm − 1 at 550 nm) that was observed in the summer 2006 at a suburban site in Beijing. The summer average value and annual mean value are 206 ± 215 Mm − 1 and 182 ± 201 Mm − 1 at SDZ, respectively. These results at SDZ were similar as those Yan et al.' result (Yan et al., 2008). The summer average value and annual mean value were190 ± 167 Mm − 1 and 175 ± 189 Mm − 1 at SDZ obtained by Yan et al., respectively. (Yan et al., 2008). The decreased σsp at suburban sites in summer may be attributed to the pollution control measures in Beijing area from July to September 2008 for Olympic Game. The autumn average value 112 ± 136 Mm − 1at SDZ was two-third lower than that observed at a rural site in Yangtze Delta Region during November 1999 with the value of 353 ± 202 Mm − 1 (Xu et al., 2002). However, the annual mean value of σsp at these three sites in Beijing was about three to five times greater than the mean value 60 ± 30 Mm − 1 (550 nm) measured from December 2005 to November 2007 at Granada, an urban site in south-eastern Spain (Lyamani et al., 2010).

100 Table 1 The seasonal and annual averages ofσsp (unit: Mm− 1).

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/ 286 ± 318 325 ± 323 292 ± 277 301 ± 307

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Monthly statistical distributions of σsp based on valid hourly average data during the period of measurement were presented in Fig. 3. The statistical distributions are presented as box-whisker plots where the whiskers denote the 5 and 95 percentiles, the bottom and top of the box denote the 25 and 75 percentiles, and the horizontal line within the box denotes the 50 percentiles. The mean values ofσsp are denotes by the blank circle. The 50 percentiles (median values) are typically different from the mean values because the distributions of σsp are not normally distributed. The statistics and the median value for entire study period are presented by the last box-whisker and a horizontal line in each plot so deviations above and below the median value can be easily identified. Fig. 3a showed that the σsp was higher in late autumn and early winter, and lower in early autumn (September and October, 2008) at BL. The highest σsp in the winter was most probably due to a combination of increased emissions of

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particulate matters from heating sources and low boundary layer height (BLH) (Zhao et al., 2009; Guinot et al., 2006). The winter maximum of σsp corresponded to maximum concentration of PM2.5 with highest hour average 512 μg m − 3, which was appeared in a serious haze episode. The increased stable weather and two fog and haze episodes in December resulted in the accumulation of particulate matters (PM) that correspondingly caused the increase of σsp. The total monthly precipitation was 72.8 Mm in September 2008 that increased 60% compared with the same period of last thirty years. The frequency of northerly wind was 67% in October 2008, which was 10% higher than the annual mean value 57% and nearly 2.3 times as the frequency of southerly wind in this month. The abundant precipitation and frequent northerly winds in September and October in 2008 were beneficial for PM deposition and dispersion, which was mostly responsible for the decrease of σsp in early autumn. The values of σsp in April 2009 were higher also, which was probably attributed to the stable meteorological conditions in this month. A high pollution episode with the daily average σsp above 400 Mm − 1 sustained for 7 days in this month. The daily average value σsp was 1353 Mm − 1 at 12 April, and this value was the highest value during this measurement period. The unfavorable meteorological conditions had a regional impact and caused the higher σsp in the rural area as well (Fig 3c). Although the σsp data could not be used during summer period, it could be estimated by the measurement of PM2.5 due to the good relationship betweenσsp and PM2.5 concentration that had been proved in previous study (Chow et al., 2006). The good linear relationship betweenσsp and the PM2.5 was presented in Fig.4a with daily average data at BL from September 2008 to May 2009. Thus, it could be deduced that the σsp should be higher in summer due to the higher level of PM2.5 concentration in this season, especially in June and July 2008 (Fig. 4b). The higher σsp in summer at another urban site had been reported by He et al. (2009). The high temperature and humidity may have enhanced the photochemical transformation that favors high fine particles concentration in summer. These results indicated that seasonal fluctuations inσsp in urban areas were mostly dominated by seasonal variability in both emissions and meteorological conditions. At the suburban site CP, the higherσsp was observed in early summer (June-July 2008) and lower values in autumn and winter. At the rural site SDZ, higherσsp appeared in summer and spring, lower values in autumn and winter. Comparing to urban area, the anthropogenic emission sources is relatively weaker in suburban area, and much insignificant in rural area. The seasonal variation of σsp was mainly attributed to the variability of meteorological conditions. Analysis of wind direction data at CP and SDZ sites revealed that the prevailing winds were northerly in the autumn and winter. However, the wind flow was mainly from the south in the spring and summer. In all seasons, theσsp in the E–S–W sectors were higher than those in the W–N–E sectors. Taking SDZ site as example, the prevailing winds are northeasterly in the autumn and winter and southwesterly in the spring and summer as shown in Fig. 5a. The level of σsp in the S–W sectors was much higher than in other sectors, while those in the N–ENE sectors much lower than in other sectors (Fig. 5b). In autumn and winter, the prevailing northerly wind carried clean air to Beijing and

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diluted the pollutants in the atmosphere, which resulted in the lowerσsp in rural and suburban areas. During spring and summer, prevailing southerly winds provided regional transport of air pollutants from southern urban regions to northern rural area. Meanwhile, the increased fine particles due to photochemical transformation caused the higher level of σsp. The seasonal wind patterns, which determined the transport of pollutants, seemed to outweigh other meteorological factors in influencing σsp in the suburban and rural areas. Compared with other season, it could be found that the σsp was evidently lower in autumn (Fig.5b). The abundant precipitation in September and October as well as the frequent northerly winds in November probably contributed to the decrease of σsp. The rainfall was about 2 and 3 times as much as that in the same period of last thirty years in September and October, respectively. The enhanced wet deposition of PM therefore reduced σsp in these two months. In November, three strong northerly wind episodes processed 8 days in total, which diluted the pollutants significantly and resulted in rapid decrease of σsp. Furthermore, the significant decrease of σsp from June to September 2008 could be found at both CP and SDZ, and the PM2.5 reduced obviously at BL as while. The most important reason should be various pollution control measures taken by Chinese government at Beijing and vicinity from July to September, 2008. The organics and nitrate concentrations were reduced by 25%–80% compared with that observed in June 2008, and the sulfate concentration dropped about 5%–10% (Zhang et al., 2009). The significant reduction of these major scattering aerosol species inevitably decreased the aerosol scattering coefficient (Malm et al., 1996). The meanσsp values were 197 and 130 Mm − 1 at CP and SDZ during the Olympic Game period (8, August – 24, September, 2008) that decreased by about 60% by comparing with the mean values 491 and 319 in June, respectively.

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At these three sites, the σsp (525 nm) showed clear diurnal variation with different pattern. As shown in Fig. 6, the σsp had two peaks in spring at BL with one in the morning between 06:00 and 11:00 and the other around mid-night. In autumn and winter, there was only one night peak around 22:00 in the σsp. The lowest σsp was observed around 15:00 in all seasons. This diurnal pattern was mostly due to variations in diurnal local anthropogenic activities and meteorological conditions. The mean daily patterns of PM2.5 concentration, wind speed and temperature for different seasons were shown in Fig. 6. PM2.5 showed the similar diurnal cycle as that of σsp. The higher values of σsp and PM2.5 measured in the morning could be mostly attributed to the intense traffic and anthropogenic emissions during the morning rush hours. Furthermore, the low wind speed and low solar heating favor a rather low BLH that caused a large particle loading near the surface therefore high values of σsp. With the development of boundary layer in the daytime, the σsp decreased after the morning peak and reached the minimum in the midafternoon with the wind speed was generally largest. The decreases of BLH and wind speed in afternoon companying with increased source activity during the evening rush hour resulted in the high loading of aerosol and σsp during evening hours. Around 23:00, the significant reductions in source

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activities and removal of particles by dry deposition led to the decrease of σsp in the night. The morning peak of σsp in spring might be attributed to the production of secondary aerosols with the increasing solar radiation and temperature. The solar radiation in Beijing area is stronger in spring and summer, and lower in autumn and winter (Hu et al., 2007; Hu et al., 2010). In addition, it could be seen in Fig. 6 that the PM2.5 was highest in summer, which was mainly attributed to the “bad” meteorological conditions during this period. There were nine episodes characterized by stable weather pattern over Beijing area in summer 2008, which caused the accumulation of pollutants including PM2.5. There were 24 days with daily average PM2.5 concentration higher than 100 μg/m 3 were found during this stable weather period. This high PM2.5 concentration day was accounted for 40% of total days (daily average PM2.5 higher than 100 μg/m3) during the study period. The frequently unfavorable weather conditions resulted in the higher PM2.5 concentration in summer 2008. At suburban site CP, the σsp displayed three peaks in autumn and winter. One appeared in the morning between 06:00 and 11:00 and the other in the evening between 18:00 and 21:00 (Fig. 7). The third peak occurred around mid-night. The large emission of aerosol in the morning and evening rush hour mostly contributed to the two peaks in these periods. The night-time truck traffic emissions on the high-

way near this station might be responsible for the night peak. The increased BLH and wind speed caused the decrease of σsp in the afternoon and the reduced emissions in the late night resulted in the minimum of σsp in the early morning. The diurnal pattern of σsp in summer was different from that in winter and autumn, which showed higher value in daytime and lower value in nighttime. In summer, the BLH usually remains higher for a longer time during afternoon, a tendency that may cause the almost unchanging aerosol concentrations during this period (Guinot et al., 2006; Miao et al., 2008). The similar phenomenon could also be found in urban and rural area. The diurnal variation was obviously weaker in summer than that in winter. At the rural site SDZ, the σsp generally showed a unimodal pattern with a significant peak between 16:00 and 22:00 and a minimum around 13:00 (Fig. 8). The diurnal variations of σsp appeared to be consistent with the boundary layer growth and solar-driven up-slope to down-slope circulation in mountainous regions. The SDZ station is located on the south slope of a hill and is surrounded by mountains except to the southwest. On average, the winds have strong diurnal variation with SW in the afternoon and NE from midnight to the morning (the annual mean diurnal variation of wind direction in Fig.8). Up-slope flow from the southern plain usually accompanies boundary layer growth during the

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morning hours following sunrise, carrying pollutants emitted in the southern plain to the sampling site by mid-morning and continuing throughout the daytime. As the boundary layer collapses in the evening, the winds usually change to down-slope (northerly), bringing clean air to the site and leading to the decrease in σsp during the evening and night. In addition, there was a small σsp peak in the morning during the spring and winter, which probably caused by the local human activities surrounding the site. The morning peak was also found in aerosol absorption coefficient at SDZ site by Yan et al. (2008). With the boundary layer growth, the wind speed and temperature have evident diurnal variation, increasing from morning to afternoon and then decreasing till early morning. The stronger development of the boundary layer resulted in the obvious decrease of σsp around noon. 3.3. Mass scattering efficiencies (αsp) In this study, relationships between σsp and PM2.5 concentration are derived for BL and SDZ for their same measurement instruments and methods. Most PM2.5 particles have diameters comparable to the wavelength of the incident light, resulting in high particle mass scattering efficiency (αsp). The particles larger than 2.5 μm tend to scatter light less uniformly than smaller particles. A statistical relationship

is useful for estimation of σsp or PM2.5 from each other (Chow et al., 2006). The average mass scattering efficiency can be estimated by dividing the average scattering coefficient by the average mass concentration for a given sampling period, or the slope from a linear regression of scattering coefficient and mass concentration (Hand and Malm, 2007). In this study, the αsp was estimated as the regression slope by using nonweighted least-squares regression of daily average σsp on PM2.5 concentration, that had been used in previous study (Chow et al., 2006). Comparisons of αsp at BL and SDZ in different season are summarized in Table 2. The σsp and PM2.5 concentration showed good agreement with the high correlation coefficient 0.92 at BL and SDZ. The αsp obtained with the observation data during June 2008–May 2009 was 5.88 and 4.81 m 2/g at BL and SDZ, respectively. The αsp at BL was about twice higher than that observed in June 1999 in Beijing with a value of 2.6 m 2/g (Bergin et al., 2001), and similar to the value 5.1 m 2/g during winter 1997 in Mexico City (Chow et al., 2002). The seasonal behavior of αsp was different at BL and SDZ. The αsp showed weak seasonal trend that ranged from 5.57 to 6.25 m 2/g at BL, was consistent with the seasonal pattern of PM2.5 (Zhao et al., 2009). At the rural site SDZ, the αsp was evidently lower in autumn compared with that

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Fig. 8. Same as Fig. 6 but for the measurements at SDZ.

in other seasons, which might be partially attributed to biomass burning surrounding this site during autumn harvesting period (Zheng et al., 2005). The corn field burning surround-

ing SDZ site was recorded in October 2008. Biomass burning resulted in the emission of black carbon aerosol that mainly absorbed light and therefore caused the lower scattering efficiency of PM2.5.

Table 2 Comparison of αsp derived from linear regression between σsp (y-axis) and PM2.5 concentration (x-axis) for June 2008-May 2009 and four seasons. The unit of the slope (αsp) and intercept is m2/g and Mm− 1, respectively.

3.4. Scattering properties in haze episodes

Period

Parameter

Site BL

SDZ

0.92 265 5.88 −46.51 NA NA NA NA 0.95 91 6.25 −74.44 0.97 88 5.57 −8.56 0.78 86 5.79 −54.5

0.92 322 4.81 −16.3 0.98 89 4.97 −45.27 0.98 78 3.71 −19.48 0.91 88 5.08 −0.77 0.93 67 6.23 −30.79

June 2008–May 2009

Summer

Autumn

Winter

Spring

Corr. (r) N Slope Intercept Corr. (r) N Slope Intercept Corr. (r) N Slope Intercept Corr. (r) N Slope Intercept Corr. (r) N Slope Intercept

Two typical fog and haze episodes during the study period were selected for their extremely high σsp and the different spatial distribution pattern. The scattering properties and influence of meteorological conditions were studied in this part. The first episode was observed during Nov. 9–13, 2008 (episode I) and the second one occurred from April 10 to 13, 2009 (episode П). The synoptic weather patterns during episode I and II were both characterized by stagnant weather system. During episode I, a weak ridge controlled the northern China and the sinking air was unfavorable pollution diffusion. The uniform pressure field over Beijing region resulted in very weak wind at surface, which led to the accumulation of air pollutants during this episode. However, a stationary trough controlled most parts of the northern China region that led to the accumulation of air pollutants during episode II. Beijing region was in front of a low pressure system where the south-west warm-wet air stream was easily formed. As shown in Fig. 9, the wind direction and wind speed changed significantly from episode I to episode П. The northeasterly wind was prevailing during episode I with much lower wind speed. The average daily wind speed was lower than 1.0 m/s at BL and CP, and lower than 1.5 m/s

X. Zhao et al. / Atmospheric Research 101 (2011) 799–808

5.0m/s

Episode

807

Episode

SDZ

CP BL

RH (%)

BL 120

CP

100

SDZ

80 60 40 20 0 BL

σsp(525nm) (Mm-1)

2000

CP SDZ

1500 1000 500 0 09/11

10/11

11/11

12/11

13/11

10/04

11/04

12/04

13/04

Fig. 9. Hourly wind vector, RH and σsp during episode I (Nov. 9–13, 2008) and П (Apr. 10–13, 2009).

at SDZ on Nov. 11 and 12. Winds during episode П were generally from south-southwest, and the wind speed was much stronger than that in episode I. The relative humidity was relatively uniform in space and had no evident difference between episode I and П. The different wind pattern resulted in distinct spatial distribution pattern of σsp during two episodes. During the episode I, the highest hourly averages of σsp were 1996, 1255 and 568 Mm − 1 at BL, CP and SDZ, respectively. The daily average of σsp exceeded 1000 Mm − 1 at BL on Nov. 11 and 12, which caused very poor visibility with the range from 4 to 6 km. During this episode, the average value of σsp 962 Mm − 1at BL was about 2 and 3 times of that at CP and SDZ, respectively. The σsp showed a significant decreasing trend from urban site to rural site. However, the σsp was relatively spatially uniform during the second episode. The highest hourly values of σsp were recorded at April 13 with 1774 and 1432 Mm − 1 at BL and SDZ, respectively. The average value of σsp was 935 Mm − 1 at BL and 626 Mm − 1 at SDZ during episode П. The average σsp at BL was close to that during episode I, but it was nearly 2 times of that during episode I at SDZ. The calm wind was prevailing in Beijing area during episode I. The poor diffusion conditions enhanced the accumulation

of pollutants including aerosols in urban area and resulted in significant spatial difference in σsp. The strong southerly winds could easily transport pollutants from southern urban regions to the northern rural area, which reduced the spatial difference of σsp but increased regional pollution level. 4. Conclusion With σsp and mass concentration of PM2.5 measurement data from June 2008 to May 2009 at three stations in Beijing, the temporal variation characteristics of σsp has been investigated in this study. The σsp showed a decrease trend from urban area to rural area with mean values of 301 ± 307, 263 ± 263, 182 ± 201 Mm − 1 at BL (urban site), CP (suburban site) and SDZ (rural site), respectively. The σsp showed different seasonal patterns at three sites. The σsp was higher in late autumn and early winter, and lower in early autumn at BL. It should be also higher in summer corresponding with the high level of PM2.5 in June and July, 2008. The seasonal fluctuations in σsp in urban areas were mostly dominated by seasonal variability in both emissions and meteorological conditions. At CP, the higherσsp was observed in early

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X. Zhao et al. / Atmospheric Research 101 (2011) 799–808

summer and lower values in autumn and winter. At SDZ, summer and spring presented largerσsp than other season. The seasonal wind patterns seemed to outweigh other meteorological factors in influencing σsp in the suburban and rural areas. Significant diurnal variations of σsp with different pattern were observed at three sites. The σsp had two peaks in spring at BL appeared in the morning between 06:00 and 11:00 and around mid-night, respectively. In autumn and winter, only a night peak around 22:00 was observed in σsp. The lowest σsp appeared around 15:00 in all seasons. The afternoon decreases of BLH and wind speed companying with increased source activity resulted in the high loading of aerosol and σsp during evening hours. The morning peak of σsp in spring might be attributed to the production of secondary aerosols. At suburban site CP, the σsp displayed three peaks in autumn and winter. There was a peak occurred around mid-night besides the morning and evening peaks. The night-time truck traffic emissions on the highway near this station might be responsible for the night peak. In summer, the σsp showed higher value in daytime and lower value in nighttime due to the longer persistence of BLH in the afternoon. At the rural site SDZ, the σsp showed a unimodal pattern with a significant peak between 16:00 and 22:00 and a minimum around 13:00. The boundary layer growth and solar-driven up-slope to down-slope circulation in SDZ region mostly dominated the diurnal variation of σsp. The mass scattering efficiency (αsp) of PM2.5 was estimated with daily averages of σsp and PM2.5 concentration. The αsp decreased from urban to rural site with the average values of 5.88 and 4.81 m 2/g at BL and SDZ, respectively. The αsp showed weak seasonal variation at BL, and lower value in autumn At SDZ. The biomass burning surrounding SDZ site might be partially responsible for the low αsp during autumn. Two typical fog and haze episodes during the study period were selected for analyzing the scattering properties and influence of meteorological conditions. The σsp showed a significant decreasing trend from BL to SDZ during the first episode, while was relatively uniform during the second one. The weak winds enhanced the accumulation of pollutants in urban area and resulted in significant spatial difference in σsp in episode I. The stronger southerly winds carried pollutants to the northern rural area and reduced the spatial difference of σsp during episode П, but increased regional pollution level. Acknowledgments This work was supported by the Beijing Natural Science Foundation (No. 8092010) and the Special Grant in Atmospheric Sciences Field supported by CMA (No. GYHY200806027). The measurement systems were maintained by He Di, Dong Fan, Yang Yadong, Zhou Huaigang, Wang Zhenfa and others. References Bergin, M.H., Cass, G.R., Xu, J., Fang, C., Zeng, L., Yu, T., Salmons, L., Kiang, C., Tang, X., Zhang, Y., Chameid, W., 2001. Aerosol radiative, physical, and chemical properties in Beijing during June 1999. J. Geophys. Res. 106 (D16), 17969–17980.

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