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Original Research Papers

Impact of the regional transport of urban Beijing pollutants on downwind areas in summer: ozone production efficiency analysis


B. Z. Ge,

State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, CN
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X. B. Xu,

Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, CN
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W. L. Lin,

Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, CN; Center for Atmosphere Watch and Services, Meteorological Observation Centre, China Meteorological Administration, CN
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J. Li,

State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, CN
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Z. F. Wang

State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, CN
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Ambient measurements of SO2, O3, NO x , NO y and CO were made at Shangdianzi (SDZ), a rural site in the northeast (NE) of Beijing, and urban Beijing (China Meteorological Administration) from 1 June 2008 to 31 August 2008. The pollutants at SDZ showed very different levels under different wind conditions, with the levels under the southwest (SW) wind being much higher than those under the NE wind. The SW wind facilitates the transport of urban plume to SDZ, whereas the NE wind provides a background condition. At SDZ, the Ozone (O3) concentration in air masses from urban Beijing was found to be 33.4 ± 0.4 ppbv higher than that from clean regions in summer. The ozone production efficiency (OPE x ) for the urban plume and background condition was 4.0 and 5.3, respectively. Based on these OPE x values and the NO z values for the respective conditions, the contribution of in-situ production in the urban plume to the level of O3 at SDZ is estimated to be 8.6 ppbv, corresponding only to 25.7% of the total impact of urban plume transport. This suggests that direct transport of O3 rather than in-situ photochemistry contributes mainly to the summer elevation of the level of O3 at SDZ.

How to Cite: Ge, B.Z., Xu, X.B., Lin, W.L., Li, J. and Wang, Z.F., 2012. Impact of the regional transport of urban Beijing pollutants on downwind areas in summer: ozone production efficiency analysis. Tellus B: Chemical and Physical Meteorology, 64(1), p.17348. DOI:
  Published on 01 Jan 2012
 Submitted on 12 Aug 2011

1. Introduction

Ozone (O3) is one of the most important oxidants and the dominant precursor of radicals (OH and NO3) in the atmospheric troposphere. As one of the greenhouse gases, O3 plays a significant role in climate change and atmospheric chemistry (Akimoto, 2003). Elevated concentration of surface O3 is of great concern because of its adverse impacts on human health and ecosystems (Mills et al., 2011). Most studies show that the elevated concentration of surface O3 is because of the increased concentration of its precursors (i.e. NOx, CO and VOCs), which originate mainly from anthropogenic sources (Chameides et al., 1992; Bowman and Seinfeld, 1994; Finlayson-Pitts and Pitts, 1997; Tang et al., 2010). This is true in cities, especially in megacities (Wang et al., 2000; Molina and Molina, 2004; Shao et al., 2006; Chan and Yao, 2008; Ran et al., 2009; Yan et al., 2011). However, frequent high-O3 events occur not only in cities but also in rural or remote areas, where local emission of anthropogenic pollutants is not important. This phenomenon is usually caused by transport of polluted air masses and photochemical formation of O3 in these air masses. For example, transport of polluted air masses are believed to elevate O3 levels at Chinese regional background sites (Chan et al., 2003; Lin et al., 2008; Xu et al., 2008) or even global background sites (Li et al., 2009).

Beijing is one of the megacities in Asia and the major population centre in the city cluster of Beijing–Tianjin–Tangshan region in North China, where the regional air pollution is characterised by high concentrations of both primary and secondary pollutants (Shao et al., 2006). The emissions of SO2, NOx and VOCs are mainly related to fuel burning from industry, power plants, domestic heating, vehicles and solvent use in urban Beijing (Hao et al., 2005). These pollutants may strongly influence the air quality of the downwind areas of Beijing. This view is supported by an early study of Yang et al. (2005), who showed high similarity in aerosol mass and elements between Beijing downtown and suburb areas. Li et al. (2011)reported that the aerosol in urban Beijing has large impact on the lifetimes of NO2, CO and SO2 and may increase the transport distance of gaseous pollutants. Wang et al. (2006) also reported a high O3 pollution case in a mountainous area north of Beijing and attributed the high O3 pollution to a polluted plume from urban Beijing.

To monitor the long-term changes of atmospheric compositions and related properties over North China, a regional background station was established in the early 1980s at the north edge of the North China Plain (NCP). This station, called Shangdianzi (SDZ), has been one of the Global Atmosphere Watch (GAW) stations. Located between the heavily polluted and fairly clean areas, SDZ is a very interesting site for atmospheric chemistry studies. In the past few years, a number of studies (Yang et al., 2005; Lin et al., 2008; Meng et al., 2009; Ge et al., 2010; Stohl et al., 2010; Shen et al., 2011) have been done at this site, focusing on different topics. Surface O3 at SDZ has been one of the topics that deserve a careful study. Initial measurements show that the hourly mean concentration of surface O3 at SDZ can be much higher than 100 ppb (Meng et al., 2009), indicating that photochemical smog can occur at this background site. To better understand the origin of surface O3 at SDZ, Lin et al (2008) investigated the contributions of pollutants from the NCP to the background level of surface O3 at SDZ and found that such contributions accounted for about 28.9 ppb in summer during 2004–2006. Ozone production efficiency (OPEx), which is defined as the number of molecules of O3 formed per NOx removed from atmospheric O3-forming oxidation cycles [i.e. P(O3)/P(NOx)] (Liu et al., 1987) and is calculated from observations of NOy and NOx (Kleinman et al., 1994), is one of the useful indicators in the study of photochemical pollution. A few studies have paid attention to OPE in Beijing's urban and rural areas. Based on measurements made at a Peking University site, Chou et al. (2009) obtained OPE values ranging from 3.9 to 9.7. An (2006) modelled OPE in the Beijing urban areas and reported a value of about 3.0. Based on in-situ measurements of O3, NOx, NOy, and so on, Ge et al (2010) estimated the OPE at SDZ to be in the range of 0.2–21.1, with an average of 4.9. All these OPE values are within the range of the OPE values found in America and Europe (Rickard et al., 2002; Xu et al., 2009).

Generally, surface O3 at a background site can come from the transport of O3 (including O3 formed during transport), in-situ photochemical production by the transported O3 precursors and pseudo natural O3 background. The study of Lin et al. (2008) only shows the total impact of urban plume on the level of surface O3 at SDZ. The OPE study of Ge et al. (2010)cannot differentiate contribution of the in-situ photochemical reactions from O3 transported to the site. Therefore, the roles of different factors influencing the O3 formation and OPEx at the site are still not very clear. In this article, we present the variation characteristics of O3 and its precursors in Beijing's urban and rural areas (SDZ) in the summer of 2008, study the contributions of in-situ photochemical production and transport from southwestern plume (Beijing city and the NCP) to the afternoon enhancement of O3 at SDZ. The OPEx from southwestern and northeast (NE) plume and the correlation with daily photochemical age is also presented in this article.

2. Measurements

2.1. Observation sites

The measurements were made at an urban Beijing site and a regional background site in North China. The urban site is located on the rooftop of a building in China Meteorological Administration (CMA: 39.95°N, 116.32°E, 96 m a.s.l.) in Beijing city, whereas the background site, SDZ (40°39′N, 117°07′E, 293.9 m a.s.l.), is located 100 km NE of Beijing city and is one of the WMO/GAW regional background stations in China. Figure 1 shows the locations of the two sites and the surrounding topography. More details about the sites are given in Lin et al. (2008, 2011).

Fig. 1.   

Locations of the CMA and SDZ sites and the topography around them. The contour lines with number indicate the height of terrain; the red-colour shaded areas show the intensity of NOx emission during 2006 from Wu et al. (2011) Wind vectors with blue colour indicate the observations at 15:00 on 10 June 2008, and in black the MM5-simulated data at the same time. The figure on the right shows the diurnal patterns of Ox and O3 at SDZ and CMA on 10 June 2008 and the postponement of 3 h of the concentration peaks at SDZ (reproduced with permission from B.Z. Ge).

As indicated in a previous study (Lin et al., 2008), the valley topography facilitates the transport of pollutants from the NCP to SDZ. In summer, the prevailing winds are southwest (SW) from afternoon to early evening and NE during night and morning. Therefore, pollutants from the urban area of Beijing and its surrounding areas may be transported to SDZ during afternoon and be cleaned up as the NE wind (clean air masses from rural area) blows at night.

2.2. Instruments and data

Commercial instruments from Thermo Electron Corporation, USA were used to measure O3 (49C), NO/NO2/NOx (42CTL), NO/NOy (42CY), CO (48CTL) and SO2 (43CTL) at CMA and SDZ. All instruments were housed in an air-conditioned rooftop room of the building (38 m above ground level) at CMA and an air-conditioned bungalow at SDZ, and the air inlets were installed 1.8 m above the roofs. Daily zero/span checks were automatically done using dynamic gas calibrators (Model 146C) combined with zero air suppliers (Model 111) and standard gas mixtures for SO2, NO and CO. More frequent zero checks (every 6 h) for CO analysers were carried out. The multipoint calibrations of CO, SO2, NOx and NOy analysers were made every month at CMA and every season at SDZ using the standard gases, which were compared against National Institute of Standards and Technology (NIST) traceable standards (Scott Specialty Gases, USA). An O3 calibrator (49C PS) was used to calibrate the O3 analysers at the sites. The calibrator is traceable to the Standard Reference Photometer maintained by WMO World Calibration Centre in Switzerland (EMPA). High-resolution data (5 or 1 min averages) were recorded and hourly average values are presented and analysed in this article.

3. Results and analysis

3.1. Characteristics of air pollutants

Figure 2 shows the time series of SO2, NOy, CO, O3 and Ox at SDZ and of SO2, NOx, CO, O3 and Ox at CMA in summer (1 June to 31 August 2008). Instead of using as the total oxidant at SDZ, the Ox (≡O3  +  NO2  +  NOz) in this study includes more important odd nitrogen oxidants other than NO2, particularly HNO3 (Chou et al., 2009), and it was 4 ppb in daytime and 1.4 ppb in nighttime higher than during summer time, which took up 7 and 3% of the mean concentration of Ox during daytime and nighttime, respectively. However, the observation of NOy was absent at the CMA site, the total oxidant for this site is given by as before (St John et al., 1998) and might be underestimated by 20% during high-O3 episodes according to Chou et al. (2009). Significant day-to-day variations of pollutants were observed during the period. These variations are caused by many factors, such as emissions from local and outside, meteorological parameters and atmospheric chemistry (Li et al., 2007; Meng et al., 2009). It is worth to mention that the mixing ratios of all species at both sites were lower in August when the 2008 Beijing Olympic Games were held than those in the other 2 months during the observation period and did not exceed the values of the Grade-II standards of Chinese Ambient Air Quality. Much stricter emission reduction measures were implemented during the Olympic Games and the air quality was improved greatly, as reported in many studies (Witte et al., 2009; Huang et al., 2010; Wang et al., 2010a Wang et al., 2010b; Yang et al., 2010; Yu et al., 2010; Zhang et al., 2011). However, the level of O3 at SDZ did not show month-to-month differences exceeding those found in the summer months of the normal years, for example, those reported by Lin et al. (2008). Moreover, the calculated monthly OPE for the SW plume was nearly stable. Therefore, in this study, we do not treat the data during the Olympic Games separately.

Fig. 2.   

Time series of SO2, NOx, NOy, CO, O3 and Ox at SDZ and CMA during summer 2008 (reproduced with permission from B.Z. Ge).

The hourly maximal Ox level at CMA and SDZ reached 138 and 169 ppb, respectively, on 10 June 2008 with almost similar daily amplitude of Ox (95.8 ppb at CMA and 92.6 ppb at SDZ). Besides, the Ox peak at CMA was 3 h earlier (at 14:00) than that at SDZ (at 17:00). This example shows that, as the high-O3 events (daily maximal mixing ratio of 1 h averaged Ox over 100 ppb) occur, the daily increase of total oxidant at SDZ may be similar to that at the urban site. The difference in the peak values of Ox between SDZ and CMA may be attributable to the difference in the O3 concentrations in the previous night. At the urban site, the higher NOx level because of vehicle emissions causes larger consumption of O3 during the night. In fact, out of the 39 high-O3 days, 28 (about 72%) days showed higher peak of Ox at SDZ than at CMA and 68% of these days showed higher concentration of Ox in the previous evening at SDZ and 74% of the days showed similar daily amplitude of Ox in these two sites during the observation periods (see Table 1) . Figure 3 shows the scatter plot of the daily amplitude of Ox at CMA against that at SDZ during the summer of 2008. As can be seen in the figure, the daily amplitudes at both sites are significantly correlated (R  =  0.78, P  <  0.01) and the slope of the fitted line, 1.15 (close to 1), suggests similar daily amplitudes of Ox at both sites.

Fig. 3.   

Scatter plot of daily amplitude of Ox at SDZ and CMA (reproduced with permission from B.Z. Ge).

The diurnal patterns of CO, SO2 and NOy at SDZ look very different from those at CMA, whereas O3 and Ox show similar diurnal patterns at both sites (Fig. 4). The CO and NOx concentrations at CMA show similar diurnal patterns, with elevated concentration during the night, a peak around 8:00 and a valley in the afternoon, fairly consistent with those at the same site in winter (Lin et al., 2011). At SDZ, the peaks of CO and SO2 occur in late afternoon (around 17:00), similar to those of O3 and Ox. The late occurrences of these pollutant peaks may be attributed to the transport of urban plume to the SDZ site, which causes enhanced concentrations of air pollutants in the afternoon. Figure 5 may help to clarify the impact of the transport of urban plume. As indicated by the wind vectors in Fig. 5a, the wind direction changes around noon from northeasterly (from the clean rural sector) to southwesterly (from the urban and polluted rural sector). The wind directions in the entire afternoon favour the transport of urban plume to SDZ, which can inevitably elevate the concentrations of pollutants, such as CO, NOx and SO2. The fact that the concentrations of O3 and Ox at SDZ peaked 3 h later than those at CMA also support the idea of the transport of urban plume towards SDZ. Another evidence of the transport is the diurnal variation of the ratio of NOx/NOy, which shows a continuous increase after 12:00 (Fig. 5b) and suggests that air with more freshly emitted NOx from urban sector replaces gradually more or less aged air over SDZ. In the following section, we will quantify the influence of such air transport.

Fig. 4.   

Average diurnal cycles of CO, SO2, NOx/NOy and O3/Ox at SDZ and CMA in summer 2008 (reproduced with permission from B.Z. Ge).

Fig. 5.   

Average diurnal cycles of wind vector (a) and the ratio NOx/NOy (b) at SDZ in summer 2008 (reproduced with permission from B.Z. Ge).

3.2. Impacts of precursors from the urban area on the O3 concentration at SDZ

To investigate the relationships among SO2, CO, Ox and NOy at SDZ and CMA, Pearson correlations are calculated from the hourly concentrations of trace gases and meteorological parameters and are listed in Table 2. Compared to the study of the winter measurements from Gucheng (Lin et al., 2009) and the CMA site (Lin et al., 2011), the summer concentrations of the primary pollutants at SDZ are less significantly correlated among each other, like those concentrations of primary pollutants at Gucheng (Lin et al., 2009). This phenomenon may indicate that the concentrations of primary pollutants in summer are more influenced by some processes other than emission and transport than in winter. Such processes can be photochemical reactions, wet and dry depositions (Pan et al., 2010).

The concentrations of the pollutants at SDZ are significantly correlated with those at CMA, especially those of SO2, CO and Ox, with R  =  0.60, 0.53 and 0.72, respectively, suggesting close relationships between pollutants in urban plume and those at SDZ. To quantify the effect of the transport of urban pollutants on Ox formation at SDZ, the rose distributions of average concentrations of O3, CO, NOx and NOy at SDZ are plotted in Fig. 6. Among the gases, O3, NOx and NOy are subjected to stronger influences of chemical reactions, whereas CO is not and hence can be used as a marker. In summer, the frequency of wind direction is the highest from SW (46.0%) and then from NE (28.6%). This indicates that the urban plumes from SW, containing more pollutants, exert much stronger influences on the levels of ambient pollutants at SDZ than the clean air masses from NE. A difference of 33.4 ± 0.4 ppbv between the average concentrations of O3, 33.5 ± 0.4 ppbv between those of Ox, not shown in Fig. 6, from SW and NE plume can be calculated from the statistics, suggesting that urban plumes from SW may elevate the concentration of Ox at SDZ by 33.5 ± 0.4 ppbv, a result similar to that based on the 2004–2008 measurements (Lin et al., 2008).

Fig. 6.   

Rose distributions of the average concentrations of O3 (a), CO (b), NOx (c) and NOy (d) over summer 2008 at SDZ (reproduced with permission from B.Z. Ge).

The impacts of urban plume on the Ox concentration at SDZ may be decomposed as

(1 )

where (Oxtrans_impacts) represents the total impacts of urban plume on the Ox concentration at SDZ, and (Oxtrans), (Oxtrans_production) and (Oxin-situ_prodution) are the Ox increases due to transport of Ox already formatted in urban area, transport of Ox formatted during air travelling to SDZ and in-situ Ox production enhanced by precursors transported to SDZ from urban area, respectively. According to the above result, (Ox,trans_impact) is 33.5 ± 0.4 ppbv. In the following section, the effects of regional transport and the enhancement of in-situ Ox production will be quantified and analysed.

As can be seen in Fig. 6, the differences in the NOy and CO concentrations were also large between the SW–NE directions, with 6.95 ± 1.19 ppbv for NOy and 360 ± 80 ppbv for CO. However, the average concentration of NOx from SW is similar to that from NE, with a difference of only 0.25 ± 0.16 ppbv between both directions. This may be caused by more intensive photochemical losses of NOx in the SW plume. Larger emissions of VOCs in the polluted sector may favour the production of O3, transform NOx into NOz and increase the concentration of NOz (Xu et al., 2011). In addition, few NOx transformed to NOz during night and early morning, when the wind from NE sector is dominant, may result in smaller difference of NOx between the SW–NE directions.

3.3. Impacts of photochemical production

It is shown in Section 3.2 that pollutants in the SW plume could increase the concentration of Ox at SDZ by 30 ppbv. However, the detailed contributions from the transport of pollutants and from the enhancement of the in-situ O3 production at SDZ are unknown (see Eq. 1). Here, we estimate the contributions by using the OPEx of different plumes. In this study, linear regressions are applied to (Ox) (O3  +  NO2  +  NOz) versus (NOz) (NOy – NOx) data and the slopes of the regression lines are taken as daily OPEx (Chou et al., 2009). Data during 6:00–19:00 are used for the regressions. Only slopes of the regression lines with higher correlation coefficients (R2  >  0.6) and positive intercepts (the background Ox concentration) are considered to be effective daily OPEx for this study. In order to study the O3 formation characteristics at SDZ, the daily OPEx as a function of chemical ageing calculated by (NOz)/(NOy) is plotted in Fig. 7. As clearly shown in this figure, there is a significant negative correlation between OPEx and (NOz)/(NOy), indicating that the OPEx at SDZ decreases significantly with the ageing of air parcels. This result is consistent with that of Marion et al. (2001), Olszyna et al. (1994) and Trainer et al. (1995) and indicates a reduction of OPE with the increase of precursor emissions. Model simulations by Lei et al. (2008) show that the O3 production rate decreases with the increase of chemical age parameter for downwind areas of Mexico City. However, the study by (Chou et al., 2009) shows a positive correlation between OPEx and (NOz)/(NOy) for the urban site, Peking University. The different correlation between OPEx and (NOz)/(NOy) often exist among urban and its downwind areas and this may be attributed to the transport of urban plume to its downwind site. According to this study, more specifically, the air with freshly emitted NOx from urban sector replaces the aged air over SDZ and decreases the ratios of NOz/NOy. Besides, the increased concentration of Ox at SDZ would not be produced by the local photochemical production because the air parcel is fresh, but strongly might be the daily transported from high O3 concentration area, such as Beijing downtown and the NCP.

Fig. 7.   

The correlation between the daily OPEx and (NOz)/(NOy). The red-solid points indicate outliers of 27 and 28 July and are not included in the regression. The winds on these 2 days were always from SW with no direction change and hence are not considered as normal conditions (reproduced with permission from B.Z. Ge).

The relationship between Ox and NOz can be very different under different wind conditions. Here, we use the method of Nunnermacker et al. (1998) to obtain OPE values representing the urban plume and background. Fig. 8 shows the scatter plot of the concentrations of Ox and NOz in the SW and NE wind conditions, with results of linear regressions. The slopes of the (Ox) – (NOz) line for the SW and NE winds are 4.0 ± 0.32 and 5.3 ± 0.55 ppb ppb−1, respectively. These values are in the range of those (3.9–9.7) based on the measurements from the Peking University site during high-O3 episodes (Chou et al., 2009) and those (2–8) simulated for the Pearl River Delta region (Wang et al., 2010c) and consistent with the value in previous study for SDZ (average 4.3 for clear days) (Ge et al., 2010). The OPEx value for the NE wind (OPEx-NE) is higher than that for the SW plume (OPEx-SW), suggesting that air masses from the clean sector produce O3 more efficiently than those from the polluted sector. This result is consistent with those reported in other studies (Carpenter et al., 2000; Kleinman et al., 2002; Rickard et al., 2002; Lin et al., 2009; Thielmann et al., 2002). It is noteworthy that the correlation coefficient of the (Ox) – (NOz) correlation for the SW wind (0.63) is smaller than that for the NE wind (0.80). This may be attributable to the impact of the pollutants’ transport (O3 and NOx) from the polluted sector on the local concentrations of Ox and NOz at SDZ, as under the SW transport conditions, larger parts of variances of the Ox and NOz concentrations are not related to local photochemistry, on which the (Ox) – (NOz) correlation is based. The impact of the SW transport is particularly important during afternoon as mentioned in Section 3.1.

Fig. 8.   

Scatter plot of Ox versus NOz at SDZ during the summer of 2008. The black points show data under SW wind conditions and the red ones show those under NE wind conditions (reproduced with permission from B.Z. Ge).

Factually, the OPEx-NE could be used as the in-situ OPEx as the aged air parcel (NOx/NOy below 0.25) from rural background area and the OPEx-SW as the OPEx of the urban plume (NOx/NOy above 0.40). Factually, the value of OPEx-SW is similar to that for Beijing urban area (An, 2006) if considering the (Ox) as (O3  +  NO2) instead (O3  +  NO2  +  NOz), and is in the OPEx range of 3.9–9.7 obtained by Chou et al. (2009) using the same method. Therefore, the in-situ Ox production enhanced by urban plume can be calculated as following:

(2 )
(3 )

where α is the correcting coefficient (0.53) for correcting NOz loss during the transport of pollutants from the source region to the observation point according to Ge et al. (2010)and the can be considered as the average additional NOz produced by urban plume at SDZ. However, according to a previous study (Ge et al., 2010), the photochemical production of NOz in SW direction has been lost by more than a half owing to dry deposition during transport, could be small and is assumed to be zero. The and are 7.8 and 3.9, respectively. We obtained the upper limit level of as 3.9 (7.8 – 3.9  =  3.9). The Ox elevation due to in-situ production enhanced by urban plume is estimated to be 8.6 ppbv, corresponding to about 25.7% of the total impact (about 33 ppbv) of the SW plume on the level of Ox at SDZ. This indicates that in-situ Ox production enhanced by urban plume is not the dominant factor for Ox pollution at SDZ and contributes only to one-fourth of the total impact from transport of urban pollutants.

To support this view, we calculated the in-situ photochemical production at SDZ during 20–23 July 2008 using the CBMZ-OBM (observation based cbm-z model) model. In this case, the hourly maximum of O3 concentration reached 124.5 ppbv at 17:00 on 23 July. For the model calculation, we used the hourly observations of VOCs, NOx and daily minimum of O3 (instead of Ox for eliminating the hourly NO2  +  NOz observation impact) concentration as well as hourly meteorological data. The modelled and observed O3 concentrations agree well with each other (not shown). The O3 accumulations caused by in-situ photochemistry and transport are estimated from the model result and observational data (Fig. 9). The in-situ photochemistry contributed 26.3% on average and about 50% during afternoon to the observed O3 level, which is consistent with the above result.

Fig. 9.   

The impacts of in-situ photochemistry and urban plume transport on the concentration of O3 at SDZ (a) and the relative contributions of the two factors (b) (reproduced with permission from B.Z. Ge).

3.4. The source analysis of NOy at rural site

Although the NOy–CO and NOy–SO2 correlations during summer at SDZ are less significant than those during winter at CMA and Gucheng (see Section 3.2) with the correlation coefficients of 0.46 and 0.63, respectively, the correlations are statistically significant at P  =  0.01 (Table 2). This indicates that NOy share some common sources with CO and SO2 during summer at SDZ. Usually, stationary sources (mainly coal-burning) emit much more SO2 than CO, whereas mobile sources emit much more CO than SO2. Both types of sources emit NOy (Lin et al., 2009 Lin et al., 2011). Stehr (2000) and Tong et al. (2005) used the multilinear regression method to estimate the relative contributions of different types of sources to NOy at the shore of Chesapeake Bay, Maryland, and in two national parks of the United States, respectively. The same method was applied by Lin et al. (2011)to estimate the relative contributions of stationary and mobile sources to NOy at CMA, an urban site of Beijing. To see the differences in NOy sources between the CMA and SDZ sites, we follow the same approach to obtain the relative contributions of stationary and mobile sources to NOy at the SDZ site. Suppose that NOy at SDZ can be calculated using the multilinear model

(4 )

where α1 and α2 represent the fitted coefficients of SO2 and CO, and β is the intercept. Based on the regression, α1, α2 and β are 0.147, 0.01 and 3.48, respectively, and the multiple regression coefficient is 0.62 (P  =  0.01). The condition index is 6.83 (<30) and the variance inflation factor is 1.69 (<10), suggesting the regression is statistically significant and the collinearity of independents is not significant.

The average concentrations of SO2, CO and NOy in summer 2008 and the coefficients α1 and α2 are used to calculate the relative contributions of the stationary and mobile sources to NOy. On average, the relative contributions of the stationary and mobile sources to NOy at SDZ during summer are estimated to be 4 ± 1 and 68 ± 28%, respectively. The relative contribution of mobile sources to NOy is comparable to those from the other studies, such as 47% in 2006 in Beijing city based on the emission data (Zhang et al., 2009) and 66% at a urban site in Beijing during winter (Lin et al., 2011). However, the relative contribution of stationary sources is significantly smaller than that of 40% for the CMA site in Beijing during winter of 2007–2008 (Lin et al., 2011). This may be caused by the emission control imposed for the Olympic Games 2008, which was implemented mainly in summer 2008 and reduced emissions from power plants and other industrial sources more efficiently in Beijing and surrounding areas. Another reason for the high contribution of stationary sources in the study of Lin et al. (2011)may be more emission of SO2 in winter time due to house heating.

It should be noted that the less significant NOy–CO and NOy–SO2 correlations for SDZ may cause large uncertainties in the results from the application of the multilinear model to the SDZ data. On the other hand, the results may still be reliable as the air at the regional background site is well mixed and less directly influenced by local sources.

4. Conclusions

Ground-based measurements of trace gases SO2, CO, NO/NOx/NOy and O3 were made at a rural (SDZ) and an urban (CMA) site in the summer of 2008. Statistical analysis of the daily peaks of O3 at SDZ and CMA reveals that about 72% of the high-O3 days show higher Ox peak at the rural site than at the urban site and more than half of these days showed higher concentrations of Ox at SDZ in the previous nights and similar daily amplitudes of Ox for both sites. The diurnal variation of Ox showed similar patterns at SDZ and CMA, but with the peak of the Ox concentration at SDZ (17:00) 3 h later than that at CMA (14:00). The peaks of other pollutants (CO and SO2) at SDZ also occurred at around 17:00, suggesting that urban plume transport after wind direction change (at about 12:00) is the main reason for the elevated concentrations of pollutants. Significant correlations of the pollutants between SDZ and CMA indicate that air pollutants at the rural site, SDZ, are strongly influenced by urban plumes of Beijing. A total impact of urban plume transport on the average concentrations of O3 at SDZ is estimated to be 33.4 ± 0.4 ppbv for the summer of 2008.

The daily OPEx value was derived from the daytime measurements of Ox and NOz and found to be negatively correlated with the photochemical age of air parcel. The OPEx for the SW and NE plumes were estimated to be 4.0 and 5.3, respectively. From these values and the NOz values for the SW and NE plumes, the contribution of in-situ production in the urban plume to the level of O3 at SDZ, averaged over the summer of 2008, was estimated to be 8.6 ppbv, corresponding to 25.7% of the total impact of urban plume transport. This suggests that the in-situ photochemistry plays only a small role in the elevation of Ox at SDZ and direct transport of O3 makes a major contribution under the condition of urban plume transport.

5. Acknowledgements

We thank the operators of the SDZ station for carrying out the measurements. This work is supported by National Natural Science Foundation of China (No.40775074), the Basic Research Fund of CAMS (No.2011Z003) and CMA (GYHY200706036, GYHY201106050) and Special Fund for Environmental Protection Research in the Public Interest (201009002) and the CAS Strategic Priority Research Program (No. XDA05100501) and Beijing Municipal Science & Technology Commission (No. D09040903670904).


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