Environ. Sci. Technol. 2009, 43, 7590–7591
Response to Comments on “Atmospheric Particulate Matter Pollution during the 2008 Beijing Olympics” I appreciate the interest from Tang et al. (1)and Yao et al. (2)in our recent publication (3). Many of their comments were already addressed in our publication. Their main concerns regard sampling methodology and site location, our definition of source control and nonsource control periods, and the use of a multiple linear regression model to quantify the relative contributions of meteorology and source control measures that account for the variation in particulate matter (PM) concentrations. I stand by our main conclusion that observed trends indicate that meteorology accounted for more of the PM concentration variation than source control measures during our period of observation. Sampling Methodology and Site. All quality control and quality assurance procedures used for our sample collection, including correction for humidity and the U.S. Environmetal Protection Agency methods used, are described in our publication ( ref 3, p 5315, and Supporting Information, pp S12-13). The relationship we used for the correction of filter mass for humidity was highly correlated for the most significant PM size fractions (PM2.5-10 and PM2.5) with r2 of 0.734 and 0.662 and p ) 0.0001 (ref 3, Supporting Information, pp S12-S13). The use and comparison of cascade impactors and tapered element oscillating microbalances (TEOM) for the collection of PM is the subject of ongoing research, and both techniques have their respective sampling artifacts (4-6). Positive sampling artifacts due to adsorption of gases during the collection of PM with cascade impactors have been shown to be reduced in urban environments like Beijing when samples are collected over 24 h periods (6). Our air sampling site was located 25 m above traffic level on top of a seven story building at Peking University (PKU) and near Olympic events that took place at traffic level (ref 3, p 5315). The PM concentrations we measured at 25 m are a conservative measure of what athletes and spectrators experienced at traffic level near PKU because of dilution. In addition, our sampling site was located only 100 m horizontally from a site on the PKU campus that has been previously used for air quality studies (7). Our cascade impactor was not colocated with the TEOM monitors of the Beijing Environmental Protection Bureau (EPB). We acknowledged that the factor of 1.3 difference between our PM10 concentrations and the Beijing EPB PM10 concentrations may be due to site differences as well as differences in the sampling and measurement methods used (ref 3, pp 5314-5315). A factor of 1.3 between gravimetric PM10 methods and TEOM methods has been previously reported (ref 3, p 5315). We reported average PM2.5 and PM10 concentrations over our sampling period from 9 a.m. to 9 a.m. The Beijing EPB reported the average PM10 concentrations from 12 a.m. to 12 a.m. As a result, our sample collection period was shifted by 9 h (from 12 a.m. to 9 a.m.) from the Beijing EPB sampling period. Because these 9 h occurred during a relatively low emission period of the day (8), it introduces little uncertainty to the comparison, and our PM10 concentrations were wellcorrelated with the Beijing EPB PM10 concentrations at Wanliu (r2 ) 0.91, p < 0.001) and the Olympic Center (r2 ) 0.91, p < 0.001) as well as the Beijing EPB average for all of Beijing (r2 ) 0.92, p < 0.001) and the urban Beijing EPB sites within the 5th Ring Road of Beijing (r2 ) 0.90, p < 0.001) (ref 3, p 7590
9
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 43, NO. 19, 2009
5315, and Figure SI.3 and Table SI.1 of the Supporting Information). We note that a shift in PM concentration magnitudes will not change the trends our interpretation relied on. The correlations of Beijing EPB PM10 concentrations and our PM10 concentrations calculated by Tang et al. in their point 3 are incorrect because the sampling days were misaligned. Our PM2.5/PM10 ratios are within the range of previously published values for Beijing. We measured a PM2.5/PM10 ratio of 0.76 ( 0.05 (range 0.62-0.84) during the source control period and 0.75 ( 0.06 (range 0.64-0.86) during the nonsource control period, and these ratios are not statistically different (ref 3, p 5316 and Table 2). In Beijing, PM2.5/PM10 ratios of 0.29 to 0.85 have been measured by others at different times and different sites (7-12). No other PM2.5 concentrations in Beijing during our period of observation have been published, so a comparison between our values and others is not possible. Assessment of the Relative Importance of Meteorology and Source Control Measures. We defined “source control” and “non-source control” time periods with respect to restrictions in automobile traffic from available information (3). Quantitative information regarding other source control measures implemented during our period of observation is not available. Regression models have been previously used to describe the influence of meteorology (ref 3, p 5317) and traffic (13) on particulate matter concentrations. Gietl et al. demonstrate that in Munster, Germany, meteorology accounts for more of the variability in PM10 concentration than traffic (13). Our data indicate that some of the highest PM concentrations occurred during the source control periods, while some of the lowest PM concentrations occurred during the nonsource control time periods (ref 3, Figure 1). Clearly, this suggests that variables other than source control measures, including meteorology, played a significant role in the resulting PM concentrations. I welcome the publication of alternative approaches for assessing and quantifying the role of meteorology and source control measures in accounting for variation in Beijing PM concentrations during our period of observation. I stand by our conclusion that meteorology accounted for more of the variation in PM concentration than source control measures during our period of observation.
Literature Cited (1) Tang, T.; Shao, M.; Hu, M. Comment on “Atmospheric Particulate Matter Pollution during the 2008 Beijing Olympics”. Environ. Sci. Technol. 2009; DOI: 1021/es902217x. (2) Yao, X.; Xu, X.; Sabaliauskas, K.; Fang, M. Comment on “Atmospheric Particulate Matter Pollution during the 2008 Beijing Olympics”. Environ. Sci. Technol. 2009; DOI: 1021/ es902276p. (3) Wang, W. T.; Primbs, T.; Tao, S.; Simonich, S. L. M. Atmospheric particulate matter pollution during the 2008 Beijing Olympics. Environ. Sci. Technol. 2009, 43 (14), 5314– 5320. (4) Charron, A.; Harrison, R. M.; Moorcroft, S.; Booker, J. Quantitative interpretation of divergence between PM10 and PM2.5 mass measurement by TEOM and gravimetric (Partisol) instruments. Atmos. Environ. 2004, 38 (3), 415–423. (5) Green, D. C.; Fuller, G. W.; Baker, T. Development and validation of the volatile correction model for PM10: An empirical method for adjusting TEOM measurements for their loss of volatile particulate matter. Atmos. Environ. 2009, 43 (13), 2132–2141. (6) Turpin, B. J.; Saxena, P.; Andrews, E. Measuring and simulating particulate organics in the atmosphere: Problems and prospects. Atmos. Environ. 2000, 34 (18), 2983–3013. 10.1021/es902531w CCC: $40.75
2009 American Chemical Society
Published on Web 09/03/2009
(7) van Pinxteren, D.; Bruggemann, E.; Gnauk, T.; Iinuma, Y.; Muller, K.; Nowak, A.; Achtert, P.; Wiedensohler, A.; Herrmann, H. Size- and time-resolved chemical particle characterization during CARE Beijing 2006: Different pollution regimes and diurnal profiles. J. Geophys. Res., [Atmos.] 2009, 114. (8) Zhao, X. J.; Zhang, X. L.; Xu, X. F.; Xu, J.; Meng, W.; Pu, W. W. Seasonal and diurnal variations of ambient PM2.5 concentration in urban and rural environments in Beijing. Atmos. Environ. 2009, 43 (18), 2893–2900. (9) Sun, Y. L.; Zhuang, G. S.; Ying, W.; Han, L. H.; Guo, J. H.; Mo, D.; Zhang, W. J.; Wang, Z. F.; Hao, Z. P. The airborne particulate pollution in Beijing: Concentration, composition, distribution and sources. Atmos. Environ. 2004, 38 (35), 5991–6004. (10) Sun, Y. L.; Zhuang, G. S.; Tang, A. H.; Wang, Y.; An, Z. S. Chemical characteristics of PM2.5 and PM10 in haze-fog episodes in Beijing. Environ. Sci. Technol. 2006, 40 (10), 3148– 3155. (11) He, K. B.; Yang, F. M.; Ma, Y. L.; Zhang, Q.; Yao, X. H.; Chan, C. K.; Cadle, S.; Chan, T.; Mulawa, P. The characteristics of
PM2.5 in Beijing, China. Atmos. Environ. 2001, 35 (29), 4959– 4970. (12) Chan, C. Y.; Xu, X. D.; Li, Y. S.; Wong, K. H.; Ding, G. A.; Chan, L. Y.; Cheng, X. H. Characteristics of vertical profiles and sources of PM2.5, PM10, and carbonaceous species in Beijing. Atmos. Environ. 2005, 39 (28), 5113–5124. (13) Gietl, J. K.; Klemm, O. Analysis of traffic and meteorology on airborne particulate matter in Munster, northwest Germany. J. Air Waste Manage. Assoc. 2009, 59 (7), 809–818.
Staci L. Massey Simonich Department of Environmental & Molecular Toxicology and Department of Chemistry, Oregon State University, Corvallis, Oregon 97331-7301 ES902531W
VOL. 43, NO. 19, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
7591
