between human health and air pollution. Studies conducted in Asian countries indicate that associations are similar to those in Western countries (Health Effects Institute 2004). Nevertheless, local authorities need population- specific information on current health risks of air pollution to develop air pollution control strategies adapted to local conditions. The aim of this study was to analyze the role of different particle size fractions in the size range of 3 nm–1 mμ with respect to respi - ratory health in Beijing, China. Data and Methods The study was conducted from March 2004 to December 2006 (1,036 days) in Beijing, China. Data. Particle measurements were per- formed at a background measuring station on the campus of the Peking University (PKU) located in the northwestern part of Beijing in the Haidian district (Figure 1). The campus area is primarily residential and commercial, without heavy traffic or industrial sources. The inlet of the sampling system was placed 20 m above ground on top of a six-floor building located > 500 m away from major roads. Local emission sources within a 1-km radius include vehicular traffic and fuel combustion for domestic cooking, heating, and construc- tion. A study of the spatial variability of PM2.5 mass and chemical composition in 1999–2002 showed only minor differences between a PKU campus site and an urban measurement site located approximately 10 km southeast from the PKU measurement site. The setup of the measurement station is described in detail else- where (e.g., Wehner et al. 2004, 2008). We continuously measured aerosol num- ber size distributions between 3 nm and 1 mμ. Sampling was done using a Twin Differential Mobility Particle Sizer (TDMPS; Birmili et al. 1999), consisting of two Hauke-type differen- tial mobility analyzers and two condensation particle counters (models 3010 and 3025; TSI Inc., St. Paul, MN, USA) which covered the size range from 3 nm to 800 nm (mobility diameter) and an Aerodynamic Particle Sizer (APS; model 3321; TSI Inc.) which meas- ured particles between 800 nm and 1 μm (aerodynamic diameter). To combine both measurements, APS data were transformed from aerodynamic diameter to Stokes diam- eter assuming an effective particle density of 1.7 g/cm3 for the particles > 800 nm, because these particles are dominated by sulfate and crustal material in Beijing (Yao et al. 2003). A low-flow PM10 inlet was used to minimize contamination by large dust particles. The ambient aerosol was dried in a diffusion drier before entering the air-conditioned laboratory to avoid condensation of water in the inlet systems during warm and humid days in sum- mertime. The data were corrected for losses due to diffusion and sedimentation within the inlet line. Size-dependent losses for the TDMPS inlet line were estimated using empirical par- ticle loss corrections (diffusion and gravita- tion) from Willeke and Baron (1993). Losses of 4-nm and 10-nm particles were estimated to be 35% and approximately 10%, respectively. Number size distributions were converted to particle number concentrations (PNC) and particle surface area concentrations (PSC) assuming spherical particles. For our analy- sis, we calculated daily means for 3–10 nm, 10–30 nm, 30–50 nm, 50–100 nm, 100– 300 nm, and 300–1,000 nm size fractions. Total particle number or surface area concen- tration were computed as the sum of all frac- tions, and UFP as the sum of particle number concentrations < 100 nm. In addition, daily particle mass (PM10), sulfur dioxide (SO2), and nitrogen diox- ide (NO2) concentrations were gath - ered from the monitoring network of the Beijing Environmental Protection Bureau. Measurements were obtained as averages of eight fixed monitoring sites located in differ- ent parts of the urban area (Figure 1). Daily mean meteorologic data from a measurement station near the Beijing Capital International Airport (Figure 1) were gathered from an internet weather service (Weather Underground 2009) because measurements from the meteorologic station closest to the particulate measurement station were incom- plete. The Pearson correlation coefficients for valid days between the two data sources were 0.99 and 0.95 for daily air temperature and relative humidity, respectively, indicating a good agreement. We collected data on hospital emergency room visits (ERV) from the Peking University Airport–meteorological measurement site PNC measurement site Beijing municipal environmental monitoring sites Peking University Third Hospital Beijing administrative area Beijing urban area Haidian district Particles and respiratory health Third Hospital, located in the Haidian district (Figure 1), where patients within 10 km of the measurement site were likely to be treated (personal communication with hospital doc- tors). The data acquisition system of the hos- pital recorded only patients who did not stay longer than 1 day. A standardized form was completed by medically trained study per- sonnel at PKU, School of Public Health, by abstracting the data from the medical records. A database was built on the basis of these files, and respiratory clinical end points were coded according to the International Classification of Diseases, 10th Revision (ICD-10) [World Health Organization (WHO) 1993] for respi- ratory diseases (ICD-10 codes J00–J99). Total respiratory ERV comprise acute upper respira- tory infections (J00–J06), pneumonia (J18), acute bronchitis (J20), other diseases of the upper respiratory tract (J30–J39), and chronic lower respiratory diseases (J40–J47). In addi- tion, location of permanent residence was recorded for each case; based on this infor- mation, only patients from Haidian district were considered for further analysis. Because of an outbreak of the severe acute respira- tory syndrome in China in 2003, all patients with body temperature > 38°C were sepa- rately treated in the hospital, and these cases were excluded. Assignment of the diagnoses to ICD-10 disease categories were quality- assured by a nosological expert from the Third Hospital, resulting in a good agreement, as the percentage of misclassification was about 4%. Statistical analysis. We applied a time-se- ries analysis using generalized additive Poisson regression models (Hastie and Tibshirani 1987) to estimate associations between air pollutants and respiratory ERV. 20 km N Figure 1. Map of Beijing, the study area, with administrative (outline) and urban (inner area) area, Haidian district (grey), and measurement stations. Environmental Health Perspectives • volume 119 | number 4 | April 2011 509