Background: Epidemiologic evidence for a causative association between black carbon (BC) and health outcomes is limited. Objectives: We estimated associations and exposure–response relationships between acute respiratory inflammation in schoolchildren and concentrations of BC and particulate matter with an aerodynamic diameter of ≤ 2.5 μm (PM2.5) in ambient air before and during the air pollution intervention for the 2008 Beijing Olympics. Methods: We measured exhaled nitric oxide (eNO) as an acute respiratory inflammation biomarker and hourly mean air pollutant concentrations to estimate BC and PM2.5 exposure. We used 1,581 valid observations of 36 subjects over five visits in 2 years to estimate associations of eNO with BC and PM2.5 according to generalized estimating equations with polynomial distributed-lag models, controlling for body mass index, asthma, temperature, and relative humidity. We also assessed the relative importance of BC and PM2.5 with two-pollutant models. Results: Air pollution concentrations and eNO were clearly lower during the 2008 Olympics. BC and PM2.5 concentrations averaged over 0–24 hr were strongly associated with eNO, which increased by 16.6% [95% confidence interval (CI), 14.1–19.2%] and 18.7% (95% CI, 15.0–22.5%) per interquartile range (IQR) increase in BC (4.0 μg/m3) and PM2.5 (149 μg/m3), respectively. In the two-pollutant model, estimated effects of BC were robust, but associations between PM2.5 and eNO decreased with adjustment for BC. We found that eNO was associated with IQR increases in hourly BC concentrations up to 10 hr after exposure, consistent with effects primarily in the first hours after exposure. Conclusions: Recent exposure to BC was associated with acute respiratory inflammation in schoolchildren in Beijing. Lower air pollution levels during the 2008 Olympics also were associated with reduced eNO.

The aerosol–planetary boundary layer (PBL) interaction was proposed as an important mechanism to stabilize the atmosphere and exacerbate surface air pollution. Despite the tremendous progress made in understanding this process, its magnitude and significance still have large uncertainties and vary largely with aerosol distribution and meteorological conditions. In this study, we focus on the role of aerosol vertical distribution in thermodynamic stability and PBL development by jointly using micropulse lidar, sun photometer, and radiosonde measurements taken in Beijing. Despite the complexity of aerosol vertical distributions, cloud-free aerosol structures can be largely classified into three types: well-mixed, decreasing with height, and inverse structures. The aerosol–PBL relationship and diurnal cycles of the PBL height and PM_2.5 associated with these different aerosol vertical structures show distinct characteristics. The vertical distribution of aerosol radiative forcing differs drastically among the three types, with strong heating in the lower, middle, and upper PBL, respectively. Such a discrepancy in the heating rate affects the atmospheric buoyancy and stability differently in the three distinct aerosol structures. Absorbing aerosols have a weaker effect of stabilizing the lower atmosphere under the decreasing structure than under the inverse structure. As a result, the aerosol–PBL interaction can be strengthened by the inverse aerosol structure and can be potentially neutralized by the decreasing structure. Moreover, aerosols can both enhance and suppress PBL stability, leading to both positive and negative feedback loops. This study attempts to improve our understanding of the aerosol–PBL interaction, showing the importance of the observational constraint of aerosol vertical distribution for simulating this interaction and consequent feedbacks.

The concentrations of fine particulate matter (PM) and ozone in Beijing often exceed healthful levels in recent years, therefore China is to taking steps to improve Beijing's air quality for the 2008 Olympic Games. In this paper, the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System was used to investigate a heavy air pollution episode in Beijing during 3–7 April 2005 to obtain the basic information of how heavy air pollution formed and the contributions of local sources and surround emissions. The modeling domain covered from East Asia with four nested grids with 81 to 3 km horizontal resolution focusing on urban Beijing. This was coupled with a regional emissions inventory with a 10 km resolution and a local 1 km Beijing emissions database. The trend of predicted concentrations of various pollutants agreed reasonably well with the observations and captured the main features of this heavy pollution episode. The simulated column concentration distribution of PM was correlated well with the MODIS remote sensing products. Control runs with and without Beijing emissions were conducted to quantify the contributions of non-Beijing sources (NBS) to the Beijing local air pollution. The contributions of NBS to each species differed spatially and temporally with the order of PM_2.5>PM₁₀>SO₂> soil for this episode. The percentage contribution of NBS to fine particle (PM_2.5) in Beijing was averaged about 39%, up to 53% at the northwest of urban Beijing and only 15% at southwest. The spatial distribution of NBS contributions for PM₁₀ was similar to that for PM_2.5, with a slightly less average percentage of about 30%. The average NBS contributions for SO₂ and soil (diameter between 2.5 μm and 10 μm) were 18% and 10%. In addition, the pollutant transport flux was calculated and compared at different levels to investigate transport pathway and magnitude. It was found that the NBS contribution correlated with the transport flux, contributing 60% of PM₁₀ concentration in Beijing at the time of transport flux peak during a strong episode with a transport path from southwest to northeast.