Runkui Li

Multi-site time series analysis of acute effects of multiple air pollutants on respiratory mortality: a population-based study in Beijing, China.

In large cities in China, the traffic-related air pollution has become the focus of attention, and its adverse effects on health have raised public concerns. We conducted a study to quantify the association between exposure to three major traffic-related pollutants - particulate matter < 10 μm in aerodynamic diameter (PM10), carbon monoxide (CO) and nitrogen dioxide (NO2) and the risk of respiratory mortality in Beijing, China at a daily spatiotemporal resolution. We used the generalized additive models (GAM) with natural splines and principal component regression method to associate air pollutants with daily respiratory mortality, covariates and confounders. The GAM analysis adjusting for the collinearity among pollutants indicated that PM10, CO and NO2 had significant effects on daily respiratory mortality in Beijing. An interquartile range increase in 2-day moving averages concentrations of day 0 and day 1 of PM10, CO and NO2 corresponded to 0.99 [95% confidence interval (CI): 0.30, 1.67], 0.89 (95% CI: 0.27, 1.51) and 0.95 (95% CI: 0.29, 1.61) percent increase in daily respiratory mortality, respectively. The effects were varied across the districts. The strongest effects were found in two rural districts and one suburban district but significant in only one district. In conclusion, high level of several traffic-related air pollutants is associated with an increased risk of respiratory mortality in Beijing over a short-time period. The high risk found in rural areas suggests a potential susceptible sub-population with undiagnosed respiratory diseases in these areas. Although the rural areas have relatively lower air pollution levels, they deserve more attention to respiratory disease prevention and air pollution reduction.

The association between ambient air pollution and daily mortality in Beijing after the 2008 olympics: a time series study.

In recent decades, ambient air pollution has been an important public health issue in Beijing, but little is known about air pollution and health effects after the 2008 Beijing Olympics. We conduct a time-series analysis to evaluate associations between daily mortality (nonaccidental, cardiovascular and respiratory mortality) and the major air pollutants (carbon monoxide, nitrogen dioxide and particulate matter less than 10 µm in aerodynamic diameter) in Beijing during the two years (2009∼2010) after the 2008 Beijing Olympics. We used generalized additive model to analyze relationship between daily mortality and air pollution. In single air pollutant model with two-day moving average concentrations of the air pollutants, increase in their interquartile range (IQR) associated with percent increase in nonaccidental mortality, 2.55 percent [95% confidence interval (CI): 1.99, 3.11] for CO, 2.54 percent (95% CI: 2.00, 3.08) for NO2 and 1.80 percent (95% CI: 1.21, 2.40) for PM10, respectively; increases in the IQR of air pollutant concentrations associated with percent increase in cardiovascular mortality, 2.88 percent (95% CI: 2.10,3.65) for CO, 2.63 percent (95% CI: 1.87, 3.39) for NO2 and 1.72 percent (95% CI: 0.88, 2.55) for PM10, respectively; and increase in IQR of air pollutant concentrations associated with respiratory mortality, 2.39 percent (95% CI: 0.68, 4.09) for CO, 1.79 percent (95% CI: 0.11, 3.47) for NO2 and 2.07 percent (95% CI: 0.21, 3.92) for PM10, respectively. We used the principal component analysis to avoid collinearity of varied air pollutants. In addition, the association stratified by sex and age was also examined. Ambient air pollution remained a significant contributor to nonaccidental and cardiopulmonary mortalities in Beijing during 2009∼2010.

Effect modification of the association between temperature variability and daily cardiovascular mortality by air pollutants in three Chinese cities

There is limited evidence showing the mortality effects of temperature variability (TV) on cardiovascular diseases. The joint effects between TV and air pollutants are also less well-established. This study aims to assess the effect modification of TV-cardiovascular mortality by air pollutants in three Chinese cities (Beijing, Nanjing and Chengdu). Data of daily mortality, air pollutants and meteorological factors from 2008 to 2011 was collected from each city. TV was calculated as the standard deviation of daily maximum and minimum temperatures over exposure days. The city-specific effect estimates of TV on cardiovascular mortality were calculated using a quasi-Poisson regression model, adjusting for potential confounders (e.g., seasonality and temperature). An interaction term of TV and a three-level air pollutants stratum indicator was included in the models. Effect modifications by air pollutants were assessed by comparing the estimates of TVs effect between pollutant stratums and calculating the corresponding 95% confidential interval of the differences. Multivariate meta-analysis was conducted to obtain the pooled estimates. The data showed that TV was associated with increased risk of cardiovascular mortality, especially for longer TV exposure days (0-8 days, TV08). This association was still observed after adjusting for air pollutants on current day or the previous two days. Stronger estimates were observed in females, but no significant difference between males and females was detected, indicating the absence of evidence of effect modification by gender. Estimates of TV-cardiovascular mortality varied across two season periods (warm and cool season) and age groups, but the evidence of effect modification by age and seasons was absent. Regarding the effect modification of TV-cardiovascular mortality association by air pollutants, a significant effect modification was identified for PM10, but not for NO2 and SO2 in the whole population for all TV exposure days. This finding also persisted in subgroups, specifically in females and the elderly.

Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality: a time-series study

Objective To demonstrate an application of Bayesian model averaging (BMA) with generalised additive mixed models (GAMM) and provide a novel modelling technique to assess the association between inhalable coarse particles (PM10) and respiratory mortality in time-series studies. Design A time-series study using regional death registry between 2009 and 2010. Setting 8 districts in a large metropolitan area in Northern China. Participants 9559 permanent residents of the 8 districts who died of respiratory diseases between 2009 and 2010. Main outcome measures Per cent increase in daily respiratory mortality rate (MR) per interquartile range (IQR) increase of PM10 concentration and corresponding 95% confidence interval (CI) in single-pollutant and multipollutant (including NOx, CO) models. Results The Bayesian model averaged GAMM (GAMM+BMA) and the optimal GAMM of PM10, multipollutants and principal components (PCs) of multipollutants showed comparable results for the effect of PM10 on daily respiratory MR, that is, one IQR increase in PM10 concentration corresponded to 1.38% vs 1.39%, 1.81% vs 1.83% and 0.87% vs 0.88% increase, respectively, in daily respiratory MR. However, GAMM+BMA gave slightly but noticeable wider CIs for the single-pollutant model (−1.09 to 4.28 vs −1.08 to 3.93) and the PCs-based model (−2.23 to 4.07 vs −2.03 vs 3.88). The CIs of the multiple-pollutant model from two methods are similar, that is, −1.12 to 4.85 versus −1.11 versus 4.83. Conclusions The BMA method may represent a useful tool for modelling uncertainty in time-series studies when evaluating the effect of air pollution on fatal health outcomes.

Acute Effects of Nitrogen Dioxide on Cardiovascular Mortality in Beijing : An Exploration of Spatial Heterogeneity and the District-specific Predictors

The exploration of spatial variation and predictors of the effects of nitrogen dioxide (NO2) on fatal health outcomes is still sparse. In a multilevel case-crossover study in Beijing, China, we used mixed Cox proportional hazard model to examine the citywide effects and conditional logistic regression to evaluate the district-specific effects of NO2 on cardiovascular mortality. District-specific predictors that could be related to the spatial pattern of NO2 effects were examined by robust regression models. We found that a 10 μg/m3 increase in daily mean NO2 concentration was associated with a 1.89% [95% confidence interval (CI): 1.33–2.45%], 2.07% (95% CI: 1.23–2.91%) and 1.95% (95% CI: 1.16–2.72%) increase in daily total cardiovascular (lag03), cerebrovascular (lag03) and ischemic heart disease (lag02) mortality, respectively. For spatial variation of NO2 effects across 16 districts, significant effects were only observed in 5, 4 and 2 districts for the above three outcomes, respectively. Generally, NO2 was likely having greater adverse effects on districts with larger population, higher consumption of coal and more civilian vehicles. Our results suggested independent and spatially varied effects of NO2 on total and subcategory cardiovascular mortalities. The identification of districts with higher risk can provide important insights for reducing NO2 related health hazards.

A Two-Stage Method to Estimate the Contribution of Road Traffic to PM2.5 Concentrations in Beijing, China

Background: Fine particulate matters with aerodynamic diameters smaller than 2.5 micrometers (PM2.5) have been a critical environmental problem in China due to the rapid road vehicle growth in recent years. To date, most methods available to estimate traffic contributions to ambient PM2.5 concentration are often hampered by the need for collecting data on traffic volume, vehicle type and emission profile. Objective: To develop a simplified and indirect method to estimate the contribution of traffic to PM2.5 concentration in Beijing, China. Methods: Hourly PM2.5 concentration data, daily meteorological data and geographic information were collected at 35 air quality monitoring (AQM) stations in Beijing between 2013 and 2014. Based on the PM2.5 concentrations of different AQM station types, a two-stage method comprising a dispersion model and generalized additive mixed model (GAMM) was developed to estimate separately the traffic and non-traffic contributions to daily PM2.5 concentration. The geographical trend of PM2.5 concentrations was investigated using generalized linear mixed model. The temporal trend of PM2.5 and non-linear relationship between PM2.5 and meteorological conditions were assessed using GAMM. Results: The medians of daily PM2.5 concentrations during 2013–2014 at 35 AQM stations in Beijing ranged from 40 to 92 μg/m3. There was a significant increasing trend of PM2.5 concentration from north to south. The contributions of road traffic to daily PM2.5 concentrations ranged from 17.2% to 37.3% with an average 30%. The greatest contribution was found at AQM stations near busy roads. On average, the contribution of road traffic at urban stations was 14% higher than that at rural stations. Conclusions: Traffic emissions account for a substantial share of daily total PM2.5 concentrations in Beijing. Our two-stage method is a useful and convenient tool in ecological and epidemiological studies to estimate the traffic contribution to PM2.5 concentrations when there is limited information on vehicle number and types and emission profile.

Sediment Delivery across Multiple Spatio-temporal Scales in an Agriculture Watershed of the Chinese Loess Plateau

There is a consensus that sediment delivery ratio in the Chinese Loess Plateau is close to 1 at the inter-annual timescale. However, little information is available about the sediment delivery at finer timescales. We evaluated the sediment delivery from plots to watersheds at the event or intra-annual, annual, and inter-annual timescales within the Wudinghe river basin, a 30,261 km2 basin in the Loess Plateau. We calculated the ratio of sediment output to sediment input and presented the temporal change of the channel morphology to determine whether sediment deposition occurs. Although a single flood event frequently has a sediment yield exceeding 10,000 t km−2, sediment deposition rarely occurs except during some small runoff events (sediment yield < 5000 t km−2) or dry years (sediment yield < 10,000 t km−2) when moving from slopes up to the main channels of the Wudinghe River. This observation suggests a sediment delivery ratio close to 1 even at the event or intra-annual and the annual timescales, but not necessarily at the interannual timescale. Such a high sediment delivery ratio can be related to hyper-concentrated flows, which have very strong sediment transport capacity even at low flow strength. Because hyper-concentrated flows are well-developed in the whole Loess Plateau, a sediment delivery ratio close to 1 below the interannual timescale possibly remains true for other rivers in the Loess Plateau.

Ambient Fine Particulate Matter Exposure and Risk of Cardiovascular Mortality: Adjustment of the Meteorological Factors

Few studies have explicitly explored the impacts of the extensive adjustment (with a lag period of more than one week) of temperature and humidity on the association between ambient fine particulate matter (PM2.5) and cardiovascular mortality. In a time stratified case-crossover study, we used a distributed lag nonlinear model to assess the impacts of extensive adjustments of temperature and humidity for longer lag periods (for 7, 14, 21, 28 and 40 days) on effects of PM2.5 on total cardiovascular mortality and mortality of cerebrovascular and ischemic heart disease and corresponding exposure-response relationships in Beijing, China, between 2008 and 2011. Compared with results only controlled for temperature and humidity for 2 days, the estimated effects of PM2.5 were smaller and magnitudes of exposure-response curves were decreased when longer lag periods of temperature and relative humidity were included for adjustments, but these changes varied across subpopulation, with marked decreases occurring in males and the elderly who are more susceptible to PM2.5-related mortalities. Our findings suggest that the adjustment of meteorological factors using lag periods shorter than one week may lead to overestimated effects of PM2.5. The associations of PM2.5 with cardiovascular mortality in susceptible populations were more sensitive to further adjustments for temperature and relative humidity.

The spatial variation in the effects of air pollution on cardiovascular mortality in Beijing, China

Owing to lack of data from multiple air quality monitoring stations, studies about spatial association between concentrations of ambient pollutants and mortality in China are rare. To investigate the spatial variation of association between concentrations of particulate matter less than 10 μm in aerodynamic diameter (PM10), nitrogen dioxide (NO2) and carbon monoxide (CO) and cardiovascular mortality in Beijing, China, we collected data including daily deaths, concentrations of PM10, NO2 and CO, and meteorological factors from 1 January 2009 to 31 December 2010 in all 16 districts of Beijing. Generalized additive model (GAM) and generalized additive mixed model (GAMM) were used to examine the citywide and district-specific effects of PM10, NO2 and CO on cardiovascular mortality. The citywide effect derived from GAMM was lower than that derived from GAM, and the strongest effects were identified for 2-day moving average lag 0–1. The interquartile increases in concentrations of PM10, NO2 and CO were associated with 2.46 (95% confidence interval (CI), 1.22–3.72), 4.11 (95%CI, 2.82–5.42) and 2.23 (95%CI, 1.14–3.33) percentage increases in daily cardiovascular mortality by GAMM, respectively. The relative risk of each district compared with reference district was generally statistically significant. The death risk associated with air pollutants varies across different geographic districts in Beijing. The data indicate that the risk is high in suburban areas and rural counties. We found significant and spatially varied adverse effects of air pollution on cardiovascular deaths across the rural and urban areas in Beijing.

Linear spectral unmixing using endmember coexistence rules and spatial correlation

ABSTRACT Mixed pixels are often formed when surface materials are smaller than the spatial resolution of a sensor, or two or more ground features fall within a pixel. Spectral unmixing, decomposing a mixed pixel into a set of endmembers and their corresponding abundance fractions, is an important method for extracting the underlying spectral and spatial information from remote sensing images. Recent studies have shown that it is difficult to increase the accuracy of unmixing using single pixel processing. Here, we suggest combining information on the fundamental interrelations of ground components and a priori knowledge on how ground components co-exist or exclude each other according to general geographic and geomorphic relations with spectral information may allow improved unmixing. Therefore, we propose a novel spectral unmixing method to estimate endmember abundances based on linear spectral mixing model with endmember coexistence rules and spatial correlation (LSMM-R&C). This method was implemented by incorporating endmember coexistence rules along with spatial correlation into a weighted least square method. Experiments with both synthetic and real satellite images were carried out to verify the proposed method, and its performance was also evaluated in comparison to the commonly used LSMM (linear spectral mixture method), LAU (local adaptive unmixing), ISU (iterative spectral unmixing) and ISMA (iterative spectral mixture analysis) methods. LSMM-R&C showed the smallest error, and was more effective at revealing the detailed spatial distribution of endmembers’ abundance, showing high potential for solving the problem of spatial heterogeneity among neighbouring pixels.