Chang-Fu Wu

Mortality risk attributable to high and low ambient temperature: a multicountry observational study.

Summary Background Although studies have provided estimates of premature deaths attributable to either heat or cold in selected countries, none has so far offered a systematic assessment across the whole temperature range in populations exposed to different climates. We aimed to quantify the total mortality burden attributable to non-optimum ambient temperature, and the relative contributions from heat and cold and from moderate and extreme temperatures. Methods We collected data for 384 locations in Australia, Brazil, Canada, China, Italy, Japan, South Korea, Spain, Sweden, Taiwan, Thailand, UK, and USA. We fitted a standard time-series Poisson model for each location, controlling for trends and day of the week. We estimated temperature–mortality associations with a distributed lag non-linear model with 21 days of lag, and then pooled them in a multivariate metaregression that included country indicators and temperature average and range. We calculated attributable deaths for heat and cold, defined as temperatures above and below the optimum temperature, which corresponded to the point of minimum mortality, and for moderate and extreme temperatures, defined using cutoffs at the 2·5th and 97·5th temperature percentiles. Findings We analysed 74 225 200 deaths in various periods between 1985 and 2012. In total, 7·71% (95% empirical CI 7·43–7·91) of mortality was attributable to non-optimum temperature in the selected countries within the study period, with substantial differences between countries, ranging from 3·37% (3·06 to 3·63) in Thailand to 11·00% (9·29 to 12·47) in China. The temperature percentile of minimum mortality varied from roughly the 60th percentile in tropical areas to about the 80–90th percentile in temperate regions. More temperature-attributable deaths were caused by cold (7·29%, 7·02–7·49) than by heat (0·42%, 0·39–0·44). Extreme cold and hot temperatures were responsible for 0·86% (0·84–0·87) of total mortality. Interpretation Most of the temperature-related mortality burden was attributable to the contribution of cold. The effect of days of extreme temperature was substantially less than that attributable to milder but non-optimum weather. This evidence has important implications for the planning of public-health interventions to minimise the health consequences of adverse temperatures, and for predictions of future effect in climate-change scenarios. Funding UK Medical Research Council.

Global variation in the effects of ambient temperature on mortality: a systematic evaluation

Background: Studies have examined the effects of temperature on mortality in a single city, country, or region. However, less evidence is available on the variation in the associations between temperature and mortality in multiple countries, analyzed simultaneously. Methods: We obtained daily data on temperature and mortality in 306 communities from 12 countries/regions (Australia, Brazil, Thailand, China, Taiwan, Korea, Japan, Italy, Spain, United Kingdom, United States, and Canada). Two-stage analyses were used to assess the nonlinear and delayed relation between temperature and mortality. In the first stage, a Poisson regression allowing overdispersion with distributed lag nonlinear model was used to estimate the community-specific temperature-mortality relation. In the second stage, a multivariate meta-analysis was used to pool the nonlinear and delayed effects of ambient temperature at the national level, in each country. Results: The temperatures associated with the lowest mortality were around the 75th percentile of temperature in all the countries/regions, ranging from 66th (Taiwan) to 80th (UK) percentiles. The estimated effects of cold and hot temperatures on mortality varied by community and country. Meta-analysis results show that both cold and hot temperatures increased the risk of mortality in all the countries/regions. Cold effects were delayed and lasted for many days, whereas heat effects appeared quickly and did not last long. Conclusions: People have some ability to adapt to their local climate type, but both cold and hot temperatures are still associated with increased risk of mortality. Public health strategies to alleviate the impact of ambient temperatures are important, in particular in the context of climate change.

Land use regression models for estimating individual NOx and NO2 exposures in a metropolis with a high density of traffic roads and population

This study is conducted to characterize the intra-urban distribution of NOx and NO2; develop land use regression (LUR) models to assess outdoor NOx and NO2 concentrations, using the ESCAPE modeling approach with locally specific land use data; and compare NOx and NO2 exposures for children in the Taipei Metropolis by the LUR models, the nearest monitoring station, and kriging methods based on data collected at the measurement sites. NOx and NO2 were measured for 2 weeks during 3 seasons at 40 sampling sites by Ogawa passive badges to represent their concentrations at urban backgrounds and streets from October 2009 to September 2010. Land use data and traffic-related information in different buffer zones were combined with measured concentrations to derive LUR models using supervised forward stepwise multiple regressions. The annual average concentrations of NOx and NO2 in Taipei were 72.4 ± 22.5 and 48.9 ± 12.2 μg/m(3), respectively, which were at the high end of all 36 European areas in the ESCAPE project. Spatial contrasts in Taipei were lower than those of the European areas in the ESCAPE project. The NOx LUR model included 6 land use variables, which were lengths of major roads within 25 m, 25-50 m, and 50-500 m, urban green areas within 300 m and 300-5,000 m, and semi-natural and forested areas within 500 m, with R(2)=0.81. The NO2 LUR model included 4 land use variables, which were lengths of major roads within 25 m, urban green areas within 100 m, semi-natural and forested areas within 500 m, and low-density residential area within 500 m, with R(2)=0.74. The LUR models gave a wider variation in estimating NOx and NO2 exposures than either the ordinary kriging method or the nearest measurement site did for the children of Taiwan Birth Cohort Study (TBCS) in Taipei.

Effects of Personal Exposure to Particulate Matter and Ozone on Arterial Stiffness and Heart Rate Variability in Healthy Adults

The effects on heart rate variability (HRV) and arterial stiffness from exposure to ambient particulate matter and ozone have not been studied simultaneously. The aim of this study was to analyze these effects with refined exposure estimates from personal measurements of ozone and size-resolved particulate matter mass concentrations. The authors recruited 17 mail carriers in a panel study in Taipei County, Taiwan, during February-March, 2007, and each subject was followed for 5-6 days. Personal ozone and size-fractionated particulate matter exposures were monitored during working hours while carriers delivered mail outdoors. Cardiovascular effects were evaluated with heart rate variability (HRV) indices and an arterial stiffness index, the cardio-ankle vascular index (CAVI). The authors used linear mixed models to examine the association between personal exposure data and the HRV index and CAVI. They found that an interquartile range increase in personal exposure to ozone and particulate matter of between 1.0 and 2.5 microm was associated with a 4.8% and 2.5% increase in CAVI, respectively, in the single-pollutant models. In contrast, the personal exposure data showed no significant effects on HRV. In 2-pollutant models, personal ozone exposure remained significantly associated with the CAVI measurements. The study results indicate that vascular function may be more sensitive to air pollutants than the autonomic balance.

Computed tomography of air pollutants using radial scanning path-integrated optical remote sensing

We propose a novel application of computed tomography (CT) for path-integrated optical remote sensing of air pollutants. We conducted a preliminary study with data obtained from simulated scanning of non-overlapping radial beam segments through Gaussian test distributions and experimentally measured test maps. The smooth basis function minimization (SBFM) algorithm, which fits parametric distributions rather than fitting individual pixel concentrations, was used to reconstruct two-dimensional concentration maps from this beam geometry. The results show that quite good reconstructions are possible with this approach. In contrast to the complex beam geometries proposed in the past for CT, this technique could be applied directly to air monitoring data from a variety of current optical sensing instruments. This development could vastly broaden the application of CT to obtain rapid reconstructions of ambient air pollution data.

Temperature Variability and Mortality: A Multi-Country Study.

Background: The evidence and method are limited for the associations between mortality and temperature variability (TV) within or between days. Objectives: We developed a novel method to calculate TV and investigated TV-mortality associations using a large multicountry data set. Methods: We collected daily data for temperature and mortality from 372 locations in 12 countries/regions (Australia, Brazil, Canada, China, Japan, Moldova, South Korea, Spain, Taiwan, Thailand, the United Kingdom, and the United States). We calculated TV from the standard deviation of the minimum and maximum temperatures during the exposure days. Two-stage analyses were used to assess the relationship between TV and mortality. In the first stage, a Poisson regression model allowing over-dispersion was used to estimate the community-specific TV-mortality relationship, after controlling for potential confounders. In the second stage, a meta-analysis was used to pool the effect estimates within each country. Results: There was a significant association between TV and mortality in all countries, even after controlling for the effects of daily mean temperature. In stratified analyses, TV was still significantly associated with mortality in cold, hot, and moderate seasons. Mortality risks related to TV were higher in hot areas than in cold areas when using short TV exposures (0–1 days), whereas TV-related mortality risks were higher in moderate areas than in cold and hot areas when using longer TV exposures (0–7 days). Conclusions: The results indicate that more attention should be paid to unstable weather conditions in order to protect health. These findings may have implications for developing public health policies to manage health risks of climate change. Citation: Guo Y, Gasparrini A, Armstrong BG, Tawatsupa B, Tobias A, Lavigne E, Coelho MS, Pan X, Kim H, Hashizume M, Honda Y, Guo YL, Wu CF, Zanobetti A, Schwartz JD, Bell ML, Overcenco A, Punnasiri K, Li S, Tian L, Saldiva P, Williams G, Tong S. 2016. Temperature variability and mortality: a multi-country study. Environ Health Perspect 124:1554–1559; http://dx.doi.org/10.1289/EHP149

A land use regression model for estimating the NO2 concentration in shanghai, China

Limited by data accessibility, few exposure assessment studies of air pollutants have been conducted in China. There is an urgent need to develop models for assessing the intra-urban concentration of key air pollutants in Chinese cities. In this study, a land use regression (LUR) model was established to estimate NO2 during 2008-2011 in Shanghai. Four predictor variables were left in the final LUR model: the length of major road within the 2-km buffer around monitoring sites, the number of industrial sources (excluding power plants) within a 10-km buffer, the agricultural land area within a 5-km buffer, and the population counts. The model R(2) and the leave-one-out-cross-validation (LOOCV) R(2) of the NO2 LUR models were 0.82 and 0.75, respectively. The prediction surface of the NO2 concentration based on the LUR model was of high spatial resolution. The 1-year predicted concentration based on the ratio and the difference methods fitted well with the measured NO2 concentration. The LUR model of NO2 outperformed the kriging and inverse distance weighed (IDW) interpolation methods in Shanghai. Our findings suggest that the LUR model may provide a cost-effective method of air pollution exposure assessment in a developing country.

Greenhouse gas emission reductions from domestic anaerobic digesters linked with sustainable sanitation in rural China.

Anaerobic digesters provide clean, renewable energy (biogas) by converting organic waste to methane, and are a key part of Chinas comprehensive rural energy plan. Here, experimental and modeling results are used to quantify the net greenhouse gas (GHG) reduction from substituting a household anaerobic digester for traditional energy sources in Sichuan, China. Tunable diode laser absorption spectroscopy and radial plume mapping were used to estimate the mass flux of fugitive methane emissions from active digesters. Using household energy budgets, the net improvement in GHG emissions associated with biogas installation was estimated using global warming commitment (GWC) as a consolidated measure of the warming effects of GHG emissions from cooking. In all scenarios biogas households had lower GWC than nonbiogas households, by as much as 54%. Even biogas households with methane leakage exhibited lower GWC than nonbiogas households, by as much as 48%. Based only on the averted GHG emissions over 10 years, the monetary value of a biogas installation was conservatively estimated at US

Evaluation and quality control of personal nephelometers in indoor, outdoor and personal environments

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Projections of temperature-related excess mortality under climate change scenarios

16.07 ton(-1) CO(2)-eq), which is available to partly offset construction costs. The interaction of biogas installation programs with policies supporting improved stoves, renewable harvesting of biomass, and energy interventions with substantial health cobenefits are discussed.