Journal
ENVIRONMENTAL RESEARCH
Volume 120, Issue -, Pages 27-32Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.envres.2012.08.007
Keywords
Black carbon; Fine particle; Time-series; Mortality
Funding
- National Basic Research Program (973 Program) of China [2011CB503802]
- Gong-Yi Program of China Meteorological Administration [GYHY201206027]
- Science and Technology Commission of Shanghai Municipality [11DZ2260900]
- Gong-Yi Program of China Ministry of Environmental Protection [201209008, 200809109]
- National Natural Science Foundation of China [30800892]
- Program for New Century Excellent Talents in University [NCET-09-0314]
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There is only limited monitoring data of black carbon for epidemiologic analyses. In the current study, we used the distributed lag models to evaluate the association between mortality outcomes (both total and cause-specific) and exposure to black carbon and fine particle (PM2.5) in Shanghai, China. During our research period, the mean daily concentrations of black carbon and PM2.5 were 3.9 mu g/m(3) and 53.9 mu g/m(3), respectively. The regression results showed that black carbon was significantly associated with total and cardiovascular mortality, but not with respiratory mortality. An inter-quartile range increase (2.7 mu g/m(3)) of black carbon corresponded to a 2.3% (95% confidence interval [CI]: 0.6-4.1), 3.2% (95% CI: 0.6-5.7), and 0.6% (95% CI: -4.5 to 5.7) increase in total, cardiovascular and respiratory mortality, respectively. When adjusted for PM2.5, the effects of black carbon increased and remained statistically significant; in contrast, the associations of PM2.5 with daily mortality decreased and became statistically insignificant after adjustment for black carbon. To our knowledge, this is the first study in China, or even in Asian developing countries, to report the acute effect of black carbon and PM2.5 on daily mortality simultaneously. Our findings suggest that black carbon is a valuable additional air quality indicator to evaluate the health risks of ambient particles. (c) 2012 Elsevier Inc. All rights reserved.
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