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Objective: To investigate spatial-temporal distribution characteristics of air quality indexes( AQI) in Shenzhen City and provide scientific basis for control of air pollution., Methods: The monitoring data of AQI collected at the 19 monitoring posts in Shenzhen City from 2014 to 2016 were pooled and analyzed, and daily, seasonal and annual means of AQI at each monitoring post were forked out. The theory of spatial autocorrelation analysis was adopted in analyzing strength of the spatial autocorrelation and spatial clustering patterns of AQI., Results: The median of AQI of Shenzhen City was50. 0, and the air quality level of Shenzhen City was level 2. PM&#95;(2. 5) was the primary air pollutant in 2014, and O&#95;3 was the primary air pollutant in 2015 and 2016 respectively. From the time distribution, the air quality in Shenzhen City was the worst in the winter but the best in the summer, and the air quality in night was worse than the day. Spatial autocorrelation analysis showed that there was positive spatial autocorrelation of AQI in Shenzhen. The global moran's I of AQI was 0. 167( Z = 2. 000, P < 0. 05), and the greary coefficient was 0. 801( Z = 1. 711, P < 0. 05). The local moran's I of AQI was 1. 027( P < 0. 05) in Guangming New District. The moran scatter plot of AQI in Guangming New District was in the first quadrant, and appeared to be in a high-high clustering pattern. The moran scatter plot of AQI in Yantian District was in the third quadrant, and appeared to be in a low-low clustering pattern., Conclusion: The air quality of Shenzhen City was better. PM&#95;(2. 5) and O&#95;3 were the primary air pollutant. It is necessary to emphasize and strengthen the prevention and control of air pollution in Winter, especially in several administrative districts of the northwest of Shenzhen City.

Large and growing literature has explored whether temperature modified the effect of particular matter (PM) on mortality, but results of the modification effect are inconsistent. In this study, we reviewed information from 29 studies to get the qualitative evidence of the modification effects of temperature on PM to mortality, and the data from 16 of the 29 studies were extracted to conduct a meta-analysis. Temperatures were grouped into three level: "low", "middle" and "high" according to the original studies. The random effect model was used in the meta-analysis with the relative risk (RR) as the measure indicator. The RRs (95% confidence intervals, CIs) for non-accidental death, cardiovascular death and respiratory death per 10 μg/m 3 increase in PM 10 were 1.004 (1.003, 1.006), 1.005 (1.003,1.007), and 1.005 (1.000,1.010) in the low temperature level, 1.005 (1.004,1.006), 1.005 (1.004,1.007), and 1.008 (1.006, 1.010) in the middle temperature level, and 1.012 (1.010, 1.015), 1.016 (1.010, 1.022) and 1.019 (1.010,1.028) in the high temperature level, respectively. In conclusion, moderate evidence exists that temperature modifies the effect of PM 10 on mortality. The effect of PM 10 on respiratory death was the greatest, while the effect on non-accidental death was the smallest in the same temperature level. In addition, the effects of PM 10 on all the three kinds of mortality were the biggest in the high-temperature level, and the smallest in the low-temperature level., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The effect modification of meteorological factors on the association between ambient Sulphur dioxide (SO 2 ) and mortality is critical for designing intervention policy. Existing studies did not result in consistent conclusions on the effect modification, and Years of life lost (YLLs) was rarely used as a health impact indicator to examine the modifying effect. This study aims to estimate the mean air temperature and relative humidity modification effects on the impact of SO 2 on daily mortality and YLLs in Chengdu, China. Mortality, YLLs, air pollution and meteorological data were collected for 2011-2014. Three analytical approaches based on generalized additive models (GAMs) were used, including bivariate response surface model, product term model, and stratification model. We found that the effects of SO 2 on mortality and YLLs depended on temperature at various lags, but did not depend on relative humidity. SO 2 exhibited larger adverse effects on mortality in high temperature level (22.8-29.4°C) days than in low temperature level (-0.3-9.3°C) days, with a 10μg/m 3 increment in SO 2 , non-accidental death increased by 0.8% (0.001, 0.015)at low temperature level, but increased by 1.4% (0.005, 0.024) at high temperature level. On the contrary, SO 2 showed greater adverse effects on YLLs in low temperature days than in high temperature days, with a 10μg/m 3 increment in SO 2 , non-accidental YLL increased by 40.580 (31.478, 49.682) at high temperature level, but increased by -2.703 (-14.668, 9.261) at low temperature level. We concluded that the effect of SO 2 on mortality and YLLs may depend on temperature in Chengdu, China. Our results highlight the importance of considering the interaction between SO 2 and temperature on health outcomes in future research. Also, policy makers should enhance the emission control of SO 2 in extreme temperature days in Chengdu., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Exposure to ambient air pollution has been clearly linked to adverse reproductive outcome and fecundation index, but its effects on male semen quality are still uncertain. In this study, we reviewed information from ten studies to get the qualitative evidence of the influence of the ambient air pollution on sperm quality and collected data from six of the ten studies to conduct meta-analysis. The original studies classified participants into different exposure levels and the highest and lowest expose levels were chosen as high expose and low expose groups, respectively. The random-effect model was used in the meta-analysis with the weight mean difference (WMD) as the measure indicator. The WMDs (95% confidence intervals, CIs) of sperm volume, sperm count, semen concentration, sperm progressive motility, total motility, and normal morphology were 0.09 (-0.04, 0.23), 0.46 (-4.47, 5.39), -8.21 (-20.38, 3.96), -7.76 (-16.26, 0.74), -7.61 (-16.97, 1.74) and -3.40 (-7.42, 0.62), respectively. In conclusion, although the differences are not statistically significant between the two groups, the overall trends and evidence from this review indicate the chronic exposure to ambient pollutants at high level may alter men sperm quality., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Large and growing literature has explored whether temperature modified the effect of particular matter (PM) on mortality, but results of the modification effect are inconsistent. In this study, we reviewed information from 29 studies to get the qualitative evidence of the modification effects of temperature on PM to mortality, and the data from 16 of the 29 studies were extracted to conduct a meta-analysis. Temperatures were grouped into three level: "low", "middle" and "high" according to the original studies. The random effect model was used in the meta-analysis with the relative risk (RR) as the measure indicator. The RRs (95% confidence intervals, CIs) for non-accidental death, cardiovascular death and respiratory death per 10 μg/m3 increase in PM10 were 1.004 (1.003, 1.006), 1.005 (1.003,1.007), and 1.005 (1.000,1.010) in the low temperature level, 1.005 (1.004,1.006), 1.005 (1.004,1.007), and 1.008 (1.006, 1.010) in the middle temperature level, and 1.012 (1.010, 1.015), 1.016 (1.010, 1.022) and 1.019 (1.010,1.028) in the high temperature level, respectively. In conclusion, moderate evidence exists that temperature modifies the effect of PM10 on mortality. The effect of PM10 on respiratory death was the greatest, while the effect on non-accidental death was the smallest in the same temperature level. In addition, the effects of PM10 on all the three kinds of mortality were the biggest in the high-temperature level, and the smallest in the low-temperature level [ABSTRACT FROM AUTHOR]

Attributable risk is an important indicator for planning and evaluating public health interventions. However, most current measures of the attributable risk of air pollutants have not considered temporal relationships between exposure and risk. More importantly, limited information is available regarding the attributable risk due to ambient air pollutants in basin regions like the Sichuan Basin, China. To quantify the association between PM 10 and deaths in the Basin region, we used a measure proposed recently within the framework of the distributed lag non-linear model to estimate the attributable risk in Chengdu, China. Meanwhile, we examined the association between PM 10 and years of life lost (YLL). Our analysis showed that population-attributable fractions for non-accidental, respiratory, and cardiovascular mortality were 0.569% (95% CI: − 3.474%, 4.374%), 0.695% (95% CI: − 5.260%, 6.457%), and 0.631% (95% CI: − 6.973%, 7.390%), respectively. On average, a 1 μg/m 3 increase in PM 10 was associated with cumulative increases of 0.26893, 0.30437, and 0.21924 YLL for non-accidental, respiratory, and cardiovascular mortality, respectively, referring to 20 μg/m 3 . In addition, we found an inverse U-shaped pattern for the cumulative risk with 350 μg/m 3 as the reverse point. With a 1 μg/m 3 increase in PM 10 , YLL changed more significantly than mortality. Moreover, PM 10 demonstrated remarkable effects on YLL among men and the elderly. [ABSTRACT FROM AUTHOR]