[Effects of Interaction between PM2.5 and O 3 8-h max on Mortality of Cardiovascular Diseases in Chengdu].

OBJECTIVE: To explore the health risks of the interactive effects between PM2.5 and ozone on cardiovascular mortality in Chengdu. METHODS: Daily data on the mortality of cardiovascular diseases, including data for both men and women, during 2014-2016 were collected. The meteorological data, the daily average of particulate matter with aerodynamic diameter less than 2.5 micrometers (PM2.5), and the daily ozone 8 h maximum concentration (O 3 8-h max) in Chengdu of the same period were also collected. Generalized Additive Models (GAMs) were adopted to explore the respective adverse health effects of PM2.5 and O 3 8-h max and the synergistic effects between PM2.5 and O 3 8-h max on the mortality of cardiovascular diseases in the city. RESULTS: The highest health risks of PM2.5 and O 3 8-h max for mortality of cardiovascular diseases were found to be the strongest for the cumulative effect of the lag of one day (lag01). For every 10 µg/m 3 increment in the mass concentration of PM2.5 (lag01), the associated increase in risks for total, male, and female cardiovascular mortalities was 0.35%, 0.26% and 0.38%, respectively. For every 10 µg/m 3 increment in the mass concentration of O 3 8-h max (lag01), the associated increase in risks for total, male, and female cardiovascular mortalities was 0.66%, 0.43%, and 1.05%, respectively. The total, male, and female cardiovascular mortalities all reached their maximum values when high concentration of PM2.5 coexisted with high concentrations of O 3 8-h max. CONCLUSION: There was a synergistic amplification effect between high concentrations of PM2.5 and high concentrations of O 3 8-h max on cardiovascular mortality.

[Interactive Effects of the Influencing Factors on the Changes of O3 Concentrations Based on GAMs Model in Chengdu].

To explore the influence characteristics of the interaction effects between meteorological factors on ozone(O3) concentration in Chengdu, daily air pollutants and meteorological data from 2014 to 2019 were collected. Generalized additive models(GAMs) were adopted to explore the effects of different factors on O3 concentration. The results showed that the relationship between O3 and maximum temperature, sunshine hours, relative humidity, wind speed, precipitation, maximum mixed depth(MMD), and ventilation coefficient(VC) was non-linear. Specifically, the maximum temperature, sunshine hours, MMD, and relative humidity had a significant influence on O3 concentration throughout the year. It is worth noting that the influence of relative humidity and precipitation on O3 concentration during summer was more significant than that for the whole year. In the multi-meteorological factors GAMs of O3 concentration, the meteorological factors mentioned above, except average wind, had significant impacts on O3 concentration change. For the whole year, the judgment coefficient(R2) was 0.849 and the variance explanation rate was 85.1%. The maximum temperature was the most important influencing factor on O3 concentration throughout the year. During summer, corresponding R2 was 0.811 and the explanation rate of variance was 81.3%; however, maximum temperature and MMD were the dominant meteorological factors. In the interaction GAMs, for the whole year, the interaction between maximum temperature and sunshine hours, relative humidity, and precipitation, and the interaction between sunshine hours and MMD had a significant impact on O3 concentrations. The interaction between maximum temperature and sunshine hours played a leading role in changes of O3 concentration. The high temperature+strong radiation+MMD(about 2000 m) +no precipitation were conducive to the formation of O3 concentration, but in summer, only the maximum temperature, sunshine hours, and VC had the most significant effect on the O3 concentration, and strong high temperatures+strong radiation+the little horizontal wind in summer were conducive to the formation of O3 concentration near the surface. In summary, GAMs model can not only be used to identify the dominant influencing factors of O3 pollution, but also quantitatively analyze the influence of single effects and interaction of influencing factors on O3 concentration, which has great significance for the prevention and control of O3 pollution.

Mortality Risk Attributed to Ambient Temperature in Nanjing, China.

We examined the attributed fractions of all-cause, cardiovascular, and respiratory mortality that were attributed to extreme and moderate cold and heat during 2010-2016 in Nanjing. Our results showed that 12.81%, 19.78%, and 25.33% of all-cause, cardiovascular, and respiratory mortalities, respectively, were attributed to temperature. The highest attributed fractions for three types of mortality were at 4 ℃ and the attributed fractions were high around 4 ℃, which falls within the moderate cold temperatures. Although moderate cold has lower RR than extreme cold, it occurred on more days than did extreme cold. Therefore, health burden caused by moderate cold requires further attention in the future.

Association between Ambient Air Pollution and Hospital Emergency Admissions for Respiratory and Cardiovascular Diseases in Beijing: a Time Series Study.

OBJECTIVE: To investigate the association between ambient air pollution and hospital emergency admissions in Beijing. METHODS: In this study, a semi-parametric generalized additive model (GAM) was used to evaluate the specific influences of air pollutants (PM10, SO2, and NO2) on hospital emergency admissions with different lag structures from 2009 to 2011, the sex and age specific influences of air pollution and the modifying effect of seasons on air pollution to analyze the possible interaction. RESULTS: It was found that a 10 µg/m3 increase in concentration of PM10 at lag 03 day, SO2 and NO2 at lag 0 day were associated with an increase of 0.88%, 0.76%, and 1.82% respectively in overall emergency admissions. A 10 µg/m3 increase in concentration of PM10, SO2 and NO2 at lag 5 day were associated with an increase of 1.39%, 1.56%, and 1.18% respectively in cardiovascular disease emergency admissions. For lag 02, a 10 µg/m3 increase in concentration of PM10, SO2 and NO2 were associated with 1.72%, 1.34%, and 2.57% increases respectively in respiratory disease emergency admissions. CONCLUSION: This study further confirmed that short-term exposure to ambient air pollution was associated with increased risk of hospital emergency admissions in Beijing.

The association between diurnal temperature range and emergency room admissions for cardiovascular, respiratory, digestive and genitourinary disease among the elderly: a time series study.

OBJECTIVES: To evaluate the short-term effect of diurnal temperature range (DTR) on emergency room (ER) admissions among elderly adults in Beijing. METHODS: After controlling the long-time and seasonal trend, weather, air pollution and other confounding factors, a semi-parametric generalized additive model (GAM) was used to analyze the exposure-effect relationship between DTR and daily ER admissions among elderly adults with different lag structures from 2009 to 2011 in Beijing. We examined the effects of DTR for stratified groups by age and gender, and conducted the modifying effect of season on DTR to test the possible interaction. RESULTS: Significant associations were found between DTR and four major causes of daily ER admissions among elderly adults in Beijing. A 1 °C increase in the 8-day moving average of DTR (lag 07) corresponded to an increase of 2.08% (95% CI: 0.88%-3.29%) in respiratory ER admissions and 2.14% (95% CI: 0.71%-3.59%) in digestive ER admissions. A 1 °C increase in the 3-day and 6-day moving average of DTR (lag 02 and lag 05) corresponded to a 0.76% (95% CI: 0.07%-1.46%) increase in cardiovascular ER admissions, and 1.81% (95% CI: 0.21%-3.45%) increase in genitourinary ER admissions, respectively. The people aged 75 years and older were associated more strongly with DTR than the 65-74 age group. The modifying effect of season on DTR was observed and it was various in four causes. CONCLUSIONS: This study strengthens the evidence that DTR is an independent risk factor for ER admissions among elderly persons. Some prevention programs that target the elderly and other high risk subgroups for impending large temperature changes may reduce the impact of DTR on people's health.

[Introduction and calibration of the Chinese sun hazemeter network].

Much of the current uncertainty in the quantitative assessment of the climate and environment change is due to our lack of knowledge of the aerosol, for which the large-scale sun hazemeter ground-based network directly provides basic data. The data also can revise the results of the satellite remote sensing. Depending on the stations of CERN, the standard network was first built in China. The accurate and reliable hazemeter (LEDs) was uniformly used in the network. The hazemeters were calibrated by Langley plot method and transfer calibration and were uniformly checked. The AODs, which were synchronously retrieved from hazemeters (RSD < 3%) and CEMIL (RSD < 5%), were coherent and comparable. The stability and reliability of the hazemeters and the network was approved.

[AOD and angstrom parameters of aerosols observed by the Chinese sun hazemeter network from August to December 2004].

Atmospheric aerosol optical depth (AOD(lamda=500 nm)), Angstrom turbidity coefficient (beta) and Angstrom wavelength exponent (alpha) are obtained using the CERN sun hazemeter network from Aug to Dec, 2004. The results are as follows: At the Tibetan Plateau, Haibei and Lhasa, the mean of AOD is 0.09, 0.12; the mean of beta is 0.05, 0.13; the mean of a is 1.09, 0.06, respectively. At the Northeast of China, Hailun and Sanjiang, the mean of AOD is 0.14, 0.15; the mean of beta is 0.04, 0.06; the mean of a is 2.32, 1.58, respectively. At the desert region of North China, e.g., Fukang, Shapotou and Eerduosi, the range of averaged AOD is from 0.17 to 0.32; the range of averaged beta is from 0.09 to 0.19; the range of averaged a is from 0.68.to 1.28. At the forest areas, e.g. Changbai Mountain, Beijing forest and Xishuangbanna, the range of averaged AOD is from 0.19 to 0.42; the range of averaged beta is from 0.12 to 0.19; the range of averaged a is from 1.11 to 1.25. At agriculture areas, e.g. Shenyang, Fengqiu, Taoyuan and Yanting, the range of averaged AOD is from 0.34 to 0.68; the range of averaged beta is from 0.18 to 0.38; the range of averaged a is from 0.97 to 1.39. At the littoral areas and the lake of East China, e.g. Jiaozhou Bay, Shanghai City and Tai Lake, the range of averaged AOD is from 0.49 to 0.68; the range of averaged beta is from 0.21 to 0.29; the range of averaged a is from 1.24 to 1.37. At the inland cities, Beijing City and Lanzhou City, the mean of AOD is 0.47, 0.81; the mean of beta is 0.20, 0.45; the mean of a is 1.66, 0.89, respectively. The variations of aerosol properties at nineteen stations are explained in the paper.