In recent 2 years, the incidence of influenza showed a slight upward trend in Guangxi; therefore, some joint actions should be done to help preventing and controlling this disease. The factors analysis of affecting influenza and early prediction of influenza incidence may help policy-making so as to take effective measures to prevent and control influenza. In this study, we used the cross correlation function (CCF) to analyze the effect of climate indicators on influenza incidence, ARIMA and ARIMAX (autoregressive integrated moving average model with exogenous input variables) model methods to do predictive analysis of influenza incidence. The results of CCF analysis showed that climate indicators (PM2.5, PM10, SO2, CO, NO2, O3, average temperature, maximum temperature, minimum temperature, average relative humidity, and sunshine duration) had significant effects on the incidence of influenza. People need to take good precautions in the days of severe air pollution and keep warm in cold weather to prevent influenza. We found that the ARIMAX (1,0,1)(0,0,1)12 with NO2 model has good predictive performance, which can be used to predict the influenza incidence in Guangxi, and the predicted incidence may be useful in developing early warning systems and providing important evidence for influenza control policy-making and public health intervention.
• Air masses from Zhejiang Province is the major source of O3 in suburban Shanghai.• O3 formation was in VOC-sensitive regime in rural Shanghai.• O3 formation was most sensitive to propylene in rural Shanghai. A high level of ozone (O3) is frequently observed in the suburbs of Shanghai, the reason for this high level remains unclear. To obtain a detailed insight on the high level of O3 during summer in Shanghai, O3 and its precursors were measured at a suburban site in Shanghai from July 1, 2016 to July 31, 2016. Using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and concentration weighted trajectories (CWT), we found that Zhejiang province was the main potential source of O3 in suburban Shanghai. When the sampling site was controlled by south-western winds exceeding 2 m/s, the O3-rich air masses from upwind regions (such as Zhejiang province) could be transported to the suburban Shanghai. The propylene-equivalent concentration (PEC) and ozone formation potential (OFP) were further calculated for each VOC species, and the results suggested that propylene, (m+p)-xylene, and toluene played dominant roles in O3 formation. The Ozone Isopleth Plotting Research (OZIPR) model was used to reveal the impact of O3 precursors on O3 formation, and 4 base-cases were selected to adjust the model simulation. An average disparity of 18.20% was achieved between the simulated and observed O3 concentrations. The O3 isopleth diagram illustrated that O3 formation in July 2016 was in VOC-sensitive regime, although the VOC/NOx ratio was greater than 20. By introducing sensitivity (S), a sensitivity analysis was performed for O3 formation. We found that O3 formation was sensitive to propylene, (m+p)-xylene, o-xylene and toluene. The results provide theoretical support for O3 pollution treatment in Shanghai. 相似文献
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