Fine particulate matter (PM2.5) levels, carbon dioxide (CO2) levels and particle-number concentrations (PNC) were monitored in train carriages on seven routes of the mass transit railway in Hong Kong between March and May 2014, using real-time monitoring instruments. The 8-h average PM2.5 levels in carriages on the seven routes ranged from 24.1 to 49.8 µg/m3, higher than levels in Finland and similar to those in New York, and in most cases exceeding the standard set by the World Health Organisation (25 µg/m3). The CO2 concentration ranged from 714 to 1801 ppm on four of the routes, generally exceeding indoor air quality guidelines (1000 ppm over 8 h) and reaching levels as high as those in Beijing. PNC ranged from 1506 to 11,570 particles/cm3, lower than readings in Sydney and higher than readings in Taipei. Correlation analysis indicated that the number of passengers in a given carriage did not affect the PM2.5 concentration or PNC in the carriage. However, a significant positive correlation (p < 0.001, R2 = 0.834) was observed between passenger numbers and CO2 levels, with each passenger contributing approximately 7.7–9.8 ppm of CO2. The real-time measurements of PM2.5 and PNC varied considerably, rising when carriage doors opened on arrival at a station and when passengers inside the carriage were more active. This suggests that air pollutants outside the train and passenger movements may contribute to PM2.5 levels and PNC. Assessment of the risk associated with PM2.5 exposure revealed that children are most severely affected by PM2.5 pollution, followed in order by juveniles, adults and the elderly. In addition, females were found to be more vulnerable to PM2.5 pollution than males (p < 0.001), and different subway lines were associated with different levels of risk. 相似文献
In this paper, we consider a two-period competition model of a remanufacturing supply chain consisting of three members: a new product manufacturer, a recycler and a remanufacturer. The manufacturer supplies new products in the first period and the remanufacturer participates in the competition in the second period. We consider three scenarios in the second period: (1) there is no government subsidy in the competition; (2) there is only government subsidy in the competition; (3) there are both government subsidy and tax in the competition. First, we give the optimal decision-making of the manufacturer, the remanufacturer and the government in the three scenarios; second, we analyse changes in the decision-making of the manufacturer and remanufacturer in the three scenarios and compare their results. We analyse the effects of government subsidy and tax and their asymmetric use on manufacturers’ and remanufacturers’ decision-making variables and competitive performance. We also take consumer awareness of environmental protection into account and examine its impact on subjects’ decisions. Lastly, we operate a numerical example to show the results. 相似文献
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.