Studies On Air Pollution And Its Health Effects In The Typical Cities Of China And Their Forecast

With the industrialization and urbanization developing rapidly, the urban air pollution is becoming more and more serious, resulting in haze weather increased significantly in recent years. The impact of air pollution on human health has become increasingly serious, which has attracted much attention of technology, health care workers and the general public. It’s urgent for government and relevant departments to provide sensitive diseases forecast in time according to the condition of weather and atmospheric pollution, in order to take protective measures advance to minimize the adverse effects of air pollution on human health and so on. Although many domestic and foreign environmental medical workers have studied in atmospheric pollution and its effects on human health recent years, but domestic related research of China is still in start stages compared with foreign countries, and research in its forecast is also very rare, needed to study in depth.According to above all, this paper is based on the analysis about characteristics of spatial and temporal distribution of air pollution and the meteorological factors of the atmospheric pollution in China, and then the two heavily polluted cities of Beijing and Lanzhou were selected as typical representative, analyzing the changes of two cities’ pollutant concentration and temperature, and the influence of the two synergistic effect on the incidence of related diseases. On the basis of above, the related sensitive diseases prediction models were established respectively, which can provide theoretical and technical support for the prediction of relative sensitive diseases in China, and provide scientific basis for the relevant government departments to develop appropriate prevention and control measures to cope with air pollution and its impact on human health in the same time. The main results of this paper are as follows: 1. By analyzing API data of 120 major cities in China from 2004 to 2013, the spatial distribution of API had declined from north to south, with several high pollution centers in north which were Urumqi, Lanzhou and Beijing, while the API for southern cities hold a stable level at number 60 throughout the year; Seasonal mean value of API appeared "higher in winter than that of summer" overall, ordering in winter > spring > autumn > summer, and the transformer of API was greater than the southern city of years in the north. What’s more, PM10 has been a common phenomenon as the primary pollutant nationally. The period of API time series showed annual or half year period oscillation.2. Results of air quality index(AQI) data analysis for 366 cities in mainland China for 2015 showed that: The AQI of northern cities were higher than that of the southern overall of the year, and in central and southern of Urumqi, and beijing-tianjin-hebei region have become the high pollution value centers. PM10 has become the main pollutants in northwest China in spring, summer and autumn; While PM2.5 has become the main pollutant in winter of China east and central; O3 has become increasingly prominent pollutants of part regions in summer and autumn3. According to the analysis about the distribution and change regulation of air pollution meteorological parameters(APMP) of 7 typical cities’(Harbin, Beijing, Lanzhou, Urumqi, Nanjing, Guangzhou), also study the relationship between APMP and API. We found that the inversion layer thickness with a positive correlation to API, which means the inversion layer thickness was thick in winter and thin in summer; And the distribution of maximum mixing depths enjoying a negative correlation with API, which showed an inverse phase with inversion layer in the year, with thin in winter and thick in summer. As for the stabilization energy, which was positively related to API, has an annual maximum in winter and the minimum in early summer, and the stable energy of the northern cities were greater than that of southern. Thus it can be seen that the heavy pollution of northern city in China was due to the double function of the increasing pollution caused by heating and the decreasing of the diffusion capacity of the atmospheric boundary layer. In addition, we found temperature threshold related to severe air pollution, near which the atmospheric stratification tended to be stable, the wind speed was easier to reach the minimum and the vertical stability energy was easier to be close to the maximum, leading to the most unfavorable meteorological conditions of pollutant dispersion in vertical and horizontal, can act as an important indicator in air pollution potential prediction.4. We found that the effects of 3 major air pollutants(PM10, SO2 and NO2) on diseases were lagged in Beijing and Lanzhou. The excess rate(ER) of the respiratory system(cardiovascular system) emergency, which affected by cumulative 2 days(5 days) heavy pollution of above, reach the maximum in Beijing, while ER of the respiratory system disease in hospitalization of Lanzhou reached the maximum when the effect of heavy pollution corresponded to a 6-days cumulation of the three pollutants above, and all of them through the significant test of α=0.01 level, having statistical significance. In the most significant lag time, an increase of 10μg/m3 in PM10、SO2 and NO2 were significantly associated with the ER of 1.72%(1.39%), 1.34%(1.56%) and 2.57%(1.18%) for emergency department visits of respiratory system(cardiovascular system) disease in Beijing; Corresponding ER were 0.45%, 1.35% and 3.02% of hospitalization numbers of respiratory system disease in Lanzhou, respectively.5. The effect of pollutants on children(less than or equal to 14 years old) and elderly(over 65 years) respiratory system diseases were higher than in adults(15-64 years old), and the influence of the elder for cardiovascular system disease was higher than the children and adults in Beijing, the same as the impact on respiratory disease in Lanzhou, especially for children. In short, the elderly and children were more sensitive to air pollution for respiratory diseases than the adults, as for the cardiovascular system disease, the elder was most sensitive to air pollution. At the same time, both of the two cities’ results showed that the influence of air pollution on the female was more obvious than the male.6. The exposure-response relationships between average temperature respectively with respiratory system emergency disease in Beijing, and respiratory system disease in hospitalization in Lanzhou, reversed "J" type, with the lowest incidence of a temperature threshold of 12.0°C and 14.7°C respectively; And the exposure-response relationship between average temperature with the cardiovascular system emergency disease in Beijing was reverse "V" type, with the highest incidence of a temperature threshold of 10.7°C; while the exposure-response relationship between the numbers of hospitalized patients with cardiovascular system diseases in Lanzhou was reverse "U", with the highest incidence of threshold interval from 8.0°C-20.0°C.7. The analysis result of synergistic effects between air temperature and pollutants(PM10, SO2 and NO2) on respiratory diseases showed that: the number of emergency disease visits of respiratory system in Beijing and respiratory disease inpatients in Lanzhou all were the most in case of high pollution in low temperature background, indicating that the effect of high pollution in low temperature condition on the respiratory system diseases incidence has a synergistic exacerbated. Also, we found that high pollution exacerbated the hospital cardiovascular system disease emergency visits in Beijing and cardiovascular system disease hospitalization patients in Lanzhou when the temperature was in the high temperature threshold range.8. Selected BP neural network and least squares support vector machine(LSSVM) two kinds of forecast model, considering the basic meteorological elements, pollutant concentration, and the pollution meteorological parameters, respectively, established the respiratory and cardiovascular system diseases forecast models in Beijing and Lanzhou, and optimized the relevant parameters. The forecast results showed that the BP neural network experiment forecasting accuracy were 66.73% and 72.16% of the respiratory and cardiovascular system diseases, and the accuracy of LSSVM experiment prediction were 79.73% and 85.09% in Beijing, respectively. The experiment prediction accuracy of BP neural network were 44.12% and 51.54% in the respiratory and cardiovascular system diseases and the accuracy of LSSVM experiment prediction were 54.45% and 63.20% in Lanzhou, respectively. Obviously, the forecast effect of LSSVM model which owe practical popularize value, was better than that of BP neural network model.