Iranian Journal of

Background and Objective: Rainfall and groundwater level are important parameters of DRASTIC index, thus their time-series were examined using time series analysis for Mahidasht plain vulnerability in Kermanshah Province.
Materials and Methods: DRASTIC model is a quantitative model that seven parameters for transfer of pollution are considered including depth of water table, net recharge, aquifer, soil, topography, unsaturated environment and hydraulic conductivity. The data was prepared in seven-layer information in Arc GIS10 software. After integration, weighting and ranking, DRASTIC index for the region was estimated between 34 and 120. Precipitation is an uncertainty factor in water projects. Precipitation is the origin of other uncertainties such as surface runoff, recharge, and water balance.  Underground water level and recharge are main factors in the DRASTIC model that are considered as component hydrological variables and time series, thus, they were analyzed and forecasted using stochastic methods on the horizon in 2032.
Results: Finally, selection of the data predicted in 2032 and the creation of dual new depth to the water table and recharge, as well as the weighting and ranking of the repeated placement in the DRASTIC model, another vulnerabilities map is prepared in which the index DRASTIC was 34 to 110 units.
Conclusion: Results showed that due to further decrease of water table and reduced rainfall, DRASTIC index will be less in the next 18 years (2014-2032).
 

Background and Objective: This study aimed to evaluate the correlation between climatic parameters and air pollution with cardiovascular disease and its associated death during 2014 in Mashhad by time series model.
Materials and Methods: Patient data (including outpatient and hospitalization) and cardiovascular mortality were obtained from the emergency medical center and Ferdowsi organization of Mashhad. Climatic parameters such as temperature, pressure, relative humidity, wind speed, and rainfall were gathered from meteorological organization. Air pollutants data were collected from Mashhad environmental pollutants monitoring center for the statistical period of 2014-2015. In this study, Jenkins Box time series model (combined model of autoregression and moving average known as ARIMA) with significance level of 5% was used to investigate the effect of climatic parameters and air pollution values on cardiovascular disease and daily, weekly and monthly excess mortality rate. Then, the effect of various seasons on the total number of patients with cardiac issues and the resulting death was investigated by Kruskal-Wallis nonparametric test.
Results: The final model for determination of monthly correlation between climatic elements and air pollutants with the number of cardiovascular patients and its corresponding death was found to be best fitted by ARIMA (0,0,0). The monthly survey revealed that humidity (positive correlation), temperature (positive correlation), wind speed (negative correlation), and PM_2.5 (negative correlation) with average values of 16.2471, 48.1628, 122.38, and 7.3905, respectively, had significant effects on the number of people experiencing cardiovascular disease. However, the monthly survey of mortality rate due to cardiovascular disease exhibited significant correlation (p < 0.05) with pressure (positive correlation), temperature (negative correlation), and rainfall (negative correlation) with average values of 6.5904, 1.5728, and 1.1704, respectively. The results showed a significant difference between the numbers of patients experiencing cardiovascular diseases in different seasons of the year with the highest recorded number of 3778 in autumn.
Conclusion:  The results suggest moderate correlation between atmospheric elements and air pollutants with the numbers of people experiencing cardiovascular diseases in short periods; however, in the case of long-term mortality, the correlation was strong. This study showed that climatic elements and air pollutants effectively affect cardiovascular diseases, while only climatic elements played a significant role in mortality. The main challenge of the present study is that cardiovascular disease and its resulting death may be influenced by parameters other than those considered in this study, such as multiple individual and environmental confounding variables.