Lodging is a major meteorological disaster that significantly affects the yield of summer maize. Investigating the impact of lodging during the milk stage on water use efficiency (WUE) and yield is crucial for accurately assessing lodging-induced losses and guiding summer maize production. Based on crop, meteorological, disaster survey, and CO₂/H₂O flux data collected at the Zhengzhou Agro-meteorological Experimental Station during the 2016-2017 growing seasons, this study constructed models of net ecosystem productivity (NEP) and evapotranspiration (ET) to simulate the population-level WUE. A wind-induced lodging event that occurred in Zhengzhou on August 25, 2016 was analyzed using the model validated by 2017 observations. The results show that under normal conditions, the simulated WUE values agreed well with flux observations, with a mean absolute error of -0.08 mg C·g^-1 H₂O and a relative error of -5.39%. After lodging, the simulated WUE values were markedly lower than those under non-lodging conditions, with a daily average decrease of 0.31 mg C·g^-1 H₂O, corresponding to a reduction of 20.37%. At the yield level, WUE decreased by 3.87%. Both NEP and ET declined following lodging, with a larger reduction in NEP than in ET, leading to a decrease in WUE. Lodging also reduced the hundred-grain weight by 2.8% and the grain weight per plant by 10.8%, resulting in an overall yield reduction of approximately 5.0%.

In order to find out the relationship between temperature and the number of hospitalized patients with respiratory diseases, relevant departments reasonably implement disease prevention and early warning in county-level cities in Liaoning Province. Based on the daily meteorological observation data and respiratory system hospitalization data of Beipiao City and Xifeng County in Liaoning Province from 2016 to 2018, the seasonal distribution characteristics and age distribution characteristics of the number of hospitalizations with respiratory system were analyzed. On this basis, the generalized additive model (GAM) and the distributed lag non-linear model (DLNM) were used to explore the effect of temperature on the number of hospitalizations for respiratory diseases, and the results were stratified by sex and age. Modeling using attributable fractions (AF) to quantify the disease risk of exposure to specific temperature ranges (eg, extreme cold temperature, moderate cold temperature, moderate hot temperature, extreme hot temperature). The results show that the annual peak of the number of hospitalizations for respiratory diseases in the two places occurs in winter and spring, and the majority of the sick people are children and the elderly. The optimal temperatures for people in Beipiao City and Xifeng County are 26.2 ℃ and 22.2 ℃, respectively. The impact of temperature on the incidence of respiratory diseases is dominated by the lag effect of cold temperature, and the immediate effect of hot temperature is not significant. In Beipiao City and Xifeng County, 27.0% (95% confidence interval: 20.3%-32.9%) and 29.0% (95% confidence interval: 22.1%-35.0%) of respiratory system hospitalizations were attributed to temperature, respectively, and the disease risk was mainly moderate cold temperature. The incidence of Beipiao City and Xifeng County was attributed to moderate cold temperature accounted for 25.9% (95% confidence interval: 19.5%-31.5%) and 28.1% (95% confidence interval: 21.5%-33.9%), respectively. In terms of age distribution, compared with the adult group, the percentage of diseases attributable to moderate cold is higher in the children group and the elderly group. In addition, the elderly group is also more sensitive to extreme low temperatures. In terms of gender stratification, women are more susceptible to low temperature than men. The temperature of the two county-level cities in Liaoning Province has different effects on different groups of people, the risk of disease caused by temperature on women and elderly residents is high.

In order to master the occurrence regularity of winter wheat late frost injury in He nan Province，and take timely measures for disaster prevention and reduction，this paper firstly selects these risk evaluation indexes including the winter wheat late frost harmful chilling accumulation and frequency (risk) ，the planting area of winter wheat (exposure) ， and the ratio of irrigated and tillable field area，well number per unit area (vulnerability)to establish risk evaluation system，and then determines the weight of winter wheat late frost risk evaluation index by using analytic hierarchy process，finally the winter wheat late frost freeze risk evaluation model was built． Based on 1984 － 2013 climate data， the late frost of winter wheat in He nan Province was evaluated by using the risk assessment model，and according to the winter wheat late frost risk evaluation model for grid computing in ArcGIS，the winter wheat late frost risk zoning map in He nan Province was obtained． The results show that the late frost risk index was high which ranged from 0． 289 to 0． 483 in the eastern Shangqiu，Zhoukou，Luohe，most part of Zhumadian，some part of Xinyang and Nanyang，while in most of Sanmenxia， Luoyang，Jiyuan，Jiaozuo，Zhengzhou，Anyang，Hebi，Xinxiang and other areas the late frost risk index was less than 0．123． Finally， the correlation analysis was carried out between the late frost index caculated by using historical statistical data and the results of this study，and the correlation coefficient was 0．78，which showed that the winter wheat late frost risk zoning results in He nan Province were consistent with the historical statistics．