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Seasonal Variation in Microclimates and the Role of Regional Weather and Environmental Factors

机译:小气候的季节性变化以及区域天气和环境因素的作用

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Microclimates are an important component of our ecosystem, and can impact human health through heat-related injuries or by affecting disease vectors. Research on microclimates can be difficu our understanding of the temporal and environmental variation of microclimates is limited. Microclimate data (temperature and relative humidity) were collected over a twelve-month period in a small community in Ecuador, and summarized for over each 24-hour collection period. Using generalized linear models with generalized estimating equations, we assessed the variability of microclimate variables across time and environmental variables, including urbanicity, elevation and vegetation coverage. With local weather station and remotely-sensed climate data, we assessed the relationship between regional weather and microclimates. Two-hundred and eighty-seven log-days of data were collected; the absolute maximum temperature was in July, and the absolute minimum occurred in August. Relative humidity of 100% occurred frequently during the sampling period; the absolute minimum occurred in March. Some microclimate variables were more temporally stable than others (mean, median, and minimum temperature and maximum relative humidity); urban sites had higher temperature variability (p=0.0169) and rural sites had higher mean relative humidity (p=0.0137), compared to suburban areas. Microclimate temperature variables were associated with remotely-sensed surface temperature (p=0.047). Miicroclimate minimum (p=0.0001) and mean (p=0.045) temperature were associated with climate station temperature minimum and mean measures, respectively. Relative humidity mean (p<0.0001), median (p<0.0001), minimum (p=0.038), and maximum (p=0.0018) were associated with the number of days with precipitation at the climate station. These data demonstrate the need for climate and health researchers to reconsider the meaning and impact of climate variables across spatial scales.
机译:小气候是我们生态系统的重要组成部分,可通过与热相关的伤害或影响疾病的传播媒介而影响人类健康。研究小气候可能很困难;我们对微气候的时间和环境变化的理解是有限的。在厄瓜多尔的一个小社区中,在十二个月的时间内收集了小气候数据(温度和相对湿度),并对每个24小时的收集时间进行了汇总。使用具有广义估计方程的广义线性模型,我们评估了随时间和环境变量(包括城市化,海拔和植被覆盖)的微气候变量的变异性。利用当地的气象站和遥感气候数据,我们评估了区域天气与小气候之间的关系。收集了287个日志日的数据;绝对最高温度为7月,绝对最低温度为8月。采样期间经常出现100%的相对湿度;绝对最小值发生在3月。一些小气候变量在时间上比其他变量更稳定(平均,中位数,最低温度和最大相对湿度);与郊区相比,城市地区的温度变化较大(p = 0.0169),农村地区的平均相对湿度较高(p = 0.0137)。小气候温度变量与遥感表面温度有关(p = 0.047)。微气候最低温度(p = 0.0001)和平均温度(p = 0.045)分别与气候站的最低温度和平均测量值相关。相对湿度平均值(p <0.0001),中位数(p <0.0001),最小值(p = 0.038)和最大值(p = 0.0018)与气候站降水的天数相关。这些数据表明,气候与健康研究人员需要重新考虑整个空间尺度上气候变量的含义和影响。

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