空间时间流预测的多变量建模.
Sandra De Iaco1,2,3, Claudia Cappello2, Antonella Congedi2
1National Future Center of Biodiversity, 90133 Palermo, Italy.
Entropy (Basel, Switzerland)
|July 29, 2023
概括
本研究使用多变量地质统计学模拟意大利的时空流. 这些发现有助于监测温室气体排放和室内暴露风险,特别是在夏季.
科学领域:
- 环境科学 环境科学
- 地质统计学 在地质统计学
- 环境监测 环境监测
背景情况:
- 流量数据对于监测温室气体排放和评估室内暴露至关重要.
- 流受到/沉积物和大气变量 (如湿度,温度和降水) 的影响.
研究的目的:
- 模拟和预测意大利威尼托地区流密度的时空分布.
- 估计未采样地点和时间的流量,帮助环境风险评估.
主要方法:
- 利用多变量地质统计学和时空线性同区域化模型.
- 在各种时空滞后的实证共变矩阵中使用联合对角化.
- 为未来的风险评估生成预测的流图和概率图.
主要成果:
- 成功建模了子流量密度的时空分布.
- 制作每月预测的流量图和概率图,表明夏季风险增加.
- 提供了与替代单变量和多变量模型的比较.
结论:
- 多变量地质统计学有效地建模了复杂的时空流数据.
- 开发的模型和地图是环境监测和公共卫生风险评估的宝贵工具.
- 在夏季确定了更高的气呼出风险,需要特别注意.
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