首页> 外文会议>Third International Conference on Air Pollution Ⅲ - Vol.3: Urban Pollution, Sep 26-29, 1995, Porto Carras, Greece >Conditions and trends of air pollution levels in the metropolitan Zone in the city of Toluca
【24h】

Conditions and trends of air pollution levels in the metropolitan Zone in the city of Toluca

机译:托卢卡市大都市区空气污染水平的状况和趋势

获取原文
获取原文并翻译 | 示例

摘要

The city of Toluca is located 60 km. to the west of Mexico City, and due to its accelerated demographic and industrial growth, one of the main concerns of the State Environmental Department is the potential increment in air pollution indexes. Records about important pollutants have been collected every hour since April 1993 for seven locations in the zone. These data have been analyzed statistically looking for trend changes and potential differences among locations. Due to the great amount of missing data, only two locations provided enough weekly averages to allow for statistical analysis. The daily data were deseasonalized and weekly averages used to estimate missing data via ARIMA models. To construct forecasts and to detect trend changes, ARIMA models were adjusted to the available series. To identify the corresponding models bootstrap samples from the actual series were obtained and the ACF and PACF functions constructed from these samples. The estimation phase was performed by using actual data and at the validation stage, bootstrap principles were also applied, this time the bootstrap samples were generated from the series residuals. Forecasts for the last 10 weeks of 1994 were computed, and the forecasting ability of the models finally tested by computing performance measures from the actual data corresponding to these weeks. Discussion of main findings and the validated models for each series are presented.
机译:托卢卡市(Toluca)位于60公里。墨西哥城以西,由于人口和工业增长的加速,国家环境部门的主要关注之一是空气污染指数的潜在增加。自1993年4月以来,每小时在该区域的七个地点收集有关重要污染物的记录。对这些数据进行了统计分析,以查找趋势变化和位置之间的潜在差异。由于缺少大量数据,因此只有两个位置提供了足够的每周平均值以进行统计分析。每日数据经过季节性缩减,每周平均值用于通过ARIMA模型估算缺失数据。为了构建预测并检测趋势变化,将ARIMA模型调整为可用的序列。为了识别相应的模型,从实际系列中获得了引导程序样本,并从这些样本构造了ACF和PACF函数。估计阶段是通过使用实际数据执行的,在验证阶段,还应用了自举原理,这一次自举样本是从系列残差生成的。计算了1994年最后10周的预测,并通过根据与这几周相对应的实际数据计算性能指标最终测试了模型的预测能力。介绍了每个系列的主要发现和经过验证的模型。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号