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Determination of Haze API From Forest Fire Emission During the 1997 Thick Haze Episode in Malaysia using NOAA AVHRR Data

机译:使用NOAA AVHRR数据确定马来西亚1997年浓雾事件中森林火灾排放的雾霾API

摘要

The results of a study conducted at the UTM Centre for Remote Sensing is reported to quantify haze from forest fire emission using NOAA AVHRR data. In this study, NOAA AVHRR LAC data dated 22 September 1997, one of the worst thick haze episode in Malaysia were used. The relationship between measured Air Pollution Index (API) of the measurements were carried out by Alam Sekitar Malaysia Sdn. Bhd. (ASMA) at five selected air pollution stations in Peninsular Malaysia. These relationships were shown as the best regression model. Finally, these models were used in generating maps of haze-intensity for individual haze components, namely carbon monoxide (CO), Ozone (O3), PM10, sulphur dioxide (SO2) and nitrogen dioxide (NO2) in order to predict haze API from NOAA AVHRR data. The results indicated that NOAA AVHRR data are very useful in reporting regional haze occurrence continuously.
机译:据报道,在UTM遥感中心进行的一项研究结果使用NOAA AVHRR数据量化了森林火灾排放中的雾霾。在这项研究中,使用了日期为1997年9月22日的NOAA AVHRR LAC数据,这是马来西亚最严重的霾天气之一。测量的测量空气污染指数(API)之间的关系由Alam Sekitar Malaysia Sdn。 Bhd。(ASMA)在马来西亚半岛的五个选定的空气污染站。这些关系显示为最佳回归模型。最后,这些模型用于生成单个雾度成分的雾度强度图,即一氧化碳(CO),臭氧(O3),PM10,二氧化硫(SO2)和二氧化氮(NO2),以便根据NOAA AVHRR数据。结果表明,NOAA AVHRR数据对于连续报告区域霾天气的发生非常有用。

著录项

  • 作者

    Ahmad Asmala; Hashim Mazlan;

  • 作者单位
  • 年度 2000
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  • 原文格式 PDF
  • 正文语种 en
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