不同精度地形数据对面源在不同地形条件下大气预测的影响
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摘要
【目的】在使用AERMOD模式进行复杂地形区域大气预测时,控制气象条件与污染源源强等参数相同,采用分辨率更高的DEM地形数据可使得预测结果更加精确。【方法】设置气象条件相同,对于同一无组织面源,在复杂山地、复杂河谷2种地形条件下分别进行不添加地形数据、添加90 m×90 m精度地形数据、添加30 m×30 m精度地形数据的大气预测。【结果】在复杂山地地形条件下,不添加地形数据、添加90 m×90 m精度地形数据下预测结果与添加30 m×30 m精度地形数据下最优预测结果相关性分别为24.0%与52.4%;在复杂河谷地形条件下,不添加地形数据、添加90 m×90 m精度地形数据下预测结果与添加30 m×30m精度地形数据下最优预测结果相关性分别为48.7%与89.3%。【结论】在使用AERMOD模式进行大气预测时,若面源为复杂山地地形,建议采用30 m×30 m精度地形数据,以提升预测结果的准确性。
【Objective】Using the AERMOD model for atmospheric prediction of complex terrain areas by controlling meteorological conditions and pollution sources with other parameters of the same,the application of higher resolution DEM terrain data could make prediction results more accurate.【Method】For the same unorganized surface source,firstly the same meteorological conditions were set,and then under the two terrain conditions,the three atmospheric predictions(adding no terrain data,adding 90 m × 90 m precision terrain data,adding 30 m ×30 m precision terrain data) were carried out.【Result】Under complicated mountain terrain condition,the correlations of the prediction results under adding no terrain data and adding the 90 m × 90 m precision terrain data with the optimal prediction results under adding the 30 m × 30 m precision terrain data was 24. 0 % and 52. 4 %. In complicated valley terrain,the correlation of the prediction results under adding no terrain data and adding the 90 m × 90 m precision terrain data between the optimal prediction results under adding the 30 m × 30 m precision terrain data were 48. 7 % and 89. 3 %.【Conclusion】The present study indicated that when using the AERMOD for atmospheric prediction,if the surface source was located in a complicated mountain terrain,it was recommended to use the 30 m × 30 m precision terrain data to improve the accuracy of the forecast results.
【Objective】Using the AERMOD model for atmospheric prediction of complex terrain areas by controlling meteorological conditions and pollution sources with other parameters of the same,the application of higher resolution DEM terrain data could make prediction results more accurate.【Method】For the same unorganized surface source,firstly the same meteorological conditions were set,and then under the two terrain conditions,the three atmospheric predictions(adding no terrain data,adding 90 m × 90 m precision terrain data,adding 30 m ×30 m precision terrain data) were carried out.【Result】Under complicated mountain terrain condition,the correlations of the prediction results under adding no terrain data and adding the 90 m × 90 m precision terrain data with the optimal prediction results under adding the 30 m × 30 m precision terrain data was 24. 0 % and 52. 4 %. In complicated valley terrain,the correlation of the prediction results under adding no terrain data and adding the 90 m × 90 m precision terrain data between the optimal prediction results under adding the 30 m × 30 m precision terrain data were 48. 7 % and 89. 3 %.【Conclusion】The present study indicated that when using the AERMOD for atmospheric prediction,if the surface source was located in a complicated mountain terrain,it was recommended to use the 30 m × 30 m precision terrain data to improve the accuracy of the forecast results.
引文
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[8]安兴琴,安俊岭,吕世华,等.复杂地形城市SO2扩散特征的模拟研究[J].城市环境与城市生态,2005(3):23-26.
[9]HJ 2.2-2008,环境影响评价技术导则大气环境[S].
[10]付鹏,仝纪龙,潘峰,等.不同地形数据对大气预测结果的影响性分析[J].环境工程,2016(3):170-173+52.
[2]王小燕.AERMOD在区域大气环评中的应用研究[D].兰州大学,2013.
[3]EPA.User's Guide for the AMS/EPA Regulatory Model-AERMOD[R].2004,9(EPA-454/B-03-001).
[4]吕信红.大气环评预测模式之AERMOD应用研究[D].扬州:扬州大学,2011.
[5]张智锋,刘雪锦,贾佳,等.地形数据输入范围对AERMOD预测结果的影响[J].环境科学与技术,2014(5):182-186.
[6]Akula Venkatram,Roger Brode,Alan Cimorelli,et al.A complex terrain dispersion model for regulatory applications[J].Atmospheric Environment,2001,35(24):4211-4221.
[7]李可欣.气象、地形数据参数在大气环境影响预测模式中的应用及研究[D].哈尔滨:东北林业大学,2011.
[8]安兴琴,安俊岭,吕世华,等.复杂地形城市SO2扩散特征的模拟研究[J].城市环境与城市生态,2005(3):23-26.
[9]HJ 2.2-2008,环境影响评价技术导则大气环境[S].
[10]付鹏,仝纪龙,潘峰,等.不同地形数据对大气预测结果的影响性分析[J].环境工程,2016(3):170-173+52.