4.7 Article

Analysis of acid rain patterns in northeastern China using a decision tree method

Journal

ATMOSPHERIC ENVIRONMENT
Volume 46, Issue -, Pages 590-596

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2011.03.004

Keywords

Acid rain; Decision tree; Geographical position; Terrain characteristics; Meteorological data; Column SO2 and NO2; Northeast China

Funding

  1. Open Foundation of State Key Laboratory of Remote Sensing [OFSLRSS201013]
  2. State Key Fundamental Science Funds of China [2010CB428503]
  3. State High Technology Funds of China [2009AA122001, 2009AA122005]
  4. State Data Synthesis and Analysis Funds of China [2007FY110300-04, 2007FY110300-08]

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Acid rain is a major regional-scale environmental problem in China. To control acid rain pollution and to protect the ecological environment, it is urgent to document acid rain patterns in various regions of China. Taking Liaoning Province as the study area, the present work focused on the spatial and temporal variations of acid rains in northeastern China. It presents a means for predicting the occurrence of acid rain using geographic position, terrain characteristics, routinely monitored meteorological factors and column concentrations of atmospheric SO2 and NO2 The analysis applies a decision tree approach to the foregoing observation data. Results showed that: (1) acid rain occurred at 17 stations among the 81 monitoring stations in Liaoning Province, with the frequency of acid rain from 0 to 84.38%; (2) summer had the most acid rain occurrences followed by spring and autumn, and the winter had the least; (3) the total accuracy for the simulation of precipitation pH (pH <= 4.5, 4.5 < pH <= 5.6, and pH > 5.6) was 98.04% using the decision tree method known as C5. The simulation results also indicated that the distance to coastline, elevation, wind direction, wind speed, rainfall amount, atmospheric pressure, and the precursors of add rain all have a strong influence on the occurrence of acid rains in northeastern China. (C) 2011 Elsevier Ltd. All rights reserved.

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