环境污染一直是我国非常重视的问题，大气污染问题更是重中之重。空气污染物浓度与人们的生活健康息息相关。雾霾是现今秋冬天气中常见的一种天气现象，是由雾和霾组成的，但是两者之间又有很大区别。空气湿度大于90%时称之为雾，霾则小于80%，而雾霾介于两者之间[1]。本文根据北京市的环境污染数据，使用R语言对北京市近十几年的环境污染主要成分的数据进行主成分分析和时间建模，和对环境污染的预测，进而为提高北京市的环境质量，改善居民的生活环境提供依据。
Environmental pollution has always
been a very important issue in China, especially the air pollution. The concentration
of air pollutants is closely related to people’s life and health. Haze is a
common weather phenomenon in autumn and winter, it is composed of fog and haze,
but there is a big difference between them. When air humidity is greater than 90%,
it is called fog, while haze is less than 80%, whereas haze is between the two [1]. Based on the data of environmental pollution in recent ten years in
Beijing, this paper uses R language to conduct principal component analysis and
to establish the time series model. Utilizing the model, we predict
environmental pollution, which provides a basis to improve the environmental
quality of Beijing and the living environment of residents.
