基于SPSS的空气质量指数的影响因素分析及预测

Analysis and prediction of influential factors of air quality index based on SPSS

本文利用2015~2019年廊坊市空气质量指数以及2019年廊坊市逐日空气质量指数AQI与多种空气污染物的观测资料,对廊坊市空气质量变化特征及其与污染物的数值进行了分析。结果表明:与2013~2018年相比,2019年廊坊市空气质量有进一步改善,但总体空气质量并不乐观。空气质量为良的等级出现频率最高,其次为轻度污染,首要污染物以PM 2.5为主。运用科学的手段与方法对环境空气质量影响因素进行预测,以便提出更有效的治理对策,改善环境,减小飞速发展的经济对环境造成的巨大压力。

In this paper,the air quality index of Langfang City in 2015-2019 and the daily air quality index AQI of 2019 and various air pollutants observation date were used to analyze the air quality variation characteristics and the values of pollutants in Langfang.The results show that compared with 2013-2016,the air quality in Langfang has improved further in 2019,but the overall air quality is not optimistic.The grade with good air quality ranks the highest,followed by mild pollution.The primary pollutant is PM2.5.Scientific methods to predict how the factors affect ambient air quality,so as to propose more effective countermeasures,improve environmental problems,and reduce the enormous pressure on the environment caused by the fast-growing economy.