摘要
目的分析2016—2023年乌鲁木齐市大气细颗粒物(PM_(2.5))污染状况,并建立预测模型,为大气污染防治工作提供参考。方法通过我国生态环境部网站收集2016—2023年乌鲁木齐市PM2.5监测资料,采用时序图、季节指数分析PM_(2.5)质量浓度的时间变化趋势。利用2016—2023年PM_(2.5)月均质量浓度建立自回归移动平均(ARIMA)模型,用2023年数据进行验证,采用平均绝对百分比误差(MAPE)评价模型的拟合效果,并预测2024—2025年PM_(2.5)月均质量浓度。结果2016—2023年乌鲁木齐市大气PM_(2.5)日均质量浓度呈下降趋势(r_(s)=-0.239,P<0.001),1月、2月和12月的季节指数较高,具有一定的季节性。建立最优预测模型为ARIMA(1,0,0)(1,1,0)12,赤池信息准则值为727.38,修正的赤池信息准则值为727.88,贝叶斯信息准则值为737.10。2023年PM_(2.5)月均质量浓度的预测值与实际值比较,绝对误差范围为0.31~7.45μg/m^(3),相对误差范围为0.01~0.53,MAPE为14.42%。经预测,2024—2025年乌鲁木齐市PM_(2.5)月均质量浓度与2016—2023年变化趋势基本一致。结论2016—2023年乌鲁木齐市大气PM_(2.5)质量浓度呈下降趋势,冬季质量浓度相对较高;ARIMA(1,0,0)(1,1,0)12可用于乌鲁木齐市大气PM_(2.5)污染状况的短期预测。
Objective To analyze the characteristics of fine particulate matter(PM_(2.5))pollution in Urumqi City,Xinjiang Uygur Autonomous Region from 2016 to 2023 and establish a prediction model,so as to provide the reference for air pollution prevention and control.Methods PM_(2.5) monitoring data of Urumqi City from 2016 to 2023 were collected through the website of Ministry of Ecology and Environment of China.The changing trend of PM_(2.5) concentration was analyzed using temporal chart and seasonal index.PM_(2.5) monthly average concentrations from 2016 to 2023 were used to establish an autoregressive integrated moving average(ARIMA)model,and the data in 2023 was fitted and compared with the actual values,using mean absolute percentage error(MAPE)to evaluate the effectiveness of the model,and PM_(2.5) monthly average concentration from 2024 to 2025 was predicted.Results PM_(2.5) daily average concentration in Urumqi City showed a decreasing trend from 2016 to 2023(r_(s)=-0.239,P<0.001),with high seasonal indexes in January,February and December,indicating certain seasonal characteristics.The optional model was ARIMA(1,0,0)(1,1,0)12,with the value of Akaike information criterion,corrected Akaike information criterion,and Bayesian information criterion being 727.38,727.88 and 737.10,respectively.PM_(2.5) monthly average concentration in 2023 was fitted and compared with the actual values,with an absolute error range of 0.31-7.45μg/m^(3),a relative error range of 0.01-0.53,and MAPE of 14.42%.PM2.5 monthly average concentration in Urumqi City from 2024 to 2025 was predicted to be consistent with the trend from 2016 to 2023.Conclusions PM_(2.5) concentration in Urumqi City showed a tendency towards a decline from 2016 to 2023,and was relatively high in winter.ARIMA(1,0,0)(1,1,0)12 can be used for short-term prediction of PM_(2.5) pollution in Urumqi City.
作者
陈佩弟
肖婷婷
李新秀
郑帅印
黄芸
CHEN Peidi;XIAO Tingting;LI Xinxiu;ZHENG Shuaiyin;HUANG Yun(School of Public Health,Xinjiang Second Medical College,Karamay,Xinjiang 834000,China;Karamay Center for Disease Control and Prevention,Karamay,Xinjiang 834000,China)
出处
《预防医学》
2024年第6期510-513,共4页
CHINA PREVENTIVE MEDICINE JOURNAL
基金
2022年自治区级大学生创新创业训练计划项目(S202213560013)
2023年自治区级大学生创新创业训练计划项目(S202313560010)
新疆维吾尔自治区高校科研计划项目(XJEDU2022P147)
新疆第二医学院青年科学基金项目(QK202211)。
关键词
细颗粒物
大气污染
自回归移动平均模型
预测
fine particulate matter
air pollution
autoregressive integrated moving average model
prediction
