摘要
基于哈尔滨市空气污染物共39个月数据,利用Holt-Winters指数平滑法,探究其时空变化特征。结果显示,SO_(2)于2021年浓度均值同比2020年减少34.25%、CO浓度同比减少9.14%、NO_(2)浓度同比减少29.36%、PM_(2.5)则呈现出市内道外区和市郊呼兰区双高的空间特点。其中SO_(2)与CO浓度随季节变化明显,根据Person分析表明两者相关性较高。SO_(2)、CO、NO_(2)和PM_(2.5)浓度虽有季节性反复,但年均值在逐年降低,整体呈螺旋式下降。根据H-W forecast分析时空变化趋势表明,在2022下半年SO_(2)与CO浓度预测值比同期上涨17.03%、PM_(2.5)相较同期上涨8.63%、NO_(2)预测值则下降8.75%。合理利用时间序列预测可以使相关部门更加精准、有效地对未来空气污染进行“预治理”。
Based on the 39-month data of air pollutants in Harbin,the Holt-Winters exponential smoothing method was used to investigate the temporal and spatial variation characteristics.The results showed that the average concentration of SO_(2)in 2021 decreased by 34.25%,CO concentration decreased by 9.14%,NO_(2)concentration decreased by 29.36%comparing with that in 2020,and PM_(2.5)showed the spatial characteristics with a high level in the outer area of the city center and a high level in the suburban Hulan District.Among them,the concentrations of SO_(2)and CO varied significantly with seasons,and the correlation between them was high according to Person analysis.Although the concentrations of SO_(2),CO,NO_(2),and PM_(2.5)had seasonal repetitions,the annual average values were decreasing year by year,and the overall decline was spiraling.According to the analysis of the temporal and spatial trends of the H-W forecast,in the second half of 2022,the predicted values of SO_(2)and CO concentrations increased by 17.03%comparing with the same period,PM_(2.5)increased by 8.63%,and the predicted NO_(2)decreased by 8.75%.A reasonable use of time series forecasting model could enable relevant departments to"pre-treat"future air pollution more accurately and effectively.
作者
欧阳迪
崔佳
OUYang Di;CUI Jia(College of Management,Harbin Normal University,Harbin 150025,China)
出处
《环境保护科学》
CAS
2023年第2期112-119,共8页
Environmental Protection Science
关键词
空气污染
碳中和
时间序列
能源转型
air pollution
carbon neutrality
time series
energy transition
