| 中国三大城市群PM2.5浓度非线性变化分析 |
| 摘要点击 1540 全文点击 229 投稿时间：2023-02-28 修订日期：2023-04-10 |
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| 中文关键词 PM2.5 创新趋势分析（ITA） 季节和趋势突变的贝叶斯估计（Beast） 非线性变化 趋势 突变 |
| 英文关键词 PM2.5 innovative trend analysis （ITA） Bayesian estimator of abrupt seasonal and trend change （Beast） nonlinear variation trend abrupt change |
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| 中文摘要 |
| 以三大城市群为研究区，基于PM2.5浓度数据，利用ITA和Beast方法定量分析PM2.5时间序列的非线性变化过程.结果表明：①三大城市群PM2.5污染程度下降明显，高浓度区域明显缩小；PM2.5浓度空间极化程度降低，空间差异缩小.大多数地区的PM2.5浓度都具有下降的趋势，但变化程度并不相同.京津冀PM2.5浓度相较于长三角和珠三角，仍处于较高水平.②三大城市群PM2.5浓度具有冬春季高、夏秋季低的季节变化特征.冬季与夏季PM2.5浓度差异明显， PM2.5浓度在夏季的收敛性大于冬季.PM2.5浓度高的区域下降趋势明显，但珠三角的PM2.5浓度下降趋势相较于长三角和京津冀不明显.③三大城市群PM2.5浓度时间序列均具有显著下降趋势，且京津冀>长三角>珠三角；PM2.5浓度在冬季下降趋势最大.PM2.5污染等级越高，下降趋势越明显.④京津冀PM2.5浓度时间序列趋势分量具有两个突变点，季节分量中具有一个突变点；长三角PM2.5浓度时间序列的趋势分量和季节分量均无突变点；珠三角PM2.5浓度时间序列的季节分量无突变点，趋势分量具有一个突变点.结果可为区域空气污染治理相关工作的开展提供科学的参考. |
| 英文摘要 |
| ITA and Beast methods were used to quantitatively analyze the nonlinear process of a PM2.5 concentration time series based on the PM2.5 concentration data of the three major urban agglomerations in China. The results showed that： ① the degree of the PM2.5 pollution in the three major urban agglomerations had decreased， and the high-concentration areas had noticeably shrunk. The degree of spatial polarization of PM2.5 concentration was reduced， and the spatial difference was narrowed. The PM2.5 concentration in most areas showed downward trends， but the degree of change was not the same. Compared with the YRD and PRD， the concentration of PM2.5 in the BTH was still at a relatively high level. ② The concentration of PM2.5 in the three major urban agglomerations had seasonal variation characteristics that were high in winter and spring and low in summer and autumn. There were obvious differences in PM2.5 concentration between winter and summer， and the convergence of PM2.5 concentration in summer was greater than that in winter. Areas with high PM2.5 concentration also had obvious downward trends， but the downward trends of PM2.5 concentration in the PRD were not obvious compared with those in the YRD and BTH. ③ The PM2.5 concentration time series of the three major urban agglomerations all had significant downward trends： Beijing-Tianjin-Hebei （BTH） > the Yangtze River Delta （YRD） > the Pearl River Delta （PRD）. The PM2.5 concentration had the largest downward trends in winter. The higher the PM2.5 pollution level， the greater the downward trends. ④ The trend component of the PM2.5 concentration time series in the BTH had two change points， and there was one change point in the seasonal component. The trend and seasonal components of the PM2.5 concentration time series in the YRD had no change point. There was no change point in the seasonal component but one change point in the trend component of the PM2.5 concentration time series in the PRD. These results can provide scientific references for regional air pollution control. |
