地理科学进展 ›› 2023, Vol. 42 ›› Issue (6): 1124-1138.doi: 10.18306/dlkxjz.2023.06.008

• 研究论文 • 上一篇    下一篇

大气污染对京津冀地区夏季植被生长峰值的影响

鲍艳磊1,2,3,5(), 吴朝阳4,*(), 郑东博1,2,3   

  1. 1.河北师范大学地理科学学院,石家庄 050024
    2.河北省环境演变与生态建设实验室,石家庄 050024
    3.河北省环境变化遥感识别技术创新中心,石家庄 050024
    4.中国科学院地理科学与资源研究所,北京 100101
    5.河北水利电力学院水利工程系,河北 沧州 061001
  • 收稿日期:2022-06-29 修回日期:2022-10-21 出版日期:2023-06-28 发布日期:2023-06-26
  • 通讯作者: * 吴朝阳(1982— ),男,江苏扬州人,研究员,主要从事全球变化遥感、生态遥感研究。E-mail: wucy@igsnrr.ac.cn
  • 作者简介:鲍艳磊(1993— ),女,河北衡水人,博士生,主要研究方向为生态遥感。E-mail: 18333196164@163.com
  • 基金资助:
    国家自然科学基金项目(42125101)

Effects of air pollution on summer peak vegetation growth in the Beijing-Tianjin-Hebei region

BAO Yanlei1,2,3,5(), WU Chaoyang4,*(), ZHENG Dongbo1,2,3   

  1. 1. College of Geographical Sciences, Hebei Normal University, Shijiazhuang 050024, China
    2. Hebei Key Laboratory of Environmental Change and Ecological Construction, Shijiazhuang 050024, China
    3. Hebei Technology Innovation Center for Remote Sensing Identification of Environmental Change, Shijiazhuang 050024, China
    4. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    5. Department of Hydraulic Engineering, Hebei University of Water Resources and Electric Engineering, Cangzhou 061001, Hebei, China
  • Received:2022-06-29 Revised:2022-10-21 Online:2023-06-28 Published:2023-06-26
  • Supported by:
    National Natural Science Foundation of China(42125101)

摘要:

植被物候是指示气候变化的重要因子,大气污染物变化对植被生长峰值的影响尚未得到充分探究。论文利用卫星观测的归一化植被指数(Normalized Difference Vegetation Index,NDVI)2001—2015年的时序数据,分析京津冀地区植被生长季峰值(peak of growing season,POS)、生长期最大值(maximum vegetation growth,NDVImax)的时间变化,探究大气污染物(PM2.5)对POS、NDVImax的影响,阐明PM2.5对POS、NDVImax与气象因子响应机制的影响。结果表明:燕山和太行山区POS较早且NDVImax较大,东南部平原POS较晚,张家口地区、燕山和太行山区NDVImax呈显著增加趋势。季前降水(季前指POS或NDVImax与影响因子偏相关系数绝对值最大值对应的时间距多年平均POS的时间长度)对POS、NDVImax的影响均较大,显著相关区域分别占研究区域的12.9%、15.2%;温度影响所占比例分别为8.7%、5.9%(P<0.1)。在PM2.5的影响下,不同季节不同地区降水和温度的反馈不同;物候对由PM2.5引起的降水和温度变化的响应同样具有空间异质性。PM2.5导致中东部平原和北部燕山地区降水对POS的提前作用被低估,张家口北部丘陵地区POS的提前作用被高估,东部、南部平原和坝上地区温度对POS的提前作用被高估;整体来看,PM2.5对NDVImax的间接作用表现为降低NDVImax (P<0.1)。长期来看,京津冀大部分地区,PM2.5的直接作用表现为PM2.5使POS提前、NDVImax增大(P<0.1)。研究结果主要揭示了京津冀地区植被生长峰值对气候变化及大气污染物的响应,对深入理解不同地区植被生长对气候变化和大气污染变化的响应和反馈具有重要意义。

关键词: 归一化植被指数, 生长季峰值, 生长期最大值, PM2.5, 气象因子, 京津冀

Abstract:

Vegetation phenology is a sensitive indicator of climate change, and the effects of different meteorological factors and changes in atmospheric pollutants on peak vegetation growth have not been fully explored. In this study, we used satellite observed normalized difference vegetation index (NDVI) data from 2001 to 2015 to investigate the temporal changes of peak of growing season (POS) and maximum vegetation growth (NDVImax) in the Beijing-Tianjin-Hebei region by the Theil-Sen slope estimator. We also analyzed the effects of preseason temperature and precipitation on POS and NDVImax considering the effects of the fine particulate matter (PM2.5) to investigate the indirect effect of PM2.5 on POS and NDVImax in the region, and the direct effects of PM2.5 on POS and NDVImax by partial correlation analyses. The results showed that earlier POS and higher NDVImax occurred in the Yanshan Mountains and Taihang Mountains, POS in the eastern and southern plains were relatively late, and the NDVImax in Zhangjiakou City, the Yanshan Mountains, and the Taihang Mountains showed a significant increasing trend. Preseason precipitation had a greater impact on POS and NDVImax (the area where significant correlation was found accounted for 12.9% and 15.2% of the study area), which was similar to the effect of temperature (8.7% and 5.9%, respectively). Under the impact of PM2.5, the feedbacks of precipitation and temperature were different in different regions and seasons, and the responses of phenology to the changes of precipitation and temperature caused by PM2.5 also showed spatial heterogeneity. PM2.5 led to the underestimation of the advancing effect of precipitation on POS in the central and eastern plains and northern Yanshan Mountains, overestimation of the advancing effect of precipitation on POS in the northern Zhangjiakou area, and overestimation of the advancing effect of temperature on POS in the eastern and southern plains and the Bashang areas. Overall, the indirect effect of PM2.5 on NDVImax was reducing NDVImax (P<0.1). In the long run, PM2.5 would directly advance POS and increase NDVImax in most areas of the Beijing-Tianjin-Hebei region (P<0.1). Our study revealed the response of peak vegetation growth to climate factors and atmospheric pollutants in the Beijing-Tianjin-Hebei region, which are of great significance for an in-depth understanding of the response and feedback of vegetation growth to changes in the climate and air pollution.

Key words: NDVI, POS, NDVImax, PM2.5, meteorological factors, Beijing-Tianjin-Hebei region