| 引用本文: | 刘杰,何云川,邓建明,汤祥明,姚昕.2025.南四湖地区1951—2020年气温短期波动特征及其影响[J].地球环境学报,16(2):194-205 |
| LIU Jie,HE Yunchuan,DENG Jianming,TANG Xiangming,YAO Xin.2025.Characteristics and impacts of short-term temperature f luctuations in the Nansi Lake region from 1951 to 2020[J].Journal of Earth Environment,16(2):194-205 |
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| 南四湖地区1951—2020年气温短期波动特征及其影响 |
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刘杰1, 2，何云川1，邓建明1, 2*，汤祥明1, 2，姚昕3
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1. 中国科学院南京地理与湖泊研究所 湖泊与环境国家重点实验室，南京 210008
2. 中国科学院大学，北京 100049
3. 聊城大学 地理与环境学院，聊城 252000
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| 摘要: |
| 为探究南四湖地区气温短期波动的逐月、季节和年际变化特征，并进一步分析2013—2020年气温短期波动对空气质量的影响，利用南四湖地区1951—2020年最高气温（Tmax）、平均气温（Tmean）和最低气温Tmin）的逐日数据，基于均方差方法、分段线性回归、广义可加模型和Mann-Kendall趋势检验等进行分析。结果表明：（1）南四湖地区1951—1990年Tmax、Tmean和Tmin的波动幅度下降趋势显著（P＜0.01），降幅分别为0.166、0.107和0.129 ℃∙(10a)−1；1991—2020年Tmax、Tmean和Tmin的波动幅度上升趋势不显著（P＞0.05）。（2）南四湖地区1951—1990年气温短期波动季节差异明显，冬季和春季波动降幅均显著（P＜0.05），而夏季仅Tmax的波动降幅显著（P＜0.05）；1991—2020年气温波动无明显季节差异（P＞0.05）。（3）南四湖地区Tmax的逐月波动幅度最大，Tmin次之，Tmean最小。1951—1990年，Tmax在1、2和6月波动幅度下降趋势显著（τ＜0，P＜0.05），Tmin在1、3、4和6月波动幅度下降趋势显著（P＜0.05）；1991—2020年Tmax、Tmean和Tmin的逐月波动幅度趋势均不显著（P＞0.05）。（4）南四湖地区Tmin的逐月短期波动对AQI（P＜0.05）和空气污染物（P＜0.01）影响显著。研究揭示了南四湖地区气温短期波动变化规律及其对空气质量的影响，为南四湖地区空气污染防控和生态调控提供理论基础。 |
| 关键词: 南四湖地区 气温短期波动 均方差 广义可加模型 空气质量 |
| DOI：10.7515/JEE222083 |
| CSTR：32259.14.JEE222083 |
| 分类号: |
| 基金项目:国家自然科学基金项目（41971146）；中国科学院南京地理与湖泊研究所青年科学家小组项目（E1SL002） |
| 英文基金项目:National Natural Science Foundation of China (41971146); Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences Foundation (E1SL002) |
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| Characteristics and impacts of short-term temperature f luctuations in the Nansi Lake region from 1951 to 2020 |
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LIU Jie1, 2, HE Yunchuan1, DENG Jianming1, 2*, TANG Xiangming1, 2, YAO Xin3
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1. State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography & Limnology, Chinese Academy of Sciences, Nanjing 210008, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
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| Abstract: |
| Background, aim, and scope Located across Shandong, Henan, Jiangsu, and Anhui provinces, the Nansi Lake region has prominent ecological environment characteristics. Moreover, the Nansi Lake is a vital regulation and storage lake in the China South-to-North Water Diversion Eastern Route Project. Studying the characteristics of short-term temperature fluctuations in the Nansi Lake region is of great significance for understanding the response of the ecological environment to climate change in this region. Therefore, this study explored monthly, seasonal, and interannual variations of the short-term temperature fluctuations, and their effects on air quality from 2013 to 2020 in the Nansi Lake region. Materials and methods The daily maximum temperature (Tmax), mean temperature (Tmean) and minimum temperature (Tmin) in the Nansi Lake region from 1951 to 2020 were analyzed by the root mean square (RMS), piecewise linear regression, generalized additive models and Mann-Kendall trend test. The warming mutation points in the Nansi Lake region were analyzed by piecewise linear regression. Then the short-term temperature fluctuation amplitudes before and after the warming mutation points were analyzed by the RMS method. Both the generalized additive models and the Mann-Kendall trend test were used to reveal the long-term trends of the short-term temperature fluctuation amplitudes in the Nansi Lake region, and to further analyze the impact of short-term temperature fluctuation amplitudes on air quality. Results (1) Annually, the fluctuation amplitudes of Tmax, Tmean, and Tmin decreased significantly from 1951 to 1990 (P＜0.01), the slope was 0.166, 0.107 and 0.129 ℃·(10a)−1, respectively. While no clear trends were found from 1991 to 2020 (P＞0.05). (2) Seasonally, the fluctuation amplitudes of Tmax, Tmean, and Tmin in winter and spring decreased significantly (P＜0.05) from 1951 to 1990. However, only Tmax fluctuation amplitudes decreased significantly in summer (P＜0.05). The seasonal difference in temperature fluctuation amplitudes was not significant from 1991 to 2020 (P＞0.05). (3) The monthly fluctuation amplitudes of Tmax in the Nansi Lake region were the largest, and followed by fluctuation amplitudes of Tmin, the fluctuation amplitudes of Tmean were the smallest. From 1951 to 1990, the fluctuation amplitudes of Tmax in January, February, and June decreased significantly (τ＜0, P＜0.05), as well as the fluctuation amplitudes of Tmin in January, March, April, and June (P＜0.05). From 1991 to 2020, the monthly fluctuation amplitudes of Tmax, Tmean, and Tmin were not significant (P＞0.05). (4) The short-term fluctuation amplitudes of Tmin in the Nansi Lake region had a significant impact on AQI (correlation analysis, P＜0.05) and air pollutants (correlation analysis, P＜0.01). Discussion Climate change would not only lead to an increase in mean temperature but also an increase in temperature fluctuations. The current study analyzed the long-term trends of temperature fluctuations. Compared with long-term temperature change, short-term temperature fluctuations would significantly impact aquatic ecosystems, air quality, and so on. The RMS was suitable for the short-term temperature fluctuation analysis and would provide a new idea for future climate-related research. The short-term temperature fluctuations showed a downward trend from 1951 to 1990 in the Nansi Lake region, indicating that the temperature fluctuations became gentle and the temperature became more stable. Previous studies found that the intra-seasonal variability of Tmean in winter showed a linear weakening trend from 1961 to 2018 in China, and the RMS was generally greater than 3.0 ℃. It was weaker from the late 1980s to 2004 and stronger after 2005. In this study, the RMS of Tmean was generally greater than 2.5 ℃ in winter from 1951 to 2020 in the Nansi Lake region and was lower in 2007 (2.2 ℃), and the long-term temperature fluctuations showed a sawtooth shape. Several studies suggested that seasonal temperature fluctuations had weakened due to global warming. This study found that the short-term temperature fluctuations were not significant from 1991 to 2020 in the Nansi Lake region. Compared with 1951 to 1990, the seasonal temperature fluctuations were weakened. Recently, the short-term temperature fluctuations were relatively large in the Nansi Lake region, which might lead to an increase in extreme hydrological events, aggravation of lake heat waves, and aggravation of water eutrophication. Conclusions (1) From 1951 to 1990, the short-term temperature fluctuation amplitudes in winter and spring showed a downward trend, and the short-term change of temperature tended to be stable. (2) The short-term fluctuation amplitudes of Tmin had a great impact on air quality. The short-term fluctuation amplitudes of Tmin were significantly positively correlated with AQI, NO2, CO, PM2.5, and PM10, but negatively correlated with O3. Recommendations and perspectives The intensity and frequency of short-term temperature fluctuations in the Nansi Lake region had increased in recent years. It was expected that the impact on the ecological environment would be more significant. While paying attention to global warming, follow-up research should also consider the impact of short-term temperature fluctuations on the ecological environment, and formulate corresponding strategies to mitigate the negative impact of temperature fluctuations. |
| Key words: the Nansi Lake region short-term temperature f luctuations root-mean-square (RMS) generalized additive models air quality |
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