长沙市城市生态系统碳通量时间变化与影响因子研究

发布时间：2018-03-31 15:13

本文选题：涡动相关　切入点：CO_2通量　出处：《中南林业科技大学》2015年硕士论文

【摘要】：受温室气体排放增加的影响,全球气温逐渐增加,气候变暖。城市与人类的关系密切,使城市生态系统在全球变化中起着重要作用。而城市生态系统逐渐成为大气中一个重要碳源。全球已有的对城市生态系统CO2通量的研究主要集中在欧美、日本等发达国家,但与森林、草地、湿地和农田生态系统等下垫面较为均一的陆地生态系统相比,研究仍然较少。本文以城市生态系统为研究对象,基于涡动相关技术获取的2012～2014年连续观测的长沙市城市生态系统碳通量及与碳循环的相关数据,分析了城市生态系统碳通量变化特征及其影响因子。主要结论如下：(1)二次坐标旋转(DR)或三次坐标旋转(TR)变换的pitch角和TR变换的roll角变化大且有明显的方向性,平面拟合(PF)变换的pitch角和roll角数值固定；平均垂直速度观测值不为0,DR和TR变换使全年平均垂直速度为0,PF变换使平均垂直速度明显减小,但不为0。PF变换后的碳通量(Fc_PF)与测定的碳通量(Fc_measured)的相关性与DR变换后的碳通量(Fc_DR)与测定的碳通量(Fc_measured)的相关性。因此,平面拟合倾斜校正方法最适合于本研究。(2)气温呈单波型变化,月均最高气温出现在7月,最低气温出现在1月或2月。各月降水分布非常不均匀,但主要集中在上半年,月总降水量最多在5月、6月,最少在10月、12月。PAR年变化与温度相似,最大月总量出现在7月,最小月总量出现在1月,年变化幅度大。(3)CO2通量具有明显的日变化和季节变化特征。在一天当中,夜间CO2通量为正值且变化幅度小,白天CO2通量基本上为负值且变化幅度大,CO2通量负值持续时间随季节不同而不同。CO2通量日变化有“双峰双谷”的特点,峰值受人为活动影响,谷值受环境因素影响。由1月到7月,平均日较差逐月增大,由7月到12月平均日较差逐月减小。在一年中,CO2通量呈多种变化趋势,最小值一般出现在夏季,最大值与人为排放有关,规律性不强。(4)碳通量对环境因子的响应与时间尺度有关。温度在日、月尺度上与CO2通量呈负相关关系；光合有效辐射(PAR)在日尺度上与CO2通量呈对数函数关系,在月尺度上呈二次多项式函数关系；风速与CO2通量在日尺度上有三次多项式函数关系。风向与CO2通量呈正弦关系。不同类型下垫面的分布会对CO2通量产生影响,风向在0～180。,源大于汇,在180～360。汇大于源。
[Abstract]:Affected by the increase in greenhouse gas emissions, the global temperature is gradually increasing and the climate is warming. Cities are closely related to human beings. The urban ecosystem is becoming an important carbon source in the atmosphere. The research on the CO2 flux of urban ecosystem is mainly concentrated in the developed countries, such as Europe and America, Japan and so on. However, compared with the terrestrial ecosystems with more homogeneous underlying surfaces, such as forests, grasslands, wetlands and farmland ecosystems, the study is still less. Based on the eddy correlation technique, the carbon fluxes of Changsha urban ecosystem and the data related to the carbon cycle were continuously observed from 2012 to 2014. The characteristics of carbon flux variation and its influencing factors in urban ecosystem are analyzed. The main conclusions are as follows: 1) the pitch angle of quadratic coordinate rotation or cubic coordinate rotation (TRT) transformation and the roll angle of tr transform vary greatly and have obvious directivity. The values of pitch angle and roll angle are fixed in plane fitting pitch transform, and the mean vertical velocity is not equal to 0 Dr and tr transform, so that the annual average vertical velocity is 0% PF transform and the average vertical velocity is obviously reduced. However, the correlation between the carbon flux (not 0.PF) and the measured carbon flux (Fcmeasurement) and the correlation between the carbon flux after Dr transformation and the measured carbon flux (Fcmeasurement). Therefore, the plane fitting tilt correction method is most suitable for the single-wave change of temperature in this study. The monthly mean maximum temperature appears in July, and the lowest temperature in January or February. The monthly precipitation distribution is very uneven, but it is mainly concentrated in the first half of the year. The maximum monthly total precipitation is in May, June, at least in October, and the annual variation of par in December is similar to that of temperature. The maximum monthly total occurred in July, and the minimum monthly total occurred in January. The annual variation of CO2 flux was significant. The diurnal and seasonal variation of CO2 flux was obvious. During the day, the night CO2 flux was positive and the variation was small. During the day, the CO2 flux is basically negative and the duration of the negative CO2 flux varies with the seasons. The diurnal variation of .CO2 flux has the characteristics of "double peaks and double valleys", and the peak value is affected by human activities. From January to July, the mean daily range increased month by month, and decreased from July to December. The maximum value is related to anthropogenic emissions, but the response of carbon flux to environmental factors is related to time scale, and the temperature is negatively related to CO2 flux on the daily and monthly scales. The photosynthetic active radiation (par) has a logarithmic relationship with CO2 flux on a daily scale and a quadratic polynomial function on a monthly scale. The relationship between wind speed and CO2 flux is cubic polynomial function on the daily scale. Wind direction and CO2 flux are sinusoidal. The distribution of different types of underlying surface will affect the CO2 flux. The wind direction is 0 ~ 180.The source is larger than the sink, and the sink is larger than the source.
【学位授予单位】：中南林业科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X171

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