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海南岛甲烷浓度与关键气候因子的季节性关联特征

  • 郑彬彬1

    机 构：

    1. 海南大学 生态与环境学院,海口, 570228

    ×
  • ，余瑞1

    机 构：

    1. 海南大学 生态与环境学院,海口, 570228

    ×
  • ，周晓阳1

    机 构：

    1. 海南大学 生态与环境学院,海口, 570228

    ×
  • ，刘玉洁2,3

    机 构：

    2. 中国科学院地理科学与资源研究所,北京, 100101

    3. 中国科学院大学,北京, 100049

    ×
  • ，孙志刚2,3

    机 构：

    2. 中国科学院地理科学与资源研究所,北京, 100101

    3. 中国科学院大学,北京, 100049

    ×
  • ，史文娇2,3

    机 构：

    2. 中国科学院地理科学与资源研究所,北京, 100101

    3. 中国科学院大学,北京, 100049

    ×
  • ，邓祥征2,3

    机 构：

    2. 中国科学院地理科学与资源研究所,北京, 100101

    3. 中国科学院大学,北京, 100049

    ×

1. 海南大学 生态与环境学院,海口, 570228；
2. 中国科学院地理科学与资源研究所,北京, 100101；
3. 中国科学院大学,北京, 100049；

Seasonal correlation between methane concentration and climate change in tropics:case study in Hainan Island

  • ZHENG Binbin1

    Affiliation：

    1. College of Ecology and Environment,Hainan University,Haikou 570228

    ×
  • ，YU Rui1

    Affiliation：

    1. College of Ecology and Environment,Hainan University,Haikou 570228

    ×
  • ，ZHOU Xiaoyang1

    Affiliation：

    1. College of Ecology and Environment,Hainan University,Haikou 570228

    ×
  • ，LIU Yujie2,3

    Affiliation：

    2. Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101

    3. University of Chinese Academy of Sciences,Beijing 100049

    ×
  • ，SUN Zhigang2,3

    Affiliation：

    2. Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101

    3. University of Chinese Academy of Sciences,Beijing 100049

    ×
  • ，SHI Wenjiao2,3

    Affiliation：

    2. Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101

    3. University of Chinese Academy of Sciences,Beijing 100049

    ×
  • ，DENG Xiangzheng2,3

    Affiliation：

    2. Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101

    3. University of Chinese Academy of Sciences,Beijing 100049

    ×

1. College of Ecology and Environment,Hainan University,Haikou 570228；
2. Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101；
3. University of Chinese Academy of Sciences,Beijing 100049；

作者简介:

郑彬彬,女,硕士生,研究方向为生态环境遥感.zbbxgee@gmail.com;

余瑞(通信作者),男,博士,副教授,研究方向为生态环境遥感.yur@outlook.com

中图分类号:Q148

文献标识码:A

DOI:10.13878/j.cnki.jnuist.2022.04.006

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目录contents

    摘要

    甲烷(CH4)作为联合国气候报告着重强调防控的第二大温室气体,其季节性变化及与关键气候因子的关联特征对全球气候变化相关研究至关重要.本研究基于GHGSat甲烷浓度产品,解析以海南岛陆地为典型热带研究区的甲烷浓度季节性变化特征,同时厘定了海南岛甲烷浓度时空分布对关键气候因子等的敏感性,并基于增强回归树(Boosted Regression Trees,BRT)分析了非生物因子如气候和地形对甲烷浓度分布的贡献度,结果表明:1)海南岛甲烷浓度在时间上具有显著的季节性变化特征,即在4—8月呈显著下降趋势,在9—12月呈显著上升趋势,而甲烷浓度的空间分布也具有明显的区域差异性,即海岸线附近甲烷浓度较高,而甲烷浓度低值分布多集中于中部地区;2)甲烷浓度与关键气候因子的线性回归模型结果显示气温与甲烷浓度呈弱正相关,而降雨与甲烷浓度存在弱负相关关系;3)BRT模拟结果显示,三种非生物因子海拔、降雨和气温对甲烷浓度分布的贡献度分别71.95%、20.52%、5.66%.本研究可为解析关键气候因子对甲烷排放的贡献度提供科学依据.

    Abstract

    Spatio-temporal change characteristics and driving factors of methane (CH4) concentration are important to the study of global climate change.Yet few reports have been found to reveal the variation characteristics of methane concentration on different time scales and the contribution of potential climate drivers in the tropics.In this study,based on GHGsat methane concentration products,the seasonal variation characteristics of methane concentration were analyzed by taking Hainan Island as a typical tropical study area.In addition,this study determined the sensitivity of temporal and spatial distribution of methane to climatic factors in Hainan Island,and also analyzed the contribution of climate factors and topographic factors to methane concentration by using Boosted Regression Trees (BRT).The results showed that methane concentration in Hainan Island had significant seasonal variations,which was a significant downward trend from April to August and a significant upward trend from September to December;spatially,the areas with high methane concentration were mainly clustered around coastline,while low methane concentration area was mainly distributed in the middle of Hainan Island.The results of the univariate linear regression model showed that there was a weak positive correlation between air temperature and methane concentration,and a weak negative correlation between rainfall and methane concentration.The results of BRT showed that the contribution of altitude,rainfall and air temperature to methane concentration distribution is 71.95%,20.52% and 5.66%,respectively.This study can provide a scientific basis for the contribution of climatic factors to methane emissions.

    关键词

    海南岛 ； 甲烷浓度 ； 季节变化 ； 气温 ； 降雨

  • 0 引言

  • 甲烷是仅次于CO2的第二大人类活动温室气体,其对长寿命温室气体辐射强迫增加的贡献率为16%[1].甲烷在大气中的存续时间比CO2短,但其全球变暖潜能约为CO2的28倍.世界气象组织的温室气体公报显示,2020年大气中的甲烷浓度已上升到1 889×10-9 mol/mol,并且监测记录值还在不断增长[2].此外甲烷还是平流层水蒸气增加的主要贡献者[3],而对流层上部和平流层下部的水汽变化对全球变暖具有重要影响,甲烷浓度的变化关系到区域乃至全球气候变化.大气甲烷(CH4)来源既有以湿地排放为主的自然源,也有以农业和工业为主的人为源.地表甲烷源汇平衡决定了全球甲烷收支[4].地表甲烷来源包括生物源(湿地、湖泊、农业、废物/填埋场、永久冻土)、热源(化石燃料使用和自然渗漏、生物量和生物燃料燃烧)或混合源(水合物、地质).全球甲烷排放的60%来自人为源,主要包括中纬度和热带的活动,如农业活动和废物处理等,其余40%为自然源[1],主要源自湿地的甲烷排放,并且湿地的甲烷排放对关键气候因子的变化高度敏感[5].

  • 热带地区甲烷浓度在时间和空间分布上具有异质性,且关键气候因子直接或者间接影响着甲烷浓度的时空分布.从20世纪90年代中期到2000年代中期,大气中甲烷浓度的增长率接近于零,反映出其源和汇的近平衡.然而,自2006年以来,增长率再次转为正值[6],其中北半球中纬度地区和热带地区增幅最大[7],目前这一增长的成因尚未达成一致见解,但关于人类活动导致的甲烷排放增长以及气候变化导致的热带和亚热带湿地排放增加的认知却日趋明晰.热带湿地被认为是极为重要的甲烷排放来源[7],已有研究显示热带地区的甲烷排放量约占全球排放总量的2/3[4],但目前针对热带地区甲烷浓度时空分布的特征及其与气候变化的关联研究鲜有报道.关键气候因子中气温与降雨对甲烷浓度影响最为显著[8].气候变暖和降雨增加通常相伴发生[9],已有大量研究报道降雨的增加显著降低了甲烷的净吸收速率,促进了甲烷的排放[10];气温则通过影响生物系统中的反应速率[11],直接刺激产甲烷菌的生物活性,进而促进甲烷排放.典型泥炭地中甲烷排放因素的研究结果显示泥炭地甲烷排放对温度具有极强的依赖性[12-13].进一步地,Javadinejad等[14]研究发现甲烷浓度与气温、地表温度呈正相关,与降雨、湿度呈负相关.由此可见,热带地区甲烷浓度与气温和降雨变化密切关联.

  • 除此之外,大气甲烷浓度还具有明显的季节性特征.Crevoisier等[15]利用GOSAT、MODIS的卫星数据以及降雨、温度和湿度等气候数据反演得到北美地区甲烷的时空分布特征,结果表明其在北半球热带地区具有强季节性关联,其最大值出现在1—3月,最小值出现在7—9月,而在南半球热带地区具有较弱的季节性关联;Xiong等[16]研究认为中国甲烷排放通常在夏季达到最大值;Crippa等[17]根据全球大气研究排放数据库(EDGAR)5.0版提供的1970—2015年的年度人为甲烷排放网格图和2015年的月度数据发现,中国甲烷浓度的季节性变化主要原因是农业活动在6—8月达到峰值.虽然此类研究的数据具有很大的不确定性,尤其是EDGAR数据将中国地区的甲烷浓度高估了近1倍,但研究结果均表明气候因子季节性变化影响着大气甲烷浓度.目前,关于甲烷的研究多集中于甲烷汇与源及浓度变化的研究[18],而少有关于其与关键气候因子季节性关联的研究.本研究结合多种遥感数据产品探讨不同季节甲烷浓度趋势和气温趋势、降雨趋势的相关性,厘定海南岛甲烷浓度与关键气候因子的关联效应;同时利用增强回归树模型,探索关键气候因子与地形因子对甲烷浓度分布的贡献度.本研究可为实现非二氧化碳温室气体的减排与气候变化管理提供科学依据.

  • 1 材料和方法

  • 1.1 研究区概况

  • 海南岛地处热带北缘,地理位置介于108°03′~111°03′E和18°10′~20°10′N之间,高程分布区间为-43~1 821m(图1).气候类型属热带海岛季风气候,气温年较差小,全年平均气温为22.5~25.6℃,年均降雨量为900~2 500mm,一年分干湿两季,随着降雨不断增多,海南岛5月开始进入雨季直至10月结束,全年80%~90%的降水集中在雨季;11月起进入旱季持续到来年4月.地形地貌复杂多样,土地利用类型丰富,土地利用现状以林地和耕地为主,农田可全年种植.

  • 1.2 数据与处理

  • 本研究所使用的原始甲烷浓度数据来自GHGSat(https://pulse.ghgsat.com/),该数据集提供2020年4月至2021年11月、空间分辨率为2km×2km、时间分辨率为7d的全球甲烷浓度信息,此数据集经相关项目的前期研究做了系统整理[19-20].本研究将每7d的甲烷均值数据合成月尺度和年尺度数据,并在后续研究中利用1—12月的甲烷浓度月均值进行分析.气温和降雨数据源自国家科技基础条件平台——国家地球系统科学数据中心黄土高原分中心(http://loess.geodata.cn),该数据集通过Delta空间降尺度方案根据CRU发布的全球0.5°气候数据集以及WorldClim发布的全球高分辨率气候数据集在中国地区降尺度生成,并且使用496个独立气象观测点数据进行了数据验证.DEM数据集来自中国科学院资源环境科学与数据中心(https://www.resdc.cn/),数据采用WGS84椭球投影,基于最新的SRTM V4.1数据经整理拼接生成的90m的分省数据.本研究将其空间分辨率采样至0.01°,并使用ArcGIS中的空间分析工具根据海拔高度计算出坡度和坡向.

  • 图1 海南岛DEM

  • Fig.1 DEM of Hainan Island

  • 1.3 研究方法

  • 1.3.1 基于降雨效应的干湿季划分和趋势分析

  • 基于甲烷浓度像元尺度的趋势分析法能模拟海南岛中每个栅格单元的甲烷浓度变化趋势,从而反映甲烷浓度变化的方向和速率.计算公式为

  • Y=n∑i=1n i×yi-∑i=1n i∑i=1n yin∑i=1n i2-∑i=1n i2,
    (1)

  • 式中:Y 表示甲烷浓度像元线性回归方程的斜率;yi表示甲烷浓度;i代表月数;n为时间跨度.当Y ＞0时,甲烷浓度呈增加趋势;当Y=0时,甲烷浓度基本稳定,无明显变化;当Y ＜0时,甲烷浓度呈减少趋势.

  • 1.3.2 趋势相关性分析

  • 本研究计算了甲烷浓度趋势与关键气候因子趋势的相关性,如下所示:

  • r=∑i=1n xi-x-yi-y-∑i=1n xi-x-2∑i=1n yi-y-2,
    (2)

  • xi为1—12月气温或降雨的逐像元趋势,yi 为1—12月甲烷浓度的逐像元趋势,n 为像元数.随后,对甲烷浓度趋势、气温趋势以及降雨趋势构建多元线性回归模型,并以回归系数来估计各因子的贡献度,进而确定在不同气温和降雨条件下影响甲烷浓度时空分布的主导因素.

  • 1.3.3 基于BRT的相对贡献率分析

  • 使用增强回归树(Boosted Regression Tree,BRT)评估1—12月气候因子与地形因子对于海南岛甲烷浓度变化的相对影响程度.此算法通过递归二元分割预测变量数据集建立小回归树的大集合,并利用线性回归方法对该集合进行建模.本研究在进行BRT分析之前,对甲烷浓度与气候因子以及地形因子进行皮尔逊相关分析和显著性分析.使用R语言中的GBM包进行BRT分析,得到关键气候因子和地形因子在干季和湿季对甲烷浓度的相对贡献率.将1—12月平均甲烷浓度的逐像元数据作为响应变量,同一时期的气候因子和地形因子作为解释变量.BRT算法原理如下:

  • 假设数据集为D=x1,y1,x2,y2,⋯,xN,yN,损失函数L(y,f(x)),每棵回归树的叶节点数为J,将其输入空间分割成互不相交的区域R1m,R2m, ···,Rjm ,每个区域估计的常量值bm,回归树gm(x).

  • 1)f(x)表示响应变量y (甲烷浓度)和解释变量x(气候因子和地形因子)之间的关系,将它们的初始值设置为0,则

  • f0(x)=0
    (3)

  • 2)m为迭代序列值,样本总数为n,当m=1∶n时,则残差

  • r=∂L(y,f(x))∂f(x)f(x)=fm-1(x)
    (4)

  • 3)利用最小二乘回归树对2)中所得的残差r采用平方误差作为损失函数L,通过计算损失函数L最小值求取每棵树节点的权重ρm:

  • ρm=Ly,fm-1(x)+ρgm(x)
    (5)

  • 4)通过计算回归树节点权重,更新回归树模型:

  • fm(x)=fm-1(x)+ρmgm(x)
    (6)

  • 5)输出最终的BRT模型:

  • f(x)=∑m fm
    (7)

  • 2 结果

  • 2.1 甲烷浓度变化季节性规律

  • 本研究分析2020—2021年间甲烷浓度的月均值变化的季节性规律,结果表明海南岛甲烷浓度具有季节性波动特征,且与关键气候因子的变化在月尺度上具有较高的一致性(图2).总体来看,甲烷浓度在2—8月呈缓慢下降趋势,并于8月降至最低值1 752×10-9 mol/mol,而在9月到次年1月呈迅速增加趋势,并于次年1月达到最大值约为1 878×10-9 mol/mol.相比之下,月尺度的气温数据呈现先增后减的趋势,即1—5月气温逐渐升高,并在5月气温达到最大值29.57℃,而6—12月气温逐渐降低.降雨的年内变化表现为:1—8月,降雨逐渐增加;9—10月受台风影响较大,降雨出现较为明显的波动,并在10月达到最大值327.91mm;随后的11—12月,降雨逐渐减少.基于上述气温和降雨的年内变化规律,即在1—4月、11—12月气温与降雨量较小,5—10月气温较高、降雨量大,因此,本研究将海南岛1—4月、11—12月划分为干季,5—10月划分为湿季单独分析.

  • 图2 2020—2021年甲烷浓度月均值与气温、降雨月均值变化趋势

  • Fig.2 Trends of monthly means of CH4 concentration, air temperature and rainfall from 2020to 2021

  • 2.2 海南岛甲烷浓度的空间分布和趋势变化

  • 全年、湿季以及干季的甲烷浓度空间分布分别如图3a、图3b及图3c所示.海南岛全年甲烷浓度月均值的最高值为1 900×10-9 mol/mol,最低值为1 721×10-9 mol/mol;海南岛大部分地区的甲烷浓度均大于1 800×10-9 mol/mol,甲烷浓度的高值集中在海南岛沿海地区,而在海南岛中部为甲烷浓度低值聚集区(图3a).湿季甲烷浓度的分布较为均匀,其中最高值为1 898×10-9 mol/mol,最低值为1 710×10-9 mol/mol,其分布特征与全年甲烷浓度的分布相似(图3b);干季的甲烷浓度最高值为1 903×10-9 mol/mol,最低值为1 707×10-9 mol/mol,干季甲烷浓度的高值多分布在海南岛西线,如文昌、海口、澄迈、临高、东方等市县,甲烷浓度低值则聚集在海南岛中部山区,如五指山、霸王岭以及尖峰岭一带(图3c).干季甲烷浓度最高值较湿季增加了5×10-9 mol/mol,但最低值较湿季降低了3×10-9 mol/mol.

  • 应用线性回归对海南岛甲烷浓度1—12月进行逐月趋势变化分析,绘制甲烷浓度的趋势变化空间分布图(图3d、图3e、图3f).1—12月甲烷浓度趋势变化如图3d所示,甲烷浓度呈现显著下降趋势的区域占比为50.35%(P ＜0.05),甲烷浓度呈现显著增长趋势的区域占比为0.90%(P ＜0.05),甲烷浓度无显著变化的区域占比为48.75%.从甲烷浓度变化趋势空间分布来看,甲烷浓度显著增长区域主要集中在海南岛中部地区,而显著下降区域仅零星分散在海南岛西南部.湿季甲烷浓度的趋势变化如图3e所示,甲烷浓度呈现显著下降趋势的区域占比为20.21%(P ＜0.05),甲烷浓度呈现显著增长趋势的区域占比为0.52%(P ＜0.05),甲烷浓度无显著变化的区域占比为79.27%.干季甲烷浓度的趋势变化如图3f所示,甲烷浓度呈现显著下降趋势的区域占比为26.00%(P ＜0.05),甲烷浓度呈现显著增长趋势的区域占比为1.05%(P ＜0.05),甲烷浓度无显著变化的区域占比为72.95%.干季的甲烷浓度趋势变化与全年甲烷浓度的月变化趋势变化相似,但呈显著下降趋势的区域明显减少.湿季的甲烷浓度与全年甲烷浓度的月变化趋势相比,显著增长趋势占比降低了0.38个百分点,显著下降趋势占比降低了30.14个百分点;与干季趋势相比,湿季的甲烷浓度显著增长趋势占比降低了0.53个百分点,显著下降趋势占比降低了5.79个百分点.

  • 图3 甲烷浓度空间分布及趋势变化(a、b、c分别为全年、湿季、干季甲烷浓度的空间分布; d、e、f分别为全年、湿季、干季甲烷浓度的空间趋势变化)

  • Fig.3 Spatial distributions (a-c) and trends (d-f) of CH4 concentration in the whole year (a,d), wet season (b,e) and dry season (c,f)

  • 2.3 关键气候因子对甲烷浓度季节性变化的贡献度

  • 不同季节的甲烷浓度与气候因子、地形因子进行皮尔逊相关分析以及显著性检验的结果显示:全年甲烷浓度与气温、降雨、海拔以及坡度均存在相关性(P ＜0.01),相关系数分别为0.29、-0.24、-0.37、-0.22,而与坡向无显著相关性(图4a);湿季甲烷浓度与气温、降雨、海拔以及坡度均有相关性(P ＜0.01),相关系数分别为0.22、-0.32、0.24、-0.12,而与坡向无显著相关性(图4b);干季甲烷浓度与气温、降雨、海拔、坡度均存在相关性(P ＜0.01),相关系数分别为0.32、-0.11、-0.49、-0.34(图4c).

  • 本研究选择气温、降雨、海拔和坡度作为非生物因子,计算其在不同季节对甲烷浓度分布的贡献度(由于坡向对甲烷浓度影响极小,故在文中未作分析).结果分别如图5a、5b、5c所示:影响甲烷浓度分布最大的非生物影响因子是海拔,其相对贡献率高达71.95%,其次分别为降雨、气温和坡度,相对贡献率依次为20.52%、5.66%、1.87%;对湿季甲烷浓度影响程度最大的因子也是海拔,但其相对贡献率有所减小,贡献率为53.77%,而降雨、气温和坡度的相对贡献率依次为28.98%、15.12%、2.12%;对干季甲烷浓度分布影响程度最大的仍是海拔,为75.63%,其相对贡献率远高于湿季,降雨、气温和坡度的相对贡献率依次为18.37%、3.68%、2.33%.

  • 为进一步探明关键气候因子对海南岛甲烷浓度时空分布的贡献度,本文将甲烷浓度趋势和气候因子(气温、降雨)趋势进行相关性分析.结果显示,全年、湿季、干季的甲烷浓度趋势与气温趋势均有正相关性,其中:全年甲烷浓度趋势与气温趋势的相关系数为0.29(图6a);湿季甲烷浓度趋势与气温趋势的相关系数为0.22(图6b),较全年甲烷浓度趋势同气温趋势的相关系数降低了0.07;干季甲烷浓度趋势与气温趋势的相关系数为0.32(图6c),是三者中相关性最高的,比全年甲烷浓度趋势与气温趋势的相关系数高出了0.3.不论是全年甲烷浓度趋势还是干季、湿季的甲烷浓度趋势均与降雨的趋势成负相关关系(图6d、图6e、图6f),其中:全年甲烷浓度与降雨的相关系数为-0.24(图6d);湿季甲烷浓度趋势与降雨趋势的相关系数为-0.32(图6e),相较全年甲烷浓度趋势而言,其与降雨趋势的相关系数降低了0.8;干季甲烷浓度趋势与降水趋势的相关系数为-0.11(图6f),低于前两者的相关系数,可见在干季降雨趋势对甲烷浓度趋势变化影响较小.

  • 图4 甲烷浓度与气候、地形等因子的相关性热力图(pre、tem、dem、aspect、slope分别表示降雨、气温、海拔、坡向、坡度a、b、c分别表示全年、湿季和干季三个时期)

  • Fig.4 Related thermal maps between CH4 concentration,climatic and terrain factors for the whole year (a),wet season (b) and dry season (c)(The tem,pre,aspect,dem and slope represent temperature,precipitation,aspect,altitude and slope)

  • 图5 基于BRT分析各因子对甲烷浓度分布的贡献度(pre、tem、dem、slope分别表示降雨、气温、海拔以及坡度, a、b、c分别表示全年、湿季和干季三个时期)

  • Fig.5 Contributions of each factor to methane distribution based on BRT analysis for the whole year (a),wet season (b) and dry season (c)(The pre,tem,dem and slope represent precipitation,temperature,altitude and slope)

  • 3 讨论

  • 本研究表明海南地区甲烷浓度具有极为显著的季节性,甲烷浓度在1—4月、9—12月逐渐增加,并于4月底达到最高值;5—8月逐渐下降,并于8月底降至最低值.这一结论与Crevoisier等[15]利用红外大气探测干涉仪(IASI)、高级微波探测单元(AMSU)反演2007年7月至2008年10月北热带甲烷浓度得到的结论相吻合,即甲烷浓度具有季节性变化规律,在7—9月出现最小值,在1—3月出现最大值.但Javadinejad等[14]利用GOSAT和MODIS的卫星数据以及降雨、温度和湿度等气候数据,分析了2012—2018年北美地区甲烷浓度的月变化和季节变化所得出的结果却表明:10月和9月甲烷浓度最大,3月和4月甲烷浓度最小.上述甲烷浓度季节性变化特征的差异源自季风的影响[21]:南半球西南季风的侵入是影响区域甲烷浓度偏低的原因;季风后西南气流减弱时大气甲烷浓度通常最高.甲烷浓度在2—4月出现最大峰值可能是废水和垃圾场、肠道发酵和动物粪便管理的排放起主导作用[22].Saunois等[7]认为甲烷浓度具有季节性变化特征,生产资源(湿地、稻田和燃烧的生物质)的季节性变化以及甲烷在大气反应中的排放为主要影响因素.

  • 3.1 甲烷浓度与气温的季节性关联特征

  • 温度对甲烷的产生和氧化起着重要作用.本研究中气温与甲烷浓度的线性回归分析的回归系数为0.29,表明随气温升高甲烷浓度也随之升高,这与宋朝清等[23]研究得出的结论相类似,即在环境温度小于产甲烷菌的最适温度(30~40℃)时,随着气温升高甲烷浓度会不断增高.温度的变化可以使产甲烷菌和甲烷氧化菌由休眠状态快速转化为活化状态,从而彻底改变反应的速率继而影响甲烷的排放.同时,植物介导的运输、分子扩散以及甲烷的运动也随着气温的升高而增强[24-25],进而间接影响甲烷浓度.目前已有大量研究证实了这一观点,如Sweeney等[26]的研究表明甲烷浓度对温度较为敏感,即在适宜温度内气温每升高10℃,甲烷浓度约增加1倍.Turetsky等[27]的研究发现甲烷浓度与产甲烷微生物生物量的丰度之间存在显著的正相关关系,表明温度变化也会刺激产甲烷微生物数量的增加,并且甲烷在温室气体排放总量中的相对贡献随着季节气温的升高而增加[28-29],这也与本研究中气温是影响甲烷季节性浓度分布特征的关键气候因子之一的结论相契合[30].

  • 图6 甲烷浓度趋势与气温、降雨趋势的相关性散点图(a、b、c分别表示全年、湿季、干季与气温趋势的相关性; d、e、f分别表示全年、湿季、干季与降雨趋势的相关性)

  • Fig.6 Correlations between trends of CH4 and temperature (a-c),CH4 and rainfall (d-f) for the whole year (a,d),wet season (b,e) and dry season (c,f)

  • 3.2 甲烷浓度与降雨的季节性关联特征

  • 温度和降雨的季节性变化与甲烷的浓度分布通常具有很强的关联性[31](图2).土壤中甲烷浓度受到许多环境因素的控制,如降雨、温度和氮沉降[32].本研究将甲烷浓度与降雨进行线性回归分析,其回归系数为-0.24,结果表明降雨量与甲烷浓度存在负相关关系.Wu等[31]认为8月土壤甲烷吸收速率明显低于同年7月和9月,主要原因可能是较高的降雨量导致土壤环境出现半缺氧状态,并刺激甲烷的产生[33].已有研究表明,降雨增加会影响土壤碳氮循环、生态系统呼吸和植物生长,这表明降雨在调节陆地生态系统功能方面发挥着重要作用[34].因为降雨控制土壤是否受涝[35],所以即使是微小的降雨变化也可能影响微生物的活动和丰度,从而控制土壤甲烷的生产和消耗.研究发现降雨增加显著降低了甲烷的净吸收速率,促进了甲烷的产生[10].相反,较低的土壤水分水平会减少碳的释放,这表明较干燥的土壤是主要的甲烷汇[36].

  • 4 结论

  • 本研究基于高分辨率的卫星遥感数据,对海南岛地区甲烷浓度的时空变化特征及其与气候因子的季节性关联分析得出:

  • 1)海南岛甲烷浓度存在显著的季节性变化,在2—4月浓度较大,而在8—11月浓度较低.

  • 2)甲烷浓度与气温呈正相关,在1—4月随着气温增加,甲烷浓度也随之增加;甲烷浓度和降雨存在负相关关系,在9—11月随着海南岛降雨量的增加,甲烷浓度随之降低.

  • 3)甲烷浓度受多种环境因素影响,其中最为显著的是海拔高度,这可能与海南岛的地形、植被分布及人类活动有关,但本文关注于关键气候因子的作用,人类活动的影响未作考虑,这也是未来需进一步推进的研究方向之一.

  • 4)本研究所采用的GHGSat甲烷数据产品与GOSAT数据产品相比,虽时间分辨率及空间分辨率较高,但在海南地区GHGSat数据缺失较为严重,整个海南岛地区仅有2020年4月至今的数据,且五指山热带雨林国家公园地区几乎没有甲烷的浓度数据,也影响着本文甲烷浓度与气温和降雨之间的季节性关联分析结果,且数据准确性暂未做验证,未来亟需一套全国尺度高分辨率高质量的甲烷浓度数据集,为我国非二氧化碳温室气体减排提供数据支撑.

  • 参考文献

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    • [2] IPCC.Climate change 2021:the physical science basis[R].Cambridge,UK,and New York,USA:Cambridge University Press,2021

    • [3] Keppler F,Hamilton J T G,Brass M,et al.Methane emissions from terrestrial plants under aerobic conditions[J].Nature,2006,439(7073):187-191

    • [4] Saunois M,Bousquet P,Poulter B,et al.Variability and quasi-decadal changes in the methane budget over the period 2000-2012[J].Atmospheric Chemistry and Physics,2017,17(18):11135-11161

    • [5] Fletcher S,Schaefer H.Rising methane:a new climate challenge[J].Science,2019,364(6444):932-933

    • [6] Nisbet E G,Dlugokencky E J,Bousquet P.Methane on the rise—again[J].Science,2014,343(6170):493-495

    • [7] Saunois M,Jackson R B,Bousquet P,et al.The growing role of methane in anthropogenic climate change[J].Environmental Research Letters,2016,11(12):120207

    • [8] Ringeval B,de Noblet-Ducoudré N,Ciais P,et al.An attempt to quantify the impact of changes in wetland extent on methane emissions on the seasonal and interannual time scales[J].Global Biogeochemical Cycles,2010,24(2):GB2003.DOI:10.1029/2008gb003354

    • [9] Easterling D R,Meehl G A,Parmesan C,et al.Climate extremes:observations,modeling,and impacts[J].Science,2000,289(5487):2068-2074

    • [10] Aronson E L,Helliker B R.Methane flux in non-wetland soils in response to nitrogen addition:a meta-analysis[J].Ecology,2010,91(11):3242-3251

    • [11] Davidson E A,Janssens I A.Temperature sensitivity of soil carbon decomposition and feedbacks to climate change[J].Nature,2006,440(7081):165-173

    • [12] Mikhaylov O A,Miglovets M N,Zagirova S V.Vertical methane fluxes in mesooligotrophic boreal peatland in European Northeast Russia[J].Contemporary Problems of Ecology,2015,8(3):368-375

    • [13] Marushchak M E,Friborg T,Biasi C,et al.Methane dynamics in the subarctic tundra:combining stable isotope analyses,plot-and ecosystem-scale flux measurements[J].Biogeosciences,2016,13(2):597-608

    • [14] Javadinejad S,Eslamian S,Ostad-Ali-Askari K.Investigation of monthly and seasonal changes of methane gas with respect to climate change using satellite data[J].Applied Water Science,2019,9(8):1-8

    • [15] Crevoisier C,Nobileau D,Fiore A M,et al.Tropospheric methane in the tropics-first year from IASI hyperspectral infrared observations[J].Atmospheric Chemistry and Physics,2009,9(17):6337-6350

    • [16] Xiong X,Houweling S,Wei J,et al.Methane plume over south Asia during the monsoon season:satellite observation and model simulation[J].Atmospheric Chemistry and Physics,2009,9(3):783-794

    • [17] Crippa M,Solazzo E,Huang G L,et al.High resolution temporal profiles in the emissions database for global atmospheric research[J].Scientific Data,2020,7:121

    • [18] Stocker B D,Spahni R,Joos F.DYPTOP:a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands[J].Geoscientific Model Development,2014,7(6):3089-3110

    • [19] 邓祥征,丹利,叶谦,等.碳排放和减碳的社会经济代价研究进展与方法探究[J].地球信息科学学报,2018,20(4):405-413;DENG Xiangzheng,DAN Li,YE Qian,et al.Methodological framework and research progress on the social and economic costs of carbon emission and reduction[J].Journal of Geo-Information Science,2018,20(4):405-413

    • [20] 邓祥征,蒋思坚,刘冰,等.全球二氧化碳浓度非均匀分布条件下碳排放与升温关系的统计分析[J].自然资源学报,2021,36(4):934-947;DENG Xiangzheng,JIANG Sijian,LIU Bing,et al.Statistical analysis of the relationship between carbon emissions and temperature rise with the spatially heterogenous distribution of carbon dioxide concentration[J].Journal of Natural Resources,2021,36(4):934-947

    • [21] Chandra N,Hayashida S,Saeki T,et al.What controls the seasonal cycle of columnar methane observed by GOSAT over different regions in India?[J].Atmospheric Chemistry and Physics,2017,17(20):12633-12643

    • [22] Metya A,Datye A,Chakraborty S,et al.Diurnal and seasonal variability of CO2 and CH4 concentration in a semi-urban environment of western India[J].Scientific Reports,2021,11(1):1-13

    • [23] 宋朝清,刘伟,陆海波,等.基于通量测量的稻田甲烷排放特征及影响因素研究[J].地球科学进展,2019,34(11):1141-1151;SONG Chaoqing,LIU Wei,LU Haibo,et al.Characteristics and drivers of methane fluxes from a rice paddy based on the flux measurement[J].Advances in Earth Science,2019,34(11):1141-1151

    • [24] Christensen T R,Ekberg A,Ström L,et al.Factors controlling large scale variations in methane emissions from wetlands[J].Geophysical Research Letters,2003,30(7):67.DOI:10.1029/2002gl016848

    • [25] Christensen T R,Panikov N,Mastepanov M,et al.Biotic controls on CO2 and CH4 exchange in wetlands:a closed environment study[J].Biogeochemistry,2003,64(3):337-354

    • [26] Sweeney C,Dlugokencky E,Miller C E,et al.No significant increase in long-term CH4 emissions on north slope of Alaska despite significant increase in air temperature[J].Geophysical Research Letters,2016,43(12):6604-6611

    • [27] Turetsky M R,Treat C C,Waldrop M P,et al.Short-term response of methane fluxes and methanogen activity to water table and soil warming manipulations in an Alaskan peatland[J].Journal of Geophysical Research:Atmospheres,2008,113:G00A10

    • [28] Yvon-Durocher G,Allen A P,Bastviken D,et al.Methane fluxes show consistent temperature dependence across microbial to ecosystem scales[J].Nature,2014,507(7493):488-491

    • [29] Bao T,Jia G S,Xu X Y.Wetland heterogeneity determines methane emissions:a pan-Arctic synthesis[J].Environmental Science & Technology,2021,55(14):10152-10163

    • [30] Song W M,Wang H,Wang G S,et al.Methane emissions from an alpine wetland on the Tibetan Plateau:neglected but vital contribution of the nongrowing season[J].Journal of Geophysical Research:Biogeosciences,2015,120(8):1475-1490

    • [31] Wu H B,Wang X X,Ganjurjav H,et al.Effects of increased precipitation combined with nitrogen addition and increased temperature on methane fluxes in alpine meadows of the Tibetan Plateau[J].Science of the Total Environment,2020,705:135818

    • [32] Wei D,Wang Y,Wang Y.Considerable methane uptake by alpine grasslands despite the cold climate:in situ measurements on the central Tibetan Plateau,2008-2013[J].Global Change Biology,2015,21(2):777-788

    • [33] Fang H J,Cheng S L,Yu G R,et al.Low-level nitrogen deposition significantly inhibits methane uptake from an alpine meadow soil on the Qinghai-Tibetan Plateau[J].Geoderma,2014,213:444-452

    • [34] Lin L,Zhu B,Chen C R,et al.Precipitation overrides warming in mediating soil nitrogen pools in an alpine grassland ecosystem on the Tibetan Plateau[J].Scientific Reports,2016,6:31438

    • [35] Chen X P,Wang G X,Huang K W,et al.The effect of nitrogen deposition rather than warming on carbon flux in alpine meadows depends on precipitation variations[J].Ecological Engineering,2017,107:183-191

    • [36] Menon S,Denman K L,Brasseur G,et al.Couplings between changes in the climate system and biogeochemistry[R].Berkeley:Lawrence Berkeley National Lab(LBNL),2007

  • 基本信息

    中图分类号: Q148
    文献标识码: A
    DOI: 10.13878/j.cnki.jnuist.2022.04.006

    基金信息

    国家自然科学基金(72104065)；
    海南省自然科学基金(321RC472)；
    国家重点研发计划(2016YFA0602500)；

    引用信息

    稿件历史

    收稿日期: 2022-01-16

  • 参考文献

    • [1] Caesar L,McCarthy G D,Thornalley D J R,et al.Current Atlantic meridional overturning circulation weakest in last millennium[J].Nature Geoscience,2021,14(3):118-120

    • [2] IPCC.Climate change 2021:the physical science basis[R].Cambridge,UK,and New York,USA:Cambridge University Press,2021

    • [3] Keppler F,Hamilton J T G,Brass M,et al.Methane emissions from terrestrial plants under aerobic conditions[J].Nature,2006,439(7073):187-191

    • [4] Saunois M,Bousquet P,Poulter B,et al.Variability and quasi-decadal changes in the methane budget over the period 2000-2012[J].Atmospheric Chemistry and Physics,2017,17(18):11135-11161

    • [5] Fletcher S,Schaefer H.Rising methane:a new climate challenge[J].Science,2019,364(6444):932-933

    • [6] Nisbet E G,Dlugokencky E J,Bousquet P.Methane on the rise—again[J].Science,2014,343(6170):493-495

    • [7] Saunois M,Jackson R B,Bousquet P,et al.The growing role of methane in anthropogenic climate change[J].Environmental Research Letters,2016,11(12):120207

    • [8] Ringeval B,de Noblet-Ducoudré N,Ciais P,et al.An attempt to quantify the impact of changes in wetland extent on methane emissions on the seasonal and interannual time scales[J].Global Biogeochemical Cycles,2010,24(2):GB2003.DOI:10.1029/2008gb003354

    • [9] Easterling D R,Meehl G A,Parmesan C,et al.Climate extremes:observations,modeling,and impacts[J].Science,2000,289(5487):2068-2074

    • [10] Aronson E L,Helliker B R.Methane flux in non-wetland soils in response to nitrogen addition:a meta-analysis[J].Ecology,2010,91(11):3242-3251

    • [11] Davidson E A,Janssens I A.Temperature sensitivity of soil carbon decomposition and feedbacks to climate change[J].Nature,2006,440(7081):165-173

    • [12] Mikhaylov O A,Miglovets M N,Zagirova S V.Vertical methane fluxes in mesooligotrophic boreal peatland in European Northeast Russia[J].Contemporary Problems of Ecology,2015,8(3):368-375

    • [13] Marushchak M E,Friborg T,Biasi C,et al.Methane dynamics in the subarctic tundra:combining stable isotope analyses,plot-and ecosystem-scale flux measurements[J].Biogeosciences,2016,13(2):597-608

    • [14] Javadinejad S,Eslamian S,Ostad-Ali-Askari K.Investigation of monthly and seasonal changes of methane gas with respect to climate change using satellite data[J].Applied Water Science,2019,9(8):1-8

    • [15] Crevoisier C,Nobileau D,Fiore A M,et al.Tropospheric methane in the tropics-first year from IASI hyperspectral infrared observations[J].Atmospheric Chemistry and Physics,2009,9(17):6337-6350

    • [16] Xiong X,Houweling S,Wei J,et al.Methane plume over south Asia during the monsoon season:satellite observation and model simulation[J].Atmospheric Chemistry and Physics,2009,9(3):783-794

    • [17] Crippa M,Solazzo E,Huang G L,et al.High resolution temporal profiles in the emissions database for global atmospheric research[J].Scientific Data,2020,7:121

    • [18] Stocker B D,Spahni R,Joos F.DYPTOP:a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands[J].Geoscientific Model Development,2014,7(6):3089-3110

    • [19] 邓祥征,丹利,叶谦,等.碳排放和减碳的社会经济代价研究进展与方法探究[J].地球信息科学学报,2018,20(4):405-413;DENG Xiangzheng,DAN Li,YE Qian,et al.Methodological framework and research progress on the social and economic costs of carbon emission and reduction[J].Journal of Geo-Information Science,2018,20(4):405-413

    • [20] 邓祥征,蒋思坚,刘冰,等.全球二氧化碳浓度非均匀分布条件下碳排放与升温关系的统计分析[J].自然资源学报,2021,36(4):934-947;DENG Xiangzheng,JIANG Sijian,LIU Bing,et al.Statistical analysis of the relationship between carbon emissions and temperature rise with the spatially heterogenous distribution of carbon dioxide concentration[J].Journal of Natural Resources,2021,36(4):934-947

    • [21] Chandra N,Hayashida S,Saeki T,et al.What controls the seasonal cycle of columnar methane observed by GOSAT over different regions in India?[J].Atmospheric Chemistry and Physics,2017,17(20):12633-12643

    • [22] Metya A,Datye A,Chakraborty S,et al.Diurnal and seasonal variability of CO2 and CH4 concentration in a semi-urban environment of western India[J].Scientific Reports,2021,11(1):1-13

    • [23] 宋朝清,刘伟,陆海波,等.基于通量测量的稻田甲烷排放特征及影响因素研究[J].地球科学进展,2019,34(11):1141-1151;SONG Chaoqing,LIU Wei,LU Haibo,et al.Characteristics and drivers of methane fluxes from a rice paddy based on the flux measurement[J].Advances in Earth Science,2019,34(11):1141-1151

    • [24] Christensen T R,Ekberg A,Ström L,et al.Factors controlling large scale variations in methane emissions from wetlands[J].Geophysical Research Letters,2003,30(7):67.DOI:10.1029/2002gl016848

    • [25] Christensen T R,Panikov N,Mastepanov M,et al.Biotic controls on CO2 and CH4 exchange in wetlands:a closed environment study[J].Biogeochemistry,2003,64(3):337-354

    • [26] Sweeney C,Dlugokencky E,Miller C E,et al.No significant increase in long-term CH4 emissions on north slope of Alaska despite significant increase in air temperature[J].Geophysical Research Letters,2016,43(12):6604-6611

    • [27] Turetsky M R,Treat C C,Waldrop M P,et al.Short-term response of methane fluxes and methanogen activity to water table and soil warming manipulations in an Alaskan peatland[J].Journal of Geophysical Research:Atmospheres,2008,113:G00A10

    • [28] Yvon-Durocher G,Allen A P,Bastviken D,et al.Methane fluxes show consistent temperature dependence across microbial to ecosystem scales[J].Nature,2014,507(7493):488-491

    • [29] Bao T,Jia G S,Xu X Y.Wetland heterogeneity determines methane emissions:a pan-Arctic synthesis[J].Environmental Science & Technology,2021,55(14):10152-10163

    • [30] Song W M,Wang H,Wang G S,et al.Methane emissions from an alpine wetland on the Tibetan Plateau:neglected but vital contribution of the nongrowing season[J].Journal of Geophysical Research:Biogeosciences,2015,120(8):1475-1490

    • [31] Wu H B,Wang X X,Ganjurjav H,et al.Effects of increased precipitation combined with nitrogen addition and increased temperature on methane fluxes in alpine meadows of the Tibetan Plateau[J].Science of the Total Environment,2020,705:135818

    • [32] Wei D,Wang Y,Wang Y.Considerable methane uptake by alpine grasslands despite the cold climate:in situ measurements on the central Tibetan Plateau,2008-2013[J].Global Change Biology,2015,21(2):777-788

    • [33] Fang H J,Cheng S L,Yu G R,et al.Low-level nitrogen deposition significantly inhibits methane uptake from an alpine meadow soil on the Qinghai-Tibetan Plateau[J].Geoderma,2014,213:444-452

    • [34] Lin L,Zhu B,Chen C R,et al.Precipitation overrides warming in mediating soil nitrogen pools in an alpine grassland ecosystem on the Tibetan Plateau[J].Scientific Reports,2016,6:31438

    • [35] Chen X P,Wang G X,Huang K W,et al.The effect of nitrogen deposition rather than warming on carbon flux in alpine meadows depends on precipitation variations[J].Ecological Engineering,2017,107:183-191

    • [36] Menon S,Denman K L,Brasseur G,et al.Couplings between changes in the climate system and biogeochemistry[R].Berkeley:Lawrence Berkeley National Lab(LBNL),2007

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