地理学报  2015 , 70 (9): 1477- https://doi.org/10.11821/dlxb201509010

Orginal Article

中国大陆Cs-137背景值研究

张威, 潘少明, 张克新, 曹立国, 赵捷

南京大学地理与海洋科学学院,南京 210023

Study of the Cesium-137 Reference Inventory in the Mainland of China

ZHANG Wei, PAN Shaoming, ZHANG Kexin, CAO Liguo, ZHAO Jie

School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China

收稿日期: 2015-06-12

修回日期:  2015-07-19

网络出版日期:  2015-09-20

版权声明:  2015 《地理学报》编辑部 本文是开放获取期刊文献,在以下情况下可以自由使用:学术研究、学术交流、科研教学等,但不允许用于商业目的.

基金资助:  国家自然科学基金(41271289, 41166002, 41230751)国家基础科学人才培养基金(J1103408) [Foundation: National Natural Science Foundation of China, No.41166002, No.41271289, No.41230751National Science Fund for Fostering Talents in Basic Science, NoJ1103408]

作者简介:

作者简介:张威(1993-), 男, 主要研究方向为地球化学和气候变化。E-mail: tianxinzw@outlook.com

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摘要

土壤侵蚀是关系人类生存与可持续发展的重大环境问题。20世纪60年代以来,Cs-137作为一种人工放射性示踪核素,被广泛应用于土壤侵蚀及堆积研究。而准确估算区域Cs-137背景值(Cs-137 Reference Inventory, CRI)是应用Cs-137开展土壤侵蚀研究的前提条件,其结果直接影响土壤侵蚀速率结果的准确性和可靠性。基于现有文献资料中获取的中国大陆102个CRI实测数据,以及全球降水气候中心提供的降水量再分析资料(空间分辨率2.5°×2.5°、0.5°×0.5°,1981-2010年),在借鉴Walling & He模型(Walling & He Model, WHM)和Michio Aoyama模型(Michio Aoyama Model, MAM)的基础上,本文建立了中国大陆CRI修正模型(Modified CRI Model for the Mainland of China, MCM),并利用Kriging/Cokriging插值方法计算了中国大陆CRI的空间分布。模型评估与对比分析表明,MCM模拟值与实测值大致吻合,且总体高于WHM和MAM模拟值,MCM能对中国大陆CRI进行较高分辨率、较高精度的模拟。模拟结果显示,中国大陆CRI的范围为141~12123 Bq/m2,在东北及新疆局部地区达到最大值,最小值主要集中于25°N以南地带。除新疆局部地区外,中国大陆CRI分布整体呈现自西向东,同纬度地区随降水量增加而增加的特点,而纬向上主要呈现随纬度增加而增加的特点。此外,大尺度大气流场、再悬浮过程、局部核试验等因素增加了中国大陆CRI分布的不均匀性。

关键词: Cs-137 ; 背景值 ; 修正模型 ; 中国大陆

Abstract

Soil erosion is a serious environmental problem closely associated with sustainable development and ultimately the survival of mankind. Cesium-137, a unique artificial radioactive tracer, has been widely applied to the study of soil erosion and deposition since the 1960s. Furthermore, it is a basis for determining a Cesium-137 Reference Inventory (CRI) that employs cesium-137 to measure soil erosion, which can directly influence the accuracy and reliability of the soil erosion rate. This paper references 102 CRI data samples collected from over 80 documents; it also uses the monthly precipitation dataset from the Global Precipitation Climatology Centre from 1981-2010, with spatial resolutions of 2.5°×2.5° and 0.5°×0.5°. The Modified CRI Model for the Mainland of China (MCM) that the paper established is based on incorporating and modifying two previous models, the Walling & He Model (WHM) and the Michio Aoyama Model (MAM). Then we calculate the geographical distributions of CRI by using Kriging/Cokriging interpolation. The model assessment and comparative analysis demonstrate that MCM simulated values are generally in agreement with the observed values and greater than WHM and MAM simulated values. MCM can be applied to higher resolution and higher precision CRI modeling in the Mainland of China. The results show that the range of CRI in the Mainland of China is between 141 and 12123 Bq/m2, and the maximum values are found in parts of northeast China and Xinjiang regions. The minimum values generally come from the regions south of 25°N. Except for some parts of Xinjiang, distributions of CRI in the Mainland of China indicate that CRI increases with precipitation from west to east of the same latitude, while zonal distributions of CRI indicate that CRI increases with the increase of the latitude. Besides, other factors such as large-scale atmospheric flow field, re-suspension, and local nuclear testing contribute to the heterogeneity of CRI in the Mainland of China.

Keywords: cesium-137 ; reference inventory ; modified model ; Mainland of China

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张威, 潘少明, 张克新, 曹立国, 赵捷. 中国大陆Cs-137背景值研究[J]. , 2015, 70(9): 1477- https://doi.org/10.11821/dlxb201509010

ZHANG Wei, PAN Shaoming, ZHANG Kexin, CAO Liguo, ZHAO Jie. Study of the Cesium-137 Reference Inventory in the Mainland of China[J]. 地理学报, 2015, 70(9): 1477- https://doi.org/10.11821/dlxb201509010

1 引言

全球土壤侵蚀及其引起的土地退化、土壤酸化、土壤污染等环境问题逐渐引起关注,成为当前各国学者竞相研究的热点[1-5]。2014年国际原子能机构报告(IAEA TECDOC SERIES 2014 Report)指出,土地退化正影响着全球1.9亿hm2的农业用地,并以每年500~700万hm2的速度迅速增加[6]。全球土壤退化评估调查(Global Assessment of Soil Degradation Survey)显示,土壤侵蚀是当前最为普遍的土地退化形式,占据84%的土地退化区域,造成全球每年近400亿美元的社会经济损失[7-9]。随着气候变暖以及人类活动影响的加剧,土壤侵蚀问题日益严重[10],如何进行更加高效的土壤评估、如何获得更加可靠的土壤空间数据、如何更加合理地计算土壤侵蚀速率成为摆在各国学者面前的重要科学问题。

Cs-137是典型的人工放射性核素,半衰期为30.2年,环境中的Cs-137主要来源于20世纪50-70年代的大气核试验。1963年,Yamagata等在Nature上发表了第一篇应用Cs-137示踪技术进行土壤侵蚀研究的文章[11]。随后,Cs-137示踪技术以其能够简便、高效、准确地获取土壤流失、沉积以及空间再分布信息的特点,被广泛应用于土壤侵蚀与泥沙沉积研究。应用Cs-137技术开展土壤侵蚀研究的前提条件是科学、准确地确定研究区域Cs-137背景值(Cs-137 Reference Inventory, CRI)。CRI可定义为在一定区域内,单位面积Cs-137大气沉降通量或未受扰动土壤Cs-137面积浓度值。CRI的测定和研究作为环境科学的一项基础工作,不仅可为土壤侵蚀研究提供基础信息,也可为区域性物质输运定量研究提供科学依据。

目前,确定CRI的方法主要有三种,一是利用Cs-137大气沉降记录进行计算,二是基于CRI全球空间分布估算模型进行模拟,三是通过现场踏勘采样及实验室测量得到。中国大陆地区缺少Cs-137大气沉降记录,并且,由于社会经济的快速发展和人类活动的加剧,理想的背景值采样区的寻找与确定愈加困难。因此,模型法或可成为中国大陆CRI研究的突破口。

1998年,Garcia利用联合国原子辐射效应科学委员会提供的Sr-90全球分布,计算了每10°纬度圈的Cs-137全球沉降[12]。在此基础上,Walling等认为降水量对Cs-137大气沉降有重要影响[13-14],并按照10°×45°分区网格建立了全球尺度Cs-137背景值分布模型[15]。随后,齐永青等[16]尝试将该模型引入中国,虽然模拟结果普遍低于实测值,但同样具有十分重要的借鉴意义。Aoyama等[17]基于前人研究,建立了Cs-137、Sr-90等放射性核素沉降数据库,并按照10°×10°分区网格绘制了全球CRI分布图。总体而言,已有的CRI模型法研究大多立足于全球尺度的模拟,模拟的空间尺度较大的同时,也意味着其模拟精度较低,在区域性CRI研究中的应用受到限制。20多年来,中国学者一直致力于Cs-137示踪技术在土壤侵蚀与环境评价中的应用,研究区域已涉及黄土高原、四川盆地、东北黑土区、华南丘陵区、青藏高原和新疆地区等,基本能够覆盖全国,这为中国大陆CRI模拟带来了可能。

本文以中国大陆地区为研究对象,通过评估现有的CRI研究资料并开展模型优化与对比研究,计算了中国大陆CRI的分布情况及分布特征,从而为区域性CRI研究提供新方法,也可为进一步定量研究中国大陆地区土壤侵蚀和堆积,以及区域物质输移和沉积物示踪提供借鉴与参考。

2 数据与方法

2.1 数据准备

2.1.1 CRI实测数据库

本文通过收集文献资料建立中国大陆CRI实测数据库,从而为中国大陆CRI模拟提供数据基础。自20世纪80年代以来,中国大陆地区CRI相关研究文献总计约300余篇,文献资料皆来自国内外知名学术期刊,通过剔除无实测CRI的研究文献及同一区域的重复性研究文献,在作进一步分析与评估的基础上,筛选出具有“采样设计合理、实验方法科学、数据科学可靠”等特点的CRI研究文献资料,均出自国内长期从事该方面研究的学者、单位,从而建立中国大陆CRI实测数据库。该数据库从80余篇文献或论文[18-100]中获取总计102个CRI实测数据,实测数据皆通过对研究地区未受干扰点的野外采样方法获得,数据结果科学可信。CRI采样点位及实测值可见(图1),CRI实测点位分布虽然并不均匀,且主要集中在黄土高原、四川盆地、云贵高原及内蒙古高原西南部等地,但基本能够覆盖中国大陆地区,满足进一步分析建模的基本条件。

图1   中国大陆CRI采样点位

Fig. 1   Sampling locations of CRI in the Mainland of China

土壤剖面中的Cs-137蓄积总量计算公式如下:

CPI=i= 1nCi×Bi×Di(1)

式中:CPI是采样点土壤剖面的Cs-137总量(Bq/m2),背景值采样点的CPI即为背景值;n为采样层数;i为层序号;Ci为第i采样层中Cs-137的比活度(Bq/kg);Bi为第i采样层的土壤容重(kg/m3);Di为第i采样层的厚度(m)。

Cs-137衰变校正公式,本文统一衰变校正至2015年1月1日:

CPIN=CPIn12N-nT(2)

式中:CPIN是衰变校正至第N年的Cs-137总量(Bq/m2);n是原参考文献中提供的第n年的CPI(Bq/m2);T是Cs-137的半衰期,为30.2年。

2.1.2 降水量数据

本文的降水量数据资料是来自全球降水气候中心(Global Precipitation Climatology Centre, GPCC)提供的1981-2010年月降水量再分析数据,其空间分辨率为2.5°×2.5°和0.5°×0.5°,该数据资料集源自全球气象观测站观测数据的再分析,并已通过质量检测(数据来源:http://www.esrl.noaa.gov/psd/data/gridded/reanalysis/)。

虽然该资料与本文的研究(1945-2015年)在时间尺度上并不相同,但是,该资料同时具有2.5°×2.5°、0.5°×0.5°分辨率降水量数据满足研究要求;并且,Aoyama等[17]在建模过程中也采用了1987-1998年2.5°×2.5°分辨率的降水量数据。因此,认为GPCC数据是目前最适合本研究的降水量数据集。

2.2 中国大陆CRI修正模型

本文借鉴了Walling & He模型(Walling & He Model, WHM)及Michio Aoyama模型(Michio Aoyama Model, MAM),并作修正,从而建立了适用于中国大陆地区的CRI修正模型(Modified CRI Model for the Mainland of China, MCM)。WHM的建模方法是将全球划分为10°×45°网格,网格沉降总量由Garcia[12]提供的全球10°纬度带Cs-137沉降通量计算求得,网格内任意点CRI则利用其与降水量正相关关系求得[15]。WHM的优点是能够基于降水量的空间分布,实现全球任意点的CRI计算;而缺点是网格较大,且每个网格的沉降通量依托于模拟值。MAM基于全球713个采样点位的CRI实测数据,并将全球划分为10°×10°网格,假定相邻网格的CRI与降水量成正比,从而获得全球10°×10°网格的CRI空间分布[17]。与WHM相比,MAM网格分辨率明显提高,网格CRI计算依托于实测数据,相对准确。然而,MAM只能获得10°×10°网格准确的CRI数据,未能考虑网格内降水量分布情况,且网格空间尺度仍然较大,对区域性CRI模拟的精度仍然较低。

通过分析WHM和MAM,确定了MCM建模的三个基本原则:一是采用实测数据进行网格计算与模拟;二是网格内基于降水量分布计算任意点CRI;三是缩小网格空间尺度以适应区域性CRI研究。因此,MCM建模步骤如下:

第一步 建立2.5°×2.5°空间网格。首先将中国地区进行2.5°×2.5°网格化处理,中国大陆占据总计187个网格,将CRI实测数据库中的102个数据项导入,则占据52个网格。每个网格中的实测值个数范围在0~7个,平均每个网格中约有0.545个实测值,标准差系数范围在3.9%~66.8%。

第二步 假设相邻网格CRI与年均降水量正相关。众多研究表明,全球大气中Cs-137的沉降受主要受地球风带与气压带影响,相同纬度圈中Cs-137的大气沉降通量和降水量大致成正比[101-103]。假定经向相邻网格CRI与年均降水量正相关,并利用GPCC提供的1981-2010年2.5°×2.5°分辨率的降水量数据,计算中国大陆187个2.5°网格CRI。

对中国大陆任意第ij列2.5°网格Ri, j,i = 1, 2, 3,…, 17,j = 1, 2, 3,…, 27。CRi, j)记为网格Ri, j处的CRI,PRi, j)记为网格Ri, j处的年均降水量,则有:

CRi,j+1=PRi,j+1PRi,j×CRi,j(3)

第三步 0.5°×0.5°网格化处理。对中国大陆进一步0.5°×0.5°网格化处理,由此每个2.5°网格被分为25个0.5°网格。本文认为2.5°网格内CRI是随降水量分布而均匀分布,0.5°网格的CRI可通过2.5°网格内25个0.5°网格的年均降水量关系求得。基于此,本文利用GPCC提供的1981-2010年0.5°×0.5°分辨率的降水量再分析数据,计算了中国地区0.5°网格CRI。

将每个Ri, j网格的0.5°网格记为为Ri, j rm, n,其中,m, n = 1, 2, 3, 4, 5。设中国大陆任一点X经纬度坐标为(φ, θ),φ范围为13.75~55.75°N,θ范围为71.25~137.25°E。点X所在0.5°网格为Ri, j rm, n,则有:

Cφ,θ=CRi,jrm,n=25×PRi,jrm,nPRi,jrm,n×CRi,j(4)

其中,

i=17-roundφ-φmin2.5j=1+roundθ-θmin2.5m=90-5×i-roundφ-φmin0.5n=6-5×j+roundθ-θmin0.5(5)

第四步 基于Kriging/Cokriging插值的任意点CRI计算。Kriging/Cokriging插值是地理地质作图中常用的一种最优内插法,它首先考虑的是空间属性在空间位置上的变异分布,确定对一个待插点值有影响的距离范围,从而实现线性、无偏和最小估计方差的估计。本文基于0.5°网格CRI计算结果作进一步Kriging/Cokriging插值处理,从而实现中国大陆任意点CRI模拟。

3 结果与讨论

3.1 模型分析与评估

3.1.1 对实测点的模拟与评估

图2   模拟值与实测值对比分析

Fig. 2   Comparative analysis of simulated and observed values

利用MCM、WHM、MAM三个模型对102个CRI实测点位进行模拟,并与实测值作对比分析,以评估模型的模拟效果(图2)。三个模型模拟结果与实测值分布趋势大致相同,且MCM模拟结果与实测值基本吻合,同一位置MCM模拟值或实测值基本高于WHM和MAM模拟值(图3)。对实测值与模拟值作统计分析可知(表1),针对中国大陆102个实测CRI,MCM模拟结果误差在20%以内有81个,占总数的近80%,而WHM和MAM误差在20%以内所占比例皆小于40%。与WHM和MAM模拟结果相比,MCM均方根误差相对较小,仅为其38%左右,表明MCM模拟值与实测值的偏差相对较小。Pearson相关分析可知,MCM模拟值与实测值的相关系数、复相关系数分别为0.906、0.821,在0.01水平(双侧)上显著正相关,且相关性远优于WHM和MAM模拟,而MAM模拟值与实测值的复相关系数仅为0.094。

表1   模拟值与实测值统计分析

Tab. 1   Statistical analysis of simulated and observed values

模型误差20%内所占比例均方根误差Pearson相关性复相关系数R2
MCM79.41%318.310.906**0.821
WHM36.28%823.400.415**0.172
MAM38.24%819.000.306**0.094

注:**. 在0.01 水平(双侧)上显著相关。

新窗口打开

从三个模型对实测点的模拟结果来看,WHM、MAM模拟值对中国大陆地区的CRI模拟整体呈现偏小的特点,其主要原因可能是:WHM基于10°纬度带的1954-1984年全球沉降,并没有考虑1985年后的沉降,1986年的切尔诺贝利核事故也可能对Cs-137局部沉降造成一定的积累。MAM则基于全球713个采样点背景值数据,对1986年后的采样数据减去了切尔诺贝利核事故的影响值,并统一衰变校正至1969年底。1986年后的全球Cs-137沉降虽然相对较少,但两个模型皆由于研究时间、采样年份等因素限制并将其未加入模拟。

图3   模拟值与实测值拟合分析

Fig. 3   Correlation analysis of simulated and observed values

3.1.2 模型不确定性分析

与全球尺度的CRI模型如WHM、MAM相比,MCM能对中国大陆地区进行较高分辨率、较高精度的模拟,然而,模型仍旧存在一定的误差或不足。MCM基于现有的CRI实测数据进行模拟,但对中国大陆地区而言,实测点位数据仍然较少,且点位分布不均匀,主要集中在中部如四川盆地、黄土高原等地,而东部沿海及西北内陆地区则相对较少。本文采用的降水量数据来自再分析资料,经过数据同化处理的降水量可能与实际值存在一定的误差。

模型对采样点数据进行网格化处理,假定网格内CRI随降水量均匀分布,这可能对模拟结果产生一定误差。模型只考虑了降水量因素对CRI的影响,并未将地形及土壤条件、植被覆盖、土地利用类型等因素纳入考虑,可能造成模拟结果的偏大或偏小。此外,差值方法也可能对模型计算结果造成一定影响。

3.2 中国大陆CRI分布特征分析

基于MCM,本文计算了中国大陆CRI的分布,图4a、4b分别展示了中国大陆年均降水量和CRI空间分布情况。本文将中国大陆分为西北地区(I)、华北地区(II)、东北地区(III)、西南地区(IV)、华中地区(V)、华东地区(VI)、华南地区(VII)等七个区,由图可知,中国大陆CRI的范围为141~12123 Bq/m2,CRI最大值位于I区新疆局部地区及III区,最小值区域则集中于VII区、IV区西部及南部地带及I区南部地区。除新疆局部地区外,中国大陆CRI分布整体呈现自西向东,同纬度地区随降水量增加而增加的特点,反映了从大陆性气候到季风性气候的过渡。I区大部分地区属于温带大陆性荒漠气候,年均降水量基本在50~150 mm之间,然而却在局部地区出现CRI最大值,一些研究表明[31, 35-36],这可能与中国地区20世纪六、七十年代在新疆罗布泊地区先后进行了一系列大气核试验有关。同时,该地区靠近乌克兰、哈萨克斯坦境内及俄罗斯北部新地岛附近的核试验点,且位于来自西北和北极地区的气团运动路径上,Cs-137干沉降或可造成区域性CRI的积累[104]

图4   中国大陆降水量分布及基于MCM、WHM、MAM的CRI分布

Fig. 4   Distributions of precipitation and CRI (based on MCM, WHM and MAM simulations) in the Mainland of China

在全球范围内,土壤Cs-137浓度的区域性变化主要是降雨量分布不均的结果[105],而在0°~50°N范围内,Cs-137沉降量呈现随纬度增加而增加的特点[106]图4c、4d分别展示了根据WHM和MAM计算的中国大陆CRI分布情况。WHM模拟结果显示,CRI最小值位于I区,最大值则与MCM、MAM模拟结果一致,都位于III区,体现了东北地区受风带气压带影响降水量较大而导致CRI较高,此外,Liu等研究表明东北地区沙尘暴的频率显著增加[107],沉降于地表的Cs-137再悬浮作用也可能导致东北地区CRI的积累[108],即当Cs-137沉降到土壤被细颗粒物质吸附后,当土壤受风力作用产生沙尘,Cs-137将随风力搬运形成再悬浮,从而携带更多的Cs-137沉降。MAM模拟结果的最小值主要位于VII区,与MCM模拟结果一致,这主要体现了纬度对Cs-137沉降量的影响。

整体而言,MCM模拟结果明显较WHM和MAM模拟结果的分辨率更高,且CRI模拟值也相对较高。宏观尺度上,CRI分布的不均匀性主要可能为气候条件、大尺度大气流场、地形及土壤条件、局部核试验或核泄漏等因素的综合影响[104]。区域尺度上(表2,图4),III区CRI总体高于II区,处于东部沿海地带的VI区总体高于处于内陆地带的V区及IV区,其可能原因是中国东部沿海地区由于海陆性质差异而形成的海陆间大气运动,大气运动可携带更多的Cs-137尘埃。此外,沿海地区易受台风影响[16],强大的台风气旋可富集其经过区域大气中的悬浮尘埃颗粒,因此台风降水可带来更多Cs-137沉降。

表2   中国大陆七大区域CRI变化

Tab. 2   CRI variance of seven regions in the Mainland of China

分区区域名称MCM范围(Bq/m2)WHM范围(Bq/m2)MAM范围(Bq/m2)
I西北地区214~12123275~13211695~5240
II华北地区727~3035629~18211830~5799
III东北地区1665~40961066~22463455~7120
IV西南地区141~5663421~10661314~5601
V华中地区1292~2119697~10961112~3563
VI华东地区875~2382712~12101081~4115
VII华南地区231~1721562~7821152~1881

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4 结论

(1)基于102个CRI实测资料,建立了中国大陆CRI实测数据库,并通过借鉴前人的研究模型建立适用于中国大陆地区的CRI修正模型,从而实现了区域性CRI的模拟。本文基于实测数据及网格化建模进行区域性CRI研究的方法,或可成为今后CRI研究的一种行之有效的手段。

(2)运用MCM、WHM、MAM三个模型对实测点的模拟结果表明,MCM模拟值与实测值基本吻合,WHM和MAM模拟明显小于实测值和MCM模拟值,这可能与WHM和MAM皆未考虑1985年后的Cs-137沉降有关。整体而言,MCM对中国大陆CRI模拟效果相对较好,模拟的分辨率、精度皆有较大提高,且对中国大陆的适用性较好。而模型的误差主要来自于采样点位分布的不均匀性与低密度特征,今后或可通过增加均匀采样点位的方法完善模型结果。此外,空间插值方法以及基于数据同化的降水量再分析数据对模拟的结果也可产生一定影响。

(3)中国大陆CRI分布主要受气候条件、大尺度大气流场、地形及土壤条件、局部核试验或核泄漏等因素的综合影响。基于MCM的中国大陆CRI的范围为141~12123 Bq/m2,除新疆局部地区外,中国大陆CRI分布整体呈现自西向东,同纬度地区随降水量增加而增加的特点。从纬向分布看,CRI主要呈现同等或相似降水量条件下,随纬度增加而增加的特点。此外,局部大气核试验、Cs-137再悬浮过程也可能对中国大陆CRI分布造成一定影响。

(4)通过探讨中国大陆CRI及其分布特征,一方面,可为中国大陆地区进一步开展CRI研究提供参考与借鉴;另一方面,随着中国大陆地区土壤侵蚀、水土流失等环境问题的日益严重,也可为进一步定量研究中国大陆地区土壤侵蚀和堆积,以及区域物质输移和沉积物示踪提供科学基础。

The authors have declared that no competing interests exist.


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