Seasonal and spatial distribution of nonylphenol in Lanzhou Reach of Yellow River

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国际 会议
1 月 8 日-10 日 1 月 8 日-10 日 2 月 13 日-13 日
The 96th Annual Meeting of the Transportation Research Board
The 96th Annual Meeting of the Transportation Research Board 全国道路交通安全
论文宣读“Analysis of Fatigued Driving Lateral Performance
Considering Highway Horizontal Alignment Design-A Field Study
in China” 大会报告“Comparison between
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Tests Data”
上海 英国
邀请报告“Driving mode decision-making method for
automated vehicles with human-vehicle cooperation ”
论文宣读“Experimental
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32. 严新平 33. 严新平
34. 吕能超 35. 2
6 月 21-23 日
TRANSNAV 2017
国际 会议
6 月 21 日-23 日
TRANSNAV 2017
国际 会议
6 月 25 日-30 日
第二十七届国际海洋 与极地工程大会 (ISOPE 2017)
国际 会议
6 月 25 日-30 日 7 月 6 日-9 日 7 月 6 日-9 日

211250315_浙江近岸海域溶解氧的时空分布特征

211250315_浙江近岸海域溶解氧的时空分布特征

2023年 第4期海洋开发与管理13浙江近岸海域溶解氧的时空分布特征刘瑞娟,陈思杨,余骏,刘希真,赵聪蛟,张晓辉(浙江省海洋监测预报中心 杭州 310007)收稿日期:2022-08-24;修订日期:2023-02-10基金项目:自然资源部海洋生态系统动力学重点实验室开放研究基金项目(M E D 202003);浙江省自然资源厅2021年度科技项目(2021-74);浙江省自然资源厅2022年度科技项目(2022-86㊁2022-88).作者简介:刘瑞娟,工程师,博士,研究方向为海洋生态预警监测通信作者:陈思杨,高级工程师,博士,研究方向为海洋生态预警监测摘要:溶解氧是海洋生态系统中重要的生源要素,其含量及分布变化直接或间接影响海洋生命活动㊂文章以2014 2018年浙江近岸海域海水监测数据为基础,系统分析溶解氧及其饱和度的时空变化特征,并对该海域内低氧现象作了初步探讨㊂结果表明,浙江近岸海域溶解氧及其饱和度时空变化特征明显㊂空间跨度分析显示,溶解氧及其饱和度平面分布为不同季节呈现不同的分布特征,垂直分布为表层高于底层,表底层差异在春夏季较大㊁秋冬季较小,主要与表层光合作用和季节性温盐跃层有关㊂时间跨度分析显示,表层溶解氧含量最高出现在冬季,最低出现在夏季,主要是受水温和表层光合作用的影响;夏季表层溶解氧含量最高出现在2018年,最低出现在2015年,这可能主要是受海表温度的影响㊂此外,研究发现近岸海域外侧少量区域出现低氧现象,其潜在风险正在进一步跟踪监测中㊂关键词:浙江近岸海域;溶解氧;时空分布;低氧中图分类号:P 734.2;P 76 文献标志码:A 文章编号:1005-9857(2023)04-0013-08S p a t i a l a n dT e m po r a lD i s t r i b u t i o no fD i s s o l v e d O x y g e n i nZ h e j i a n g Co a s t a lA r e a L I U R u i j u a n ,C H E NS i y a n g ,Y UJ u n ,L I U X i z h e n ,Z H A O C o n g ji a o ,Z H A N G X i a o h u i (M a r i n eM o n i t o r i n g a n dF o r e c a s t i n g C e n t e r o f Z h e j i a n g P r o v i n c e ,H a n gz h o u310007,C h i n a )A b s t r a c t :D i s s o l v e do x y g e n i s a n i m p o r t a n t b i o g e n i c e l e m e n t i nm a r i n e e c o s ys t e m ,a n d t h e v a r i a -t i o no f i t s c o n t e n t a n d d i s t r i b u t i o n c o u l d a f f e c tm a r i n e l i f e a c t i v i t i e s d i r e c t l y o r i n d i r e c t l y .I n t h i s p a p e r ,t h e s p a t i a l a n d t e m p o r a l v a r i a t o n c h a r a c t e r i s t i c sw e r e s y s t e m a t i c a l l y a n a l y z e d a n d t h e o c -c u r r e n c e o f h y p o x i aw a s p r e l i m i n a r i l y d i s c u s s e db a s e do nt h e s e a w a t e r f i e l d m o n i t o r i n g d a t a i n Z h e j i a n g c o a s t a l a r e a f r o m2014t o 2018.T h e r e s u l t s s h o w e d t h a t t h e s p a t i a l a n d t e m p o r a l v a r i a -t i o n c h a r a c t e r i s t i c s o f d i s s o l v e do x y g e na n d i t s s a t u r a t i o nw e r e o b v i o u s i nZ h e j i a n g c o a s t a l a r e a .T h e s p a t i a l s p a n a n a l y s i s s h o w e d t h a t t h e h o r i z o n t a l d i s t r i b u t i o n o f d i s s o l v e d o x y ge n a n d i t s s a t -u r a t i o n p r e s e n t e d d if f e r e n tc h a r a c t e r i s t i c si n d i f f e r e n ts e a s o n s ,a n dt h ev e r t i c a ld i s t r i b u t i o ns h o w e d t h a t d i s s o l v e do x y g e na n d i t s s a t u r a t i o n i n t h e s u r f a c e l a y e rw a s h i gh e r t h a n t h a t i n t h e Copyright ©博看网. All Rights Reserved.14海洋开发与管理2023年b o t t o ml a y e r,a n d t h ed i f f e r e n c eb e t w e e nt h es u r f a c e l a y e r a n dt h eb o t t o ml a y e rw a s l a r g e r i n s p r i n g a n d s u mm e r,b u t s m a l l e r i na u t u m n a n dw i n t e r,w h i c hw a s r e l a t e d t o s u r f a c e p h o t o s y n-t h e s i s a n d s e a s o n a l t h e r m o h a l o c l i n e.T h e t i m e s p a na n a l y s i s s h o w e dt h a t t h eh i g h e s td i s s o l v e d o x y g e n c o n t e n t i ns u r f a c e l a y e r a p p e a r e d i nw i n t e r a n dt h e l o w e s t i ns u mm e r,w h i c h w e r ea f-f e c t e db y w a t e r t e m p e r a t u r ea n ds u r f a c e p h o t o s y n t h e s i s,a n dt h eh i g h e s td i s s o l v e do x y g e ni n s u r f a c e l a y e r i n s u mm e r a p p e a r e d i n2018a n d t h e l o w e s t i n2015,w h i c hw a sm a i n l y c a u s e db y s e a s u r f a c e t e m p e r a t u r e.I na d d i t i o n,h y p o x i aw a s a l s o f o u n d i ns o m ea r e a so u t s i d e t h e c o a s t a l a r e a,a n d i t s p o t e n t i a l r i s k s a r eb e i n g f u r t h e r t r a c k e d a n dm o n i t o r e d.K e y w o r d s:Z h e j i a n g c o a s t a l a r e a,D i s s o l v e do x y g e n,S p a t i a l a n d t e m p o r a l d i s t r i b u t i o n,H y p o x i a0引言溶解氧是海洋生态系统中的重要生源要素参数,是海洋生命活动必不可少的物质[1],对海洋生态系统的稳定具有至关重要的作用㊂海水中溶解氧的变化是各种物理㊁化学和生物共同作用的结果[2],其饱和度的变化可以表征水体生态环境的变化㊂在近岸海域,溶解氧及其饱和度的变化受到多种因素的共同影响,包括入海径流㊁外海洋流㊁浮游生物光合呼吸作用㊁有机质的降解等,但在某个区域的主要控制因素可能略有差异,因此分析特定海域溶解氧及其饱和度的影响因素,对于掌握该区域海洋生态环境的变化与生态系统的稳定性具有重要意义㊂低氧现象是目前全球海洋领域关注的焦点问题,现在被认为是海洋生态灾害现象,其可以导致海洋生物生境消失㊁生物死亡㊁物种组成和群落结构改变㊁生物多样性降低以及生物竞争加剧等[3],严重威胁海洋生态系统安全㊂通常水体中溶解氧含量低于3m g/L时称为低氧,低于2m g/L时称为缺氧,这种现象目前多出现在近岸河口区域㊂国外如墨西哥湾等存在很严重的缺氧现象㊂国内目前研究较多的是长江口和珠江口外侧海域存在季节性底层低氧现象[3-4]㊂其中,长江口附近低氧主要是由长江入海径流形成温盐跃层阻碍上下层水体交换和底层有机质降解耗氧所导致的[5-6]㊂浙江是海洋大省,海域面积辽阔,受长江入海径流影响较大,对于浙江近岸海域溶解氧的调查研究可以追溯到20世纪80年代㊂樊安德[7]对浙江近岸水深浅于20m区域的四季溶解氧分布状况进行报道;王玉衡等[8]研究浙南区域春季溶解氧分布状况,并探讨与其他要素的相互关系;杨庆霄等[9]和胡小猛等[10]在对黄东海溶解氧的时空分布特征研究中涉及部分浙江海域;卢勇等[11]对长江口及邻近海域表层水体溶解氧饱和度的季节变化研究中涉及浙北部分海域;柴小平等[12]分析浙江近岸海域春季溶解氧饱和度分布状况及影响因素㊂而针对浙江近岸全部管辖海域多年多季节的海水溶解氧及其饱和度的变化研究还未见报道㊂已有研究表明,浙江近岸海域底层也存在低氧区[13,5],并存在明显的季节变化,春末夏初形成,8月最为严重,秋季减弱,冬季消失[14-15],但对于低氧的多年连续监测报道还较缺乏㊂本研究基于2014 2018年多年多季节的浙江近岸海域溶解氧和相关参数的监测数据,分析浙江近岸海域溶解氧的时空分布特征及其影响因素,并结合资料分析研究区域低氧的年际发生情况及可能原因,对于深入了解浙江近岸海域溶解氧的变化及其对生态系统的影响具有重要意义,同时为预警海洋生态系统的变化提供数据资料支撑㊂1材料与方法1.1研究区域研究区域为浙江近岸海域,北界从浙沪交界的金丝娘桥起向海延伸至领海外部界线,南界从浙闽交界的虎头鼻经七星岛(星仔岛)南端至27ʎN往东延伸至领海外部界线,面积约4.4万k m2[16]㊂分析数据来源于浙江近岸海域海洋生态环境监测任务, 2014 2018年分别有299个㊁312个㊁315个㊁344个和344个水质监测站位㊂选用2018年3月(冬季)㊁5月(春季)㊁8月(夏季)和10月(秋季)的表底层监测数据进行季节变化和空间变化的分析,选用Copyright©博看网. All Rights Reserved.第4期刘瑞娟,等:浙江近岸海域溶解氧的时空分布特征152014 2018年8月(夏季)表层监测数据进行年际变化的分析,选用2014 2018年8月(夏季)底层监测数据初步探讨低氧现象出现的情况㊂研究区域主要受到浙闽沿岸流和台湾暖流的影响㊂浙闽沿岸流主要分布在长江口以南的浙闽沿岸区域,由长江和钱塘江的入海径流与海水混合而成,具有低温㊁低盐㊁高营养盐的特征㊂春秋冬季,浙闽沿岸流受东北季风的影响向西南方向流动,影响研究海域,其中冬季影响程度和范围最广,可至50m等深线的近海一侧,表层最多可达60m 等深线;夏季浙闽沿岸流受东南季风的影响而转为东北流向,只影响浙北海域[17-18]㊂台湾暖流是黑潮的分支,来源于北赤道暖流,自西南流向东北,冬季影响范围有限,位于50m等深线的外海一侧,在底层最多可达30m等深线;夏季较强劲,进一步向陆延伸,对浙江近岸海域的影响较大[17-19]㊂1.2研究方法1.2.1实验方法海水样品的采集和分析均严格按照海洋监测规范[20]和海洋调查规范[21]的相关要求进行㊂现场使用采水器采集水样,溶解氧水样采集后立即加入氯化锰和碱性碘化钾进行现场固定,待样品瓶内沉淀完全后加酸溶解,再用硫代硫酸钠滴定,根据滴定用量换算溶解氧的含量㊂温度㊁盐度和p H值根据现场携带的温度计㊁盐度计和p H计测定获取㊂活性磷酸盐㊁活性硅酸盐㊁硝酸盐㊁亚硝酸盐和氨盐等营养盐的水样通过0.45μm醋酸纤维滤膜过滤后带回实验室,通过分光光度法测定㊂所有样品的分析测定过程均通过质量控制,符合质量控制要求㊂1.2.2计算方法溶解氧饱和度的计算参考海洋调查规范[21],其计算公式为:r(O)=ρ(O)ρ(O')ˑ100%式中:ρ(O)为测得水样的氧浓度;ρ(O')为在现场水温㊁盐度下,氧在海水中的饱和浓度㊂氧在不同水温㊁盐度海水中的饱和浓度为:l n c(O')=A1+A2(100/T)+A3l n(T/100)+A4(T/100)+S[B1+B2(T/100)+B3(T/100)2]+0.4912式中:c(O')为在现场水温㊁盐度下,氧在海水中的饱和浓度;T为现场的海水热力学温度;S为现场的海水盐度;A㊁B为常数,其量值分别为A1=-173.4292㊁A2=249.6339㊁A3=143.3483㊁A4=-21.8492,B1=-0.033096㊁B2=0.014259㊁B3=-0.001700㊂其中,单位换算为:ρ(O')=c(O')ˑ16/1000 1.2.3数据统计分析本研究利用E x c e l进行数据统计分析,利用A r c G I S进行反距离插值拟合绘制平面分布图,利用R语言进行多要素相关性分析绘图,利用O r i g i n绘制相关图件㊂2结果与讨论2.1空间分布2.1.1水平分布根据浙江近岸海域表层海水溶解氧含量及饱和度的四季平面分布,各季节呈现不同的分布特征㊂冬季,溶解氧含量在浙北和浙南海域存在明显的分界,浙南海域略高,基本在9m g/L以上,浙北海域略低,基本在8~9m g/L范围内,小部分外侧海域处于7~8m g/L区间内㊂饱和度分布与溶解氧类似,也存在明显的区域差异,浙南海域基本处于100%~110%的饱和状态,而浙北海域均处于未饱和状态,大部分处于80%~90%范围内,杭州湾部分海域甚至低于80%㊂冬季生物活动较弱,溶解氧含量及饱和度主要受到温度㊁盐度等物理过程的控制,此时由东北流向西南的浙闽沿岸流影响最为显著,其携带的低温低盐海水控制浙江近岸海域,使浙北海域水温低于浙南海域㊂另外,杭州湾及附近海域是强潮汐河口区域,强烈的混合作用使溶解氧难以达到平衡状态[22],从而浙南海域溶解氧含量和饱和度高于浙北海域㊂春季,杭州湾和舟山以外海域以及温台外侧海域溶解氧含量较高,基本在8m g/L以上;浙江中部部分近岸海域溶解氧含量较低,整体呈现外侧海域高于近岸的趋势㊂饱和度分布与溶解氧含量类似,总体上外侧海域高于近岸,大多处于90%~110%范围内,整体呈现近饱和状态,部分外侧海域饱和度高于110%㊂总体上,外侧海域溶解氧含量和饱Copyright©博看网. All Rights Reserved.16海洋开发与管理2023年和度高于近岸,这可能与外侧海域浮游植物先开始生长繁殖进行光合作用产生氧气有关㊂进入春季,浙闽沿岸流逐步退缩,台湾暖流逐渐增强并向北向岸扩展,外侧海域受其影响水温和透明度均较高,海水环境逐渐适宜藻类的生长繁殖,光合作用逐渐增强,产生氧气提高溶解氧含量和饱和度㊂夏季,水温最高,受水温影响的溶解氧含量下降,大多海域处于7~8m g/L范围内,只有小部分海域处于8m g/L以上,沿岸海湾河口区域如象山港㊁三门湾和乐清湾处于6~7m g/L的区间内㊂除浙北个别站位外,全省大部分海域处于过饱和状态,其中浙南海域饱和度基本高于110%,部分海域甚至高于130%,明显高于浙北海域㊂夏季溶解氧含量降低,是因为此时季节升温和强劲台湾暖流的影响使水温升高;而饱和度明显升高,是因为夏季浮游植物光合作用最强,持续不断产生氧气㊂浙南海域水温和透明度高于浙北海域,浮游植物生长更为旺盛,因而浙南海域饱和度普遍高于浙北海域㊂秋季,溶解氧含量整体呈现为7~8m g/L的状态,杭州湾区域整体偏高,处于8~9m g/L的范围内㊂此外,部分象山港和三门湾等沿岸海湾河口区域的溶解氧含量也较高,只有舟山外侧个别站位处于6~7m g/L的范围内,研究海域表层溶解氧分布较均匀㊂绝大部分海域溶解氧饱和度处于100%~ 110%范围内,总体呈现饱和状态,只有小部分海域处于90%~100%的未饱和状态㊂总体上,溶解氧含量和饱和度分布相对均匀,可能与秋季影响溶解氧含量分布的因素较单纯有关㊂此时生物活动减弱,对溶解氧含量影响不显著,同时台湾暖流逐步减弱,浙闽沿岸流开始增强,整个海域温差减小,使溶解氧含量分布较均匀㊂2.1.2垂直分布浙江近岸海域海水溶解氧和饱和度的垂直分布特征如图1所示㊂不论季节变化,溶解氧平均含量和平均饱和度均是表层高于底层㊂冬㊁春㊁夏㊁秋季表底层平均溶解氧含量差值分别为0.30m g/L㊁0.83m g/L㊁1.06m g/L㊁0.35m g/L,平均饱和度的差值分别为4%㊁12%㊁19%㊁1%,可见春夏季表底层溶解氧含量和饱和度差异较大,秋冬季差异相对较小㊂春季至夏季表层海水中浮游植物光合作用强烈并产生大量氧气,同时上层海水温度较高,形成温盐跃层,限制水体的垂直交换,影响表层溶解氧向底层传输;此外,上层产生的有机质不断沉降至底层进行降解耗氧,使得表底层溶解氧和饱和度差值变大㊂秋冬季水体层化减弱,垂直混合作用增强,表层溶解氧可以被携带至底层,使表底层溶解氧和饱和度趋于均衡㊂图1浙江近岸海域表底层溶解氧平均含量和平均饱和度F i g.1 A v e r a g e o f d i s s o l v e do x y g e n c o n t e n t a n d s a t u r a t i o n i n s u r f a c e a n db o t t o m w a t e r s o f Z h e j i a n g c o a s t a l a r e a2.2时间分布2.2.1季节变化浙江近岸海域表层溶解氧含量㊁饱和度㊁温度和盐度的季节变化如图2所示㊂图2浙江近岸海域表层溶解氧含量㊁饱和度㊁温度和盐度的季节变化F i g.2 S e a s o n a l v a r i a t i o n s o f s u r f a c e d i s s o l v e do x y g e n, s a t u r a t i o n,t e m p e r a t u r e a n d s a l i n i t y i nZ h e j i a n g c o a s t a l a r e a表层溶解氧含量在冬季最高,春秋季次之,夏季最低,与温度㊁盐度呈现相反的变化规律,饱和度Copyright©博看网. All Rights Reserved.第4期刘瑞娟,等:浙江近岸海域溶解氧的时空分布特征17却与之相反㊂冬季,生物活动较弱,溶解氧主要受温度㊁盐度等物理因素的控制,此时受低温低盐的浙闽沿岸流影响,近岸海域温度和盐度均较低,氧气在海水中的溶解度较大,同时由于风力较大,海气交换作用强烈,大气中的氧气可以更多地被寒冷的海水所吸收,溶解氧含量达到全年最高值,表层平均值为8.82m g /L ,同时由于温盐较低,理论饱和溶解氧含量较高,饱和度较低,平均约为97%,处于未饱和状态;春季,受温度和生物活动的共同影响,虽然浮游植物开始繁殖进行光合作用产生氧气,但海水温度逐渐上升,氧气溶解度降低,因此相较于冬季,溶解氧含量有所降低,表层平均值为7.95m g /L ,但饱和度明显升高,表层平均约为103%,整体处于饱和状态;夏季,海水温度明显升高,浮游植物光合作用达一年中最强,产生大量氧气,但过高的海水温度使氧气溶解度进一步降低,导致过多的氧气自海水中逸出,表层溶解氧含量进一步降低,平均约为7.41m g /L ,但处于过饱和状态,平均约为113%;秋季,海水温度逐渐降低,氧气溶解度增大,溶解氧含量进一步升高,表层平均值为7.62m g /L ,浮游植物产氧减少,饱和度逐步降低,平均约为101%,处于饱和状态㊂2.2.2 年际变化夏季是浙江近岸海域表层海水溶解氧含量最低但饱和度最高的季节,2014 2018年浙江近岸海域夏季表层溶解氧含量及其饱和度的变化如图3所示㊂图3 浙江近岸海域夏季表层溶解氧含量及饱和度的年际变化F i g .3 I n t e r a n n u a l v a r i a t i o n s o f s u r f a c e d i s s o l v e do x y ge n a n d s a t u r a t i o n i nZ h e j i a n g co a s t a l a r e a i n s u mm e r 表层溶解氧含量的变化范围为6.42~7.41m g /L ,饱和度的变化范围为95%~113%,二者的年际变化趋势一致㊂2015年溶解氧含量最低,饱和度最低(95%),处于未饱和状态;2018年溶解氧含量最高,饱和度最高(113%),处于过饱和状态㊂为探讨影响表层溶解氧含量和饱和度年际变化的主要因素,将5年浙江近岸海域夏季表层溶解氧含量㊁饱和度与温度㊁盐度和各类营养盐进行相关性分析,结果如图4所示(D O :溶解氧;D O%:溶解氧饱和度;T :温度;S :盐度;P O 3-4:磷酸盐;S i O 2-3:硅酸盐;N O -2:亚硝酸盐;N O -3:硝酸盐;N H +4:氨氮;I N :无机氮)㊂图4 浙江近岸海域夏季表层溶解氧含量㊁饱和度㊁温度㊁盐度及各类营养盐的相关性F i g .4 C o r r e l a t i o n s o f s u r f a c e d i s s o l v e do x y ge n ,s a t u r a t i o n ,t e m p e r a t u r e ,s a l i n i t y an dn u t r i e n t s i n Z h e j i a n g co a s t a l a r e a i n s u mm e r 溶解氧含量和饱和度呈显著正相关,且二者与温度呈正相关,与硝酸盐和无机氮呈显著负相关㊂同时,温度与硝酸盐也呈显著负相关,说明表层溶解氧含量及饱和度的年际变化主要与温度和硝酸盐等无机氮有关,温度高时溶解氧含量和饱和度均高,此时硝酸盐等无机氮含量却低㊂2015年和2018年夏季表层海水温度平均分别约为28.1ħ和29.7ħ,硝酸盐含量平均约为0.643m g /L 和0.566m g/L ㊂2018年较2015年海水温度高,刺激Copyright ©博看网. All Rights Reserved.18海洋开发与管理2023年浮游植物的光合作用,产生更多的氧气,使溶解氧含量及饱和度升高,同时浮游植物强烈的光合作用消耗更多的硝酸盐等无机氮,使无机氮含量降低㊂因此,表层海温是影响5年来表层溶解氧含量及饱和度年际变化的主要因素㊂2.3低氧现象夏季和底层是溶解氧含量最低的季节和层次㊂根据2014 2018年夏季底层溶解氧含量分布,浙江近岸海域底层溶解氧含量的低值区出现在舟山外侧海域,浙南外侧海域偶有分布㊂仔细观察夏季底层溶解氧含量数据,发现2014年舟山外侧海域有4个站位处于2~3m g/L范围内,2018年浙南外侧海域有2个站位处于2~3m g/L范围内,出现低氧现象,其他年份和站位均大于3m g/L,未表现出低氧乃至缺氧现象㊂可见,浙江近岸外侧海域底层目前出现低氧现象的站位不多,但仍存在出现低氧现象的潜在风险㊂近岸海域底层低氧是多种物理与生物地球化学过程共同作用的结果㊂据以往研究[23],浙江近海低氧较长江口外海域出现时间更早㊁持续时间更长㊂春季底层有机质氧化分解耗氧,而后旺发的浮游植物碎屑分解进一步加剧低氧;夏季水体出现层化,阻碍氧气垂直交换,低氧程度最为严重;至秋季逐渐消失㊂同时,外海低氧水体即台湾暖流底层水在浙江近海的上升提供较低的背景值也是重要因素之一㊂在全球气候变暖的背景下,随着大气和海水温度的升高,径流量的改变㊁热带风暴等极端气候事件㊁生物代谢作用的改变等是否会进一步加剧低氧现象仍不得而知[24],因此浙江近岸海域底层低氧现象值得进一步关注和研究,目前浙江也正在进一步的跟踪监测㊂3结论本研究基于2014 2018年浙江近岸海域海水溶解氧及相关理化因子的监测数据,研究浙江近岸海域溶解氧含量及饱和度的时空分布及影响因素,并结合资料分析低氧现象,得出3项主要结论㊂(1)表层溶解氧含量和饱和度在不同季节呈现不同的平面分布特征㊂四季溶解氧含量和饱和度均是表层高于底层,表底层的差异在春夏季表现较大,秋冬季较小,主要是受季节性温盐跃层和表层光合作用产氧的影响㊂(2)表层溶解氧含量和饱和度存在明显的季节变化,冬季表层溶解氧含量最高,夏季表层饱和度最高,这主要是受水温和浮游植物光合作用的影响㊂表层溶解氧含量和饱和度也表现出年际差异,温度是影响这种年际变化的主要因素㊂(3)2014年和2018年夏季外侧小部分海域底层出现低氧现象,主要是受底层有机物降解耗氧㊁水体层化阻碍氧垂直交换和低氧台湾暖流提供较低背景值影响,未来研究海域低氧现象的潜在风险值得进一步关注㊂参考文献(R e f e r e n c e s):[1]李潇,王晓莉,刘书明,等.天津近岸海域溶解氧含量分布特征及影响因素研究[J].海洋开发与管理,2017,34(8):75-78.L IX i a o,WA N G X i a o l i,L I U S h u m i n g,e t a l.C h a r a c t e r i s t i c so fd i s s o l ve do x y g e na n di t saf f e c t i ng f a c t o r s i n T i a n j i no f f sh o r es e a w a t e r[J].O c e a n D e v e l o p m e n ta n d M a n a g e m e n t,2017,34(8):75-78.[2]石晓勇,陆茸,张传松,等.长江口邻近海域溶解氧分布特征及主要影响因素[J].中国海洋大学学报,2006,36(2):287-290.S H I X i a o y o n g,L U R o n g,Z H A N G C h u a n s o n g,e t a l.D i s t r i b u t i o na n dm a i n i n f l u e n c e f a c t o r s p r o c e s s o f d i s s o l v e d o x-y g e n i n t h e a d j a c e n t a r e a o f C h a n g j i a n g e s t u a r y i nA u t u m n[J].P e r i o d i c a l o f O c e a n U n i v e r s i t y o f C h i n a,2006,36(2): 287-290.[3]叶丰,黄小平.近岸海域缺氧现状㊁成因及其生态效应[J].海洋湖沼通报,2010(3):91-99.Y EF e n g,HU A N G X i a o p i n g.T h e s t a t u s,c a u s e s a n de c o l o g i c a le f f e c t s o f c o a s t a l h y p o x i a[J].T r a n s a c t i o n so fO c e a n o l o g y a n dL i m n o l o g y,2010(3):91-99.[4]林洪瑛,刘胜,韩舞鹰.珠江口底层海水季节性缺氧现象及其引发C T B的潜在威胁[J].湛江海洋大学学报,2001,21(S1): 25-29.L I N H o n g y i n g,L I U S h e n g,HA N W u y i n g.P o t e n t i a lt r i g g e rC T B,f r o ms e a s o n a lb o t t o m w a t e rh y p o x i a i nt h eP e a r lR i v e rE s t u a r y[J].J o u r n a lo fZ h a n j i a n g O c e a n U n i v e r s i t y,2001,21(S1):25-29.[5]李宏亮,陈建芳,卢勇,等.长江口水体溶解氧的季节变化及底层低氧成因分析[J].海洋学研究,2011,29(3):78-87.L IH o n g l i a n g,C H E NJ i a n f a n g,L U Y o n g,e t a l.S e a s o n a l v a r i a-t i o no fD Oa n d f o r m a t i o nm e c h a n i s mo f b o t t o m w a t e r h y p o x i a o fC h a n g j i a n g R i v e rE s t u a r y[J].J o u r n a lo f M a r i n eS c i e n c e s,Copyright©博看网. 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a l .C u r r e n t c o n d i t i o n s i n s u mm e r i n t h eZ h e j i a n g o f f s h o r e [J ].J o u r n a l o fM a r i n e S c i -e n c e s ,2014,32(3):16-25.[18] 王翠,郭晓峰,方婧,等.闽浙沿岸流扩展范围的季节特征及其对典型海湾的影响[J ].应用海洋学学报,2018,37(1):1-8.WA N GC u i ,G U O X i a o f e n g ,F A N GJ i n g ,e t a l .C h a r a c t e r i s t i c s o f s e a s o n a l s p a t i a le x p a n s i o no fF u j i a na n dZ h e j i a n g co a s t a l c u r r e n t a n d t h e i r b a y e f f e c t s [J ].J o u r n a l o fA p p l i e dO c e a n o g-r a p h y,2018,37(1):1-8.[19] 曾定勇,倪晓波,黄大吉.冬季浙闽沿岸流与台湾暖流在浙南海域的时空变化[J ].中国科学:地球科学,2012,42(7):1123-1134.Z E N G D i n g y o n g ,N I X i a o b o ,HU A N G D a j i .T e m po r a la n d s p a t i a lv a r i a b i l i t y o ft h eZ h e -M i n C o a s t a lC u r r e n ta n dt h e T a i w a n W a r m C u r r e n ti n w i n t e ri nt h es o u t h e r n Z h e j i a n gc o a s t a l s e a [J ].S c i e n t i a S i n i c a T e r r a e ,2012,42(7):1123-1134.[20] 国家质量监督检验检疫总局,国家标准化管理委员会.海洋监测规范:海水分析:G B17378.4-2007[S ].北京:中国标准出版社,2007.G e n e r a l A d m i n i s t r a t i o n o fQ u a l i t y S u p e r v i s i o n ,I n s p e c t i o n a n d Q u a r a n t i n e o f t h eP e o p l e 'sR e p u b l i c o f C h i n a ,S t a n d a r d i z a t i o n A d m i n i s t r a t i o no fC h i n a .S p e c i f i c a t i o n f o rm a r i n em o n i t o r i n g:s e a w a t e r a n a l y s i s :G B17378.4-2007[S ].B e i j i n g:S t a n d a r d s P r e s s o fC h i n a ,2007.[21] 国家质量监督检验检疫总局,国家标准化管理委员会.海洋调查规范:海水化学要素调查:G B /T12763.4-2007[S ].北京:中国标准出版社,2007.G e n e r a l A d m i n i s t r a t i o n o fQ u a l i t y S u p e r v i s i o n ,I n s pe c t i o n a n d Copyright ©博看网. 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All Rights Reserved.。

23552333_探究干海参复水后干重率与蛋白质含量、盐分的相关性

23552333_探究干海参复水后干重率与蛋白质含量、盐分的相关性

Nov. 2020 CHINA FOOD SAFETY99分析与检测复水后干重率指将复水后的海参,除去其体内人工掺加的、可溶于水的盐以及胶类物质等成分后,再将参体烘干后得到的干物质重量占总重量的百分率[1]。

该指标可以有效反映海参中是否存在非法添加糖、胶类物质、盐分等,以达到为海参增重的目的的恶劣行径[2]。

1 实验材料及方法1.1 实验材料干海参样品购于辽宁省、山东省等地。

1.2 试验方法取3只干海参,高速粉碎(25 000 r /min)至试样全部通过830 μm (20目)筛,处理后密封、备用。

检验方法见表1。

2 结果和分析检测结果通过SPSS22.0进行统计分析,以平均值±标准偏差表示,显著性界值分为极显著(P <0.01)、显著(P <0.05)、不显著(P >0.05)三类。

取12组干海参样品,按照方法测定后,结果如表2。

以蛋白质含量、盐探究干海参复水后干重率与蛋白质含量、盐分 的相关性□ 王鹤亭 苗 蕾 大连产品质量检验检测研究院有限公司摘 要:探究干海参多项指标之间的关系有利于全面评价干海参的质量。

通过相关性分析得出复水后干重率与蛋白质含量呈正相关性,与盐分含量呈负相关。

实验证明,通过检测复水后干重率可以有效防止生产者加入糖类、盐类及其他物质给海参增重,是控制干海参产品掺假的重要指标。

关键词:干海参;复水后干重率;蛋白质;盐分表1 海参检验方法明细检验项目 检测方法复水后干重率GB 31602-2015《食品安全国家标准 干海参》蛋白质GB 5009.5-2016《食品安全国家标准 食品中蛋白质的测定》盐分GB 5009.44-2016《食品安全国家标准 食品中氯化物的测定》表2 干海参复水后干重率、蛋白质、盐分结果编号复水后干重率/%蛋白质/%盐分/%编号复水后干重率/%蛋白质/%盐分/%154.651.319.7775.960.93.78274.369.80.42878.767.1 4.33348.342.227.6949.038.525.9467.354.116.41083.265.40.74548.446.826.71131.225.652.2分含量为X 1、X 2,复水后干重率为Y ,分析复水后干重率与蛋白质、盐分的相 关性。

若尔盖高原湿地不同微地貌区甲烷排放通量特征

若尔盖高原湿地不同微地貌区甲烷排放通量特征

植物生态学报 2016, 40 (9): 902–911 doi: 10.17521/cjpe.2016.0029 Chinese Journal of Plant Ecology 若尔盖高原湿地不同微地貌区甲烷排放通量特征周文昌1,2崔丽娟1*王义飞1李伟1康晓明11中国林业科学研究院湿地研究所湿地生态功能与恢复北京市重点实验室, 北京 100091; 2湖北省林业科学研究院, 武汉 430075摘要若尔盖高原是我国泥炭沼泽湿地的主要分布区、青藏高原的主要甲烷(CH4)排放中心。

为了研究湿地微地貌环境对高原湿地CH4排放通量的影响, 2014年5–10月, 采用静态箱和快速温室气体分析仪原位测量若尔盖高原湖滨湿地3种泥炭沼泽5种微地貌环境下的CH4排放通量特征。

结果表明: (1)常年性淹水泥炭湿地洼地(P-hollow)和草丘(P-hummock)生长季平均CH4排放通量为68.48和40.32 mg·m–2·h–1, 季节性淹水的泥炭湿地洼地(S-hollow)和草丘(S-hummock)平均CH4排放通量为2.38和0.63 mg·m–2·h–1, 而无淹水平坦地(Lawn)平均CH4排放通量为3.68 mg·m–2·h–1; (2)湿地5种微地貌区CH4排放通量为(23.10 ± 30.28) mg·m–2·h–1 (平均值±标准偏差)), 变异系数为131%。

分析显示这5种微地貌区CH4排放通量的平均值与其水位深度平均值存在显著的线性正相关关系(R2 = 0.919, p < 0.01), 表明水位深度是控制湿地微地貌区CH4排放通量空间变化的主要因子;(3) P-hummock、P-hollow和S-hummock的CH4排放通量存在显著的季节变化, Lawn和S-hollow无明显的季节性变化, 但5种微地貌区在夏季或秋季均观测到CH4排放通量峰值, 其影响因子可能与水位深度、土壤温度和凋落物输入密切相关; (4) P-hollow可能时常发生冒泡式CH4排放, 这可能导致过去低估了若尔盖高原湿地的CH4排放量。

全球变暖下南大洋吸热的季节变化特征

全球变暖下南大洋吸热的季节变化特征

第54卷 第3期 2024年3月中国海洋大学学报P E R I O D I C A L O F O C E A N U N I V E R S I T Y O F C H I N A54(3):009~019M a r .,2024全球变暖下南大洋吸热的季节变化特征❋罗 菁1,2,郑小童1,2❋❋(1.中国海洋大学物理海洋教育部重点实验室,海洋与大气学院,山东青岛266100;2.青岛海洋科学与技术试点国家实验室,山东青岛266237)摘 要: 本文基于第六次耦合模式比较计划的未来高排放情景试验模拟结果,研究全球变暖背景下未来南大洋吸热的季节变化㊂发现在未来变暖气候下南大洋占全球海洋累积吸热的近一半㊂未来南大洋海洋吸热有明显季节变化:南半球春㊁秋季吸热峰值大致位于63ʎS ,夏季70ʎS 附近吸热最小,冬季58ʎS 附近吸热全年最大㊂秋㊁冬季海洋吸热的空间结构由湍流热通量主导;春㊁夏季高纬度海洋吸热主要受辐射通量影响㊂进一步研究发现,南大洋60ʎS 以南海区净热通量变化趋势与海冰变化有关㊂春㊁夏季海冰消融通过海冰-反照率反馈机制产生较大的海洋吸热,而秋㊁冬季海冰消融加强了海洋向大气放热,造成海洋吸热减少,年平均下二者显著抵消㊂在南大洋30ʎS 60ʎS 海区,海洋吸热主要受湍流热通量变化影响,夏㊁秋季吸热较少,冬㊁春季吸热较大,这与气候态混合层深度的季节变化有显著关系㊂此外,本文研究还发现,南大洋上层海洋热量的经向输送对全球变暖的响应也存在显著的季节变化,冬㊁春季经向热输送的增强范围相较于夏㊁秋季向赤道和向下延伸,与气候态混合层深度和西风增强的季节变化有关㊂关键词: 南大洋;海洋吸热;海气相互作用;全球变暖;季节变化中图法分类号: P 728.1 文献标志码: A 文章编号: 1672-5174(2024)03-009-11D O I : 10.16441/j.c n k i .h d x b .20220388引用格式: 罗菁,郑小童.全球变暖下南大洋吸热的季节变化特征[J ].中国海洋大学学报(自然科学版),2024,54(3):9-19.L u o J i n g ,Z h e n g X i a o t o n g .C h a r a c t e r i s t i c s o f s e a s o n a l v a r i a t i o n o f t h e S o u t h e r n O c e a n h e a t u p t a k e u n d e r g l o b a l w a r m i n g[J ].P e r i o d i c a l o f O c e a n U n i v e r s i t y of C h i n a ,2024,54(3):9-19. ❋ 基金项目:国家重点研究发展计划项目(2018Y F A 0605704)资助S u p p o r t e d b y t h e N a t i o n a l K e y R e s e a r c h a n d D e v e l o p m e n t P r o gr a m o f C h i n a (2018Y F A 0605704)收稿日期:2022-09-06;修订日期:2022-10-27作者简介:罗 菁(1998 ),女,硕士生㊂E -m a i l :l u o j i n g@s t u .o u c .e d u .c n ❋❋ 通信作者:郑小童(1982 ),男,博士,博士生导师㊂E -m a i l :z h e n gx t @o u c .e d u .c n 海洋占全球表面积的71%,对全球气候变化起重要调节作用㊂与大气相比海洋热容量更大,能吸收更多的热量并向下输送,因此,全球变暖中超过90%额外增加的能量被海洋吸收和储存[1-2],能够有效减缓全球表面温度的增暖速率[3-5],同时还延长了气候系统对外强迫响应的时间尺度[6-7]㊂南大洋指30ʎS 以南将太平洋㊁大西洋㊁印度洋连成一片的广袤海洋,占全球海洋总面积约30%,却主导了全球海洋热量储存和吸收㊂基于过去几十年的观测资料发现,南大洋次表层增暖十分显著[8-9],且加热深度远远超过全球海洋平均水平,同时还伴随着海平面的明显上升[10]㊂R o e m m i c h 等[3]通过多元观测资料研究发现,2006 2013年南半球热带外(20ʎS 90ʎS )海洋储存的热量占全球海洋热量增加的67%~98%,其中45ʎS 附近海洋增暖趋势最强,并向下延伸至1000m ㊂这一现象在气候模式中也能得到重现[11-12]㊂基于第五次耦合模式比较计划(C o u p l e d m o d e l i n t e r c o m pa r i s o n p r o j e c t ph a s e 5,C M I P 5)的历史模拟结果,S h i 等[13]发现,20世纪南大洋累积海洋吸热(O c e a n h e a t u pt a k e ,O H U )占全球海洋吸热的72%㊂在未来高排放情景试验中,北大西洋经向翻转环流(A t l a n t i c m e r i d i o n a l o -v e r t u r n i n g ci r c u l a t i o n ,A M O C )的减弱造成副极地北大西洋O H U 大幅增加,但南大洋累积O H U 的占比依然达到约48%㊂南大洋具有独特的海洋动力过程,对这里的O H U 有重要作用㊂南大洋上空强大的西风急流能够驱动向北的海洋艾克曼输运,造成表层海水辐散,形成强劲的上升流以及超过500m 的深厚海洋混合层㊂在全球变暖背景下,上升流带来的深层冷水从大气中吸收大量的热量并进入表层以下,对海表面温度(S e a s u r f a c et e m pe r a t u r e ,S S T )上升起到抑制作用[14]㊂同时也使得O H U 过程得以持续,导致南大洋次表层增暖远大于其他海盆[8]㊂同时,向北的艾克曼输运在40ʎS 附近辐合下沉,使得该海区储热最多[6,11,15-16]㊂此外,高纬度海区的亚南极模态水沿倾斜的等密度面潜沉进入海洋内部并向低纬度流动,将吸收的热量带入海洋并存储中国海洋大学学报2024年起来,对南大洋吸热有一定作用[17]㊂除了平均海洋环流的调控作用之外,大气环流的变化也有助于南大洋的海洋吸热以及海洋热含量的重新分配㊂在全球变暖背景下,南半球西风急流向极移动并加强,会增加南大洋经向翻转环流的强度[11,18]㊂但相对而言,环流变化对南大洋O H U的贡献较小,只占约20%,而平均环流的输送效应占总O H U的80%左右[15-16]㊂大洋中尺度涡旋的南向/上向热传输是南大洋内部热量再分配的另一个不可忽视部分,平衡了平均流的北向/下向热传输[19]㊂在气候变暖的情况下,由于南向涡流热量输送减少,涡流输送的变化对南大洋增暖最大海区(即40ʎS附近)北侧的海洋热量增加具有重要贡献[15-16]㊂模式中南大洋吸热作用也可以通过检测海气界面的热通量变化进行定量诊断[12,20]㊂H u等[20]对全球海洋热通量变化进行分解后发现,感热通量和短波辐射对南大洋净热通量变化有重要贡献,而潜热通量变化不利于海洋吸热㊂基于模式模拟,最近一项研究评估了全球变暖下南大洋海气热通量反馈的变化,发现热通量的负反馈倾向于抑制南大洋海温的增暖[21]㊂南大洋海气界面净热通量变化的不同部分受不同物理过程调控㊂例如在全球变暖背景下随着海洋的增暖,南极海冰会迅速减少[22],造成海冰反照率反馈机制加剧,使海洋得到更多的短波辐射,进而加强海洋吸热㊂此外,西风急流的强度和位置变化会改变南大洋的温跃层深度,进而影响表面湍流热通量(即感热通量和潜热通量)㊂值得注意的是,南大洋高纬度海区的气候特征具有显著的季节变化,诸如太阳辐射㊁西风急流等均表现出明显的年循环特征㊂而前人对南大洋海洋吸热和储热的研究大多是基于年平均状态,少有对于不同季节海洋吸热的研究㊂本文基于第六次耦合模式比较计划(C o u p l e d m o d e l i n t e r c o m p a r i s o n p r o j e c t p h a s e6,C M I P6)未来情景试验的多模式平均结果发现,全球变暖下的南大洋吸热有明显的季节变化特征㊂随后我们进一步探讨了全球变暖下南大洋吸热的季节变化及不同过程对海洋吸热的影响,尝试理解未来气候下南大洋吸热的季节特征及其机理㊂1资料与方法1.1C M I P6模式资料本文使用了28个C M I P6气候模式的模拟结果[23-24],主要分析了历史气候模拟试验(H i s t o r i c a l)和未来情景预估试验(S h a r e d s o c i o e c o n o m i c p a t h w a y585, S S P585)的月平均输出数据㊂历史模拟试验数据长度为1850年1月 2014年12月,从工业革命前对照试验出发,包括臭氧和气溶胶㊁火山活动㊁温室气体㊁太阳常数等外强迫作用㊂S S P585情景预估试验时间长度为2015年1月 2100年12月,从历史试验出发,未来情景预估试验中气溶胶㊁温室气体㊁太阳常数的全球平均值随着时间变化,气溶胶和火山在2015 2025年递减到工业革命前的水平,辐射强迫在2100年达到8.5W㊃m-2㊂为了便于后续比较分析,我们统一模式分辨率,将所有模式大气数据均插值到2.5ʎˑ2.5ʎ的网格上,海洋和海冰数据均插值到1ʎˑ1ʎ的网格上㊂选取的28个气候模式中有23个模式具备完整的海冰数据,22个模式有完整的海洋经向流速数据,19个模式具备完整的混合层深度数据,27个模式具备完整的海洋温度数据,具体模式名称见表1㊂表1本文选取的28个C M I P6气候模式T a b l e128C M I P6c l i m a t e m o d e l s s e l e c t e d i n t h i s s t u d y 气候模式①海冰②海洋流速③混合层厚度④海温⑤A C C E S S-E S M1-5ɿɿɿɿB C C-C S M2-M RɿɿɿɿC a n E S M5-C a n O EɿɿɿC a n E S M5ɿɿɿɿC E S M2-W A C C MɿɿɿɿC E S M2ɿɿC N R M-C M6-1ɿɿɿɿC N R M-C M6-1-H RɿC N R M-E S M2-1ɿɿɿE C-E a r t h3ɿɿɿɿF G O A L S-f3-LɿɿɿɿF G O A L S-g3ɿɿɿɿG F D L-C M4ɿɿG F D L-E S M4ɿɿɿG I S S-E2-1-GɿɿɿI N M-C M4-8ɿɿɿI N M-C M5-0ɿɿɿI P S L-C M6A-L RɿɿɿɿK A C E-1-0-GM I R O C-E S2LɿɿɿM I R O C6ɿɿɿɿM P I-E S M1-2-H RɿɿɿɿM P I-E S M1-2-L RɿɿɿɿM R I-E S M2-0ɿɿɿɿN E S M3ɿɿɿN o r E S M2-L MɿɿɿN o r E S M2-MMɿɿɿU K E S M1-0-L Lɿɿɿɿ注:①C l i m a t e m o d e l;②S e a i c e;③V e l o c i t y;④M i x e d l a y e r d e p t h;⑤T e m p e r a t u r e.013期罗 菁,等:全球变暖下南大洋吸热的季节变化特征1.2研究方法本文研究区域为南半球30ʎS 以南的广袤海域(30ʎS90ʎS ,180ʎ 180ʎ)㊂本文使用了合成分析㊁相关分析㊁回归分析等统计方法,并根据前人的研究方法定义海气净热通量,累积海洋吸热㊁经向热输运等㊂文中的季节均相对于南半球而言,12 2月(D J F )为夏季,6 8月(J J A )为冬季㊂本文首先计算了海气界面的净热通量:Q n e t =S W ˌ-S W ʏ+L W ˌ-L W ʏ-Q e -Q h ㊂(1)式中:表面总短波辐射(S W )等于向下短波减向上短波;总长波辐射(L W )等于向下长波减去向上长波;短波辐射和长波辐射的总和为辐射通量;潜热(Q e )和感热(Q h )的总和为湍流热通量㊂在此基础上,我们将相较于工业革命前(减去1861 1880年的平均值)的净热通量变化值的时间积分定义为累积海洋吸热[13]㊂南大洋累积海洋吸热是对30ʎS 以南海区的净热通量进行区域加权求和并计算时间积分㊂本文还计算了南大洋上层热量的经向输运(O H C -M T ),为热含量经向梯度与经向流速的乘积:O H C M T =-∂O H C ∂y v =-∂θρ0C p ∂yv ㊂(2)式中:θ为海水温度;ρ0为海水密度;C p 为海水比热容;v 为海洋经向流速㊂当∂O H C ∂y>0,表示往北海洋热量越大,反之表示海洋热量往北越小;当v >0时,表示向北的海流,反之为向南的海流㊂2 C M I P 6气候模式中南大洋吸热及其季节差异2.1历史模拟和未来预估试验中南大洋吸热的评估在C M I P 6历史试验的1900 2014年,根据累积海洋吸热的计算,南大洋是全球最强的海洋吸热区(见图1(a )),从纬向积分的结果中也可以看出(见图1(a )右),历史时期南大洋主导全球海洋吸热,30ʎS以南海区(误差条为模式间ʃ1倍标准差㊂E r r o r b a r s a r e t h e ʃ1t i m e s s t a n d a r d d e v i a t i o n s a m o n g di f f e r e n t c l i m a t e m o d e l s .)图1 C M I P 6多模式平均的(a )历史试验,(b )S S P 585试验中累积海洋吸热的空间分布(正值为海洋吸热,负值为放热,打点区域表示通过95%的信度检验㊂)及(c )历史试验,(d )S S P 585试验中南大洋占全球海洋累积吸热比重F i g .1 S p a t i a l d i s t r i b u t i o n o f c u m u l a t i v e o c e a n h e a t u p t a k e (p o s i t i v e v a l u e i n d i c a t e s h e a t a b s o r p t i o n ,n e ga t i v e v a l u e i n d i c a t e s h e a t r e l e a s e )i n m u l t i -m o d e l e n s e mb l e m e a n o f C M I P 6(a )h i s t o r ic a l a nd (b )S S P 585e x p e r i m e n t s (s t i p p l e d r e gi o n s i n d i c a t e e x c e e d 95%s t a t i s t i c a l c o n f i d e n c e ),p r o po r t i o n o f S o u t h e r n O c e a n t o g l o b a l o c e a n c u m u l a t i v e h e a t u p t a k e i n (c )h i s t o r i c a l a n d (d )S S P 585e x pe r i m e n t s 11中 国 海 洋 大 学 学 报2024年累积海洋吸热的纬向积分值几乎全为正,最强海洋吸热位于60ʎS 以北,最大值为44.3ˑ1010J㊂历史试验中接近一半的模式模拟南大洋累积海洋吸热超过全球海洋,南大洋占全球海洋吸热比重的多模式平均结果为102.7%ʃ61%,比C M I P 5历史试验中南大洋吸热的全球贡献(70%~75%)大[12-13]㊂此外,历史模拟中南大洋吸热的模式间差异(模式间一倍标准差)较大(见图1(c ),误差线),说明C M I P 6历史试验中不同模式对南大洋吸热占比的模拟有较大差异㊂其中N o r E S M 2-L M 模式中全球海洋累积吸热为负值(即历史时期海洋净放热),南大洋吸热占比为负值;此外E C -E a r t h 3㊁F G O A L S -g3㊁M P I -E S M 1-2-L R 模式中全球海洋累积吸热明显偏大(大于600Z J ,1Z J =1021J)㊂在未来高排放情景试验的2015 2100年(见图1(b)),全球海洋累积吸热的空间分布特征有所改变,北大西洋(30ʎN 70ʎN ,80ʎW 20ʎE )海洋吸热最显著,由历史时期向大气放热转变为强烈的海洋吸热,但全球海洋累积吸热的纬向峰值依旧位于60ʎS 以北(见图1(b )右),最大值可达到196.7ˑ1010J,约为历史时期的5倍㊂未来南大洋占全球海洋吸热比重虽然下降至47.5%ʃ7%(见图1(d)),但依然是全球海洋吸热最大的海区,与前人基于C M I P 5得出的结果(48%ʃ8%)基本一致[13]㊂C M I P 6未来预估试验中累积海洋吸热的模式间差异远小于历史时期(见图1(d))㊂历史模拟阶段除温室气体外,气溶胶㊁臭氧等气候外强迫因素也对海洋吸热有重要影响[26-27],在未来高排放情景试验中此类外强迫因素的作用有所减弱㊂本文之后部分仅分析未来预估试验中南大洋吸热的季节变化㊂在全球变暖背景下,未来各个季节南大洋占全球海洋吸热的比重有明显差异(见图2)㊂从多模式平均的结果来看,南半球夏季(12 2月,D J F )南大洋吸热占比最大,为68.2%ʃ43%(见图2(a )),其中N o r E S M 2-L M ㊁N o r E S M 2-MM 模式中南大洋占比为负值,且模式间差异较大㊂春季(9 11月,S O N )次之,占比为57.8%ʃ12.3%(见图2(d ))㊂秋季(3 5月,M A M )㊁冬季(6 8月,J J A )占比较小,分别为37.6%ʃ10.2%㊁39.0%ʃ14.3%㊂(误差线表示模式间ʃ1倍的标准差㊂E r r o r b a r s a r e t h e ʃ1t i m e s s t a n d a r d d e v i a t i o n s a m o n g di f f e r e n t c l i m a t e m o d e l s .)图2 C M I P 6未来高排放情景试验中2015 2100年(a )夏季㊁(b )秋季㊁(c )冬季㊁(d)春季南大洋占全球海洋累积吸热比重F i g .2 P r o p o r t i o n o f S o u t h e r n O c e a n t o g l o b a l o c e a n c u m u l a t i v e h e a t u pt a k e f r o m 2015t o 2100i n (a )s u m m e r ,(b )a u t u m n ,(c )w i n t e r a n d (d )s p r i n g i n C M I P 6S S P 585e x pe r i m e n t s 213期罗 菁,等:全球变暖下南大洋吸热的季节变化特征2.2未来南大洋吸热的季节变化2.2.1全球海洋吸热的纬向分布特征 为了更加直观㊁突出分析未来南大洋海洋吸热状况,首先我们计算并分析了全球海洋吸热的纬向积分结果,如图3所示㊂从图3中可以看到,对于年平均而言,全球海洋吸热最大值出现在南大洋55ʎS 60ʎS,最大趋势为102.1W ㊃m -2㊃d e c a d e-1㊂从不同季节来看,南大洋海洋吸热的峰值位置有明显摆动,夏季吸热峰值位于70ʎS附近(见图3(a )),为72.6W ㊃m -2㊃d e c a d e -1,峰值全年最小㊂但此时南大洋占全球海洋吸热比重远大于其他季节(见图2(a )),是因为北半球中㊁高纬度为强烈的海洋吸热和放热,而整个南大洋区域均表现为海洋吸热㊂春季和秋季吸热峰值位于63ʎS 附近(见图3(b )和(d)),峰值分别为128.1和140.7W ㊃m -2㊃d e c a d e-1;冬季峰值大致位于58ʎS (见图3(c )),为199.7W ㊃m -2㊃d e c a d e-1,约是春秋季㊁夏季的1.5和2.7倍㊂冬季大气中赤道至极地的经向温度梯度增大,南半球中纬度西风急流加强,一方面使得海表面蒸发加强,另一方面风场驱动的海洋环流加强,急流南侧的上升流增强使得海洋吸收更多的热量,此时北半球海洋吸热也较为显著,因此冬季南大洋占全球海洋吸热比重并不大(见图2(c))㊂南大洋吸热峰值从冬季到夏季逐渐向南移动(见图3(a )㊁(c)),此后随太阳直射纬度向北移动㊂南大洋60ʎS 以南高纬度海区的净热通量在秋㊁冬季呈明显负趋势(见图3(b ) (c)),表示未来该区域海洋将失去热量;春㊁夏季和年平均,高纬度净热通量均为正趋势,表示未来海洋吸热(见图3(a ),(d ),(e))㊂(实线为多模式平均结果,阴影为模式间(1倍标准差,蓝色虚线为45ʎS 70ʎS ,间隔为5ʎ的纬度线㊂T h e s o l i d l i n e s r e pr e s e n t t h e m u l t i -m o d e l e n s e m b l e m e a n ,a n d t h e s h a d o w s a r e t h e ʃ1t i m e s s t a n d a r d d e v i a t i o n s a m o n gd i f fe r e n t c l i m a t e m o d e l s .T h e b l u e d a s h e d l i n e s a r e l a t i t u d e l i n e s of 45ʎS 70ʎS w i t h a n i n t e r v a l o f 5ʎ.)图3 C M I P 6未来高排放情景试验中2015 2100年(a )夏季㊁(b )秋季㊁(c )冬季㊁(d )春季㊁(e)年平均的累积海洋吸热(红色,单位:J )和净热通量趋势(黑色,单位:W ㊃m -2d e c a d e -1)的纬向积分图F i g .3 Z o n a l i n t e g r a l o f c u m u l a t i v e o c e a n h e a t u pt a k e (r e d ,U n i t :J )a n d n e t h e a t f l u x t r e n d s (b l a c k ,U n i t :W ㊃m -2d e c a d e -1)f r o m 2015t o 2100i n (a )s u m m e r ,(b )a u t u m n ,(c )w i n t e r ,(d )s p r i n g a n d (e )a n n u a l m e a n i n C M I P 6S S P 585e x pe r i m e n t s C M I P 6未来预估试验中累积海洋吸热和净热通量趋势沿纬度的变化高度相似,如图3所示㊂年平均下南大洋整体的累积海洋吸热和净热通量变化趋势之间存在显著的模式间正相关关系(r =0.89,图略),即表示未来增暖气候下,气候模式模拟净热通量增加越多时,南大洋累积海洋吸热将越多㊂因此在后文中我们用净热通量趋势来表征累积海洋吸热的变化,并讨论其时空特征㊂2.2.2南大洋吸热的空间分布特征 随后作者分析了未来南大洋净热通量趋势的空间结构特征,结果见图4㊁5㊂从图中可知C M I P 6未来高排放情景试验中,年平均下南大洋净热通量趋势和累积海洋吸热的空间分布高度相似(见图4(g )和图1(b )),大部分区域为显著的海洋吸热,60ʎS 附近海洋吸热最强,40ʎS 附近的大西洋和印度洋海区为较强的海洋放热,这主要是由表面向北的艾克曼输送导致的[6]㊂本文进一步分析了净热通量各项变化的空间特征(见图4(a ) (f ))㊂其中湍流热通量趋势(见图4(f ))的空间分布与净热通量(见图4(g))相似,两者空间场的相关系数为0.84㊂未来南大洋大部分海区的潜热通量趋势为负(见图4(d)),绝大部分海区的感热通量呈31中 国 海 洋 大 学 学 报2024年显著正趋势(见图4(e ))㊂辐射通量在50ʎS 附近为不均匀的负趋势(见图4(c)),其两侧为较强的正趋势,与湍流热通量相反(见图4(f))㊂受温室效应的影响长波辐射呈现空间一致的正趋势(见图4(b));短波辐射呈正-负-正的经向结构特征(见图4(a)),南大洋中部短波辐射减少可能与云辐射反馈有关㊂综上,年平均的南大洋净热通量变化主要受湍流热通量变化的影响,高纬度海区的海洋吸热主要受辐射通量影响(见图4(g))㊂(打点区域表示通过95%的信度检验㊂所有变量均取向下为正㊂S t i p p l e d r e gi o n s i n d i c a t e e x c e e d 95%s t a t i s t i c a l c o n f i d e n c e .V a r i a b l e s a r e a l l c o n v e r t e d i n t o p o s i t i v e d o w n w a r d f l u x i n t o t h e o c e a n .)图4 C M I P 6未来高排放情景试验中多模式平均的2015 2100年(a )短波㊁(b )长波㊁(c )辐射通量㊁(d)潜热㊁(e )感热㊁(f )湍流热通量㊁(g)净热通量(单位:W ㊃m -2㊃a -1)的年平均趋势空间图F i g .4 S p a t i a l d i s t r i b u t i o n o f a n n u a l m e a n (a )s h o r t w a v e ,(b )l o n gw a v e ,(c )r a d i a t i v e f l u x ,(d )l a t e n t h e a t f l u x ,(e )s e n s i b l e h e a t f l u x ,(f )t u r b u l e n t h e a t f l u x a n d (g)n e t h e a t f l u x t r e n d s (U n i t :W ㊃m -2㊃a -1)f r o m 2015t o 2100i n m u l t i -m o d e l e n s e m b l e m e a n o f C M I P 6S S P 585e x pe r i m e n t s 南大洋海洋吸热的空间分布特征也存在显著季节变化(见图5(q) (t )),最强海洋吸热纬度随季节变化而移动,冬季吸热带最强且位置靠北(见图5(s )),夏季最强海洋吸热位于南极洲附近(见图5(q)),春㊁秋季强吸热带位于60ʎS 附近(见图5(r ) (s ))㊂各季节南大洋净热通量变化趋势的主导因素有所不同,在春季和夏季,高纬度㊁南极边缘海区表现为较强的海洋吸热(见图5(t )㊁(q))㊂此时辐射通量变化由短波辐射主导,将减弱南大洋中部海洋吸热,加强南极边缘的海洋吸热(见图5(a )㊁(d)),使得吸热峰值明显向南移动㊂长波辐射变化为空间均匀的正趋势(见图5(e )㊁(h )),湍流热通量变化较弱,但在较低纬度依然主导同期的净热通量变化㊂在秋季和冬季,净热通量变化的空间特征(见图5(r )㊁(s ))与湍流热通量变化(见图5(n)㊁(o))相似,此时辐射通量变化的空间特征不显著(见图5(j)㊁(k )),主要受温室效应增强造成的长波辐射增加主导(见图5(f )㊁(g )),加强南大洋中部海洋吸热,减弱其南㊁北侧海洋放热;短波辐射变化较弱(见图5(b )㊁(c))㊂综上,我们发现春夏季高纬度海区的净热通量趋势由短波辐射主导,使南大洋吸热峰值明显南移;南大洋中部净热通量变化是辐射通量和湍流热通量相互抵消的结果㊂秋冬季南大洋净热通量趋势的空间分布主要受湍流热通量影响㊂413期罗 菁,等:全球变暖下南大洋吸热的季节变化特征((a ) (d )短波;(e ) (h )长波;(i ) (l )辐射通量;(m ) (p )湍流热通量;(q) (t )净热通量㊂打点区域表示通过95%的信度检验㊂所有变量均取向下为正㊂(a ) (d )s h o r t w a v e ;(e ) (h )l o n g w a v e ;(i ) (l )r a d i a t i v e f l u x ;(m ) (p )t u r b u l e n t h e a t f l u x ;(q ) (t )n e t h e a t f l u x .S t i p p l e d r e gi o n s i n d i -c a t e e x c e e d 95%s t a t i s t i c a l c o n f i d e n c e .V a r i a b l e s a r e a l l c o n v e r t e d i n t o p o s i t i v e d o w n w a r d f l u x i n t o t h e o c e a n .)图5 C M I P 6未来高排放情景试验中多模式平均的2015 2100年各季节热通量趋势的空间分布图F i g .5 S pa t i a l d i s t r ib u t i o n o f h e a t f l u x t r e n d s i n d i f f e r e n t s e a s o n f r o m 2015t o 2100i n m u l t i -m o d e l e n s e m b l e m e a n o f C M I P 6S S P 585e x pe r i m e n t s 3 未来南大洋吸热的季节变化调控因素3.1南极海冰消融对高纬度海洋吸热的影响下面我们进一步探讨未来全球变暖背景下南大洋吸热季节差异的调控因素㊂通过分析纬向平均的热通量以及不同因素之间的关系(见图6),我们发现:春夏季南大洋高纬度(60ʎS 以南海区)湍流热通量变化较小(见图6(a )㊁(d),绿线),高纬度海洋吸热主要受辐射通量控制,特别是短波辐射的调控(图略)㊂该季节南极海冰也显著减少(见图6(a )㊁(d ),黄线),说明此时南大洋高纬度海洋吸热主要与海冰-反照率正反馈过程有关,即海冰消融造成海洋得到更多的太阳短波辐射㊂反之,在秋冬季辐射通量变化较小(见图6(b )㊁(c ),蓝线),是因为该季节南半球高纬度太阳辐射很小,尽管此时海冰消融显著,但海冰-反照率反馈无法起作用㊂事实上,秋冬季高纬度净热通量变化主要受湍流热通量影响(见图6(b )㊁(c ),绿线),且与海冰消融呈同位相变化,说明海冰显著减少有利于海洋向大气放热㊂年平均下高纬度海洋吸热由湍流热通量和辐射通量共同控制(见图6),两者呈反向变化㊂3.2气候态混合层深度对南大洋30ʎS —60ʎS 海洋吸热的影响在南大洋60ʎS 以北的较低纬度海区,除夏季外,其余季节净热通量变化主要与湍流热通量变化有关(见图6,黑线和绿线)㊂在夏季和秋季(见图6(a )㊁(b)),由湍流热通量导致的海洋吸热较弱,在冬季和春季(见图6(b )㊁(c )),湍流热通量引起的较低纬度海洋吸热较强,说明南大洋湍流热通量变化也存在显著的季节差异,但湍流热通量的季节变化似乎与大气低层纬向风(见图6,红线)的季节变化关系明显㊂由于南大洋海洋吸热主要与海洋热力结构,特别是当地的深混合层有关,我们又考查了C M I P 6历史试验(1951 2000年)的南大洋混合层深度和其上空纬向风的气候态模拟特征(见图7)㊂气候模式中南大洋深混合层在50ʎS 55ʎS ,位于西风带南侧5个纬度左右㊂值得注意的是,南大洋混合层深度有显著的季节变化,夏季最浅(见图7(a ),黑线)㊁冬春季较深(见图7(c )㊁(d),黑线)㊂相应的海洋吸热中湍流热通量也是夏季最小(见图6(a)),冬季最大(见图6(c ))㊂因此我们认为在南大洋较低纬度海区(60ʎS 以北)海洋吸热中的湍流热通量变化部分主要与气候态的混合层深度有关㊂51中 国 海 洋 大 学 学 报2024年(实线为多模式平均结果,阴影为模式间(1倍标准差,蓝色虚线为45ʎS 65ʎS ,间隔为5ʎ的纬度线㊂T h e s o l i d l i n e s r e pr e s e n t t h e m u l t i -m o d e l e n s e m b l e m e a n ,a n d t h e s h a d o w s a r e t h e ʃ1t i m e s s t a n d a r d d e v i a t i o n s a m o n gd i f fe r e n t c l i m a t e m o d e l s .T h e b l u e d a s h e d l i n e s a r e l a t i t u d e l i n e s of 45ʎS 65ʎS w i t h a n i n t e r v a l o f 5ʎ.)图6 C M I P 6未来高排放情景试验中2015 2100年(a )夏季㊁(b )秋季㊁(c )冬季㊁(d )春季和(e)年平均的热通量趋势(黑色:净热通量,绿色:湍流热通量,蓝色:辐射通量,单位:W ㊃m -2㊃d e c a d e -1)㊁850h P a 纬向风趋势(红色,单位:m ㊃s -1㊃d e c a d e -1)㊁南极海冰覆盖率趋势(黄色,单位:%㊃d e c a d e -1)的纬向平均图F i g .6 Z o n a l m e a n o f h e a t f l u x e s t r e n d s (b l a c k :n e t h e a t f l u x ,g r e e n :t u r b u l e n t h e a t f l u x ,b l u e :r a d i a t i v e f l u x ,U n i t :W ㊃m -2㊃d e c a d e -1)a n d z o n a l w i n d t r e n d s (r e d ,U n i t :m ㊃s -1㊃d e c a d e -1)a n d s e a -i c e a r e a p e r c e n t a g e t r e n d s (ye l l o w ,%㊃d e c a d e -1)f r o m 2015t o 2100i n (a )s u m m e r ,(b )a u t u m n ,(c )w i n t e r ,(d )s p r i n g ,a n d (e )a n n u a l m e a n i n C M I P 6S S P 585e x pe r i m e n ts (实线为多模式平均结果,阴影为模式间(1倍标准差,蓝色虚线为45ʎS 60ʎS ,间隔为5ʎ的纬度线㊂T h e s o l i d l i n e s r e pr e s e n t t h e m u l t i -m o d e l e n s e m b l e m e a n ,a n d t h e s h a d o w s a r e t h e ʃ1t i m e s s t a n d a r d d e v i a t i o n s a m o n gd i f fe r e n t c l i m a t e m o d e l s .T h e b l u e d a s h e d l i n e s a r e l a t i t u d e l i n e s of 45ʎS 60ʎS w i t h a n i n t e r v a l o f 5ʎ.)图7 C M I P 6历史试验中1951 2000年(a )夏季㊁(b )秋季㊁(c )冬季㊁(d )春季和(e)年平均的30ʎS 60ʎS 气候态纬向风(红色,单位:m ㊃s -1)和混合层深度(黑色,单位:m )纬向平均图F i g .7 Z o n a l m e a n o f 30ʎS t o 60ʎS m e a n z o n a l w i n d (r e d ,U n i t :m ㊃s -1)a n d m i x e d l a ye r t h i c k n e s s (b l a c k ,U n i t :m )f r o m 1951t o 2000i n (a )s u m m e r ,(b )a u t u m n ,(c )w i n t e r ,(d )s p r i ng a n d (e )a n n u a l m e a n i n C M I P 6hi s t o r i c a l e x pe r i m e n t s 4613期罗 菁,等:全球变暖下南大洋吸热的季节变化特征3.3南大洋上层经向热输送的季节变化南大洋吸热后上层热量经向输送也存在显著季节变化(见图8(a ) (e ))㊂全球变暖背景下,南半球西风急流加强并向极移动(见图6,红线),南大洋经向翻转环流加强,海洋表面向北的埃克曼输运加强使得向北的经向热输送增强㊂C M I P 6未来高排放情景试验中南大洋上层经向热输送趋势的空间分布如图8(a ) (e)所示,最显著的特征为海洋表层南负北正的经向结构,与海洋经向流速趋势的空间结构相似(图略),大部分季节正㊁负趋势大致以45ʎS 为界,冬季分界纬度约为40ʎS (见图8(c )),夏季负信号的深度最浅(见图8(a)),冬季经向热输送的变化最大,能向下延伸至90米(见图8(c ))㊂未来气候下南大洋上升流以北的表层热量经向输送将加强,对南大洋30ʎS 60ʎS 海表吸热及热量再分配产生影响㊂图8 C M I P 6未来高排放情景试验中多模式平均的2015 2100年不同季节和年平均的南大洋上层海洋(a e)经向热输送趋势(单位:J ㊃m -2㊃s -1㊃a -1),(k o )气候态环流输运项(单位:J ㊃m -2㊃s -1㊃a -1),(pt )环流变化输运项(单位:J ㊃m -2㊃s -1㊃a -1),(f j)两项的加和(单位:J ㊃m -2㊃s -1㊃a -1)的空间分布图F i g .8 S p a t i a l d i s t r i b u t i o n o f (a e )m e r i d i o n a l h e a t t r a n s p o r t t r e n d ,(k o )m e a n c i r c u l a t i o n t r a n s po r t t e r m ,(p t )c i r c u l a t i o n v a r i a t i o n t r a n s p o r t t e r m ,a n d (f j )t h e s u m o f t w o t e r m s (U n i t :J ㊃m -2㊃s -1㊃a -1)i n t h e u p pe r S O i n d if f e r e n t s e a s o n a n d a n n u a l m e a n f r o m 2015t o 2100i n m u l t i -m o d e l e n s e m b l e m e a n o f C M I P 6S S P 585e x pe r i m e n t s 我们进一步把南大洋上层的热量经向输运作用分为气候态环流对异常海洋热量经向梯度的输运作用(简称气候态环流输运项,-∂(O H C )∂y'v -,图8(k )(o))以及异常环流对气候态海洋热量经向梯度的输运作用(简称环流变化输运项,-∂(O H C )∂y-v ',图8(p )(t ))㊂两项之和(-∂(O H C )∂y -v '-∂(O H C )∂y'v -,图8(f ) (j))与整体的热量经向输运(见图8(a ) (e ))基本一致㊂其中气候态环流输运作用在各季节差别不大(见图8(k ) (o)),说明海洋热量的经向变化在平均态环流的调控下对热量经向输运的季节变化贡献很小㊂而环流变化输运作用有显著的季节变化(见图8(p) 71中国海洋大学学报2024年(t)),在夏秋季海洋热量的向北输送主要被局限在南大洋较高纬度海区(见图8(p) (q)),而冬春季到40ʎS 均有显著的向北输送(见图8(r) (s)),这与该季节的深混合层及较强的西风增强有关㊂4结语本文基于C M I P6耦合模式的未来高排放情景试验模拟结果,分析了南大洋吸热的季节变化特征㊂研究发现:在未来变暖气候下,南大洋占全球海洋吸热的比重接近一半,是海洋热量存储的重要海区㊂此外,南大洋海洋吸热具有显著的季节变化特征㊂南半球冬季,南大洋吸热最为显著,且吸热峰值位置偏北;夏季峰值位置偏南,且峰值最小㊂其中高纬度海区(60ʎS以南)净热通量变化在春夏季主要受到辐射通量变化的影响,尤其在短波辐射-反照率正反馈作用下得到更多的海洋吸热;相反在秋冬季,由于高纬度太阳辐射很小,海冰的变化主要影响海气界面的湍流热通量变化,并与春夏季的辐射通量变化相抵消,因此年平均下高纬度海洋吸热趋势不显著㊂而在30ʎS 60ʎS较低纬度海区,海洋吸热主要受湍流热通量的影响,这一部分也存在显著的季节变化,在冬春季较强,夏秋季较弱㊂进一步分析发现,气候态混合层深度的季节变化对于此处海洋吸热变化有重要影响㊂此外,全球变暖下南大洋上层经向热量输送也存在显著的季节变化㊂相较于夏秋季,冬春季经向热输送的增强范围明显向赤道㊁向下扩张,这与气候态混合层深度和西风增强的季节变化有关㊂本文目前仅从多模式平均的角度探讨了未来南大洋吸热的季节变化㊂但值得注意的是,不同模式对于南大洋吸热的模拟有较大差异,因此有必要在后续的研究中分析模式间差异来源及其背后的物理机制,以便更为清晰的认识南大洋海洋吸热的物理机制㊂参考文献:[1] T r e n b e r t h K E,F a s u l l o J T,B a l m a s e d a M A.E a r t h's e n e r g y i m-b a l a nc e[J].J o u r n a l o f C l i m a t e,2014,27:3129-3144.[2]C h e n g L,T r e n b e r t h K E,F a s u l l o J,e t a l.I m p r o v e d e s t i m a t e s o fo c e a n h e a t c o n t e n t f r o m1960t o2015[J].S c i e n c e A d v a n c e,2017, 3(3):e1601545.[3] R o e m m i c h D,C h u r c h J,G i l s o n J,e t a l.U n a b a t e d p l a n e t a r y w a r m i n ga n d i t s o c e a n s t r u c t u r e s i n c e2006[J].N a t u r e C l i m a t e C h a n g e,2015,5:240-245.[4]F y f e J C,M e e h l G A,E n g l a n d M H,e t a l.M a k i n g s e n s e o f t h e e a r l y-2000s w a r m i n g s l o w d o w 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[11]C a i W,C o w a n T,G o d f r e y S,e t a l.S i m u l a t i o n s o f p r o c e s s e s a s-s o c i a t e d w i t h t h e f a s t w a r m i n g r a t e o f t h e s o u t h e r n m i d l a t i t u d e o-c e a n[J].J o u r n a l o f C l i m a t e,2010,23:197-206.[12]F röl i c h e r T L,S a r m i e n t o J L,P a y n t e r D J,e t a l.D o m i n a n c e o ft h e S o u t h e r n O c e a n i n a n t h r o p o g e n i c c a r b o n a n d h e a t u p t a k e i nC M I P5m o d e l s[J].J o u r n a l o f C l i m a t e,2015,28:862-886.[13]S h i J R,X i e S P,T a l l e y L D.E v o l v i n g r e l a t i v e i m p o r t a n c e o f t h eS o u t h e r n O c e a n a n d N o r t h A t l a n t i c i n a n t h r o p o g e n i c o c e a n h e a t u p t a k e[J].J o u r n a l o f C l i m a t e,2018,31:7459-7479. [14] M a n a b e S,S t o u f f e r R J,S p e l m a n M J,e t a l.T r a n s i e n t r e s p o n s e so f a c o u p l e d o c e a n-a t m o s p h e r e m o d e l t o g r a d u a c h a n g e s o f a t m o s-p h e r i c C O2.P a r tⅠ:A n n u a l m e a n r e s p o n s e[J].J o u r n a l o f C l i-m a t e,1991,4:785-818.[15] M o r r i s o n A K,G r i f f i e s S M,W i n t o n M,e t a l.M e c h a n i s m s o fS o u t h e r n O c e a n h e a t u p t a k e a n d t r a n s p o r t i n a g l o b a l e d d y i n g c l i-m a t e m o d e l[J].J o u r n a l o f C l i m a t e,2016,29:2059-2075. [16]L i u W,L u J,X i e S P,e t a l.S o u t h e r n O c e a n h e a t u p t a k e,r e d i s-t r i b u t i o n,a n d s t o r a g e i n a w a r m i n g c l i m a t e:T h e r o l e o f m e r i d i o-n a l o v e r t u r n i n g c i r c u l a t i o n[J].J o u r n a l o f C l i m a t e,2015,31: 4727-4743.[17]史久新,赵进平.中国南大洋水团,环流和海冰研究进展(19952002)[J].海洋科学进展,2002,20(4):116-126.S h i J X,Z h a o J P.A d v a n c e s i n C h i n e s e s t u d i e s o n w a t e r m a s s e s,c i r c u l a t i o n a nd se a i c e i n t h e S o u t h e r n O c e a n(1995 2002)[J].A d v a n c e s i n M a r i n e S c i e n c e,2002,20(4):116-126.[18] W a u g h D W,P r i m e a u F,D e v r i e s T,e t a l.R e c e n t c h a n g e s i n t h ev e n t i l a t i o n o f t h e s o u t h e r n o c e a n s[J].S c i e n c e,2013,339(6119): 568-570.[19] G r e g o r y J M.V e r t i c a l h e a t t r a n s p o r t s i n t h e o c e a n a n d t h e i r e f f e c to n t i m e-d e p e n d e n t c l i m a t e c h a n g e[J].C l i m a t e D y n a m i c s,2000, 16:501-515.[20] H u S,X i e S P,L i u W.G l o b a l p a t t e r n f o r m a t i o n o f n e t o c e a n s u r-f a c e h e a t f l u x r e s p o n s e t og r e e nh o u s e w a r mi n g[J].J o u r n a l o f C l i-m a t e,2020,33(17):7503-7522.[21]Z h a n g L,C o o k e W.S i m u l a t e d c h a n g e s o f t h e S o u t h e r n O c e a n a i r-s e a h e a t f l u x f e e d b a c k i n a w a r m e r c l i m a t e[J].C l i m a t e D y n a m-i c s,2021,56:1-16.[22]Z h a n g L,D e l w o r t h T L,C o o k e W,e t a l.N a t u r a l v a r i a b i l i t y o fS o u t h e r n O c e a n c o n v e c t i o n a s a d r i v e r o f o b s e r v e d c l i m a t e t r e n d s81。

固相萃取-气相色谱-质谱法测定水中10种嗅味物质的含量

固相萃取-气相色谱-质谱法测定水中10种嗅味物质的含量

固相萃取-气相色谱-质谱法测定水中10种嗅味物质的含量冯桂学;刘莉;顿咪娜;赵清华;孙韶华;贾瑞宝【摘要】水样经HLB固相萃取小柱萃取,用二氯甲烷2 mL洗脱,所得洗脱液用HP-5 MS毛细管色谱柱分离,在全扫描和选择离子监测模式下进行质谱测定.10种嗅味物质在一定的质量浓度范围内与其对应的峰面积呈线性关系,方法的检出限(3S/N)在0.50~1.0μg·L-1之间.以空白样品为基体进行加标回收试验,所得回收率在88.7%~113%之间,测定值的相对标准偏差(n=6)在2.0%~6.7%之间.%The water sample was extracted on HLB solid phase extraction column,and then eluted with 2 mL of dichloromethane.The eluate was then separated by GC on HP-5 MS capillary chromatographic column,and the analytes were determined by MS under the modes of full-scanning and selected ion monitoring.Linear relationships between values of peak area and mass concentration of the 10 odorous materials were kept in definite ranges. Detection limits (3S/N)found were ranged from 0.50 to 1.0μg·L-1 .On the base of blank sample,test for recovery was made by standard addition method,values of recovery found were in the range of 88.7%-113%,with RSD′s (n= 6 )in the range of 2 .0%-6 .7%.【期刊名称】《理化检验-化学分册》【年(卷),期】2017(053)005【总页数】5页(P502-506)【关键词】气相色谱-质谱法;固相萃取;嗅味物质;水【作者】冯桂学;刘莉;顿咪娜;赵清华;孙韶华;贾瑞宝【作者单位】山东省城市供排水水质监测中心,济南250021;山东省城市供排水水质监测中心,济南250021;山东省城市供排水水质监测中心,济南250021;山东省城市供排水水质监测中心,济南250021;山东省城市供排水水质监测中心,济南250021;山东省城市供排水水质监测中心,济南250021【正文语种】中文【中图分类】O657.63近年来,城市饮用水源嗅味污染事件频繁发生,使得公众对城市供水水质安全性产生怀疑。

河南省暖季小时极端降水时空分布特征

河南省暖季小时极端降水时空分布特征

Spatial and temporal distribution characteristics of hourly extreme rainfall in warm season in HenanYANG Junyong 1,SU Aifang 2(1.Ecology and Environment Academy of Zhengzhou University,Zhengzhou 450001;2.Henan Meteorological Observatory,Zhengzhou 450007)Abstract:Based on the hourly precipitation data from 2010to 2018at the 371meteorological stations including the 122national AutomaticWeather Stations (AWSs)and the 249backbone regional AWSs in Henan,we have conducted a statistical analysis of spatial and temporal distribution characteristics of hourly extreme rainfall in warm season (May to September)in Henan.The main results are as follows.(1)There are obvious differences in the threshold,intensity,frequency and contribution rate of hourly extreme rainfall in the 99.9th percentile in warmseason in Henan.Their high value areas are mainly in the south of the Funiu Mountains,the east of the Huanghuai Plain and the southwest of the Hwai River basin.(2)Hourly extreme rainfall events occur mainly between July and August,of which the most is in July,and the regional extreme precipitation event is more than the quater of hourly extreme rainfall events.The diurnal variation of hourly extreme rainfall frequen ⁃cy in Henan is characterized by an obvious bimodal structure,in which the main peak value appears in the evening.The diurnal variation of the frequency of hourly extreme rainfall above 80mm ·h -1shows a multi-peak structure,in which the main peak value is at night.(3)There are differences in the hourly extreme precipitation index for the four underlying surfaces including mountains,hill area,urban area and plain.The intensity of hourly extreme precipitation is the highest in the urban area,while its frequency is the lowest.The intensity of hourly ex ⁃treme precipitation is the lowest in the mountains,while its frequency is the highest.(4)Although the diurnal variation of hourly extreme pre ⁃cipitation under all four types of underlying surfaces shows a bimodal pattern,there are obvious differences in some ways.The peak values of hourly extreme precipitation in the mountains occur mainly at night,followed by evening.Those in hilly area coexist at night and in the eve ⁃ning,and their intensities are comparable.Those in plain and urban occur mainly in the afternoon,and its peak intensity in the afternoon is higher in urban area.Key words:hourly extreme rainfall;temporal and spatial distribution;diurnal variation characteristics;underlying surface杨军勇,苏爱芳.2021.河南省暖季小时极端降水时空分布特征[J].暴雨灾害,40(2):153-159YANG Junyong,SU Aifang.2021.Spatial and temporal distribution characteristics of hourly extreme rainfall in warm season in Henan [J].Torrential Rain and Disasters,40(2):153-159河南省暖季小时极端降水时空分布特征杨军勇1,苏爱芳2(1.郑州大学生态与环境学院,郑州450001;2.河南省气象台,郑州450007)摘要:利用2010—2018年河南省371个气象观测站(包含122个国家站和249个骨干区域站)逐时降水资料,对河南省暖季(5—9月)小时极端降水时空分布特征进行了统计分析。

“蒸发悖论”在秦岭南北地区的探讨

“蒸发悖论”在秦岭南北地区的探讨

“蒸发悖论”在秦岭南北地区的探讨蒋冲;王飞;刘思洁;穆兴民;李锐;刘焱序【摘要】潜在蒸散量(ET0)是大气蒸发的估计值,已经广泛应用于灌溉管理和无实测蒸发资料地区的估算.分析ET0的时空变化是研究水资源对气候变化响应的基础工作,同时对于农业水资源的优化利用也具有重要意义.根据秦岭南北47个气象站1960-2011年逐日数据,利用FAO Penman-Monteith公式计算出各站的潜在蒸散量(ET0),研究了气温、降水与ET0之间的长期变化趋势关系,对导致ET0下降的主要原因进行了讨论,着重对秦岭南北地区是否存在“蒸发悖论”进行验证.结果表明:(1)秦岭南北整体气温经历了先降后升的变化过程,1993年为突变年份,1960-1993年的降温速率和1994-2011年的升温速率均表现出由南向北递减的规律,1960-2011年整体升温速率由北向南递减.(2)1979年和1993年是ET0变化的转折点,以1979和1993为界ET0经历了“升—降—降”的变化阶段.1960-1979年仅汉水流域和巴巫谷地存在“蒸发悖论”现象,1980-1993、1994-2011和1960-2011年3个时段区域整体和各子区均发现了“蒸发悖论”现象.秋季后18a 和52a整体以及冬季前34a和52a整体均存在“蒸发悖论”现象,冬季最为明显.(3)近52年整体降水表现出不显著的下降趋势,相较于年尺度,夏季降水与ET0逆向变化趋势更为明显.(4)年尺度上,太阳辐射(日照时数)下降引起的潜热通量减少是造成ET0下降即“蒸发悖论”现象的主要原因.季节尺度,春季ET0下降的主导因素为风速,其它季节均为太阳辐射(日照时数).【期刊名称】《生态学报》【年(卷),期】2013(033)003【总页数】12页(P844-855)【关键词】秦岭南北;潜在蒸散量;蒸发悖论;气温;降水【作者】蒋冲;王飞;刘思洁;穆兴民;李锐;刘焱序【作者单位】西北农林科技大学资源环境学院,杨凌712100;西北农林科技大学资源环境学院,杨凌712100;中国科学院水利部水土保持研究所,杨凌712100;北京大学遥感与地理信息系统研究所,北京100871;西北农林科技大学资源环境学院,杨凌712100;中国科学院水利部水土保持研究所,杨凌712100;西北农林科技大学资源环境学院,杨凌712100;中国科学院水利部水土保持研究所,杨凌712100;陕西师范大学旅游与环境学院,西安710062【正文语种】中文潜在蒸散量(ET0)是指在一定气象条件下水分供应不受限制时,某一固定下垫面土壤蒸发量和植物蒸腾量的总和,它是实际蒸散量的理论上限,也是计算实际蒸散量的基础,又被称之为参考作物蒸散量[1-4]。

美丽的地方的空间顺序和季节顺序的作文儿

美丽的地方的空间顺序和季节顺序的作文儿

英文回答:In this beautiful place, the order of space and the order of seasons are intertwined and present different images。

Here,we insist on a clear season, each season having a unique charm。

In the spring, everything recovers, green grass islike flowers, and the space is full of life and energy。

In summer, the sun was bright, the lake was clear, the shaded,the space was full of freshness and tranquillity。

In autumn,the golden wheat fields were ripe, the field was golden, the autumn winders, and the space was full of harvest and maturity。

And in winter, silver is covered, snow is floating,silver is white and space is filled with serenity and purity。

The images of different seasons are intertwined, showing our firm course, approach and policy, and constitute a beautiful picture。

在这片美丽的地方,空间的顺序和季节的顺序相互交织,呈现出不同的景象。

柯本气候分类法

柯本气候分类法

05
柯本气候分类法的优缺点及改进方向
柯本气候分类法的优点与局限性
优点:
• 分类方法简单,易于理解和操作 • 适用范围广,可以应用于全球各地的气候分类 • 分类结果具有较高的实用价值,为气象学、地理学、生态学等领域的研究提供了 依据
局限性:
• 某些气候类型的划分界限较为模糊,容易导致分类结果的不确定性 • 未能充分考虑地形、洋流等地理因素对气候的影响 • 对于极端气候事件的考虑不足,可能导致分类结果的偏差
• C气候类型主要分布在亚洲的东部、东北部,欧洲的东部、北部 等地 • 气候特点:
• 四季分明,气温适中,平均气温在8℃~18℃之间 • 降水分布较均匀,年降水量在500~1000毫米之间 • 夏季温暖多雨,冬季寒冷干燥 • 植被类型:森林、草原等,植物种类丰富,适应性较强
D气候类型:寒带季风气候
柯本气候分类法的分类依据与 指标
• 柯本气候分类法主要依据以下四个指标对气候进行分类 • 平均气温(Mean annual temperature):衡量一个 地区全年气温的平均水平 • 降水量(Precipitation):衡量一个地区全年降水量的多 少 • 干燥度指数(Aridity index):衡量一个地区干燥程度的 指标,计算公式为:降水量/潜在蒸发量 • 季节划分(Seasonal distribution of temperature and precipitation):衡量一个地区气温和降水在不同 季节的分布情况
方面的影响
通过柯本气候分类法,生态学家可以评 估气候变化对生态系统的影响,为生态
保护提供依据
柯本气候分类法在农业、城市规划等领域的应用
农业领域,柯本气候分类法可以用于分析气候对农业生产的影响,如气候对作物生长、病虫害等方面的影响

219486384_1960—2021_年黑龙江省雾天气时空分布特征

219486384_1960—2021_年黑龙江省雾天气时空分布特征

1960—2021年黑龙江省雾天气时空分布特征于 璐1,杨 帆2,李明玥1,李 想11.黑龙江省气候中心,黑龙江哈尔滨 150030;2.黑龙江省气象局机关服务中心,黑龙江哈尔滨 150030摘要 基于1960—2021年黑龙江省雾天气月统计资料,利用ArcGIS软件的空间插值工具,统计分析黑龙江省雾日数时空分布特征。

结果表明:(1)1960—2021年黑龙江省平均雾日为15.6 d/年。

(2)雾年代际变化特征呈现为20世纪60~70年代增加,70年代至21世纪00年代逐年代减少,21世纪10年代又有增加趋势,2020年以后上升幅度明显。

近62年来,雾日增长率最大的地方为牡丹江绥芬河,达8.1 d/10年。

(3)从空间分布角度来看,黑龙江省雾天气基本呈现西南、东北少,西北、东南多的特征。

(4)黑龙江省雾天气出现频率为春季和冬季低,夏季和秋季高,其中以6—9月最多,3—4月最少。

(5)雾和相对湿度的增减趋势是一致的,当相对湿度增加1%时,雾日数增加1~4 d。

关键词 黑龙江省;雾日数;时空插值中图分类号:P426.4 文献标识码:B 文章编号:2095–3305(2023)05–0089-05雾霾天气会给气候、环境、交通、健康等方面造成显著的负面影响。

例如,引发酸雨(酸雾)、光化学烟雾现象;导致大气能见度下降,影响空中、水面和陆面交通;提高死亡率、使慢性病加剧、使呼吸系统及心脏系统疾病恶化,改变肺功能及结构、影响生殖能力、降低人体免疫功能等[1-3]。

多年来,国内学者对我国雾、霾天气变化特征展开了大量的研究。

在高纬度地区,雾的频率很高[4],比如在极地区域雾是常见而持续的现象,全年雾日可达80~ 100 d,反之在低纬度地区雾比较少见。

大陆内部由于水汽缺乏,所以越深入内陆,雾的频率越低,高山地区雾也比平原地区多。

我国雾日数空间分布呈现东南多、西北少的地域特点[5-8],雾日数在东南地区呈增加趋势,全国总体呈减少趋势[9-11]。

气候变暖背景下鄂尔多斯市暴雨时空分布特征及灾害防御

气候变暖背景下鄂尔多斯市暴雨时空分布特征及灾害防御

2020414文章编号 1005-8656(2020)04-0014-03中图分类号 P468.0+24 文献标识码 A doi :10.14174/ki.nmqx.2020.04.004气候变暖背景下鄂尔多斯市暴雨时空分布特征及灾害防御张连霞1,郑玉峰1,许晶1,徐桂梅2,李亚芬3(1.鄂尔多斯市气象局,内蒙古 鄂尔多斯 017000;2.内蒙古大气探测技术保障中心,内蒙古 呼和浩特 010051;3.通辽市气象局,内蒙古 通辽 028000)摘要 利用NCEP/NCC 再分析资料和鄂尔多斯地面自动气象站历史资料分析鄂尔多斯1981—2019年暴雨时空分布特征。

结果显示:暴雨分布具有明显的季节变化特征,且气候变暖以后,极端暴雨天气出现频率明显增加。

暴雨日数空间分布特征显示,鄂尔多斯市东部地区出现暴雨及大暴雨的频率最高。

暴雨对年降水的贡献率较大,尤其是气候变暖后的2016年。

针对鄂尔多斯市暴雨时空分布特征,提出暴雨灾害的相关防御措施。

关键词 气候变暖;暴雨;时空分布特征;灾害防御引言鄂尔多斯市地处内蒙古高原,常年多风少雨,但降水量集中,尤其是受全球气候变暖影响,极端暴雨天气事件频繁发生。

暴雨造成洪涝灾害和严重的水土流失,导致农田被淹、城市发生内涝,甚至引发山洪和泥石流、堤坝决口、江河泛滥,给国家和人民造成重大经济损失,同时破坏良好的生态环境。

多年来,广大气象工作者对暴雨的成因、机理以及时空分布特征等[1-8]进行了系统深入的研究,试图找出暴雨发生、发展规律,为提高暴雨预报准确率积累经验,总结指标,也为地方的经济发展和人民生命财产安全提供技术支撑。

本文通过研究鄂尔多斯市近39年暴雨时空分布特征,对全面了解鄂尔多斯市旱涝变化规律,指导本市的农牧业生产和产业结构调整以及当地政府防灾减灾救灾具有重要的现实意义。

1 资料选取和方法选用NCEP/NCC 再分析资料和1981—2019年鄂尔多斯市地面气象观测的逐月暴雨日数和降水量等历史资料,采用一元线性回归法和3年滑动平均法进行分析。

大亚湾裸甲藻种群动态及其关键调控因子

大亚湾裸甲藻种群动态及其关键调控因子

大亚湾裸甲藻种群动态及其关键调控因子赖海燕;徐宁;段舜山【摘要】Population dynamics of Gymnodinium spp. and environmental factors in aquaculture areas of Daya Bay were investigated from January to December 2008. The dominant Gymnodinium species was Gymnodinium sp., and Karenia mikimotoi, Gymnodnium catenatum and Akashiwo sanguinea were found in low density. Obvious seasonal and spatial distribution characteristics were displayed in density of Gymnodnium group. The highest density of 903 cells·mL-1 was observed in May, while the lowest in autumn and winter. And the population density of Gymnodnium group was higher in aquaculture areas and coastal areas than the open sea. Correlation analysis showed that temperature, COD (chemical oxygen demand), DON (dissolved organic nitrogen) and urea played key roles in regulating the density of Gymnodinium group. The optimal temperature range for Gymnodnium group were 25~30 ℃, while DON and urea were 156.38~187 μgN·L-1 and 17.4~38.9 μgN·L-1, respectively. When the temperature was suitable, the rise in organic nitrogen such as urea can play a trigger in the formation of Gymnodinium blooms.%2008年1-12月对大亚湾养殖海域裸甲藻种群动态和主要环境因子进行了周年调查.结果表明,大亚湾海域裸甲藻类群以直径约为16~22μm的小型裸甲藻(Gymnodinium sp.)为主,另外米氏凯伦藻(Karenia mikimotoi)、链状裸甲藻(Gymnodniumcatenatum)和血红哈卡藻(Akashiwo sanguinea)也有少量出现.裸甲藻种群密度呈现出明显的季节性变化特征:5月出现裸甲藻密度高峰,全年最大密度达到903 cells.mL-1,秋冬季节密度最小.不同站位裸甲藻密度也具有明显的空间分布差异,养殖及近岸海域密度普遍高于外海对照区.相关性分析结果表明,裸甲藻密度的关键调控因子包括温度、化学需氧量(COD)、可溶性有机氮(DON)和尿素浓度.裸甲藻高密度、高频率出现的温度范围在24~26℃,DON和尿素的质量浓度范围分别为N 156.38~187μg.L-1和N 17.4~38.9 μg.L-i.在温度适宜的条件下,尿素等有机氮含量的增加可能成为裸甲藻赤潮的触发因子.【期刊名称】《生态环境学报》【年(卷),期】2011(020)003【总页数】6页(P505-510)【关键词】裸甲藻;种群动态;大亚湾;环境因子;有机氮【作者】赖海燕;徐宁;段舜山【作者单位】暨南大学水生生物研究中心∥热带亚热带水生态工程教育部工程研究中心,广东,广州,510632;暨南大学水生生物研究中心∥热带亚热带水生态工程教育部工程研究中心,广东,广州,510632;暨南大学水生生物研究中心∥热带亚热带水生态工程教育部工程研究中心,广东,广州,510632【正文语种】中文【中图分类】X171.5裸甲藻类群(Gymnodnium spp.)隶属横裂甲藻亚纲裸甲藻目裸甲藻科(Gymnodiniaceae Lankester)。

抗生素在水环境中的分布及其毒性效应研究进展

抗生素在水环境中的分布及其毒性效应研究进展

抗生素在水环境中的分布及其毒性效应研究进展∗李经纬;刘小燕;王美欢;刘珊;余乐洹;任明忠;庄僖【摘要】In recent years, as an emerging group of environmental contaminant, the damage of antibiotics has become a growing concern. It was reported that the concentrations of antibiotics ranged from ng/Ltoμg/L in aquatic environment. With continued using and emissions of antibiotics, the residual antibiotics in aquatic will have a negative impacton the local ecosystem, which may cause the aquatic organisms to change. With the bioaccumulation of antibiotics, it could endanger the health of human beings through food chain. The concentrations and seasonal variation of antibiotics in water and sediment were reviewed. The toxic effects of antibiotics were discussed, so as to provide evidence for the further research on ecotoxicology effects of HBCD on human health.%近年来,抗生素作为一种新兴污染物,其危害性和污染控制问题已成为人们日益关注的焦点。

天津城市热岛效应的时空变化特征

天津城市热岛效应的时空变化特征

天津城市热岛效应的时空变化特征黄利萍;苗峻峰;刘月琨【摘要】In this paper, the temporal and spatial characteristics of urban heat island effect in Tianjin city in the year 2008 were analyzed by using the observation data and the 6 h ground general data from 14 automatic meteorological stations in Tianjin. The results showed that the urban heat island effect in Tianjin not only had significant diurnal, monthly, seasonal and annual variation characteristics, but also was closely related to the method to choose urban and suburban stations. Finally, the relationship be- tween urban heat island intensity and cloud, wind, humidity was analyzed by using the multiple linear regression analysis method. It was found that the wind speed was a dominant meteorological factor, but the overall impact of the meteorological elements on the urban heat island effect in Tianjin was relatively limited.%应用2008年天津市14个自动气象站逐小时资料和6h一次的地面常规资料,对天津城市热岛效应的时空特征进行了分析,结果表明:天津市热岛强度的日变化、月变化和年、季特征显著,且天津市热岛强度与城郊站的选择方法有密切关系。

去根处理对樟树林土壤呼吸的影响

去根处理对樟树林土壤呼吸的影响

去根处理对樟树林土壤呼吸的影响刘智;闫文德;王光军;郑威;梁小翠;宿少锋【摘要】Soil respiration was measured with Li-8100 soil CO, efflux system in Cinnamomum camphora plantation in forest park of Changsha, Hunan, with de-rooting treatments and trenching method, from August 2009 to July 2010. The results show that the soil respiration had a significant seasonal change both in the trenched plots and the control plots. The rates of soil CO2 efflux were about 1.426 ~ 5.641 μmol·m-2s-1 in the trenched plots, and 1.137 - 4.257 μmol·m-2s-1 in the control plots, respectively. The soil respiration rate in the trenched plots exhibited a highly markedly exponential correlation with the soil temperature at 5 cm depth (P =0.000) (without living roots) and a highly markedly quadric relationship with the soil moisture at 5 cm depth (P=0.012) . The results indicate that the root system was an important factor affecting soil CO, efflux, soil temperature and soil moisture in forest.%采用LI-8100开路式土壤C通量测定系统,对去根处理的樟树人工林土壤呼吸进行了为期1 a的观测.结果表明:去根处理和对照的土壤呼吸速率均呈现显著的季节性变化,土壤CO2呼吸速率月平均值变化动态呈单峰曲线;对照处理土壤呼吸速率变化范围为1.426~5.641 μmol·m-2s-1,去根处理后的土壤呼吸速率范围为1.137~4.257μmol·rn-2s-1;去除根系的土壤呼吸速率与5 cm土壤温度之间均呈显著指数相关(P=0.000),与5 cm土壤湿度之间呈二次曲线相关(P=0.012).根系是影响土壤CO2通量的一个重要因子.【期刊名称】《中南林业科技大学学报》【年(卷),期】2012(032)005【总页数】5页(P120-124)【关键词】土壤呼吸;樟树人工林;土壤温度;土壤湿度【作者】刘智;闫文德;王光军;郑威;梁小翠;宿少锋【作者单位】中南林业科技大学生命科学与技术学院,湖南长沙410004;中南林业科技大学生命科学与技术学院,湖南长沙410004;中南林业科技大学生命科学与技术学院,湖南长沙410004;中南林业科技大学生命科学与技术学院,湖南长沙410004;中南林业科技大学生命科学与技术学院,湖南长沙410004;中南林业科技大学生命科学与技术学院,湖南长沙410004【正文语种】中文【中图分类】S792.23;S718.51+6全球变暖对自然生态和人类生存环境已经产生并将继续产生显著影响,对可持续发展构成严重威胁。

描述气候英语作文

描述气候英语作文

Climate is a crucial aspect of our environment that plays a significant role in shaping the world we live in.It is the longterm average of weather conditions in a particular region,including temperature,humidity,precipitation,and wind patterns.Understanding climate is essential for various reasons,such as agriculture,water management,and planning for natural disasters.Temperature is a fundamental component of climate.It varies across different regions and seasons.For instance,equatorial regions typically experience high temperatures yearround,while polar regions have consistently low temperatures.The temperate zones, on the other hand,have more moderate temperatures with distinct seasonal variations.Humidity is another important factor that influences climate.It refers to the amount of water vapor in the air.High humidity can make the air feel warmer than it actually is, while low humidity can make it feel cooler.Humidity levels are often higher in tropical regions and lower in arid regions.Precipitation is the process by which water falls from the atmosphere in the form of rain, snow,sleet,or hail.The amount and type of precipitation vary greatly across different climates.Some areas receive abundant rainfall throughout the year,while others may experience long periods of drought.Wind patterns are also a key element of climate.They are influenced by global atmospheric circulation and can have a significant impact on weather conditions.For example,trade winds in the tropics are steady and generally warm,while polar winds can be cold and strong.Seasonal variations are a hallmark of many climates.In temperate regions,there are four distinct seasons:spring,summer,autumn,and winter.Each season brings its own set of weather conditions,such as warm temperatures and longer days in summer,and cold temperatures with shorter days in winter.Climate change is a pressing issue that affects global climate patterns.It is primarily caused by human activities that increase greenhouse gas concentrations in the atmosphere, leading to a rise in global temperatures.This can result in more extreme weather events, such as heatwaves,storms,and floods,and can have profound effects on ecosystems and human societies.Adaptation and mitigation are two strategies that are being employed to address climate change.Adaptation involves adjusting to the effects of climate change,such as building flood defenses or developing droughtresistant crops.Mitigation,on the other hand,focuses on reducing greenhouse gas emissions to slow the rate of climate change.In conclusion,climate is a multifaceted phenomenon that influences every aspect of life on Earth.Understanding its patterns and changes is essential for the sustainable management of our environment and for ensuring the wellbeing of current and future generations.。

海州湾方氏云鳚体长与体重分布特征及其关系

海州湾方氏云鳚体长与体重分布特征及其关系

海州湾方氏云鳚体长与体重分布特征及其关系栾静;徐宾铎;薛莹;任一平;张崇良【摘要】体长、体重是鱼类种群的基本生物学特征,能够反映鱼类个体生理状态以及所处环境条件的变化,但在实际研究中其时空变化往往被忽略.本文根据2011—2016年春、秋季海州湾8个航次的渔业资源底拖网调查数据,研究了方氏云鳚(Pholis fangi)的体长组成、体重组成,体长–体重关系和肥满度特征,并分析了上述指标的时空异质性.结果表明,海州湾方氏云鳚的群体有多个年龄组,体长、体重和体长–体重关系参数a、b及肥满度在时空上均有较大波动,且在年间差异显著.秋季各航次平均体长、体重呈现逐年增大趋势;肥满度的季节差异要大于年间差异,春季肥满度小于秋季;体长和肥满度在海州湾分布均是西南部大于东北部,但秋季肥满度分布则与此相反.调查的方氏云鳚群体基本符合正异速生长类型.体长体重特征的时空异质性可能与气候、摄食强度、性成熟比例与捕捞压力等有关,并在一定程度上反映了渔业生态系统和栖息地特征.相关研究应充分考虑体长、体重关系参数的时空变化,以为渔业资源评估提供精确参数.%Body size is a basic biological characteristic in fish populations and can reflect individual physiology as well as changing environment conditions. Slight variabilities in some biological parameters may result in complex ecological effects, and affect food web link intensity in trophic cascades. However, the spatial and temporal het-erogeneity of size composition within populations have often been ignored in many studies of fish biology. We use Fang's gunnel (Pholis fangi) in Haizhou Bay as an example for studying the variability of body size on an annual scale. P. fangi is a low trophic fish and plays an important role in the food web and ecosystem of the Yellow Sea, withincreasing dominance in Haizhou Bay. We collected annual bottom trawl surveys in Haizhou Bay in the spring and fall from 2011 to 2016. We used a range of statistical methods, included variable coefficient, covariance analysis, two-sample t-test, and Pearson correlation analysis to study the population size composition, length-weight relationship, and relative fatness of P. fangi in this area. We analyzed the annual and seasonal vari-ability as well as the spatial distribution of body length and relative body mass. The results showed that P. fangi had multiple age structure in Haizhou Bay. Their length frequency distributions were multi-modal and skewed, with the majority of captured individuals aged 2-3 years. Statistical analysis indicated that there were remarkable temporal and spatial variations in the average size and the parameters of body length-weight relationship of P. fangi, with significant differences across years (P<0.05). The average body length and relative fatness tended to be higher during autumn surveys than spring surveys. Variation in relative fatness was greater between seasons than among years. In spring, the spatial distribution of body length and relative fatness was larger in the southwest area than the northeast area of the bay. A t-test on the body length-weight relationship showed that the allometric growth patterns of P. fangi were generally positive. Correlation analyses between benthic water temperature and the length-weight relationship showed that temperature had a substantial influence on the relative fatness, body length-weight relationship, and mean body length. The spatiotemporal variability of fish size and other parameters may be attributed to their feeding intensity,maturation, fishing pressure, and environmental and habit variation, and is also likely to reflect changes in the fishery ecosystem. We suggest that the spatiotemporal variability of population size composition should be fully considered in fisheries resource management, as these basic parame-ters can contribute significantly to fishery ecosystem modelling and management strategy evaluation.【期刊名称】《中国水产科学》【年(卷),期】2017(024)006【总页数】9页(P1323-1331)【关键词】方氏云鳚;体长分布;体重分布;体长–体重关系;肥满度;时空异质性【作者】栾静;徐宾铎;薛莹;任一平;张崇良【作者单位】中国海洋大学水产学院, 山东青岛 266003;中国海洋大学水产学院, 山东青岛 266003;中国海洋大学水产学院, 山东青岛 266003;中国海洋大学水产学院, 山东青岛 266003;青岛海洋科学与技术国家实验室海洋渔业科学与食物产出过程功能实验室, 山东青岛 266003;中国海洋大学水产学院, 山东青岛 266003【正文语种】中文【中图分类】S93海州湾是位于黄海中部的沿岸开放型海湾,海域初级生产力较高, 是很多鱼类和无脊椎动物的产卵场和索饵场[1–2]。

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Seasonal and spatial distribution of nonylphenol in Lanzhou Reachof Yellow River in ChinaJian Xu,Ping Wang,Weifeng Guo,Junxing Dong,Lei Wang,Shugui Dai*College of Environmental Science and Engineering,Nankai University,94Weijin Road,Nankai District,Tianjin 300071,PR ChinaReceived 7June 2005;received in revised form 13April 2006;accepted 13April 2006Available online 9June 2006AbstractNonylphenol (NP)is known as an endocrine disruptor and consequently has drawn much environmental concern.This study focused on seasonal variation and spatial distribution of NP in various matrices including water,suspended particles,and sediment taken from Lanzhou Reach of Yellow River in China.NP was measured in July and November in 2004.Concentrations of NP in water ranged from 34.2to 599.0ng/l,in suspended particles from 49.6to 2835.2ng/g dry wt,and in sediment from 38.4to 863.0ng/g dry wt.In terms of most water and suspended particles samples,concentrations were higher in warmer seasons than in colder seasons.Good linear corre-lations (R 2=0.90in July,R 2=0.97in November)were obtained for NP concentrations between water and suspended particles.In terms of sediment samples,concentrations were higher in November than in July,probably due to greater deposition of suspended particles.Reasonable linear correlations (R 2=0.60in July,R 2=0.79in November)were obtained for NP concentrations between water and sediment.Ó2006Elsevier Ltd.All rights reserved.Keywords:Alkylphenols;Nonylphenol;Endocrine disruptors;Yellow River;Distribution1.IntroductionAlkylphenol polyethoxylates (APEs)are one of the most widely used classes of surfactants.They have been used as additives in industrial detergents,pesticides,herbicides,paints,and cosmetics (Ahel et al.,1994).Although APEs are less toxic to human and organisms,the degradation metabolites,such as nonylphenol and octylphenol,are more toxic than the parent substances and possess the abil-ity to mimic natural hormones by interacting with the estrogen receptor (Ying et al.,2002).Due to persistence in the environment,nonylphenol is bioconcentrated in organisms.High levels of nonylphenol have been found in some seafood and fish caught in Italian coast and Japa-nese rivers,respectively (Ferrara et al.,2001;Tsuda et al.,2001).And even at low concentrations,nonylphenol has adverse effect on fish hormone system (Yadetie and Male,2002).Numerous estrogenic experimental results indicate that alkylphenols especially nonylphenols could cause neg-ative health effects in both humans and wildlife through disruption of the endocrine systems (Harries et al.,1997;Ying et al.,2002).So most countries have banned the usage of alkylphenol ethoxylates surfactants,and the production of them is decreasing gradually (Renner,1997;Isobe et al.,2001).In China,production of nonylphenol polyethoxy-lates (NPnEO)is about 50000tons per year,and most of them enter into the aquatic environment.High concentra-tions of nonylphenol were found in several rivers,in tap water,and in aquatic organisms.For example,Shao et al.(2002)reported that nonylphenol concentrations ran-ged from 0.02to 6.85l g/l in the aquatic environment in Chongqing Valley of Yangtze River and Jialing River in China,and after treatment in waterworks,nonylphenol concentrations in tap water was in a range from under detected limit to 2.73l g/l.Jin et al.(2004a)found that mean concentrations of nonylphenol polyethoxylates in muscle of Carassius auratus from Tianjin section of the0045-6535/$-see front matter Ó2006Elsevier Ltd.All rights reserved.doi:10.1016/j.chemosphere.2006.04.042*Corresponding author.Tel./fax:+862223504821.E-mail address:sgdai@ (S.Dai)./locate/chemosphereChemosphere 65(2006)1445–1451waste water discharge river of Beijing ranged from40to 680ng/g wet weight,and nonylphenol ranged from30to 1510ng/g wet weight.The nonylphenol pollution is draw-ing much more attention in China.Yellow River,which is called Mother River of China,is the second largest river in China and one of the largest rivers in the world.Itflows across9provinces in north China,from west to east,with mainstream5464km long, drainage area795thousand km2,and average sand content 2.83kg/m3.It is the very important water resource for industry,agriculture and people’s living.But with the growth of economy and urbanization,more and more wastes are discharged into the river,and types and amounts of pollutants increase as well.The Lanzhou Reach belongs to upper reaches of Yellow River.Dense wastes discharge along the river in Lanzhou Reach makes the pollution very serious,which will affect the water use in downstream reaches.Among those pollutants,nonylphenol has been getting increasing attention.In order to evaluate the contamination levels of nonyl-phenols in various sample matrices from Lanzhou Reach of Yellow River,and understand their distribution and behavioral characteristics,nonylphenol was determined from water,suspended particle and sediment samples in different seasons in this study.The information obtained should be helpful for pollution control and remediating the river environment.2.Materials and methods2.1.Instruments and chemicalsA Waters1525HPLC,Waters2475fluorescence detec-tor,and Waters Amino column(l Bondapak 3.9mm i.d.·300mm·5l m)were employed in the study.Waters Oasis TM HLB cartridges were used as solid phase extraction materials.Nonylphenol(technical grade)was purchased from Tokyo Chemical Synthesis Ind.Co.Ltd.,Japan. Methanol and hexane were HPLC grade,and dichloro-methane was analytical grade.Florisil was activated at 130°C for16h before use.Ultrapure water was obtained using a Millipore Ultra-pure Water System(USA).2.2.Sampling sites and sample collectionTwelve sampling sites were selected along the river in Lanzhou Reach,as shown in Fig.1.Among them,site R1was located in upstream,where there were no indus-tries.From site R2to R9,there were many industrial and municipal wastes discharging points along the river.R12 was the endpoint of our study,which was about20km away from R9,representing NP concentrations after a per-iod of self-purification in river water.Water,suspended particle and sediment samples were collected in July and November2004,respectively.Some properties ofriverFig.1.Sampling sites of the Lanzhou Reach of Yellow River.1446J.Xu et al./Chemosphere65(2006)1445–1451water in July and November are listed in Table1.One liter offiltered water sample(0.45l m)was collected in1l glass bottle with Teflon lined cap.It was added with1%of form-aldehyde and stored at4°C until pretreatment.Thefiltered suspended particles were wrapped with aluminum foil and stored in a glass bottle atÀ20°C until analyzed.The sur-face sediment(0–20cm)samples were collected in glass bottles with Teflon lined caps and stored at about À20°C until analysis.2.3.Extraction and analysisWater samples were extracted with a solid phase extrac-tion(SPE)method.One liter of water sample was passed through a SPE cartridge at aflow rate of10ml/min,which was pre-conditioned with1ml distilled water and1ml methanol.The cartridge was rinsed with2ml of metha-nol/water(5:95,v/v),and then eluted with5ml of dichlo-romethane.The effluent was rotary evaporated to nearly dryness,then redissolved in1ml of n-hexane for HPLC analysis.Suspended particle and sediment samples were Soxhlet-extracted with dichloromethane for24h.The obtained extract was concentrated to1ml under a gentle N2stream,and purified by passing through a25·1.0cm i.d.glass clean-up column containing5g of hexane-rinsed Florisil and1g of anhydrous sodium sulfate.The column was washed with50ml of hexane,eluted with80ml of ethyl ether and hexane(1:9)for NP.The eluate was rotary-vacuum evaporated nearly to dryness at40°C, transferred to a graduated tube(rinsing theflask with methanol)and adjusted to1.0ml under a stream of nitro-gen,then analyzed by HPLC.Total organic carbon(TOC) contents of sediments were measured by oxidation method (Institute of Soil Science,1978).Mixtures of n-hexane/isopropanol(98/2,v/v)and iso-propanol/water(98/2,v/v),named solvents A and B, respectively,were used as mobile phase for HPLC analysis. Gradient elution was carried out with a linear program from95%A and5%B to80%A and20%B in10min with aflow rate of1.0ml/min.Excitation and emission wave-lengths of thefluorescence detector were233and302nm, respectively.Injection volume was20l l.2.4.Quality assurance and method validationThe instruments were calibrated daily with calibration standards,and the relative percent difference between the five-point calibration and the daily calibrations were <20%for the analyte.Recovery tests were performed by adding0.5ml of the standard solution(10l g/ml)to 1000ml deionized water and5g of sediment(blank con-trol,with NP level below detection limits),respectively. Experiments were performed6times to determine the pre-cision.The recoveries by the proposed method were81.3–85.8%for water sample,and86.6–89.4%for sediment and suspended particle samples.Good reproducibility of determination was obtained with RSD values of 3.8–9.2%.The method detection limits,10ng/g for NP,were evaluated by a signal-to-noise of3.Fig.2gives HPLC chromatograms of standard NP(1l g/ml)and recovered NP from Yellow River’sediment.3.Results and discussion3.1.Spatial distribution of nonylphenolIn July2004,sediment samples were collected in Yellow River,Lanzhou Reach,from upstream to downstream as indicated in Fig.1.The results are shown in Fig.3.NP con-centrations of the riverine sediment samples ranged from 38.4to86.3ng/g dry wt.Levels of nonlyphenol in down-stream sediment samples(R5–R12)were higher than in upstream sediment samples(R1–R4).Two high concentra-tions appeared at site R5and R7.This is correlated with characteristics of wastewater discharged from pollution sources along the river.Yellow Riverflows through Lanz-hou city.The section from site R1to R4is upstream of the city.Site R5is located in the center of the city,and the sec-tion from R6to R12is downstream of Lanzhou city. Although site R1is the start point of our study,without any industrial pollution sources here,NP levels were quite high.This may be due to the pollution contribution from an upstream branch river,Huangshui River in Qinghai Province,which is seriously polluted by domestic activities. From site R2to R4,there are some industrial and munici-pal pollution sources discharging wastewater into the river. At site R5there is a big wastewater discharge stream con-sisting of municipal and industrial wastewater.The waste-water discharge pipeline from Lanzhou oil refinery located at site R7is the biggest discharge stream in Lanzhou city. High concentrations in downstream sediments might be due to discharge of effluents containing large amount of sewage and industrial wastewater from Lanzhou city.The correlation between TOC and NP concentrations is very useful to understand the spatial distribution of NP in rivers.TOC data of sediments were determined for sediments samples in July and November respectively.Fig.4shows the relationship between TOC values and NP concentrations in sediments along the river,and good correlations for July (R2=0.59)and November(R2=0.63)are observed.From Fig.3it could be seen that concentration of NP at site R12did not decrease.After about a20km long dis-tance transport from site R11to R12,its concentration had a little increase in sediment,from54.8to58.4ng/g dry wt,suggesting that NP was quite stable in river waterTable1Some properties of river water in2004Average water temperature,°C Averagesuspendedparticlecontent,g/lpH AverageDO,mg/lAverageflux,m3/sJuly190.4538.65 6.30877November100.2918.408.681120J.Xu et al./Chemosphere65(2006)1445–14511447environment.In aquatic environment,nonylphenol polyethoxylates are rapidly degraded to nonylphenol by biodegradation and photodegradation mechanism,with half-lives from 3to 5days,while half-life of NP was about 2to 3months (Ying et al.,2002;Li and Li,2003).NP could be transported a long way by river flow.3.2.Seasonal distribution and relationship of nonylphenol in water systemConcentrations of NP in the sample matrices are listed in Table 2.Concentration levels of NP in water decreased with decreasing water temperature.Li et al.(2004a)reported the similar trend in Han River in Korea,suggest-ing the activity of microorganism in the riverine system might play a role in the levels of NP.Alkylphenol polyeth-oxylates have rapidly degraded into NP and shortened alkylphenol ethoxylates at high temperature,while the deg-radation rate becomes very slow at low temperature (Tan-ghe et al.,1998;Staples et al.,1999).NP concentrations in July ranged from 34.2to 599ng/l,and in November ranged from 41.5to 376.3ng/l in water.NP is a hydrophobic compound,with log K ow value of 4.48(Ying et al.,2002).It is readily adsorbed onsurfacesFig.2.HPLC chromatograms of the standard and recovered NP from Yellow River sediment.1448J.Xu et al./Chemosphere 65(2006)1445–1451of suspended particles and sediment in water environments.Table 2shows concentrations of NP in suspended particles ranged from 50.1to 2467.8ng/g dry wt in July,and from 49.6to 2835.2ng/g dry wt in November.In sediment NPconcentrations ranged from 41.3to 86.3ng/g dry wt in July,and from 38.9to 863.0ng/g dry wt in November.In general,NP concentrations in most suspended particles samples were higher in warmer season than in colder sea-son,while in terms of sediment samples,concentrations were higher in November than in July.This may be due to the average suspended particle contents in Lanzhou Reach of Yellow River.The average particle contents were 0.453g/l in July and 0.291g/l in November,respectively (Table 1).Deposition of suspended particles in the river may cause the increasing concentration in sediment.The difference of NP concentrations in July and November can also be seen from a simple numerical ratio of concen-trations by station locations for each of the sample ing data in Table 2we calculated ratios for the concen-trations of nonylphenol in July divided by November sep-arately for each matrix and sampling site.It turned out that 9of 12water ratios were >1and 9of 12values for sus-pended particles were >1,while only 1of 12is >1for sediment.Spatial variations of the concentration of NP in three sample matrices were similar.All sites had similar concen-tration ratios of NP between the sediment or suspended particle and water.Such similarities are shown in termsTable 2Concentrations of NP in water,suspended particles and sediment from Yellow River,Lanzhou Reach in 2004SiteWater (ng/l)Suspended particles (ng/g dry wt)Sediment (ng/g dry wt)JulyNovember July November July November R165.417381.4899.342.973.5R291.248.6121.3303.550.4191.5R379.356.389.369.344.569.9R473.441.550.149.641.338.9R5279.3113.41374.1519.386.3103.6R6108.386.2298.6192.053.264.4R7599.0376.32467.82835.283.1863.0R876.976.6378.4168.042.561.2R975.256.2335.6175.762.3186.0R1071.347.8636.4224.154.054.6R1175.479.5702.0235.354.871.2R1234.261.976.180.958.482.4All NP data were conducted on triplicate samples,with standard deviation within 5%.J.Xu et al./Chemosphere 65(2006)1445–14511449of the correlation(R2)of the NP concentrations between sediment or suspended particles and water samples in Fig.5.The values of R2for suspended particles to water were0.90and0.97in July and November,respectively. R2for sediment to water were0.60and0.79in July and November,respectively.parison with other places in the worldBesides Shao et al.(2002)reported the NP concentra-tions in the aquatic environment in Chongqing Valley ofYangtze River and Jialing River,research has been done in China(Jin et al.,2004b).Lanzhou Reach of Yellow River was moderately polluted by NP compared with pollution levels of NP in other areas of the world.Tables 3and4give the concentrations of NP in surface waters and in sediments in some countries and areas,as reviewed by Ying et al.(2002).4.ConclusionIn the three sample matrices of water,suspended parti-cles and sediment,NP levels showed seasonal and spatial variation.Temperature was the key factor affecting the sea-sonal variation of NP in water and suspended particles. The distribution and characteristics of pollution sources along the river affected the spatial variation of NP in Yellow River,Lanzhou Reach.Strong correlations bet-ween NP concentrations in water and suspended particles or sediment were observed.Although measured concentrations of NP in water,sus-pended particles and sediment are not high,some individ-ual values may exceed reported toxic levels.For example, the lowest effective concentration of NP in shrimp for sub-acute toxicity is26ng/g dry wt in sediment(Li et al.,2004). Levels of NP in suspended particle and in sediment might be potentially hazardous to organisms in the river.Because Yellow River has a characteristic of high sand content,fur-ther study should be made to investigate the environmental behavior and impact of suspended particles in the river.Table3Concentration of NP in surface watersLocation NP concentration(l g/l) Canada<LODÀ0.92UK<0.03–53Switzerland<LODÀ0.48Spain<LODÀ644Japan<LODÀ3.0USA<0.11–0.64Germany0.0067–0.134Taiwan 1.8–10Korea a0.017–1.533China(Yellow River)0.034–0.599a Li et al.,2004b.Table4Concentration of NP in sedimentsLocation NP concentration(l g/kg) UK<0.1–15USA<2.9–2960Canada0.1–72Japan30–13000Korea a10.4–5054.1China(Yellow River)38.4–863.0a Li et al.,2004b.1450J.Xu et al./Chemosphere65(2006)1445–1451AcknowledgementThis study is jointly funded by‘National Science Foun-dation of China–Yellow River Conservancy Commission’with Grant No.50239060.ReferencesAhel,M.,Giger,W.,Koch,M.,1994.Behavior of alkylphenol polyeth-oxylate surfactants in the aquatic environment.1.Occurrence and transformation in sewage treatment.Water Res.28,1131–1142. 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