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团头鲂池塘养殖生态系统晒塘阶段温室气体排放通量分析

2016-03-21刘兴国杨家朋王小冬顾兆俊程果锋中国水产科学研究院渔业机械仪器研究所农业部渔业装备与工程技术重点试验室上海200092

农业工程学报 2016年3期
关键词:温室气体团头鲂温室效应

朱 林,车 轩,刘 晃,刘兴国,时 旭,杨家朋,王小冬,顾兆俊,程果锋,朱 浩(中国水产科学研究院渔业机械仪器研究所,农业部渔业装备与工程技术重点试验室,上海 200092)



团头鲂池塘养殖生态系统晒塘阶段温室气体排放通量分析

朱林,车轩※,刘晃,刘兴国,时旭,杨家朋,王小冬,顾兆俊,程果锋,朱浩
(中国水产科学研究院渔业机械仪器研究所,农业部渔业装备与工程技术重点试验室,上海 200092)

摘要:为探讨团头鲂池塘养殖生态系统晒塘阶段温室气体的排放规律及综合增温潜势,采用静态暗箱——气相色谱法对团头鲂池塘养殖生态系统晒塘阶段温室气体(CO2,CH4,N2O)的排放进行原位测定。结果显示,团头鲂池塘养殖生态系统晒塘阶段均表现为CO2,CH4和N2O的排放源,其中CO2排放通量达(86.72±12.46) g/m2,CH4排放量达(2.01±0.34) g/m2,N2O排放量达(7.44±0.98) mg/m2;在100 a的时间尺度上,团头鲂池塘养殖生态系统在晒塘阶段综合增温潜势为(157.28±24.31) g/m2,团头鲂池塘养殖生态系统温室气体减排空间较大。

关键词:温室气体;排放控制;池塘;水产;温室效应;团头鲂;晒塘

朱林,车轩,刘晃,刘兴国,时旭,杨家朋,王小冬,顾兆俊,程果锋,朱浩. 团头鲂池塘养殖生态系统晒塘阶段温室气体排放通量分析[J]. 农业工程学报,2016,32(3):210-215.doi:10.11975/j.issn.1002-6819.2016.03.030 http://www.tcsae.org

Zhu Lin, Che Xuan, Liu Huang, Liu Xingguo, Shi Xu, Yang Jiapeng, Wang Xiaodong , Gu Zhaojun, Cheng Guofeng, Zhu Hao. Greenhouse gas emissions of Megalobrama amblycephala culture pond ecosystems during sun drying of pond[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2016, 32(3): 210-215. (in Chinese with English abstract)doi:10.11975/j.issn.1002-6819.2016.03.030http://www.tcsae.org

0 引 言

目前,臭氧层破坏和全球变暖等环境问题是由温室气体过量排放引起的。其中,CO2、CH4和N2O是最主要的温室气体,它们对温室效应的贡献分别为55%,22% 和5%[1-2]。大气中CO2,CH4和N2O的体积分数正分别以每年0.14%,0.16%和0.125%的速度增长。

一般来说,鱼或虾养殖的饲料吸收利用率不足30%[3-4]。在饲料系数1~2的情况下,约80%的被摄食饲料以液态、固态或气态形式排入环境[5-6]。中国的水产养殖产量长期以来稳居世界第一,占世界水产养殖产量的70%,是全球水产养殖的主体[7]。淡水池塘养殖是中国现阶段的主要生产模式,其产量占中国水产养殖总量的41.5%[7-8]。2012年中国团头鲂(Megalobrama amblycephala)产量70.58万t,占全国淡水养殖总产量的2.7%[9],如果按饲料系数2,饲料有机碳质量分数34%,氮质量分数6%,饲料C损失率80%,N损失率76%计算,中国团头鲂养殖池塘每年有机碳累积量达41.16万t,氮累积量达6.9万t[10]。

全球生态系统温室气体研究始于20世纪70年代,目前有大量科学家围绕该问题开展研究,这些研究主要集中在湿地、农业和水库等方面[11-14]。水产养殖生产是典型的农业生产活动,减少农业源温室气体排放对控制全球气候变化有重要作用[15]。本试验选择大宗淡水鱼池塘生态系统,在团头鲂池塘养殖生态系统晒塘阶段对3种温室气体排放通量进行监测和分析,以期为估算淡水养殖生态系统温室效应,寻求相应减排措施提供数据支撑。

1 材料与方法

1.1试验设计

2014年12月-2015年2月,试验于中国水产科学研究院池塘生态工程研究中心大宗淡水鱼养殖试验池塘进行,该池塘面积50 m×100 m,水深1.5 m,塘龄8 a,底泥厚度60 cm,采取普遍使用的“主养团头鲂、套养鲢、鳙”的养殖模式,放养规格团头鲂鱼种1593尾/667m2;套养鲢、鳙鱼种分别为80尾/667m2和20尾/667m2。养殖全程投喂淡水鱼人工配合饲料,根据气温及鱼吃食情况按鱼质量的3%~5%投喂,待12月底团头鲂全部收获之后开始晒塘。本试验从2014年12月28日至2015年1月13日,每隔15 d采一次样,计45 d。

1.2温室气体样本采集及测试方法

采用常用的静态箱法采集气样,箱体由玻璃钢材料制成,规格50 cm×50 cm×50 cm,顶部运行小风扇混合箱内气体。一个采样点重复采样3次,于采样箱关闭的0、10、20、30 min开始采样,每次采样100 mL。气体储存于0.2 L铝箔气袋中,24 h内用美国安捷伦公司生产的Agilent 6890气相色谱仪同时分析 CO2、CH4、N2O的排放通量。

1.3指标测定

底泥采样点与气样采集点为同一位置,其采样位置如图1所示,图中长方形为试验池塘,我们在圆点所示位置采集样品,其相对位置如图中标尺所示,对每个采样点用带刻度的空心PVC管(外径5 cm、内径4.8 cm)进行取样,在土层深度10 cm处取样,经计算共计72个土样;气温用水银温度计测定;泥温、氢离子浓度指数及氧化还原电位ORP(oxidation-reduction potential)用手持YSI进行在线测定;底泥含水率采用经典烘干法(105~110℃,10 h)测定;总有机碳TOC(total organic carbon)采用德国耶拿分析仪器公司的multi.N/C2100型总有机碳分析仪测定。

图1 试验池塘采样点分布示意图Fig.1 Schematic diagram of sampling point in experimental pond

1.4总温室气体排放量的计算

全球增温潜势(global warming potential,GWP)作为一种简单的基于辐射特性的相对指标,其常被用来估计不同温室气体对气候系统的潜在效应。在综合增温潜势估算中,CO2看作参考气体,CH4和N2O排放量的增减通过GWP系数转换成CO2等效量。以100 a影响尺度为计,CH4的GWP系数是34,N2O的GWP系数是298[16]。本文池塘养殖生态系统总温室气体排放量为T(g/m2,以CO2计),计算如下

式中fCO2为试验期间CO2的排放量,g/m2;fCH4为试验期间CH4的排放量,g/m2;fN2 O为试验期间N2O排放量,mg/m2。

1.5数据分析

采用Microsoft Excel2013软件对试验数据进行处理和制图,SPSS19.0软件进行统计分析,以测试数据的平均值±标准差(mean±SD)表示。

2 试验结果

2.1团头鲂池塘养殖生态系统晒塘阶段底泥理化性状

试验期间团头鲂池塘养殖生态系统晒塘阶段底泥理化数据如图2所示,1月13号的氢离子浓度指数最高,达到(8.26±0.35),12月28号、1月28号及2月13号的氢离子浓度指数分别为(7.73±0.26)、(7.75±0.37)及(7.68±0.48);TOC(底泥总有机碳)总体表现出随晒塘的进行而逐渐减少的趋势,其中12月28号最高,达(3.61±0.43) mg/L,其他3 d TOC分别为(3.32±0.17)、(3.16±0.31)、(3.23±0.27) mg/L;1月13号ORP(氧化还原电位)最高,达(216.8±27.6) mV,余下3次监测数据为(206.7±34.9)、(56.8±9.3) 及(124.8±16.5) mV;由于晒塘阶段时有雨天,池塘底泥含水率并没有一直降低,试验4 d底泥含水率分别为(55.25%±2.54%)、(54.53%±5.61%)、(46.62%±4.38%)、(48.35%±3.14%);晒塘阶段的气温较低,分别为(8.9±0.2)、(7.2±0.1)、(5.8 ±0.1)及(6.0±0.1)℃;底泥温度稍高,4 d的数据分别为(11.6±0.4)、(10.5±0.3)、(9.8±0.2)及(9.9±0.4) ℃。

图2 团头鲂池塘养殖生态系统晒塘阶段底泥理化性状Fig.2 Physical and chemical properties of bottom sediment of Megalobrama amblycephala culture pond ecosystems during sun drying of pond

2.2团头鲂池塘养殖生态系统晒塘阶段3种温室气体排放通量

团头鲂池塘养殖生态系统晒塘阶段3种温室气体排放通量如图3所示,从图3a中可以看出,CO2排放通量呈现随晒塘日期增加而逐步递减的趋势,峰值在晒塘第1 天2014年12月28号,达到(2652.46±325.36) mg/(m2·d),排放通量最低为晒塘结束日2015年2月13号,(1373.27±167.39) mg/(m2·d)。CH4是甲烷菌通过有机碳源转化而来,影响底泥CH4排放的主要因素有土壤温度和氧化还原电位(ORP)。从图3b中可以看出,CH4排放通量表现出于CO2排放通量相类似的变化趋势,CH4排放通量的峰值依然出现在晒塘首日,达到(82.42±6.32)mg/(m2·d),2月13号排放通量最低,为(7.06±2.93) mg/(m2·d)。团头鲂池塘养殖生态系统N2O产生和排放主要来源于微生物的硝化和反硝化过程,从图3c中可以看出,晒塘阶段N2O排放规律没有CO2及CH4明显,1月13号,团头鲂池塘养殖生态系统N2O排放通量最高,达到(204.57±16.84) μg/(m2·d),排放通量最低为2月13号,(90.39±10.67) μg/(m2·d)。

图3 团头鲂池塘养殖生态系统晒塘阶段3种温室气体排放通量Fig.3 Greenhouse gas emissions of Megalobrama amblycephala culture pond ecosystems during sun drying of pond

2.3团头鲂池塘养殖生态系统晒塘阶段温室气体总排放量

团头鲂池塘养殖生态系统晒塘阶段温室气体总排放量如表1所示,其中CO2排放量达(86.72±12.46) g/m2,CH4排放量达(2.01±0.34) g/m2,N2O排放量达(7.44±0.98) mg/m2,在100 a的时间尺度上,团头鲂池塘养殖生态系统在晒塘阶段表现出增加温室气体综合作用为(157.28±24.31) g/m2。本研究中团头鲂池塘生态系统晒塘阶段温室气体排放通量可观,减排空间较大。

表1 团头鲂池塘养殖生态系统晒塘阶段温室气体总排放量Table 1 Emissions of greenhouse gas combined action of Megalobrama amblycephala culture pond ecosystems during sun drying of pond

3 讨 论

好氧细菌在有氧环境下分解有机物产生二氧化碳[17]。水分、肥料效应、土壤有机碳水平和土壤温度是影响CO2排放的主要因素。土壤有机质与土壤呼吸速率之间存在极显著的相关关系,两者的相关系数为0.927[17]。土壤有机碳总量、活性有机碳与土壤呼吸都呈极显著正相关[18]。单施氮肥对土壤呼吸影响不大,而氮磷配施,尤其是高氮高磷配施能显著增加土壤呼吸量[16]。土壤呼吸与气温、土壤温度之间存在显著的相关关系,而土壤呼吸与土壤含水量之间相关性较差或无相关关系[18]。本试验中,整个晒塘阶段池塘生态系统表现为CO2排放源,晒塘第1 天2014年12月28号,气温、底泥温度、底泥含水率及底泥总有机碳水平在4次监测数据中均为最高,为好氧细菌及浮游生物提供了相对其他3组更加良好的呼吸环境,CO2排放通量达到晒塘试验阶段峰值(2652.46±325.36) mg/(m2·d);而随着晒塘的进行,气温及底泥温度降低,池塘水分逐渐减少,底泥含水率降低,底泥总有机碳水平也随之降低,CO2排放通量呈现出降低的趋势,至晒塘结束日2015年2月13号CO2排放通量最低为(1373.27±167.39) mg/(m2·d),整个晒塘阶段日均排放通量为(1948.99±632.99) mg/(m2·d)。目前,中国国内冬季农田CO2排放通量的研究主要集中在华北平原[19-23],分布范围在1 800~5 760 mg/(m2·d),略高于团头鲂养殖生态系统晒塘阶段CO2排放通量;中国湿地CO2排放通量的研究结果很多,汪青等[24]等对同属于上海的崇明东滩湿地温室气体的研究得出冬季CO2平均排放通量为3 465.84 mg/(m2·d),王蒙等[25]对冬季杭州湾滨海湿地的CO2排放通量监测结果为5 880 mg/(m2·d),对比可知,团头鲂养殖生态系统晒塘阶段CO2排放通量显著低于冬季上海附近湿地。

对水库的研究表明,缺氧环境下,甲烷菌的活动占优势,分解库底大量沉积的有机物,主要产生甲烷,及少量二氧化碳。此外,还会形成生物惰性残余,腐殖酸和黄酸[26-27]。产甲烷细菌通过2种方式制造甲烷:一种是将CO2转化成甲烷;另一种是以甲基分子(主要是乙酸)为底物进行反应[28-29]。Mirzoyan等[30]对水产养殖的底泥性质进行了研究,结果发现溶氧<1 mg/L,存在与水库沉积物相似的厌氧条件,是产生CH4的有利环境。影响CH4排放的主要因素有土壤温度和氧化还原电位和水深。从定性的角度说,一天之内土壤温度和ORP变化对稻田CH4排放通量日变化具有极显著的影响[31]。本试验中,整个晒塘阶段池塘生态系统表现为CH4排放源,晒塘开始时,气温、底泥温度虽低于产甲烷微生物的最适温度,但气温及底泥温度呈下降趋势成为了影响试验阶段CH4排放变化规律的关键因素;此时产甲烷微生物在4组当中活性最强,因此CH4排放通量达到晒塘试验阶段峰值(82.42±6.32) mg/(m2·d);而晒塘阶段CH4排放通量后两组呈现出降幅较大的现象可能是气温、底泥温度变化及ORP不稳定变化共同作用的结果,整个晒塘阶段日均排放通量为(44.54±22.96) mg/(m2·d)。中国国内冬季农田CH4排放通量分布范围在3.84~128.8 mg/(m2·d)[22,31],与团头鲂养殖生态系统晒塘阶段CH4排放通量相当;上海附近湿地冬季CH4平均排放通量为10.33 mg/(m2·d)[24],显著低于团头鲂养殖生态系统晒塘阶段CH4排放通量。

生态系统中N2O产生的主要过程是硝化和反硝化过程。硝化菌反硝化作用、硝酸盐同化还原成铵及硝酸盐异化还原成铵过程中也产生N2O[32],但产生量较小。影响N2O排放的主要因素有土壤含水量、土壤温度及C/N(碳氮比)。研究表明,在土壤湿度为90%~100%的田间持水量时,N2O排放量最大[33]。在适宜的土壤水分条件下和一定温度范围内,N2O排放随土壤温度的上升而增加[34]。在−2~5℃范围内反硝化量的平方根与温度呈直线关系[35]。N2O排放随C/N的上升而增加,C/N=20条件下的N2O排放量是C/N=5或10条件下N2O排放量的10倍[36]。根据科研人员对水产养殖的底泥性质的研究结果,养殖底泥的C/N=29.3~42.4,底泥的这种特性将极大的促进N2O排放[21],整个晒塘阶段N2O日均排放通量为(156.89±48.17) μg/(m2·d)。中国长江中下游冬季农田N2O排放通量分布范围在2.1~7.08 mg/(m2·d)[21,37-38],显著高于团头鲂养殖生态系统晒塘阶段N2O排放通量;中国科研人员对上海附近湿地冬季N2O排放通量的监测结果为0.24 mg/(m2·d)[24],显著高于团头鲂养殖生态系统晒塘阶段N2O排放通量。本试验中,淡水池塘N2O排放规律没有CO2及CH4明显,其作用机理及影响因素有待进一步研究。

4 结 论

团头鲂池塘养殖生态系统晒塘阶段均表现为CO2,CH4和N2O排放源,其中CO2排放通量达(86.72±12.46) g/m2,CH4排放量达(2.01±0.34) g/m2,N2O排放量达(7.44±0.98) mg/m2;在100 a时间尺度上,团头鲂养殖池塘系统在晒塘阶段综合增温潜势为(157.28±24.31) g/m2,池塘养殖团头鲂生态系统温室气体减排空间较大。

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Greenhouse gas emissions of Megalobrama amblycephala culture pond ecosystems during sun drying of pond

Zhu Lin, Che Xuan※, Liu Huang, Liu Xingguo, Shi Xu, Yang Jiapeng, Wang Xiaodong, Gu Zhaojun, Cheng Guofeng, Zhu Hao
(Key Laboratory of Fisher Equipment and Engineering, Ministry of Agriculture, Fisher Machinery and Instrument Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200092, China)

Abstract:Global warming and ozone depletion caused by greenhouse gases are currently two major global environmental issues. While China's freshwater aquaculture production has long been ranked first in the world, greenhouse gas emissions from freshwater ponds becomes an important source of China's greenhouse gas emissions. But the research on greenhouse gas emission in freshwater aquaculture ecosystem is limited. In order to investigate greenhouse gas emissions and comprehensive global warming potential of Megalobrama amblycephala culture pond ecosystems during pond basked, we used the static opaque chamber-GC techniques to conduct an in situ determination of greenhouse gas emissions (CO2, CH4, N2O) of Megalobrama amblycephala culture pond ecosystems. The results showed that the CO2fluxes measured in every 15 days were (2652.46±325.36), (2313.82±245.14), (1456.42±124.67) and (1373.27±167.39) mg/(m2·d) respectively for the air temperature of 8.9, 7.2, 5.8 and 6℃, at the ponds during sampling. The potential of hydrogen at the ponds during the sampling at each temperature was (7.73±0.26), (8.26±0.35), (7.75±0.37) and (7.68±0.48), respectively. The total organic carbon at the ponds for each sampling was (3.61±0.43), (3.32±0.17), (3.16±0.31) and (3.23±0.27), respectively. The redox potential for each sampling was (206.7±34.9), (216.8±27.6), (56.8±9.3) and (124.8±16.5) mV, respectively. The moisture content of sediment for samples taken at 11.2, 10.3, 9.6 and 9.8℃ was (55.25%±2.54%), (54.53%±5.61%), (46.62%±4.38%), and (48.35%±3.14%), respectively. Among December 28, January 13, January 28, February 13, 2014, when the pond temperature was the highest on December 28, the CO2emission flux peaked (2652.46±325.36) mg/(m2·d)). In comparison, on February 13 2015, the smallest CO2emission flux (1373.27±167.39) mg/(m2·d)) corresponded with the lowest pond temperature, CH4is transformed from methane bacteria via an organic carbon source. As culturing activity increased with rising temperatures, phytoplankton dies and the organic artificial diets left over by fish increases, providing a rich carbon source for methane bacteria. In this study, CH4emission flux paralleled that of CO2, and in general, CH4emission flux was positively correlated with temperature. On December 28, 2014, there was a peak of CH4emission flux (82.42 ± 6.32) mg/(m2·d)) in the freshwater ponds. From December 28, 2014 to February 13 2015, the measured CH4emission fluxes were (82.42±6.32), (81.08±7.43), (7.63±1.84) and (7.06±2.93) mg/(m2·d), respectively. On February 13 2015, the lowest water temperature was accompanied by the smallest CH4emission flux (7.06±2.93) mg/(m2·d). From December 28, 2014 to February 13 2015, the N2O emission fluxes were (172.34±10.56), (204.57±16.84), (160.36±12.87), and (90.39±10.67) μg/(m2·d), respectively. Megalobrama amblycephala culture ponds during pond basked were the source of CO2, CH4and N2O, of which CO2emission during pond basked amounted to (86.72.10±12.46) g/m2, CH4emission of (2.01±0.34) g/m2, and N2O emission of (7.44±0.98) mg/m2. For 20-years Megalobrama amblycephala culture pond ecosystems during pond basked, greenhouse gas warming potential had an increase trend. Comprehensive global warming potential was (157.28±24.31) g/m2. Therefore, there was a great potential in greenhouse gas emission reduction in Megalobrama amblycephala culture pond ecosystems.

Keywords:greenhouse gases; emission control; ponding; aquaculture; greenhouse effect; Megalobrama amblycephala; sun drying of pond

通信作者:※车轩,男,硕士,助理研究员,从事养殖水环境控制研究。上海中国水产科学研究院渔业机械仪器研究所农业部渔业装备与工程技术重点试验室,200092。Email:chexuan@fmiri.ac.cn

作者简介:朱林,男,硕士,助理研究员,从事养殖水环境控制研究。上海中国水产科学研究院渔业机械仪器研究所农业部渔业装备与工程技术重点试验室,200092。Email:zhulin@fmiri.ac.cn。

基金项目:农业部渔业装备与工程技术重点实验室开放课题项目(2013006);农业财政项目“渔业节能减排宣传与政策研究”;国家虾现代农业产业技术体系建设专项资金(CARS-47)。

收稿日期:2015-07-15

修订日期:2015-12-16

中图分类号:X171.1;S965.119

文献标志码:A

文章编号:1002-6819(2016)-03-0210-06

doi:10.11975/j.issn.1002-6819.2016.03.030

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