巢湖二氧化碳排放特征及其潛在影響因素

李宇陽,朱俊羽,俞曉琴,陳慧敏,郭燕妮,周永強,3,周 蕾,3*

巢湖二氧化碳排放特征及其潛在影響因素

李宇陽1,2,朱俊羽1,俞曉琴1,陳慧敏1,郭燕妮1,周永強1,3,周 蕾1,3*

(1.中國科學院南京地理與湖泊研究所,江蘇 南京 210008；2.南昌大學資源環境與化工學院,鄱陽湖環境與資源利用教育部重點實驗室,江西 南昌 330031；3.中國科學院大學,北京 100049)

巢湖；二氧化碳(CO2)；通量；有色可溶性有機物(CDOM)；平行因子分析(PARAFAC)

CO2作為大氣中最重要的溫室氣體成分[1],其溫室效應增溫貢獻占所有溫室氣體總貢獻的60%.雖然湖泊總表面積只覆蓋了全球陸地面積的4%[2],但湖泊的CO2排放卻在流域碳循環中發揮著重要作用[3].湖泊作為內陸水體有機碳循環的要沖與樞紐,承接了流域大量有機碳匯入.由于人類城鎮化規模擴大,在人口和農業集中地區,湖泊富營養化現象尤為嚴重[4].巢湖是長江中下游典型的富營養化湖泊,由于入湖河流的營養負荷高,大量外源有機碳從湖泊西部入湖河口匯入.有研究顯示,富營養化一般會導致浮游植物聚集與堆積,其呼吸礦化與光合作用均會影響CO2的變化[5],此外,富營養化也會增加藻生物量及藻源性有機質產生[5-6],從而影響湖泊溫室氣體的產生與排放.

溶解性有機物(DOM)是由腐殖質、富里酸、脂肪族及芳香烴類物質組成的[7],結構較為復雜,是天然有機質重要賦存形態和活性組分,富含有機碳、氮、磷、硫等生源要素[8-9],對水生生態系統具有重要意義.由于其結構的復雜性,傳統方法難以準確解析其組成.有色可溶性有機物(CDOM)是DOM中可強烈吸收紫外和可見光的部分[10].通過CDOM能強烈吸收紫外輻射且紫外激發后能發出熒光的特性得出的熒光組分峰團信息可有效表征CDOM的組成及來源,從而揭示CDOM的組成對溫室氣體排放的影響.三維熒光光譜(EEMs)結合平行因子(PARAFAC)能有效揭示CDOM熒光組分峰團信息[7,10-11],由于富含CDOM來源組成“指紋”信息,因而被廣泛應用于水生態系統中天然有機質來源組成的表征.

1 材料與方法

1.1 樣品采集

巢湖地屬安徽省合肥市,水域面積780km2,平均水深2.89m,環湖河流約33條,西經合肥,東入長江,湖水主要由地表徑流補給,入湖年平均流量最高的河流分別為杭埠河、南淝河、兆河、派河、柘皋河、白石天河、十五里河[14-15].

根據環巢湖河流分布與湖區水文特征,在巢湖西部、中部、東部湖區均勻設置13個采樣點,其中包括5個細菌計數采樣點,野外采樣分別開展于2018年1, 4, 7月,共計39個表層水與氣體樣品(圖1).水樣采集完成后,用聚乙烯瓶裝存,置于黑暗冷凍環境下轉移至實驗室.氣體采集采用頂空瓶法,將水樣灌裝在事先裝有2g KCl (消除樣品運輸過程中潛在的微生物活動)的61mL棕色玻璃瓶中[16-17],排除氣泡后用鋁蓋密封,每次野外采樣均在湖心位置取湖面上方2m處的大氣背景樣品注入真空密封棕色玻璃瓶中用以消除季節變化大氣本底CO2濃度變化,一同轉移至實驗室.

圖1 巢湖采樣點分布

圓圈表示采樣點,其中黑色對應細菌計數樣品采集點位

1.2 主要水質參數與總細菌數的測定

水樣-22℃凍存,運至實驗室后,以孔徑0.7μm Whatman GF/F玻璃纖維濾膜過濾水樣,濾后水用Shimadzu TOC-L總有機碳分析儀對水樣中溶解性有機碳(DOC)進行測定,測定時采用NPOC掃吹模式,且溫度設定為680℃[18].用體積分數90%的乙醇高溫萃取留存濾膜,再用分光光度法測定波長665與750nm的吸光度值以計算葉綠素(Chl-a)濃度.留取1mL原水加入60μL無顆粒甲醛固定,4℃下低溫保存,通過流式細胞儀對總細菌數進行測定.總氮(TN)、總磷(TP)采用紫外分光光度計(Shimazdu UV-2550UV-Vis),測量方法均參照文獻[19].常規水質參數如表層水溫(),溶解氧(DO)均用多參數水質儀(YSI-EXO2)現場測定.

1.3 CDOM紫外吸收光譜與三維熒光光譜的測定

以孔徑0.2μm Millipore濾膜對水樣進行過濾,留存100mL濾后水.吸收光譜測定時,使用Shimazdu UV-2550UV-Vis,波長范圍為200～800nm,間隔1nm,且通過扣除700nm吸光度以去除水樣顆粒散射;254為CDOM在波長254nm處的吸收系數,可用以表征CDOM相對豐度.三維熒光光譜EEMs測定時,使用Hitachi F-7000熒光光度計,以Milli-Q超純水為空白,激發波長230～450nm,間隔5nm,發射波長300～ 600nm,間隔1nm.掃描完成后對數據進行內濾波效應校正,再扣除超純水空白數據消除拉曼散射,用drEEM工具包消除掃描中的瑞利散射峰,處理完成后,將數據導入MATLAB R2015b軟件,結合平行因子分析(PARAFAC)得出組分信息[20].

腐殖化指數(HIX),生物鮮活指數(BIX)均為特定波長波段熒光強度積分比值,HIX越大,CDOM陸源來源信號越強;BIX越大,CDOM生物來源信號越強.比紫外吸收系數(SUVA254)為254與DOC濃度的比值[8],SUVA254越大表明CDOM芳香程度越高[21]. HIX與SUVA254可表征CDOM的陸源信號強弱.

1.4 水體CO2濃度及CO2擴散通量

式中:C為水氣界面擴散通量,mg/(m2×d),water為水樣中溶解性氣體濃度;air為采樣時空氣中氣體濃度,μmol/L.

式中:x為氣體交換系數, cm/h;由風速決定,風速<3m/s時,=0.66,風速>3m/s時,=0.5;c是CO2施密特數,取決于溫度,℃.

600為20℃淡水中CO2施密特數為600時標準值,由風速決定,計算公式為:

10為水面上高程10m處的風速,根據實測高度風速U決定,計算公式為[22]:

式中:10為水面高程10m處的風阻系數, 0.0013m/s;為馮卡門常數, 0.41.

1.5 水文情形的劃分

根據巢湖流域地理水文特征及合肥市年均逐月降雨量(1961～2018年),將巢湖水文情形劃分為枯水期、平水期及豐水期3種水文情形,對應降雨量分別為1月(35.6mm)、4月(90.9mm)、7月(173.8mm).

1.6 數據處理

2 結果與分析

2.1 巢湖表層水體CO2濃度與擴散通量時空變化特征

表1 不同水文情景巢湖水體CO2濃度()與擴散通量()

圖2 巢湖1、4、7月表層水體、空間分布

2.2 巢湖主要水質參數均值與標準差分析

圖3 巢湖1、4、7月不同湖區DO、TN、TP、DOC變幅

如圖3所示,采樣期間,巢湖DO實測值為4.7～15.9mg/L,月均DO高值與低值均出現在西部湖區,分別為1月(14.5mg/L)與7月(6.3mg/L),且隨著月份的增加不斷降低;湖區內TN、TP、Chl-a具有顯著的季節差異,隨月份的增加不斷增加(表2).由于巢湖獨特的水文特征,湖區TN與TP有較為明顯的季節與時空差異,從西部湖區到東部湖區逐漸降低,在西部與中部湖區,TN、TP隨著月份的變化顯著升高,高值均出現在西部湖區的7月份(7.4mg/L,0.7mg/L),東部湖區TN 4月較高;DOC從西到東也有逐漸降低的趨勢,但變化不顯著,在營養負荷較重的西部湖區4月和7月較高.

2.3 巢湖表層水體細菌豐度時空變化特征

通過流式細胞儀測定巢湖表層水體細菌豐度,結果表明,細菌總數大體上表現為7月>1月>4月,且在空間分布上大體表現為自西向東不斷降低.高值出現在西部湖區的7月(2.6×107cells/mL),低值為東部湖區的4月(0.9×106cells/mL) (圖4).

圖4 巢湖不同水文情景下細菌計數結果

2.4 巢湖表層水體、與DO、DOC、lg(Chl-a)的相關性分析

圖5 巢湖表層水體、與DO、DOC、lg(Chl-a)的相關性

2.5 巢湖表層水體可溶性有機物光譜組成特征以及各組分與、的相關性分析

用平行因子分析模型對巢湖表層水體可溶性有機物進行組分解析,最終得出四種主要熒光峰團,分別為短波類腐殖質峰C1(表征陸源類腐殖酸經微生物降解后產物,通常與入湖河流輸入息息相關[23])、類色氨酸峰C2 (藻降解的內源產生亦或生活污水新近產生[24])、類酪氨酸峰C3 (生物降解內源產生或微生物礦化產物[25])和長波類腐殖質峰C4(外源地表有機碎屑輸入[20]).模型結果詳盡情況可參見文獻[26].

表2 巢湖1、4、7月主要水質要素與CDOM光學組分比較

圖6 巢湖表層水體、與四個熒光組分C1-C4相關性

2.6 巢湖主成分分析

圖7 巢湖環境因子主成分分析(a)及主成分PC1與、的相關性分析(b)

3 討論

3.1 巢湖富營養水平對、的影響

3.2 巢湖水體CDOM來源組成對、的影響

自然湖泊CDOM主要來源于有機質的外源輸入,即土壤植被有機質或動植物殘體分解,亦或者是污水的排放[32];也可能來源于浮游植物、微生物等一系列初級生產力降解分解產生.

CDOM來源組成對CO2產生的影響還未被充分研究,但CDOM對CO2的影響毋庸置疑.CDOM因能強烈吸收紫外輻射而快速被光降解產生CO2,同時由于對水體藍光的強烈吸收從而直接影響浮游植物光合作用與呼吸作用及對CO2的吸收與釋放[13,37].CDOM中陸源腐殖質組分直接表征外源有機質的輸入,能直接影響水體營養水平及有機物的積累與降解,進而促進CO2排放,這也與主成分分析中的PC1結果相吻合,此外內源性組分由于生物活性強,與微生物新陳代謝過程息息相關,藻源性組分也可綜合表征藻華的暴發與降解.基于此,今后可從CDOM來源組成與CO2的潛在關聯出發,以期對湖泊碳循環以及二氧化碳排放作出更準確的評價.

4 結論

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致謝：感謝鄒偉、施坤、李娜、葉小銳、張成英等同志在野外及室內實驗過程中給予的幫助.

Emission of carbon dioxide from Lake Chaohu and the potential influencing factors.

LI Yu-yang1,2, ZHU Jun-yu1, YU Xiao-qin1, CHEN Hui-min1, GUO Yan-ni1, ZHOU Yong-qiang1,3, ZHOU Lei1,3*

(1.Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China；2.Key Laboratory of Poyang Lake Environment and Resource Utilization, Ministry of Education, School of Resources Environmental & Chemical Engineering, Nanchang University, Nanchang 330031, China；3.University of Chinese Academy of Sciences, Beijing 100049, China)., 2022,42(1)：425～433

Lake Chaohu；carbon dioxide (CO2)；flux；chromophoric dissolved organic matter (CDOM)；parallel factor analysis (PARAFAC)

X143,X171

A

1000-6923(2022)01-0425-09

李宇陽(1997-),男,安徽淮南人,南昌大學碩士研究生,主要從事有色可溶性有機物循環與水污染治理.發表論文2篇.

2021-05-27

國家自然科學基金資助項目(41807362);中國科學院青年創新促進會會員(2021312);江蘇省自然科學基金資助項目(BK20181104);中國科學院南京地理與湖泊研究所青年科學家小組(E1SL002)

* 責任作者, 助理研究員, zhoulei16@mails.ucas.ac.cn