北京市冬季大氣化石源CO2典型日變化的14C示蹤研究

牛振川，周衛(wèi)健,，程 鵬，吳書剛，盧雪峰，杜 花，付云翀，熊曉虎

（1. 中國科學(xué)院地球環(huán)境研究所 黃土與第四紀地質(zhì)國家重點實驗室，陜西省加速器質(zhì)譜技術(shù)及應(yīng)用重點實驗室，西安 710061；2. 西安加速器質(zhì)譜中心，西安 710061；3. 北京師范大學(xué)，北京 100875）

北京市冬季大氣化石源CO2典型日變化的14C示蹤研究

牛振川1,2，周衛(wèi)健1,2,3，程 鵬1,2，吳書剛1,2，盧雪峰1,2，杜 花1,2，付云翀1,2，熊曉虎1,2

（1. 中國科學(xué)院地球環(huán)境研究所 黃土與第四紀地質(zhì)國家重點實驗室，陜西省加速器質(zhì)譜技術(shù)及應(yīng)用重點實驗室，西安 710061；2. 西安加速器質(zhì)譜中心，西安 710061；3. 北京師范大學(xué)，北京 100875）

城市作為化石源CO2（）排放的熱點區(qū)域，獲得其大氣濃度的日變化特征對于深刻理解城市地區(qū)的時空變化規(guī)律，進而制定合理的節(jié)能減排政策至關(guān)重要。本研究通過AMS-14C技術(shù)，示蹤了北京市冬季一個典型日變化事件中大氣的變化過程，并探討了其影響因素。本次日變化事件中大氣δ13CO2的值為（-13.9 ± 0.8）‰（-14.8‰ — -12.7‰），Δ14CO2的值為（-151.6 ± 51.3）‰（（-214.2 ± 2.9）‰ — （-82.3 ± 3.0）‰），濃度為104.4 ± 44.0 μL · L-1（168.6 ± 2.7 — 52.1 ± 3.2 μL · L-1）。濃度具有較大的日變化，夜晚濃度明顯高于白天，主要是由于夜間大氣混合層高度較低、供暖消耗更多的化石燃料以及在東南風(fēng)條件下因北京不利的擴散條件而使聚積。此外，在早晚高峰期間，觀察到由于交通流量增加引起的較高濃度。同期PM2.5濃度相似的日變化過程進一步驗證了本次觀測結(jié)果的可靠性。

化石源CO2；14C示蹤；北京；日變化；冬季

南極冰芯的記錄顯示，最近80萬年以來大氣CO2濃度與溫度同步變化（Lüthi et al，2008）。近代工業(yè)革命以來，由于化石燃料的大量使用使得大氣CO2濃度由280 μL · L-1上升到目前的400 μL · L-1左右，全球溫度上升了0.74℃（IPCC，2007；GMD ESRL，2014）。由此，國際社會普遍認為有很大可能性，全球變暖是由于化石源CO2()等溫室氣體排放造成的（Rosa and Ribeiro，2001；丁仲禮等，2009）。為了應(yīng)對氣候變暖，碳減排已成為了全球共識。作為CO2的排放大國（Gregg et al，2008）和《京都議定書》的締約國，我國面臨越來越大的國際減排壓力。如何科學(xué)、準確、有效地評估我國目前大氣排放現(xiàn)狀，不僅是一個亟待解決的環(huán)境外交問題，而且是一個重要的科學(xué)問題（牛振川等，2014）。

1 采樣與分析方法

1.1 采樣地點

采樣點（40.01° N，116.35° E）位于北京市海淀區(qū)中國科學(xué)院生態(tài)環(huán)境研究中心一科研樓頂（15 m），周邊區(qū)域主要為住宅、商業(yè)、辦公、高校和公園等，是北京市城市點的典型代表。該地點位于北四環(huán)和五環(huán)之間，離繞城高速和京藏高速的直線距離超過1 km，離交通干道500 m和街道100 m以上，周邊無直接污染源。

1.2 采樣時間與方法

本次樣品采集從2014年1月15日早上8:00開始，每隔2小時采集1次樣品，一直到次日早上6:00結(jié)束，以此作為冬季日變化的典型代表。采樣前先用當?shù)乜諝鉀_洗5 min，然后將氣體樣品通過氣泵采集到5 L鋁箔氣袋（中國，大連德霖）內(nèi)，開關(guān)閥門時屏住呼吸，采樣時氣袋遠離操作者，并記錄采樣時相關(guān)的氣象參數(shù)信息。然后將氣袋包裝后迅速送回實驗室進行相關(guān)分析。

1.3 樣品CO2濃度和δ13CO2的分析方法

樣品CO2濃度由Picarro G2131-i型CO2碳同位素分析儀（Picarro公司，美國）測定。Picarro采用光腔衰蕩光譜技術(shù)（CRDS），具有線性好、精度高的優(yōu)點（Crosson，2008；Chen et al，2010）。CO2的測量精度為0.1 μL · L-1。每個樣品測試6分鐘，為減少因換樣給儀器帶來的死體積影響，僅后4分鐘的測試數(shù)據(jù)用于CO2濃度計算，將12和13的濃度相加得到樣品的CO2濃度。同時，計算后4分鐘樣品δ13C的平均值，δ13C的定義為：

1.4 樣品14C分析方法

將氣袋內(nèi)的氣體緩慢釋放到真空純化系統(tǒng)后，通過低溫液氮冷阱（-196°C）和液氮+酒精冷阱（-90°C）將樣品純化后，再經(jīng)Zn-Fe法（Slota et al，1987）將純化的CO2還原成石墨，壓靶后在西安加速器質(zhì)譜中心的3 MV多核素分析用加速器質(zhì)譜儀（Accelerator mass spectrometer，AMS）（HVEE，荷蘭）上進行14C測定，14C測量的精度在3‰左右，并用AMS得到的δ13C進行Δ14C的分餾校正。

樣品14C的含量通常用Δ14C表示，其定義為（Stuiver and Polach，1977）：

(14C/12C)SN是指樣品經(jīng)過δ13C分餾校正和放射性衰變校正后的14C/12C 的比值，(14C/12C)abs是指絕對國際放射性碳標準的14C/12C的比值。

公式(5)中等號右邊的第二項（β）可以寫為：

2 結(jié)果與分析

2.1 本底點大氣Δ14CO2值

本底點Δ14CO2值對的計算結(jié)果影響較大，最佳的本底點應(yīng)為自由對流層，但在自由對流層開展長期觀測有一定的難度，因此常用高山本底點來代替自由對流層（Turnbull et al，2009）。目前最新公開發(fā)表的Δ14CO2本底數(shù)據(jù)是2011年的Jungfraujoch站（Levin et al，2013），約為37‰；但缺乏公開發(fā)表的2014年Δ14CO2本底值?；诒镜渍睛?4CO2的值每年下降約5‰（Graven et al，2012），本文選用22‰作為2014年的本底值。但值得注意的是，由于高山本底點受當?shù)鼗騾^(qū)域化石源排放的影響，其Δ14CO2值與自由對流層會有2‰ — 3‰差別，這會給的計算結(jié)果帶來0.8 μL · L-1左右的誤差。

2.2 大氣CO2濃度的日變化

本次日變化事件中，觀測點大氣CO2濃度的日均值為508.0 ± 38.9 μL · L-1。大氣CO2濃度從10:00的最低值476.1 μL · L-1變化到04:00的最高值535.1 μL · L-1；夜晚大氣CO2濃度要比白天高約60 μL · L-1；且白天大氣CO2濃度在08:00也較高（476.1 μL · L-1）。大氣CO2濃度具有較大日變化，下文將對造成其變化的因素進行分析。

2.3 大氣δ13CO2的日變化

本次日變化事件中，大氣δ13CO2值的變化范圍為-14.8‰ — -12.7‰，均值為（-13.9 ± 0.8）‰，顯著高于瓦里關(guān)本底點的大氣δ13CO2值（-8.5 ± 0.2）‰（GMD ESRL，2014）。較低的城市大氣δ13CO2值主要是由于13C更“貧化”（平均值約-28‰）的化石燃料大量使用造成的。且白天的δ13CO2值（-13.1 ± 0.3）‰顯著（p ＜ 0.05）高于晚上（-14.5 ± 0.3）‰，這可能跟夜晚取暖使用更多的化石燃料有關(guān)。

如圖1a所示，采樣點大氣Δ14CO2的變化范圍為（-214.2 ± 2.9）‰— （-82.3 ± 2.5）‰，均值為（-145.8 ± 51.3）‰。將樣品Δ14CO2值和CO2濃度、本底Δ14CO2值以及β校正代入公式(5)得到樣品濃度。采樣點大氣濃度的日均值為104.4 ± 40.0 μL · L-1，變化范圍為52.1—168.6 μL · L-1。與瓦里關(guān)本底大氣CO2濃度（399.6 ± 4.2 μL · L-1）（GMD ESRL，2014）相比，濃度占新增大氣CO2濃度的（93.6 ± 4.5）%；且濃度和大氣CO2濃度高度相關(guān)（R2= 0.99，p＜ 0.01），這表明采樣點大氣CO2濃度的日變化主要是由于化石源排放造成的。

圖1 北京市冬季大氣Δ14CO2（a）和（b）的典型日變化狀況Fig.1 One typicalΔ14CO2(a) and(b) diurnal variations during wintertime in Beijing

限于14C較高的分析成本，本次日變化事件僅在北京市的一個采樣點開展觀測工作。那么，此采樣點觀測到的數(shù)據(jù)是否具有代表性，是否受到局地排放源的影響以及是否反映了整個北京市此次日變化的真實狀況？為此，我們分析了北京市同期大氣PM2.5濃度的變化狀況（圖2），PM2.5濃度為北京市8個站點的平均值。進行PM2.5濃度分析的原因是基于化石源排放是北京以及我國眾多城市PM2.5的重要來源（白春禮等， 2014），PM2.5的變化應(yīng)與相關(guān)聯(lián)。從圖2可以明顯地看出，北京市同期大氣PM2.5濃度與大氣具有相似的變化規(guī)律，這間接地驗證了本文觀測結(jié)果的可靠性。

圖2 同期北京市大氣PM2.5濃度的變化狀況（數(shù)據(jù)來自http://www.aqistudy.cn/）Fig.2 The hourly PM2.5concentrations on a typical wintertime diurnal event in Beijing (Data is obtained from the website: http://www.aqistudy.cn/)

3 結(jié)論

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Tracing a typical diurnal variations in atmospheric fossil fuel CO2using radiocarbon during wintertime at an urban site in Beijing

NIU Zhenchuan1,2, ZHOU Weijian1,2,3, CHENG Peng1,2, WU Shugang1,2, LU Xuefeng1,2, DU Hua1,2, FU Yunchong1,2, XIONG Xiaohu1,2
(1. State Key Laboratory of Loess and Quaternary Geology, Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710061, China; 2. Xi’an AMS Center, Xi’an 710061, China; 3. Beijing Normal University, Beijing 100875, China)

Background, aim, and scopeAs the main greenhouse gas, how much of the increased atmospheric CO2derived from the fossil fuel emissions is not only an environmental issue, but also an important scientific question. Traditional statistical methods for estimatingthe magnitude ofemissions incur some uncertainties, especially at regional scale. Radiocarbon (14C), a unique tracer, can be used to distinguish between atmosphericand CO2from other sources, and have been used to infer the spatio-temporal variations of atmosphericin recent years. Cities as emission hotspots, the diurnal atmospheric14CO2observation are important to the understanding of temporal atmospheric fossil fuel CO2() variability, thus facilitating the mitigation strategies ofemissions in China. In this study, one typical diurnal atmospheric14CO2observation was carried out at an urban site in Beijing, with the objective to trace the diurnalvariations, and to determine the factors in fl uencing them.Materials and methodsBeijing, a typical inland city, was selected in this study. It is the most central city in the Beijing-Tianjin-Hebei metropolitan region, with a population of more than 20 million. The city is surrounded by mountains in the west and north and faces the North China Plain to the south. The air sampling site is located on the roof of a building at the Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Haidian District. The site is located between the North 4th and 5th Ring roads, surrounded by dense of fi ce and commercial areas, residential districts, universities and parks. Air samples were collected in aluminum foil sampling bags every 2 hours from 8:00 am (local time) on 15th to 6:00 am (local time) on 16th in January, 2014. The CO2concentrations andδ13CO2in the air samples were measured using a Picarro G2131-I CO2Isotopic Analyzer (Picarro Inc., USA) with cavity ring down spectroscopy (CRDS). This equipment is highly linear and very stable, with very precise CO2measurements. Each sample was measured for 6 min, and only the average of the data from the last 4 min was used. The air samples in the bags were transferred to a high vacuum system with liquid nitrogen cold trap (-196 °C) and ethanol-liquid nitrogen cold trap (-90 °C) to get purified CO2, and then converted into graphite using the zinc-iron method. The14C levels of the air samples were measured using a 3 MV AMS in Xi’an, China, with a precision of 2‰—3‰ for14C measurement. The values of14C in the air samples were expressed asΔ14C, i.e., the per mil (‰) deviation from the absolute radiocarbon reference standard corrected by the convention of fractionation and decay.concentrations were calculated according to the mass balance of CO2and14C.ResultsThe CO2concentration in the diurnal event was 508.0 ± 38.9 μL · L-1, with high values at night.δ13CO2values were in the range of -14.8‰ — -12.7‰, with an average of (-13.9 ± 0.8)‰. They were lower than backgroundδ13CO2value, due to the contribution of fossil fuel emissions. Theδ13CO2values (-13.1 ± 0.3)‰ in daytime were significantly (p＜ 0.05) higher than those (-14.5 ± 0.3)‰ at night. The averageΔ14CO2value in this diurnal event was (-151.6 ± 51.3)‰((-214.2 ± 2.9)‰ — (-82.3 ± 3.0)‰), with correspondingconcentration of 104.4 ± 44.0 μL · L-1(168.6 ± 2.7 μL · L-1— 52.1 ± 3.2 μL · L-1).concentration showed high correlation with CO2, and contributed most of the offset of CO2compared to background CO2. These results indicated that the diurnal CO2variations were mainly resulted from the fossil fuel emissions.concentrations showed distinct diurnal variations, with high values at night and low values in daytime. Small peaks ofconcentrations were observed during the morning and afternoon rush hours, resulted from the emissions from transportation.DiscussionThe extremely high concentrations at that night resulted from the more fossil fuel consumption for heating and low vertical mixing height at night. Moreover,was readily accumulated when wind direction turned from north to south at that night, because the city is surrounded by mountains in the west and north. Additionally, it is robust for ourrecord, which is indirectly validated by the similar variation trends for simultaneous PM2.5concentrations in Beijing.ConclusionsOur data showed that the diurnal variations of atmosphericin Beijing were controlled by a combination of emission sources, height of vertical mixing, wind direction and topography.Recommendations and perspectivesThis study provides an example to understand the temporal variational characteristics of atmosphericand their in fl uencing factoring in Chinese cities.

fossil fuel CO2; radiocarbon tracing; Beijing; diurnal variation; wintertime

ZHOU Weijian, E-mail: weijian@loess.llqg.ac.cn

10.7515/JEE201605005

2016-05-01；錄用日期：2016-07-08

Received Date:2016-05-01;Accepted Date:2016-07-08

國家自然科學(xué)基金項目（41573136，41303072）；中國科學(xué)院西部之光項目（XAB2015A02）；中國科學(xué)院青年創(chuàng)新促進會（2016360）；黃土與第四紀地質(zhì)國家重點實驗室自主部署重點課題（LQ1301）；中國科學(xué)院地球環(huán) 境研究所青年人才項目（Y354011480，Y652001480）；陜西省自然科學(xué)基金青年項目（2014JQ2-4018）

Foundation Item:National Natural Science Foundation of China (41573136, 41303072); West Light Foundation of Chinese Academy of Sciences (XAB2015A02); Youth Innovation Promotion Association CAS (2016360); MOST Special Fund for State Key Laboratory of Loess and Quaternary Geology (LQ1301); Young Scholar Project of Institute of Earth Environment, CAS (Y354011480, Y652001480); Natural Science Foundation of Shaanxi Province, China (2014JQ2-4018)

周衛(wèi)健，E-mail: weijian@loess.llqg.ac.cn