于廣河,曹禮明,,朱 喬,王 川,黃曉鋒
深圳大氣有機(jī)硝酸酯粒徑分布特征和來源研究
于廣河1,曹禮明1,2,朱 喬2*,王 川1,黃曉鋒2
(1.深港產(chǎn)學(xué)研基地(北京大學(xué)香港科技大學(xué)深圳研修院),廣東 深圳 518057;2.北京大學(xué)深圳研究生院城市人居環(huán)境科學(xué)與技術(shù)實(shí)驗(yàn)室,廣東 深圳 518055)
于2021年3月30日至2021年4月17日利用超高分辨率氣溶膠飛行時(shí)間質(zhì)譜(Long-ToF-AMS),對(duì)深圳城市大氣中的顆粒態(tài)有機(jī)硝酸酯(pON)開展高精度分析. 基于兩種估算pON的方法,計(jì)算得出pON對(duì)有機(jī)氣溶膠(OA)的貢獻(xiàn)占比為5.08%~11.00%.pON的日變化特征顯示,其高值主要出現(xiàn)在夜間時(shí)段(19:00~6:00).pON在夜間時(shí)段與氧化程度較低的二次有機(jī)氣溶膠(LO-OOA)相關(guān)性最高,說明pON來源生成可能與夜間的新鮮二次生成相關(guān).此外,小粒徑段顆粒物對(duì)pON貢獻(xiàn)顯著,進(jìn)一步證明了夜間時(shí)段新鮮生成了較多的pON.本研究還進(jìn)一步比對(duì)了環(huán)境樣品中與pON相關(guān)的離子類型(CxHyNp+和CxHyOzNp+)及實(shí)驗(yàn)室模擬的特征質(zhì)譜,結(jié)果顯示深圳市pON生成的前體VOCs可能與植物排放和生物質(zhì)燃燒過程聯(lián)系更為密切.
有機(jī)硝酸酯;粒徑分布;來源研究;超高分辨率氣溶膠飛行時(shí)間質(zhì)譜
有機(jī)氣溶膠(OA)是大氣顆粒物的主要組成,顯著影響人體健康,大氣能見度和全球氣候變化[1-3].然而,當(dāng)前仍缺乏對(duì)有機(jī)氣溶膠來源生成的全面認(rèn)識(shí),其主要原因在于二次有機(jī)氣溶膠(SOA)的生成前體物來源廣泛,包括了人為排放和生物源排放且生成途徑復(fù)雜[4].顆粒態(tài)有機(jī)硝酸酯(pON)是OA的重要組成,在環(huán)境大氣中對(duì)OA的貢獻(xiàn)比例為5%~77%,對(duì)大氣中氮氧化物(NO)循環(huán)和臭氧生成有著重要影響[5-6].早期對(duì)pON的研究主要采用氣相色譜和傅利葉轉(zhuǎn)換紅外光譜的離線觀測方法[7],這些方法時(shí)間分辨率低,且只能給出pON中部分化學(xué)組分和分子信息,不能整體定量pON.近些年來,隨著在線觀測技術(shù)的發(fā)展,一些先進(jìn)監(jiān)測方法,如熱解離激光誘導(dǎo)熒光技術(shù)(TD-LIF)[8],熱解離光腔衰蕩光譜(TD- CRDS)[9]以及氣相和顆粒相采樣口高分辨率飛行時(shí)間化學(xué)電離質(zhì)譜(FIGAERO-HR-ToF-CIMS)[10],可以在線定量測量pON.
高分辨率氣溶膠質(zhì)譜(HR-AMS)是一種廣泛應(yīng)用于監(jiān)測氣溶膠粒徑分布和化學(xué)組成的在線儀器.雖然HR-AMS不能直接測量pON,但是可以用間接估算方法對(duì)pON進(jìn)行定量分析[11–14].目前最常用的估算方法是“NO+(NO+/NO2+)比值”法[13–16]. Farmer 等[11].根據(jù)NO+/NO2+比值在有機(jī)硝酸鹽和無機(jī)硝酸酯中顯著不同的特征,提出以下公式來定量有機(jī)硝酸酯:
因此,本文利用當(dāng)前氣溶膠質(zhì)譜的最新版本—超高分辨率飛行時(shí)間氣溶膠質(zhì)譜(Long-ToF-AMS, Aerodyne公司),對(duì)深圳市2021年4月的大氣有機(jī)硝酸酯進(jìn)行觀測研究.Long-ToF-AMS相比于普通版本的HR-AMS,擁有更長的質(zhì)譜飛行腔,使得其質(zhì)譜分辨率顯著提高,能夠更好的分辨不同質(zhì)譜碎片,從而更加精確地定量pON.除此之外,本文還聚焦pON的高分辨率粒徑特征分布,結(jié)合有機(jī)氣溶膠源解析結(jié)果,綜合分析探究pON的可能來源生成途徑.
觀測點(diǎn)位位于深圳大學(xué)城北大園區(qū)(22.6°N, 113.9°E),該點(diǎn)位位于深圳市南山區(qū),可以較好的代表全市的中等污染水平.點(diǎn)位周圍植被覆蓋率高,無明顯局地污染源.Long-ToF-AMS和其它相關(guān)監(jiān)測儀器均架設(shè)在教學(xué)樓頂層(距地面約20m),采樣管架設(shè)在樓頂,切割頭距離地面約1.5m.觀測時(shí)間為2021年3月30日~2021年4月17日.觀測期間的主要?dú)庀髤?shù)為:主導(dǎo)風(fēng)向?yàn)槠珫|風(fēng),平均風(fēng)速為(1.12±0.86) m/s,平均相對(duì)濕度為(73.3%±11.5%),平均溫度為(24.4±2.88)℃.
作為最新研發(fā)的氣溶膠質(zhì)譜版本,Long-ToF- AMS的質(zhì)譜分辨率可達(dá)7000,是普通HR-ToF- AMS的兩倍多.為了更好地分析顆粒物的粒徑分布,采樣時(shí)開啟了高分辨率飛行時(shí)間(HR-PToF)模塊,所有PToF數(shù)據(jù)件都保存為尾綴為‘_p’的數(shù)據(jù)集.Long-ToF-AMS可以在線測量真空動(dòng)力學(xué)粒徑小于1μm 的非難熔亞微米級(jí)顆粒物(NR-PM1),包括有機(jī)物(OA)、硫酸鹽(SO42-)、硝酸鹽(NO3-)、銨鹽(NH4+)和氯化物(Cl-)等,其進(jìn)樣流量為0.08L/min.整個(gè)觀測中分別進(jìn)行了兩次標(biāo)定,包括電離效率(IE)標(biāo)定、粒徑標(biāo)定和流量標(biāo)定,分別用于確定IE、粒徑和流量的校正擬合參數(shù).IE標(biāo)定所使用的標(biāo)準(zhǔn)物質(zhì)的純硝酸銨溶液,電離效率IE為6.67′10-8,NR- PM1的其它組分采用相對(duì)電離效率(RIE)進(jìn)行校正,RIE數(shù)值分別為:銨鹽3.8,硝酸鹽1.1,硫酸鹽0.8,有機(jī)物1.4,氯鹽1.3.此外,本研究還運(yùn)用了Middlebrook等[17]對(duì)AMS采集的不同化學(xué)組分的采集效率進(jìn)行了校正.
本研究對(duì)AMS數(shù)據(jù)的分析軟件為基于Igor Pro 6.37環(huán)境開發(fā)的SQUIRREL(版本1.62) 和PIKA(版本1.22) (http://cires1.colorado.edu/jimenezgroup/ ToFAMSResources/ToFSoftware/index.html)通過運(yùn)行軟件,可以得到NR-PM1中包括Org, SO42-, NO3-, Cl-和NH4+的質(zhì)量濃度.需要注意的是,這里的NO3-表示采樣過程中采集的總NO3-,其中包括了無機(jī)硝酸銨和pON.對(duì)于pON的定量,“NO+比值”法分解寫成對(duì)有機(jī)硝酸酯NO+(NOON)和NO2+(NO2,ON)的估算:
NOON=ONNO2,ON, (3)
Long-ToF-AMS對(duì)于顆粒物不同組成的粒徑基于顆粒物在PToF區(qū)域的飛行時(shí)間確定[24].本文采用高分辨率記錄顆粒物飛行時(shí)間模塊(HR-PToF)來分析具體離子碎片的粒徑.整個(gè)粒徑分布的積分區(qū)間從顆粒物動(dòng)力學(xué)直徑16nm至15906nm,分成27等分.高分辨率顆粒物粒徑數(shù)據(jù)處理方法詳見http://cires1.colorado.edu/jimenez-group/wiki/index.php/ToF-AMS_Analysis_Software#HR_PToF .主要分為4個(gè)步驟:(1)創(chuàng)建顆粒物粒徑分布的積分區(qū)間箱格數(shù).由于高分辨率質(zhì)譜信號(hào)比整數(shù)質(zhì)荷比通道信號(hào)低100倍以上,在處理數(shù)據(jù)時(shí)會(huì)通過合并采集數(shù)據(jù)時(shí)默認(rèn)的積分箱格數(shù)來降低噪聲,提高信噪比.本文選擇積分區(qū)間開始和結(jié)束前后的一段區(qū)域標(biāo)記為DC區(qū)域,來確認(rèn)采集信號(hào)的閾值.(2)進(jìn)行高分辨率質(zhì)譜峰型擬合,選擇的質(zhì)譜峰對(duì)應(yīng)濃度數(shù)據(jù)處理時(shí)候選擇的離子峰.(3)去除儀器背景值,質(zhì)譜儀器采樣時(shí),會(huì)不間斷地關(guān)閉進(jìn)樣來監(jiān)測儀器的背景信號(hào),這一背景信號(hào)可由第一步選擇的DC區(qū)域來代替,因此在這一步將減去DC區(qū)域值進(jìn)行矯正.(4)生成各高分辨離子的粒徑分布圖.本文中,基于以上處理可以得到高分辨率的NO+和NO2+離子粒徑分布圖,再根據(jù)1.2部分“NO+比值”的類似處理步驟,可以進(jìn)一步得到pON的粒徑分布[16].
表1 “NOx +比值”和PMFogr+NO2法估算pON中NO3,org官能團(tuán)的濃度結(jié)果
圖1 “NOx+比值”和PMForg+NO3法估算出的pON中NO3,org官能團(tuán)時(shí)間序列,相關(guān)性比對(duì)以及與無機(jī)硝酸鹽(NO3_inorg)的日變化趨勢
在OA的四類來源因子里,大部分pON碎片位于LO-OOA因子中.因此,在本小節(jié)里,比對(duì)了“NO+比值”法估算出的pON結(jié)果和各OA因子的相關(guān)性,進(jìn)一步探討驗(yàn)證pON可能的來源生成過程.如圖2(b)~(e)所示,pON與LO-OOA因子的相關(guān)性最高,相關(guān)性系數(shù)達(dá)到0.63.這一結(jié)果與pON碎片主要分布在LO-OOA的結(jié)果相符.進(jìn)一步將LO-OOA的觀測結(jié)果按照夜間時(shí)段(19:00~6:00)和白天時(shí)段(7:00~18:00)進(jìn)行劃分后,與pON進(jìn)行比對(duì)(圖2(f)和(g)),結(jié)果顯示:夜間時(shí)段的比對(duì)相關(guān)性進(jìn)一步增加,為0.70,說明本次觀測中,pON的夜間新鮮二次生成反應(yīng)可能較為活躍.這也與Yu等[16]提出的深圳市pON與夜間新鮮二次生成反應(yīng)關(guān)系密切的結(jié)論相符.由于夜間主導(dǎo)的NO3自由基是由NO的相關(guān)反應(yīng)生成,因此將夜間生成的pON與NO濃度進(jìn)行了相關(guān)性分析,發(fā)現(xiàn)相關(guān)性很弱(=-0.03),主要是因?yàn)镹O引起的夜間反應(yīng)體系復(fù)雜,且NO3與N2O5存在反應(yīng)平衡體系,因此pON的生成與NO濃度高低無直接相關(guān)性,這也與之前同點(diǎn)位的觀測分析結(jié)論一致[16].
顆粒物粒徑分布是反應(yīng)其在大氣中生成和演化過程的重要表征.從pON的粒徑分布特征的角度探究其生成途徑,本文使用的是超高分辨率質(zhì)譜,因此可以更好地得到NO+和 NO2+觀測數(shù)據(jù),而不受到與其位于同一整數(shù)質(zhì)荷比通道的其它碎片離子的干擾.圖3(a)顯示了PM1中OA,硫酸鹽,無機(jī)硝酸鹽(NO3_inorg)和NO3_org_ratio1的平均粒徑分布.其中,硫酸鹽,NO3_inorg和NO3_org_ratio1的粒徑分布峰值位于空氣動(dòng)力學(xué)粒徑600nm左右,驗(yàn)證了這些二次無機(jī)物種的老化特征[25].對(duì)于OA和NO3_org_ratio1,其粒徑分布中有較多小粒徑段的貢獻(xiàn)(100~300nm),而這一部分小粒徑粒子,通常認(rèn)為是一次排放或者本地新鮮的二次生成貢獻(xiàn)[26].除了分析pON的平均粒徑分布,本文還進(jìn)一步分析了NO+/NO2+比值的日變化趨勢(圖3(b)).如前文所述,NO+/NO2+比值高對(duì)應(yīng)了pON生成貢獻(xiàn)顯著.從圖中可以清楚得出,pON生成在夜間時(shí)段生成顯著,且主要位于100~1000nm粒徑段,與圖3(a)中貢獻(xiàn)顯著的粒徑段相符.
綜上,從粒徑分布的角度,本文同樣得到了pON的來源中,夜間時(shí)段的本地新鮮生成貢獻(xiàn)顯著.
除了NO+和NO2+碎片,Long-ToF-AMS采集的pON碎片還會(huì)出現(xiàn)在CHN+和CHON+類離子中.然而,目前的研究對(duì)于環(huán)境大氣pON在AMS質(zhì)譜中的碎片分布種類鮮有研究.最近,Graeffe 等[27]利用pON的幾類典型VOCs生成前體物與NO3自由基反應(yīng)模擬夜間生成pON的反應(yīng).該實(shí)驗(yàn)選用的VOCs包括:化石燃料排放的示蹤VOC萘并乙烯(acenaphthylene), 生物質(zhì)燃燒示蹤VOC愈創(chuàng)木酚(guaiacol)以及兩種典型的植物排放VOC—檸檬烯(limonene)和b-蒎烯(b-pinene).該煙霧箱實(shí)驗(yàn)同樣采用Long-ToF-AMS對(duì)生成的顆粒態(tài)pON進(jìn)行了監(jiān)測.因此,本文將實(shí)驗(yàn)采集的環(huán)境樣品中的pON質(zhì)譜與實(shí)驗(yàn)室模擬實(shí)驗(yàn)生成的pON進(jìn)行比對(duì),進(jìn)一步討論環(huán)境大氣中pON可能的生成前體物.
比對(duì)結(jié)果如圖4所示, 由于環(huán)境樣品中還有大量其它有機(jī)物物種,因此在質(zhì)譜比對(duì)上,本文更加側(cè)重同時(shí)含有的碎片組分種類比較,而不是碎片組分的占比.圖4(a)顯示了CHN+類離子的比對(duì),環(huán)境樣品中,CHN+(m/z 27)是這類離子中貢獻(xiàn)最為突出的離子,而實(shí)驗(yàn)室模擬實(shí)驗(yàn)中愈創(chuàng)木酚和檸檬烯生成的pON中也存在較為顯著的CHN+的貢獻(xiàn).除此之外,環(huán)境樣品中的CHN+類離子里與愈創(chuàng)木酚生成的pON的離子組分有較多重合.圖4(b)給出了CHON+類離子的質(zhì)譜比對(duì)結(jié)果,可以看到,環(huán)境樣品中,CH3NO+(m/z 45)和CH2NO3+(m/z 76)貢獻(xiàn)最為顯著,對(duì)比實(shí)驗(yàn)室模擬結(jié)果,這兩個(gè)碎片組分在兩種植物排放的VOCs產(chǎn)生的pON碎片中也有顯著貢獻(xiàn).綜合比對(duì)結(jié)果,深圳大氣中pON的前體生成物可能與植物排放的VOCs緊密相關(guān),而CH3NO+(m/z 45)和CH2NO3+(m/z 76)可能是其重要的示蹤碎片.這與本文前期研究中結(jié)合VOCs觀測得出的結(jié)論一致[16].此外,與愈創(chuàng)木酚為前體物的pON質(zhì)譜組分中有較多相似,說明其來源可能生物質(zhì)燃燒排放過程相關(guān),這一結(jié)論也在最近的研究中被報(bào)導(dǎo)[22,28-29].
圖4 環(huán)境樣品離子與實(shí)驗(yàn)室模擬不同VOCs前體物生成pON質(zhì)譜圖比較
3.1 利用超高分辨率飛行時(shí)間氣溶膠質(zhì)譜(Long- ToF-AMS)于2020年3月30日~2021年4月17日在深圳開展了針對(duì)大氣有機(jī)硝酸酯(pON)的觀測實(shí)驗(yàn).研究基于“NO+比值”法和PMFogr+NO3法分別估算了pON的濃度水平.結(jié)果顯示,觀測期間,pON對(duì)OA的貢獻(xiàn)比例為5.08%~11.00%.進(jìn)一步分析pON的日變化特征,顯示其濃度高值主要位于夜間(19:00~6:00)時(shí)段.
3.2 pON與各OA因子的相關(guān)性比對(duì)分析得出,pON與HOA,COA,LO-OOA和MO-OOA的相關(guān)性系數(shù)分別為0.08,0.34,0.63和0.21.pON與LO-OOA相關(guān)性顯著高于其它因子,且pON與LO-OOA的相關(guān)性在夜間時(shí)段更為顯著,R為0.70.說明深圳市大氣中pON來源與二次新鮮生成相關(guān),且在夜間時(shí)段生成反應(yīng)活躍.
3.3 pON的高分辨率粒徑分布特征顯示,與二次無機(jī)組分主要由大粒徑段粒子貢獻(xiàn)不同,pON有著顯著的小粒徑段粒子貢獻(xiàn)(空氣動(dòng)力學(xué)直徑100~300nm),說明pON來源中一次排放或者新鮮的二次生成貢獻(xiàn)顯著.NO+/NO2+比值粒徑分布的日變化趨勢同樣顯示了在夜間時(shí)段有著明顯的pON生成.
3.4 將本研究采集的環(huán)境樣品中的CHN+和CHON+類離子與實(shí)驗(yàn)室中不同VOCs模擬生成pON的結(jié)果質(zhì)譜圖進(jìn)行比較發(fā)現(xiàn),環(huán)境樣品中的碎片組成與植物排放的VOCs以及生物質(zhì)燃燒排放的VOCs生成的pON有著較多重合,說明深圳pON的VOCs生成前體物可能與植物排放以及生物質(zhì)燃燒過程緊密相關(guān).
[1] Poschl U, Atmospheric aerosols: Composition, transformation, climate and health effects [J]. Angewandte Chemie-International Edition, 2005,44(46):7520-7540.
[2] Pearce W, Holmberg K, Hellsten I, et al. Climate change on twitter: topics, communities and conversations about the 2013 IPCC Working Group 1Report [J]. Plos One, 2014,9(4).
[3] Kanakidou M, Seinfeld J H, Pandis S N, et al. Organic aerosol and global climate modelling: a review [J]. Atmospheric Chemistry and Physics, 2005,5:1053-1123.
[4] Saathoff H, Naumann K H, M?hler O, et al. Temperature dependence of yields of secondary organic aerosols from the ozonolysis of α-pinene and limonene [J]. Atmospheric Chemistry and Physics, 2009,9(5):1551-1577.
[5] Perring A E, Pusede S E, Cohen R C, An observational perspective on the atmospheric impacts of alkyl and multifunctional nitrates on ozone and secondary organic aerosol [J]. Chemical Reviews, 2013,113(8): 5848-5870.
[6] Ng N L, Brown S S, Archibald A T, et al. Nitrate radicals and biogenic volatile organic compounds: oxidation, mechanisms, and organic aerosol [J]. Atmospheric Chemistry and Physics, 2017,17(3):2103- 2162.
[7] Obrien S R, Mayewski P A, Meeker L D, et al. Complexity of holocene climate as reconstructed from a Greedland ice core [J]. Science, 1995,270,(5244):1962-1964.
[8] Rollins A W, Browne E C, Min K E, et al. Evidence for NOcontrol over nighttime SOA formation [J]. Science, 2012,337(6099):1210- 1212.
[9] Thieser J, Schuster G, Schuladen J, et al. A two-channel thermal dissociation cavity ring-down spectrometer for the detection of ambient NO2, RO2NO2 and RONO2 [J]. Atmospheric Measurement Techniques, 2016,9(2):553-576.
[10] Lopez-Hilfiker F D, Mohr C, Ehn M, et al. A novel method for online analysis of gas and particle composition: description and evaluation of a Filter Inlet for Gases and AEROsols (FIGAERO) [J]. Atmospheric Measurement Techniques, 2014,7(4):983-1001.
[11] Farmer D K, Matsunaga A, Docherty K S, et al. Response of an aerosol mass spectrometer to organonitrates and organosulfates and implications for atmospheric chemistry [J]. Proceedings of the National Academy of Sciences of the United States of America, 2010,107(15):6670-5.
[12] Hao L Q, Kortelainen A, Romakkaniemi S, et al. Atmospheric submicron aerosol composition and particulate organic nitrate formation in a boreal forestland-urban mixed region [J]. Atmospheric Chemistry and Physics, 2014,14(24):13483-13495.
[13] Xu L, Suresh S, Guo H, et al. Aerosol characterization over the southeastern United States using high-resolution aerosol mass spectrometry: spatial and seasonal variation of aerosol composition and sources with a focus on organic nitrates [J]. Atmospheric Chemistry and Physics, 2015,15(13):7307-7336.
[14] Xu L, Guo H Y, Boyd C M, et al. Effects of anthropogenic emissions on aerosol formation from isoprene and monoterpenes in the southeastern United States [J]. Proceedings of the National Academy of Sciences of the United States of America, 2015,112(1):37-42.
[15] Zhu Q, He L-Y, Huang X-F, et al. Atmospheric aerosol compositions and sources at two national background sites in northern and southern China [J]. Atmospheric Chemistry and Physics, 2016,16(15):10283- 10297.
[16] Yu K, Zhu Q, Du K, et al. Characterization of nighttime formation of particulate organic nitrates based on high-resolution aerosol mass spectrometry in an urban atmosphere in China [J]. Atmospheric Chemistry and Physics, 2019,19(7):5235-5249.
[17] Middlebrook A M, Bahreini R, Jimenez J L, et al. Evaluation of composition-dependent collection efficiencies for the aerodyne aerosol mass spectrometer using field data [J]. Aerosol Science and Technology, 2012,46(3):258-271.
[18] Fry J L, Draper D C, Zarzana K J, et al. Observations of gas- and aerosol-phase organic nitrates at BEACHON-RoMBAS 2011 [J]. Atmospheric Chemistry and Physics, 2013,13(17):8585-8605.
[19] Boyd C M, Sanchez J, Xu L, et al. Secondary organic aerosol formation from the β-pinene+NO3system: effect of humidity and peroxy radical fate [J]. Atmospheric Chemistry and Physics, 2015, 15(13):7497-7522.
[20] Bruns E A, Perraud V, Zelenyuk A, et al. Comparison of FTIR and particle mass spectrometry for the measurement of particulate organic nitrates [J]. Environmental Science & Technology, 2010,44(3):1056- 61.
[21] Sato K, Takami A, Isozaki T, et al. Mass spectrometric study of secondary organic aerosol formed from the photo-oxidation of aromatic hydrocarbons [J]. Atmospheric Environment, 2010,44(8): 1080-1087.
[22] Joo T, Rivera-Rios J C, Takeuchi M, et al. Secondary organic aerosol formation from reaction of 3-methylfuran with Nitrate Radicals [J]. ACS Earth and Space Chemistry, 2019,3(6):922-934.
[23] Paatero P, Tapper U, Positive matrix factorization - a nonnegative factor model with optimal utilization of error-estimates of data values [J]. Environmetrics, 1994,5(2):111-126.
[24] DeCarlo P F, Kimmel J R, Trimborn A, et al. Field-deployable, high-resolution, time-of-flight aerosol mass spectrometer [J]. Analytical Chemistry, 2006,78(24):8281-9.
[25] Jimenez J L, Jayne J T, Shi Q, et al. Ambient aerosol sampling using the Aerodyne Aerosol Mass Spectrometer [J]. Journal of Geophysical Research-Atmospheres, 2003,108(D7).
[26] Huang X F, He L Y, Hu M, et al. Highly time-resolved chemical characterization of atmospheric submicron particles during 2008 Beijing Olympic Games using an aerodyne high-resolution aerosol mass spectrometer [J]. Atmospheric Chemistry and Physics, 2010, 10(18):8933-8945.
[27] Graeffe F. Fragmentation patterns of particulate organic nitrates in an Aerosol Mass Spectrometer [D]. University of Helsinki, 2019.
[28] Ahern A T, Robinson E S, Tkacik D S, et al. Production of secondary organic aerosol during aging of biomass burning smoke from fresh fuels and its relationship to VOC precursors [J]. Journal of Geophysical Research-Atmospheres, 2019,124(6):3583-3606.
[29] Zhu Q, Cao L M, Tang M X, et al. Characterization of organic aerosol at a rural site in the North China Plain Region: Sources, volatility and organonitrates [J]. Advances in Atmospheric Sciences, 202138(7): 1115-1127
Sizing and source characterization of particulate organic nitrates based on long time-of-flight aerosol mass spectrometer (Long-ToF-AMS) in Shenzhen.
YU Guang-he1, CAO Li-ming1,2, ZHU Qiao2,*, WANG Chuan1, HUANG Xiao-feng2
(1.Peking University-Hong Kong University of Science and Technology Shenzhen Hong Kong Institution, Shenzhen 518055, China;2.Shenzhen Graduate School, Key Laboratory for Urban Habitat Environmental Science and Technology, Peking University, Shenzhen 518055, China)., 2022,42(4):1510~1517
In this study, a long time-of-flight aerosol mass spectrometer (Long- ToF-AMS) was applied to characterize particulate organic nitrates (pON) during March 30thto April 17thin 2021 at Shenzhen. Using cross-validation estimated methods, we calculated pON accounting for 5.08%~11.00% in total OA. The diurnal pattern with nighttime higher mass loading for pON and the best correlation with less-oxidized oxygenated OA (LO-OOA) at night indicated that pON formation might be more associated with nighttime fresh secondary formation. The high-resolution size distribution of pON showed they contained a substantial fraction of smaller size particles, further confirming the contributions from primary aerosols or newly formed secondary aerosols at night. Additionally, the potential precursors for pON formation was further explored based on comparison analysis between mass spectrum of our ambient data and the laboratory generated pON using different precursors. The results implied that volatile organic compounds (VOCs) emitted from biogenic sources and biomass burning were potential precursors for pON formation in Shenzhen.
organic nitrates;size distribution;source analysis;Long-ToF-AMS
X513
A
1000-6923(2022)04-1510-08
于廣河(1965-),男,黑龍江五常人,高級(jí)工程師,學(xué)士,主要從事環(huán)境監(jiān)測技術(shù)研究.發(fā)表論文20余篇.
2021-09-06
深圳市科技計(jì)劃資助項(xiàng)目(JCYJ20180712093002076);深港產(chǎn)學(xué)研基金資助項(xiàng)目(HT-JD-CXY-201903); 廣東省基礎(chǔ)與應(yīng)用基礎(chǔ)研究基金(2019A1515110793)
*責(zé)任作者, 博士, zhuqiao2013@pku.edu.cn