Direct Observations of Atmospheric Transport and Stratosphere-Troposphere Exchange from High-Precision Carbon Dioxide

and Carbon Monoxide Profile Measurements

You YI1,2, Zhaonan CAI1,2, Yi LIU1,2, Shuangxi FANG3, Yuli ZHANG*1, Dongxu YANG1,2,Yong WANG1, Miao LIANG3, and Maohua WANG4

1Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China2University of Chinese Academy of Sciences, Beijing 100049, China

3Meteorological Observation Centre, China Meteorological Administration, Beijing 100081, China4Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China

(Received 6 November 2019; revised 27 February 2020; accepted 3 March 2020)

ABSTRACT

The balloon-borne Aircore campaign was conducted in Inner Mongolia, China, on June 13 and 14 2018, whichdetected carbon dioxide (CO2) and carbon monoxide (CO) profiles from surface to 24 km, showing strong positive andnegative correlations between 8 km and 10 km on 13 and 14 June, respectively. Backward trajectories, meteorologicalanalyses, and CO2 horizontal distributions were combined to interpret this phenomenon. The results indicated that thesource region experienced a stratospheric intrusion and exhibited a large horizontal CO2 gradient; namely, lower COconcentrations corresponded to higher CO2 concentrations and vice versa. The laminar structure with multiple originsresulted in the highly negative correlation between CO2 and CO in the upper troposphere on 14 June. The contribution ofstratospheric air mass to the upper troposphere and that of tropospheric air mass to the lower stratosphere were 26.7% and24.3%, respectively, based on a mass balance approach. Another interesting phenomenon is that CO2 and COconcentrations increased substantially at approximately 8 km on 13 June. An analysis based on the backward trajectoryimplied that the air mass possibly came from anthropogenic sources. The slope of CO2/CO representing the anthropogenicsources was 87.3 ppm ppm−1. In addition, the CO2 profile showed that there was a large CO2 gradient of 4 ppm km−1 withinthe boundary layer on 13 June, and this gradient disappeared on 14 June.

Key words: profile measurements, CO2, CO, atmospheric transport, stratosphere–troposphere exchange

Citation: Yi, Y., and Coauthors, 2020: Direct observations of atmospheric transport and stratosphere–troposphereexchange from high-precision carbon dioxide and carbon monoxide profile measurements. Adv. Atmos. Sci., 37(6),608−616, https://doi.org/10.1007/s00376-020-9227-2.

Article Highlights:

•  CO2 and CO profiles from the surface to 25 km in Xilinhot, Inner Mongolia, on 13 and 14 June 2018 were observedusing in-situ measurements.•  CO2 and CO concentrations increased substantially at approximately 8 km on 13 June because of long-range transport,and the slope of CO2/CO was 87.3 ppm ppm−1.•  CO2 and CO profiles were highly positively correlated on 13 June and highly negatively correlated on 14 June in theupper troposphere between 8 km and 10 km owing to the stratosphere–troposphere exchange and the large horizontalgradient of CO2.

  

1.    Introduction

Carbon dioxide (CO2) is an important greenhouse gasthat has increased in the atmosphere since pre-industrial

times. Detailed observations of CO2 transport and vertical pro-files are needed to better understand carbon cycling in theEarth system. Several satellites, including OCO-2 (OrbitingCarbon Observation-2), GOSAT (Greenhouse GasesObserving Satellite), and TanSat (the Chinese dedicatedCO2-monitoring satellite), measure CO2 levels within thetotal atmospheric column globally over several days, while

 

  * Corresponding author: Yuli ZHANG

Email: zhangyuli@mail.iap.ac.cn 

 

ADVANCES IN ATMOSPHERIC SCIENCES, VOL. 37, JUNE 2020, 608–616 • Original Paper •

 

© Institute of Atmospheric Physics/Chinese Academy of Sciences, and Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020  

ground-based stations provide information on spatial/tem-poral CO2 variations and long-term trends. Vertical CO2

information is limited, but it is an important component inthe accurate calculation of regional carbon fluxes. The ver-tical distribution of CO2 varies with region due to vari-ations in atmospheric circulation. One important atmo-spheric process is the stratosphere–troposphere exchange(STE), a bidirectional process that influences the distribu-tion of trace gases in the upper troposphere and lower strato-sphere (UTLS) (Holton et al., 1995). Global aspects of STEare linked with general circulation, including the roles ofwaves, eddies, and mesoscale structures such as jet streamsand extratropical cyclone dynamics (Holton et al., 1995).The CO2 distribution would reflect such large-scaledynamic processes since CO2 has a long chemical lifetimein the atmosphere. Profiles of CO2 were used to investigatethe STE over Siberia (Sawa et al., 2004), and Inai et al.(2018) combined backward trajectory analysis with ana-lysis of vertical profiles of CO2 and found that the CO2 distri-bution in the troposphere over the equatorial Pacific was con-trolled by the monthly large-scale CO2 distribution andweekly atmospheric transport processes. The direct impactof CO2 is to change radiative. Xie et al. (2008) investigatedthe radiative effects of the CO2 doubling on the STE.

Unlike CO2, carbon monoxide (CO) has rapidlydecreased in the stratosphere and is more sensitive, varyingover short time scales (Gettelman et al., 2011). Thus, CO isoften deemed a tropospheric tracer and is linked with strato-spheric tracers such as ozone (O3) to identify the location ofthe tropopause (Zahn et al., 2002). This method, known astracer–tracer correlation, is also used to examine the distribu-tion of mixed air masses and their different source regions(Hoor et al., 2002; Pan et al., 2004; Sawa et al., 2004; Pariset al., 2010).

To better understand and quantify STE, high-resolu-tion in-situ measurements and numerical simulations are indis-pensable. Many aircraft campaigns, such as SPURT (Engelet al., 2006) and START08 (Pan et al., 2010), have been con-ducted to better interpret the distribution and budgets oftracers under different STE processes associated with typ-ical meteorological backgrounds. Hoor et al. (2005) used in-situ CO measurements from SPURT to determine that the con-tribution of extratropical tropospheric air is less than 25%within the potential temperature range of 25 K above the tro-popause mixing layer, whereas a greater portion of the tropo-spheric portion in that layer is derived from the tropics.Tarasick et al. (2019) used balloon ozonesondes and traject-ory models to determine that the contribution of strato-spheric air mass is approximately 26% in the upper andmiddle troposphere, 15% in the lower troposphere, and4.6% in the boundary layer. Xie et al. (2016) quantified thetransport of surface emissions from different regions intothe stratosphere by using numerical simulations.

We conducted aircore campaigns in inner Mongolia inJune 2018 and derived the vertical distributions of CO2 andCO from the surface to ~25 km. Aircore, which was

designed by Tans (2009), is a long stainless-steel tube openat one end. A balloon brings it to high altitude and then theaircore can collect samples during its descent. Thus, we cancollect atmospheric samples from the ground to around25 km.

In this study, we first analyzed the profiles of CO2 andCO in three layers of the atmosphere: the boundary, free tro-posphere, and lower stratosphere. Next, backward traject-ory analysis was combined with an analysis of atmosphericcolumn-averaged dry air mole fractions of carbon monox-ide (XCO) measured using the Tropospheric MonitoringInstrument (TROPOMI) (Landgraf et al., 2016) to fully illus-trate the difference in the vertical distribution of CO in thefree troposphere. The tracer–tracer correlation method wasthen applied to the simultaneously measured CO and CO2

data to distinguish different source regions. Finally, meteoro-logical analysis, backward trajectory analysis, and totalcolumn-averaged CO2 data were used to comprehensivelyinterpret the change in correlation trend between CO andCO2 and further quantify the different source distributions.

2.    Data and methods

2.1.    Aircore campaign at Xilinhot, Inner Mongolia

The aircore campaign is an important component of theSTEAM (Stratosphere and Troposphere Exchange Experi-ment over Asian Summer Monsoon) project, the aim ofwhich is to improve the understanding of the chemical anddynamic processes in the UTLS. We conducted the first air-core campaign at Xilinhot (43.9°N, 116.1°E), Inner Mongo-lia, on 13 and 14 June 2018. Xilinhot is an area in which acut-off low often occurs in June, which impacts the verticaldistribution of trace gases in the UTLS (Liu et al., 2013).

Two 30-m-long stainless-steel tubes with different dia-meters, carried on a 1000-m3 zero-pressure plastic balloon,sampled a column of air from the surface to 25 km. Aftersounding, a Picarro (G2302, https://www.picarro.com) wasused to analyze the mixing ratio of trace gases in thesample. The resolution of aircore data depends on the lengthand width of the tube and the elapsed time of storage; alonger and thinner tube and a shorter elapsed time result in ahigher resolution (Membrive et al., 2017). To maximize theresolution of aircore sampling, the Picarro G2302 was trans-ported to the campaign field instead of transporting the air-core back to the laboratory. Based on the data processingmethod of Karion et al. (2011), two CO2 profiles and two sim-ultaneously measured CO profiles were derived. Moredetailed information about the campaign can be found in Yi(2019).

2.2.    Atmospheric backward transport model

Atmospheric transport was investigated using theHybrid Single-Particle Lagrangian Integrated Trajectory(HYSPLIT) model (Stein et al., 2015). The model is ahybrid between a Lagrangian approach for advection and dif-fusion calculations and a Eulerian methodology to calculate

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pollutant air concentrations. The trajectory results presen-ted here use European Centre for Medium-Range WeatherForecasts (ECMWF) analysis fields. In this study, for CO2,a 48-h backward trajectory was used to investigate the trans-port pathways from potential source regions to our cam-paign site. For CO, which is a short-lifetime tracer, a 24-hbackward trajectory was applied to analyze its origin. Back-ward time determination was carried out according to ourexperimental dates; namely, 13 and 14 June 2018. The traject-ory differences are discussed in section 3.

3.    Campaign observations

3.1.    Meteorological overview

Meteorology strongly affects the distribution of all meas-ured species. We used the ECMWF’s interim reanalysis(ERA-Interim) for meteorological analysis. The ERA-Interim data had a horizontal resolution of 0.75° × 0.75° andwere classified according to 37 vertical pressure levels extend-ing from 1000 hPa to 1 hPa.

Figures 1a and b show the temperature, potential vorti-city (PV) isolines, and wind at 300 hPa and geopotential

 

 

Fig. 1. (a, b) ERA-Interim temperature (units: K; shaded area), PV contours (2, 4, 6, and 8 PVU; black lines),geopotential height (units: m; gray lines) and wind bars (units: m s−1) at 300 hPa, with the campaign location markedby the red pentagram: (a) 0000 UTC 13 June 2018; (b) 0000 UTC 14 June 2018. (c, d) Potential temperature lapserate cross-section along 116°E with zonal wind (units: m s−1; solid gray line), the 2-PVU isoline and 4-PVU isoline(black dashed line) and thermal tropopause (black solid line) according to the definition of WMO derived usingERA-Interim, Y-axis is pressure (hPa): (c) 0000 UTC 13 June 2018; (d) 0000 UTC 14 June 2018.

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height during the aircore campaign. The 2-PVU (1 PVU=1.0×10−6 Km2 kg−1 s−1) isoline represents the dynamic tropo-pause. Figure 1a shows that an isolated cyclone with 2-PVUand 4-PVU isolines occurred at 300 hPa around Xilinhot.Then, on 14 June, the cyclone moved southeast, and a north-westerly wind dominated Xilinhot at 300 hPa. In addition, astrong cyclone at 60°N with high PV values extended closerto the Baikal region (Fig. 1b). Overall, Xilinhot was underthe influence of a stratospheric air mass on 13 June and a tro-pospheric air mass on 14 June at 300 hPa.

Pan et al. (2009) indicated that the potential temperat-ure lapse rate (PTLR) is a diagnostic for a stratospheric intru-sion event; tropospheric air has a PTLR < 10 K km−1, andthe PTLR of background stratospheric air is > 15 K km−1.Figures 1c and d show the PTLR cross section along 116°Etogether with 2-PVU isoline, 4-PVU isoline and thermal tro-popause and zonal winds of 20, 30, and 40 m s−1. On 13June, the subtropical jet stream extended to 40°N, and a fun-nel-shaped tropopause that reached as low as 340 hPa was loc-ated at around 41.5°N, similar to the result shown in Liu etal. (2013). In addition, another funnel-shaped tropopauseoccurred at around 55°N (Fig. 1a), and a strong cyclonewith high PV values occurred at around 55°N. These two fun-nel-shaped tropopauses resulted in a ridge-shaped tropo-pause region at around 48°N, where the 2-PVU isoline wasas high as 200 hPa. For the PTLR, low PTLR air extendedinto high latitudes from the subtropics at around 150 hPa.High PTLR air from the pole moved equatorward, resultingin a layer of high-stability air above the tropopause ataround 48°N. On 14 June, the subtropical jet moved south-ward, and the large zonal gradient of PV values around Xilin-hot disappeared, indicating that mixing between the tropo-sphere and stratosphere occurred from 13 to 14 June in thatregion. Meanwhile, at 58°N, the funnel-shaped tropopausestill existed and extended deeper on 14 June, which was cor-related with the strong cyclone with high PV values extend-ing closer to the Baikal region (Fig. 1b). For PTLR, low-sta-bility air extended from the subtropics into high latitudes,and the process was even stronger than on 13 June. Then,the high-stability air extending from high latitudes to the sub-tropics was cut off by the low-stability air at 58°N. Thehigh-stability air at 48°N above the tropopause becameweaker on 14 June, indicating a possible mode of down-ward transport and mixing with low-stability air. Gettelmanet al. (2011) noted that the quasi-isentropic exchange associ-ated with the subtropical jet stream results in reduced staticstability. This is another possible explanation for why the 2-PVU isoline at 48°N became lower on 14 June. To summar-ize, the dynamical tropopause on 13 June was lower than on14 June, and the upstream STE influenced our measured in-situ profiles.

3.2.    Vertical distributions of CO and CO2

Figure 2 shows the in-situ measured profiles of CO2

and CO at Xilinhot on 13 and 14 June 2018. Each profile com-prises approximately 430 points. In the experimental setup,a high CO mixing ratio was used to fill the tube to distin-

guish the starting position of the sample. Thus, the CO atthe beginning of the stratospheric sample was rapidly mixedwith fill gas, losing its true information. We discarded theCO values above 22 km.

3.2.1.    Boundary layer

On 13 June (Fig. 2a), the CO2 concentration decreasedfrom 409.5 ppm near the surface to 405.0 ppm at the top ofthe boundary layer, with a large vertical gradient of 4 ppmkm−1. Such a structure indicates that the atmospheric bound-ary layer was stable, which constrained vertical mixing andtransport. On 14 June (Fig. 2b), CO2 levels were highest atthe top of the boundary layer but were evenly distributed.This structure indicates that strong mixing occurred withinthe boundary layer on 14 June.

3.2.2.    Free troposphere

On 13 June, the lowest CO2 concentration of 405 ppmwas observed at 3 km and the highest concentration of 409ppm was observed at 8 km. The mean vertical gradient was0.8 ppm km−1 between 3 and 8 km. Sources of CO2 aremainly near the surface; the farther away the ground, thelower the CO2 concentration. The high CO2 concentrationthat occurred at 8 km was due to the easterly wind (Fig. 3a),which brings the strong anthropogenic sources from the north-east of China. To interpret the airmass origin, the trajectorymodel HYSPLIT was used. The ERA-Interim dataset,which is the same dataset as used in the previous meteorolo-gical analyses, was used as the meteorological forcing field.On 13 and 14 June, 24-h backward trajectories were initi-ated at Xilinhot. The trajectories were added to the hori-zontal distribution of XCO derived from TROPOMI (Fig. 3).The air mass at lower altitudes around 3 km came from anearby region where the CO mixing ratio was ~95 ppb andwas transported slowly by an easterly flow (Fig. 3). The airmass at around 8 km came from the east of Xilinhot wherethe CO mixing ratio exceeded 140 ppb. From the above ana-lysis, the background atmospheric CO2 and CO concentra-tions at Xilinhot were approximately 405 ppm and 100 ppb,respectively. When Xilinhot received an air mass from North-east China, CO2 and CO concentrations increased to 409ppm and 160 ppb, respectively. On 14 June, CO2 and COwere both evenly distributed in the free troposphere due tothe strong northwesterly wind (Fig. 1b). The CO2 minimum(~404 ppm) occurred at 8 km, and the backward trajectoryindicated that the airmass was mainly from the Baikalregion where the forest is dense and anthropogenic emis-sions are few. An interesting phenomenon is the negative cor-relation between CO and CO2; this correlation was linear inthe upper troposphere, and the reason for this observation isdiscussed in section 4.

3.2.3.    UTLS

Large differences of the CO and CO2 concentration andtheir relationship in the UTLS were observed between 13and 14 June. The thermal tropopause according to the defini-tion of the World Meteorological Organization (WMO) was

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at 11 km on both days; however, according to Figs. 1a andb, the dynamic tropopause was at 340 hPa on 13 June and250 hPa on 14 June. The vertical distributions of CO2 andCO were quite different. On 13 June, the highest CO2 concen-tration was observed at 8 km (mentioned above), and CO2

and CO concentrations both decreased with increasing alti-tude. CO concentrations decreased faster than those of CO2,from 160 ppb at 8 km to 24 ppb at 14 km, but maintained sim-ilar values above 12.6 km. Meanwhile, the CO2 concentra-tion decreased from 409 ppm at 8 km to 404 ppm at 11.6 km,and then gradually decreased to 403 ppm at 14 km. Overall,on 13 June, CO and CO2 concentrations decreased linearly

in the UTLS. On 14 June, CO and CO2 concentrations werelinearly and negatively correlated between 7.5 and 11 kmand both exhibited a laminar structure. In addition, the rateof CO decrease was small on 14 June compared to the rateon 13 June above the thermal tropopause; it decreased from95 ppb at 10.5 km to 30 ppb at 14 km, whereas CO2

increased by ~1 ppm between 10.5 km and 11 km and thendecreased to 403.8 ppm at 14 km. Overall, in the lower-most stratosphere (LS), the CO mixing ratio on 14 June washigher than on 13 June. In the upper troposphere, the CO mix-ing ratio on 14 June was lower than on 13 June.

 

 

Fig. 2. (a) CO2 (red) and CO (blue) profiles, relative humidity (magenta) and temperature (black) profiles measuredsimultaneously 13 June. The y-axis represents height (km) above mean sea level; the dashed lines represent thetropopause according to the definition of the WMO; and the dash-dotted lines represent the dynamical tropopause.(b) As in (a) but for 14 June.

 

 

Fig. 3. Averaged total column mixing ratio of CO measured by TROPOMI around Xilinhot together with the 24-hbackward trajectory at lower altitude and higher altitude on (a) 13 June and (b) 14 June 2018.

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3.2.4.    Middle stratosphere

In the middle stratosphere, the variations in CO2 andCO concentrations on the two consecutive days were sim-ilar. CO2 concentration increased at ~15 km, and this trendwas also described by Engel et al. (2017). Their aircore wasalso released at midlatitude, so this small structure may repres-ent a large-scale pattern at midlatitude. The CO concentra-tion in the middle stratosphere maintained a steady value of~20 ppb, while the lapse rate of CO2 concentration was ~0.5ppm km−1 between 15 and 25 km.

4.    Applying the ratio of CO2 to CO toquantify sources

Atmospheric circulation plays an important role in thehorizontal and vertical distributions of CO and CO2 afterthey emit from sources. Generally, at the large scale, atmo-spheric tracers are transported with flow over long dis-tances if they are chemically inert, like CO2. However, ifthe tracer is chemically active, it will change depending onthe chemical reaction it undergoes; for example, CO exhib-its a large vertical gradient over the UTLS. If we focus onthe small scale, atmospheric mixing also plays a role in thedistribution of tracers, especially in the presence of strongwind shear and a large gradient of tracers. As a result, the ver-tical distributions of tracers can be strongly influenced bytransport, mixing, and the chemistry of short-lived tracers.On the other hand, we can simultaneously derive the trans-port process and mixing information if we know the pro-files of different tracers.

From the above analysis, on 13 June, the backward tra-jectories indicated that the air mass originated from differ-

ent locations. On 14 June, the distributions of CO and CO2

in the UTLS illustrated that tropospheric air and strato-spheric air were mixing. To clearly quantify their differentsources, the CO2/CO slopes are used to represent thesources. CO2/CO is widely used to distinguish the differentsources of CO2 (combustion types versus terrestrial bio-sphere) (Suntharalingam et al., 2004; Wang et al., 2010).The CO2/CO slopes in this analysis were obtained using thereduced major axis (RMA) method; this method is oftenused to derive CO2/CO slopes (Suntharalingam et al., 2004;Wang et al., 2010).

4.1.    Differences between background and anthropogenicsources

As discussed above, on 13 June, the air mass at around3 km originated from a nearby grassland, and trace gas con-centrations were low. The CO2/CO slope at this altitude was136 (ppm ppm−1) (Fig. 4a, magenta line), which was twicethat calculated in an aircraft campaign (TRACE-P) inMarch 2009 (Suntharalingam et al., 2004). The CO2/COslope varies temporally and spatially, and overall, 130 (ppmppm−1) is a typical value of the background tropospheric airin Xilinhot, Inner Mongolia, in June.

At 8 km, the air mass originated from Northeast China;XCO levels were relatively high, indicating a strong anthropo-genic source. In Fig. 4a, most of the points in the scatter-plot are located in the upper-right corner (blue points) andthe slope becomes smaller than the background value. TheCO2/CO slope representing an anthropogenic source was82.3 (ppm ppm−1), similar to the value of 15 ppb ppm−1 [equi-valent to a CO2/CO slope of 67 (ppm ppm−1)] calculated byLiu et al. (2018) over Northeast China. Our result was relat-ively higher due to the mixing of anthropogenic and back-

 

 

Fig. 4. Scatterplot of CO2 versus CO on (a) 13 June and (b) 14 June. Points are divided into four groups according tothe value of ΔCO/ΔCO2 and shown in four colors that indicate the corresponding altitudes. The RMA linearregression with slope “Slope” is plotted (solid line).

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ground air.

4.2.    Variation in the UTLS

The negative correlation between CO and CO2 concentra-tions that occurred in the UTLS on 14 June, which was con-trary to the trend observed on 13 June, was quite unusualand is difficult to explain.

A previous study (Pan et al., 2009) demonstrated thatthe low PTLR in the tropics moves northward and the highPTLR in the polar region moves southward when the subtrop-ical jet is enhanced; these are typical midlatitude STE pro-cesses. In Xilinhot, at the 300 hPa (~8.8 km) isobar surface,the PV value was higher than 2 PVU on 13 June and lowerthan 2 PVU on 14 June, suggesting that stratospheric airwas dominant at 300 hPa on 13 June but tropospheric airwas dominant on 14 June.

Based on the analyses in the previous section, there wasa large vertical gradient of CO over the UTLS region, andthe lifetime of CO is much shorter than that of CO2, so wecan apply CO as a tracer to separate the air over the UTLS.From backward trajectory analyses (Fig. 3a), on 14 June,the air mass mainly came from the Baikal region. A strongcyclone with high PV values extended closer to the Baikalregion, indicating that a stratospheric intrusion may havehappened in that area (Fig. 1b). To better understand the influ-ence of the source region on the negative correlationbetween CO and CO2 concentrations at Xilinhot over7.5–12 km, Fig. 5a presents the PTLR cross section along100°E together with the 24-h backward trajectory calcu-lated from 14 June at Xilinhot. At around 56°N, 24 h beforethe air mass reached Xilinhot, the black line indicates thatan air mass with higher static stability was transported down-ward to around 10.3 km, resulting in a sandwich-like PTLR

distribution. CO2 is an inert chemical tracer and its sourcesare concentrated on the surface; the impact of these sourcescan be transported to the upper troposphere and lower strato-sphere through atmospheric circulation. CO2 has a strong sea-sonal cycle because biospheric activity is strong in summerand weak in winter; thus, CO2 is a chemical tracer that exhib-its seasonal variation. Figure 5b shows the monthly meanatmospheric column-averaged dry air mole fractions of car-bon dioxide (XCO2) derived from GOSAT and the 48-h back-ward trajectory. The trajectory passed the steep horizontalgradient area, the black line passed the area of 406 ppmCO2, and the other two lines passed the area where CO2 was~404 ppm. The lowest concentration of CO2 in the free tropo-sphere on 14 June was ~404 ppm, corresponding well withthe source region. The vertical exchange in the UTLS with ahorizontal gradient of CO2 resulted in a strong negative correl-ation between CO and CO2 between 8 and 11 km.

According to Hoor et al. (2005), CO values rangingfrom 40 to 75 ppb indicate a mixture of tropospheric and stra-tospheric air. CO concentrations were within this rangebetween 11.4 and 12.4 km on 13 June and between 12 and13.3 km on 14 June. The CO2/CO slopes on these days weresimilar at these altitudes. A CO2/CO slope of zero wasobserved at ~13 km, suggesting that the influence of tropo-spheric air had become weaker.

4.3.    Quantifying stratospheric and troposphericcontributions

According to the above trajectory analysis, the 24-h back-ward trajectory at Xilinhot from 14 June indicated that theair mass was from the Baikal region where an STE processoccurred on 13 June. From our in-situ measured CO profileon 14 June, CO concentrations were higher in the LS and

 

 

Fig. 5. (a) Potential temperature lapse rate cross-section along 100°E on 13 June. The green, black and magenta linesrepresent 1-day backward trajectories initialized at 8.7 km, 9.7 km and 10.7 km, respectively, at the campaign site.(b) Monthly averaged total column mixing ratio of CO2 from GOSAT observations. Lines are the same as in (a) but2-day backward trajectories; each circle on the lines represents one day.

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lower in the upper troposphere compared to concentrationsmeasured on 13 June. To quantify the STE, we used themass balance approach of Hoor et al. (2005) and our in-situmeasured CO profile to estimate the stratospheric contribu-tion to the upper troposphere and the tropospheric contribu-tion to the lower stratosphere. The main theory of the massbalance approach is as follows: the air mass at the disturbedarea is derived from the mixing of various air parcels with dif-ferent mixing ratios and different ages, and the sum of mix-ing ratios of the various air parcels is 1. In this context, theLS value and upper tropospheric value of our measured COconsisted of the background stratospheric value and theextratropical tropospheric value. Thus, in the LS, 

fbkgdCbkgd+ ftropCtrop =Cmeas,LS , (1)

with fbkgd+ftrop=1. fbkgd represents the background strato-spheric contribution to the measured LS airmass, ftrop repres-ents the tropospheric contribution to the measured LS air-mass. For the background stratospheric value Cbkgd, we aver-aged the values of the two in-situ CO profiles above 15 km,which is far away from the troposphere, instead of using thereference value. For the tropospheric value Ctrop, we com-bined the in-situ measured CO and the XCO derived fromTROPOMI. Note that for 13 and 14 June, the troposphericCO values are different, since it is significantly higher on 13June, which is shown in Fig. 2a. We extracted the XCOvalue along the 24-h trajectory and considered the devi-ation of TROPOMI data from our measured in-situ profile.Finally, the typical tropospheric CO value on 13 June, Ctrop, 13

and 14 June, Ctrop, 14, was 120 ppb and 91 ppb, respectively.Cmeas, LS was calculated for separate two days, and the meanmeasured CO values in the LS on 13 June, Cmeas, LS, 13, and14 June, Cmeas, LS, 14, were 35.4 and 48.2 ppb, respectively.

Thus, the background contribution on 13 June, fbkgd, 13,and 14 June, fbkgd, 14, and the tropospheric contribution on13 June, ftrop, 13, and 14 June, ftrop,14, can be derived accord-ing to Eq. (1). The deviation between the tropospheric contri-bution on 13 June, ftrop, 13, and 14 June, ftrop, 14, was the tropo-spheric contribution due to the STE process, which was24.3%.

In the upper troposphere, the mean CO values on 13and 14 June were 140 and 87 ppb, respectively. The CO mix-ing ratio in the upper troposphere on 14 June representedthe mixture of the typical tropospheric CO value along the tra-jectory and the remaining CO from 13 June. In order to estim-ate the value of remaining CO from 13 June, we calculatedthe relative change from 13 to 14 June between 4 and 8 kmwhere the air mass was not influenced by stratospheric intru-sion. Thus, we can derive the CO value between 8 and 11km without the stratospheric intrusion. The stratospheric con-tribution is the deviation between the calculated CO valueand the measured CO value. Finally, the stratospheric contri-bution between 8 and 11 km is 26.7%.

Overall, the stratospheric contribution to the upper tropo-sphere was approximately 26.7% and the tropospheric contri-bution to the LS was approximately 24.3% in our measured

CO profile on 14 June.

5.    Conclusions

We developed an aircore system based on the proto-type (Tans, 2009; Karion et al., 2010). Our aircore consistsof a 60-m-long tube constructed using a combination of 30m of 0.125-inch tubing and 30 m of 0.25-inch tubing toimprove the resolution in the UTLS region (Membrive etal., 2017). The aircore campaign was conducted at Xilinhoton 13 and 14 June 2018.

The CO2 profiles on 13 and 14 June differed. On 13June, a large gradient of 4 ppm km−1 was observed in theboundary layer, whereas on 14 June CO2 concentrationswere consistent within the boundary layer. In the free tropo-sphere, a maximum CO2 concentration of 408 ppm wasobserved at 8 km under the influence of easterly winds thattransported CO2 from significant anthropogenic sources toXilinhot on 13 June. The slope of CO2/CO representing thestrong anthropogenic source was 82.3 ppm ppm−1. On 14June, the CO2 concentration decreased with altitude, and thelowest value of 404 ppm occurred at 8 km where the airmass originated from the Baikal region. Interestingly, COand CO2 concentrations were strongly and positively correl-ated on 13 June and strongly and negatively correlated on14 June. Upstream of Xilinhot, an STE event occurred on13 June, and the influence of the event was transported tothe campaign site on 14 June. Upon analysis of the verticaldistribution of PTLR and the horizontal distribution ofXCO2, we found that the trajectory with a higher PTLRregion, which was indicated by lower CO concentrations,passed by the region with the highest CO2 concentration.Thus, an unusual strong negative correlation between COand CO2 developed in the upper troposphere on 14 June.Based on the mass balance approach, a background strato-spheric airmass was transported downward, contributing26.7% to the upper troposphere, and tropospheric air masswas transported upward, contributing 24.3% to the LS.

Furthermore, this study shows that combining in-situCO and CO2 profiles with backward trajectories is a usefulway to investigate horizontal and vertical airmass transportand interpret the combined effect of airmass transports bring-ing different structures among gas species. Besides, the modi-fied mass balance approach in specific cases can semi-quantify the contribution of the stratospheric intrusion. Tofully understand the airmass transport, especially in theUTLS region, an aircore campaign designed to simultan-eously measure more gas species in the Tibetan region, suchas CH4, N2O and O3, will also be conducted. The interrelation-ships among these species will help to provide more detailsregarding the attributes of airmass transport.

Acknowledgements.    This research was supported by grantsfrom the Strategic Priority Research Program of the ChineseAcademy of Sciences (CAS) (Grant No. XDA17010100), theNational Natural Science Foundation of China (Grant No.41875043), the Youth Innovation Promotion Association, CAS, the

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Key Research Program of CAS (Grant No. ZDRW-ZS-2019-1), andthe External Cooperation Program of CAS (Grant No. GJHZ 1802).

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