Direct Observations of Atmospheric Transport and Stratosphere-Troposphere Exchange from High-Precisi

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1. Introduction

Carbon dioxide (CO₂) is an important greenhouse gas that has increased in the atmosphere since pre-industrial times. Detailed observations of CO₂ transport and vertical profiles are needed to better understand carbon cycling in the Earth system. Several satellites, including OCO-2 (Orbiting Carbon Observation-2), GOSAT (Greenhouse Gases Observing Satellite), and TanSat (the Chinese dedicated CO₂-monitoring satellite), measure CO₂ levels within the total atmospheric column globally over several days, while ground-based stations provide information on spatial/temporal CO₂ variations and long-term trends. Vertical CO₂ information is limited, but it is an important component in the accurate calculation of regional carbon fluxes. The vertical distribution of CO₂ varies with region due to variations in atmospheric circulation. One important atmospheric process is the stratosphere–troposphere exchange (STE), a bidirectional process that influences the distribution of trace gases in the upper troposphere and lower stratosphere (UTLS) (Holton et al., 1995). Global aspects of STE are linked with general circulation, including the roles of waves, eddies, and mesoscale structures such as jet streams and extratropical cyclone dynamics (Holton et al., 1995). The CO₂ distribution would reflect such large-scale dynamic processes since CO₂ has a long chemical lifetime in the atmosphere. Profiles of CO₂ were used to investigate the STE over Siberia (Sawa et al., 2004), and Inai et al. (2018) combined backward trajectory analysis with analysis of vertical profiles of CO₂ and found that the CO₂ distribution in the troposphere over the equatorial Pacific was controlled by the monthly large-scale CO₂ distribution and weekly atmospheric transport processes. The direct impact of CO₂ is to change radiative. Xie et al. (2008) investigated the radiative effects of the CO₂ doubling on the STE.
Unlike CO₂, carbon monoxide (CO) has rapidly decreased in the stratosphere and is more sensitive, varying over short time scales (Gettelman et al., 2011). Thus, CO is often deemed a tropospheric tracer and is linked with stratospheric tracers such as ozone (O₃) to identify the location of the tropopause (Zahn et al., 2002). This method, known as tracer–tracer correlation, is also used to examine the distribution of mixed air masses and their different source regions (Hoor et al., 2002; Pan et al., 2004; Sawa et al., 2004; Paris et al., 2010).
To better understand and quantify STE, high-resolution in-situ measurements and numerical simulations are indispensable. Many aircraft campaigns, such as SPURT (Engel et al., 2006) and START08 (Pan et al., 2010), have been conducted to better interpret the distribution and budgets of tracers under different STE processes associated with typical meteorological backgrounds. Hoor et al. (2005) used in-situ CO measurements from SPURT to determine that the contribution of extratropical tropospheric air is less than 25% within the potential temperature range of 25 K above the tropopause mixing layer, whereas a greater portion of the tropospheric portion in that layer is derived from the tropics. Tarasick et al. (2019) used balloon ozonesondes and trajectory models to determine that the contribution of stratospheric air mass is approximately 26% in the upper and middle troposphere, 15% in the lower troposphere, and 4.6% in the boundary layer. Xie et al. (2016) quantified the transport of surface emissions from different regions into the stratosphere by using numerical simulations.
We conducted aircore campaigns in inner Mongolia in June 2018 and derived the vertical distributions of CO₂ and CO from the surface to ~25 km. Aircore, which was designed by Tans (2009), is a long stainless-steel tube open at one end. A balloon brings it to high altitude and then the aircore can collect samples during its descent. Thus, we can collect atmospheric samples from the ground to around 25 km.
In this study, we first analyzed the profiles of CO₂ and CO in three layers of the atmosphere: the boundary, free troposphere, and lower stratosphere. Next, backward trajectory analysis was combined with an analysis of atmospheric column-averaged dry air mole fractions of carbon monoxide (XCO) measured using the Tropospheric Monitoring Instrument (TROPOMI) (Landgraf et al., 2016) to fully illustrate the difference in the vertical distribution of CO in the free troposphere. The tracer–tracer correlation method was then applied to the simultaneously measured CO and CO₂ data to distinguish different source regions. Finally, meteorological analysis, backward trajectory analysis, and total column-averaged CO₂ data were used to comprehensively interpret the change in correlation trend between CO and CO₂ and further quantify the different source distributions.

2. Data and methods

2.1. Aircore campaign at Xilinhot, Inner Mongolia

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2.1. Aircore campaign at Xilinhot, Inner Mongolia

The aircore campaign is an important component of the STEAM (Stratosphere and Troposphere Exchange Experiment over Asian Summer Monsoon) project, the aim of which is to improve the understanding of the chemical and dynamic processes in the UTLS. We conducted the first aircore campaign at Xilinhot (43.9°N, 116.1°E), Inner Mongolia, on 13 and 14 June 2018. Xilinhot is an area in which a cut-off low often occurs in June, which impacts the vertical distribution of trace gases in the UTLS (Liu et al., 2013).
Two 30-m-long stainless-steel tubes with different diameters, carried on a 1000-m³ zero-pressure plastic balloon, sampled a column of air from the surface to 25 km. After sounding, a Picarro (G2302, https://www.picarro.com) was used to analyze the mixing ratio of trace gases in the sample. The resolution of aircore data depends on the length and width of the tube and the elapsed time of storage; a longer and thinner tube and a shorter elapsed time result in a higher resolution (Membrive et al., 2017). To maximize the resolution of aircore sampling, the Picarro G2302 was transported to the campaign field instead of transporting the aircore back to the laboratory. Based on the data processing method of Karion et al. (2011), two CO₂ profiles and two simultaneously measured CO profiles were derived. More detailed information about the campaign can be found in Yi (2019).

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2.2. Atmospheric backward transport model

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2.2. Atmospheric backward transport model

Atmospheric transport was investigated using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model (Stein et al., 2015). The model is a hybrid between a Lagrangian approach for advection and diffusion calculations and a Eulerian methodology to calculate pollutant air concentrations. The trajectory results presented here use European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields. In this study, for CO₂, a 48-h backward trajectory was used to investigate the transport pathways from potential source regions to our campaign site. For CO, which is a short-lifetime tracer, a 24-h backward trajectory was applied to analyze its origin. Backward time determination was carried out according to our experimental dates; namely, 13 and 14 June 2018. The trajectory differences are discussed in section 3.

3. Campaign observations

3.1. Meteorological overview

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3.1. Meteorological overview

Meteorology strongly affects the distribution of all measured 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° and were classified according to 37 vertical pressure levels extending from 1000 hPa to 1 hPa.
Figures 1a and b show the temperature, potential vorticity (PV) isolines, and wind at 300 hPa and geopotential height during the aircore campaign. The 2-PVU (1 PVU=1.0×10^?6 Km² kg^?1 s^?1) isoline represents the dynamic tropopause. Figure 1a shows that an isolated cyclone with 2-PVU and 4-PVU isolines occurred at 300 hPa around Xilinhot. Then, on 14 June, the cyclone moved southeast, and a northwesterly wind dominated Xilinhot at 300 hPa. In addition, a strong cyclone at 60°N with high PV values extended closer to the Baikal region (Fig. 1b). Overall, Xilinhot was under the influence of a stratospheric air mass on 13 June and a tropospheric air mass on 14 June at 300 hPa.

Figure1. (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 marked by the red pentagram: (a) 0000 UTC 13 June 2018; (b) 0000 UTC 14 June 2018. (c, d) Potential temperature lapse rate 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 using ERA-Interim, Y-axis is pressure (hPa): (c) 0000 UTC 13 June 2018; (d) 0000 UTC 14 June 2018.

Pan et al. (2009) indicated that the potential temperature lapse rate (PTLR) is a diagnostic for a stratospheric intrusion event; tropospheric air has a PTLR < 10 K km^?1, and the PTLR of background stratospheric air is > 15 K km^?1. Figures 1c and d show the PTLR cross section along 116°E together with 2-PVU isoline, 4-PVU isoline and thermal tropopause and zonal winds of 20, 30, and 40 m s^?1. On 13 June, the subtropical jet stream extended to 40°N, and a funnel-shaped tropopause that reached as low as 340 hPa was located at around 41.5°N, similar to the result shown in Liu et al. (2013). In addition, another funnel-shaped tropopause occurred at around 55°N (Fig. 1a), and a strong cyclone with high PV values occurred at around 55°N. These two funnel-shaped tropopauses resulted in a ridge-shaped tropopause region at around 48°N, where the 2-PVU isoline was as high as 200 hPa. For the PTLR, low PTLR air extended into high latitudes from the subtropics at around 150 hPa. High PTLR air from the pole moved equatorward, resulting in a layer of high-stability air above the tropopause at around 48°N. On 14 June, the subtropical jet moved southward, and the large zonal gradient of PV values around Xilinhot disappeared, indicating that mixing between the troposphere and stratosphere occurred from 13 to 14 June in that region. Meanwhile, at 58°N, the funnel-shaped tropopause still existed and extended deeper on 14 June, which was correlated with the strong cyclone with high PV values extending closer to the Baikal region (Fig. 1b). For PTLR, low-stability 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 subtropics was cut off by the low-stability air at 58°N. The high-stability air at 48°N above the tropopause became weaker on 14 June, indicating a possible mode of downward transport and mixing with low-stability air. Gettelman et al. (2011) noted that the quasi-isentropic exchange associated with the subtropical jet stream results in reduced static stability. This is another possible explanation for why the 2-PVU isoline at 48°N became lower on 14 June. To summarize, the dynamical tropopause on 13 June was lower than on 14 June, and the upstream STE influenced our measured in-situ profiles.

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3.2. Vertical distributions of CO and CO₂

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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 comprises approximately 430 points. In the experimental setup, a high CO mixing ratio was used to fill the tube to distinguish the starting position of the sample. Thus, the CO at the beginning of the stratospheric sample was rapidly mixed with fill gas, losing its true information. We discarded the CO values above 22 km.

Figure2. (a) CO₂ (red) and CO (blue) profiles, relative humidity (magenta) and temperature (black) profiles measured simultaneously 13 June. The y-axis represents height (km) above mean sea level; the dashed lines represent the tropopause according to the definition of the WMO; and the dash-dotted lines represent the dynamical tropopause. (b) As in (a) but for 14 June.

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3.2.1. Boundary layer

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3.2.1. Boundary layer

On 13 June (Fig. 2a), the CO₂ concentration decreased from 409.5 ppm near the surface to 405.0 ppm at the top of the boundary layer, with a large vertical gradient of 4 ppm km^?1. Such a structure indicates that the atmospheric boundary layer was stable, which constrained vertical mixing and transport. On 14 June (Fig. 2b), CO₂ levels were highest at the top of the boundary layer but were evenly distributed. This structure indicates that strong mixing occurred within the boundary layer on 14 June.

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3.2.2. Free troposphere

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3.2.2. Free troposphere

On 13 June, the lowest CO₂ concentration of 405 ppm was observed at 3 km and the highest concentration of 409 ppm was observed at 8 km. The mean vertical gradient was 0.8 ppm km^?1 between 3 and 8 km. Sources of CO₂ are mainly near the surface; the farther away the ground, the lower the CO₂ concentration. The high CO₂ concentration that occurred at 8 km was due to the easterly wind (Fig. 3a), which brings the strong anthropogenic sources from the northeast of China. To interpret the airmass origin, the trajectory model HYSPLIT was used. The ERA-Interim dataset, which is the same dataset as used in the previous meteorological analyses, was used as the meteorological forcing field. On 13 and 14 June, 24-h backward trajectories were initiated at Xilinhot. The trajectories were added to the horizontal distribution of XCO derived from TROPOMI (Fig. 3). The air mass at lower altitudes around 3 km came from a nearby region where the CO mixing ratio was ~95 ppb and was transported slowly by an easterly flow (Fig. 3). The air mass at around 8 km came from the east of Xilinhot where the CO mixing ratio exceeded 140 ppb. From the above analysis, the background atmospheric CO₂ and CO concentrations at Xilinhot were approximately 405 ppm and 100 ppb, respectively. When Xilinhot received an air mass from Northeast China, CO₂ and CO concentrations increased to 409 ppm and 160 ppb, respectively. On 14 June, CO₂ and CO were both evenly distributed in the free troposphere due to the strong northwesterly wind (Fig. 1b). The CO₂ minimum (~404 ppm) occurred at 8 km, and the backward trajectory indicated that the airmass was mainly from the Baikal region where the forest is dense and anthropogenic emissions are few. An interesting phenomenon is the negative correlation between CO and CO₂; this correlation was linear in the upper troposphere, and the reason for this observation is discussed in section 4.

Figure3. Averaged total column mixing ratio of CO measured by TROPOMI around Xilinhot together with the 24-h backward trajectory at lower altitude and higher altitude on (a) 13 June and (b) 14 June 2018.

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3.2.3. UTLS

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3.2.3. UTLS

Large differences of the CO and CO₂ concentration and their relationship in the UTLS were observed between 13 and 14 June. The thermal tropopause according to the definition of the World Meteorological Organization (WMO) was at 11 km on both days; however, according to Figs. 1a and b, the dynamic tropopause was at 340 hPa on 13 June and 250 hPa on 14 June. The vertical distributions of CO₂ and CO were quite different. On 13 June, the highest CO₂ concentration was observed at 8 km (mentioned above), and CO₂ and CO concentrations both decreased with increasing altitude. CO concentrations decreased faster than those of CO₂, from 160 ppb at 8 km to 24 ppb at 14 km, but maintained similar values above 12.6 km. Meanwhile, the CO₂ concentration 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 were linearly and negatively correlated between 7.5 and 11 km and both exhibited a laminar structure. In addition, the rate of CO decrease was small on 14 June compared to the rate on 13 June above the thermal tropopause; it decreased from 95 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 then decreased to 403.8 ppm at 14 km. Overall, in the lowermost stratosphere (LS), the CO mixing ratio on 14 June was higher than on 13 June. In the upper troposphere, the CO mixing ratio on 14 June was lower than on 13 June.

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3.2.4. Middle stratosphere

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3.2.4. Middle stratosphere

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

4. Applying the ratio of CO₂ to CO to quantify sources

Atmospheric circulation plays an important role in the horizontal and vertical distributions of CO and CO₂ after they emit from sources. Generally, at the large scale, atmospheric tracers are transported with flow over long distances if they are chemically inert, like CO₂. However, if the tracer is chemically active, it will change depending on the chemical reaction it undergoes; for example, CO exhibits a large vertical gradient over the UTLS. If we focus on the small scale, atmospheric mixing also plays a role in the distribution of tracers, especially in the presence of strong wind shear and a large gradient of tracers. As a result, the vertical distributions of tracers can be strongly influenced by transport, mixing, and the chemistry of short-lived tracers. On the other hand, we can simultaneously derive the transport process and mixing information if we know the profiles of different tracers.
From the above analysis, on 13 June, the backward trajectories indicated that the air mass originated from different locations. On 14 June, the distributions of CO and CO₂ in the UTLS illustrated that tropospheric air and stratospheric air were mixing. To clearly quantify their different sources, the CO₂/CO slopes are used to represent the sources. CO₂/CO is widely used to distinguish the different sources of CO₂ (combustion types versus terrestrial biosphere) (Suntharalingam et al., 2004; Wang et al., 2010). The CO₂/CO slopes in this analysis were obtained using the reduced major axis (RMA) method; this method is often used to derive CO₂/CO slopes (Suntharalingam et al., 2004; Wang et al., 2010).

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4.1. Differences between background and anthropogenic sources

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4.1. Differences between background and anthropogenic sources

As discussed above, on 13 June, the air mass at around 3 km originated from a nearby grassland, and trace gas concentrations were low. The CO₂/CO slope at this altitude was 136 (ppm ppm^?1) (Fig. 4a, magenta line), which was twice that calculated in an aircraft campaign (TRACE-P) in March 2009 (Suntharalingam et al., 2004). The CO₂/CO slope varies temporally and spatially, and overall, 130 (ppm ppm^?1) is a typical value of the background tropospheric air in Xilinhot, Inner Mongolia, in June.

Figure4. Scatterplot of CO₂ versus CO on (a) 13 June and (b) 14 June. Points are divided into four groups according to the value of ΔCO/ΔCO₂ and shown in four colors that indicate the corresponding altitudes. The RMA linear regression with slope “Slope” is plotted (solid line).

At 8 km, the air mass originated from Northeast China; XCO levels were relatively high, indicating a strong anthropogenic source. In Fig. 4a, most of the points in the scatterplot are located in the upper-right corner (blue points) and the slope becomes smaller than the background value. The CO₂/CO slope representing an anthropogenic source was 82.3 (ppm ppm^?1), similar to the value of 15 ppb ppm^?1 [equivalent to a CO₂/CO slope of 67 (ppm ppm^?1)] calculated by Liu et al. (2018) over Northeast China. Our result was relatively higher due to the mixing of anthropogenic and background air.

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4.2. Variation in the UTLS

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4.2. Variation in the UTLS

The negative correlation between CO and CO₂ concentrations that occurred in the UTLS on 14 June, which was contrary to the trend observed on 13 June, was quite unusual and is difficult to explain.
A previous study (Pan et al., 2009) demonstrated that the low PTLR in the tropics moves northward and the high PTLR in the polar region moves southward when the subtropical jet is enhanced; these are typical midlatitude STE processes. In Xilinhot, at the 300 hPa (~8.8 km) isobar surface, the PV value was higher than 2 PVU on 13 June and lower than 2 PVU on 14 June, suggesting that stratospheric air was dominant at 300 hPa on 13 June but tropospheric air was dominant on 14 June.
Based on the analyses in the previous section, there was a large vertical gradient of CO over the UTLS region, and the lifetime of CO is much shorter than that of CO₂, so we can 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 strong cyclone with high PV values extended closer to the Baikal region, indicating that a stratospheric intrusion may have happened in that area (Fig. 1b). To better understand the influence of the source region on the negative correlation between CO and CO₂ concentrations at Xilinhot over 7.5–12 km, Fig. 5a presents the PTLR cross section along 100°E together with the 24-h backward trajectory calculated from 14 June at Xilinhot. At around 56°N, 24 h before the air mass reached Xilinhot, the black line indicates that an air mass with higher static stability was transported downward to around 10.3 km, resulting in a sandwich-like PTLR distribution. CO₂ is an inert chemical tracer and its sources are concentrated on the surface; the impact of these sources can be transported to the upper troposphere and lower stratosphere through atmospheric circulation. CO₂ has a strong seasonal cycle because biospheric activity is strong in summer and weak in winter; thus, CO₂ is a chemical tracer that exhibits seasonal variation. Figure 5b shows the monthly mean atmospheric column-averaged dry air mole fractions of carbon dioxide (XCO₂) derived from GOSAT and the 48-h backward trajectory. The trajectory passed the steep horizontal gradient area, the black line passed the area of 406 ppm CO₂, and the other two lines passed the area where CO₂ was ~404 ppm. The lowest concentration of CO₂ in the free troposphere on 14 June was ~404 ppm, corresponding well with the source region. The vertical exchange in the UTLS with a horizontal gradient of CO₂ resulted in a strong negative correlation between CO and CO₂ between 8 and 11 km.

Figure5. (a) Potential temperature lapse rate cross-section along 100°E on 13 June. The green, black and magenta lines represent 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) but 2-day backward trajectories; each circle on the lines represents one day.

According to Hoor et al. (2005), CO values ranging from 40 to 75 ppb indicate a mixture of tropospheric and stratospheric air. CO concentrations were within this range between 11.4 and 12.4 km on 13 June and between 12 and 13.3 km on 14 June. The CO₂/CO slopes on these days were similar at these altitudes. A CO₂/CO slope of zero was observed at ~13 km, suggesting that the influence of tropospheric air had become weaker.

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4.3. Quantifying stratospheric and tropospheric contributions

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4.3. Quantifying stratospheric and tropospheric contributions

According to the above trajectory analysis, the 24-h backward trajectory at Xilinhot from 14 June indicated that the air mass was from the Baikal region where an STE process occurred on 13 June. From our in-situ measured CO profile on 14 June, CO concentrations were higher in the LS and lower in the upper troposphere compared to concentrations measured on 13 June. To quantify the STE, we used the mass balance approach of Hoor et al. (2005) and our in-situ measured CO profile to estimate the stratospheric contribution to the upper troposphere and the tropospheric contribution to the lower stratosphere. The main theory of the mass balance approach is as follows: the air mass at the disturbed area is derived from the mixing of various air parcels with different mixing ratios and different ages, and the sum of mixing ratios of the various air parcels is 1. In this context, the LS value and upper tropospheric value of our measured CO consisted of the background stratospheric value and the extratropical tropospheric value. Thus, in the LS,
with f_bkgd+f_trop=1. f_bkgd represents the background stratospheric contribution to the measured LS airmass, f_trop represents the tropospheric contribution to the measured LS airmass. For the background stratospheric value C_bkgd, we averaged the values of the two in-situ CO profiles above 15 km, which is far away from the troposphere, instead of using the reference value. For the tropospheric value C_trop, we combined the in-situ measured CO and the XCO derived from TROPOMI. Note that for 13 and 14 June, the tropospheric CO values are different, since it is significantly higher on 13 June, which is shown in Fig. 2a. We extracted the XCO value along the 24-h trajectory and considered the deviation of TROPOMI data from our measured in-situ profile. Finally, the typical tropospheric CO value on 13 June, C_{trop, 13} and 14 June, C_{trop, 14}, was 120 ppb and 91 ppb, respectively. C_{meas, LS} was calculated for separate two days, and the mean measured CO values in the LS on 13 June, C_{meas, LS, 13}, and 14 June, C_{meas, LS, 14}, were 35.4 and 48.2 ppb, respectively.
Thus, the background contribution on 13 June, f_{bkgd, 13}, and 14 June, f_{bkgd, 14}, and the tropospheric contribution on 13 June, f_{trop, 13}, and 14 June, f_trop,14, can be derived according to Eq. (1). The deviation between the tropospheric contribution on 13 June, f_{trop, 13}, and 14 June, f_{trop, 14}, was the tropospheric contribution due to the STE process, which was 24.3%.
In the upper troposphere, the mean CO values on 13 and 14 June were 140 and 87 ppb, respectively. The CO mixing ratio in the upper troposphere on 14 June represented the mixture of the typical tropospheric CO value along the trajectory and the remaining CO from 13 June. In order to estimate the value of remaining CO from 13 June, we calculated the relative change from 13 to 14 June between 4 and 8 km where the air mass was not influenced by stratospheric intrusion. Thus, we can derive the CO value between 8 and 11 km without the stratospheric intrusion. The stratospheric contribution is the deviation between the calculated CO value and the measured CO value. Finally, the stratospheric contribution between 8 and 11 km is 26.7%.
Overall, the stratospheric contribution to the upper troposphere was approximately 26.7% and the tropospheric contribution 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 prototype (Tans, 2009; Karion et al., 2010). Our aircore consists of a 60-m-long tube constructed using a combination of 30 m of 0.125-inch tubing and 30 m of 0.25-inch tubing to improve the resolution in the UTLS region (Membrive et al., 2017). The aircore campaign was conducted at Xilinhot on 13 and 14 June 2018.
The CO₂ profiles on 13 and 14 June differed. On 13 June, a large gradient of 4 ppm km^?1 was observed in the boundary layer, whereas on 14 June CO₂ concentrations were consistent within the boundary layer. In the free troposphere, a maximum CO₂ concentration of 408 ppm was observed at 8 km under the influence of easterly winds that transported CO₂ from significant anthropogenic sources to Xilinhot on 13 June. The slope of CO₂/CO representing the strong anthropogenic source was 82.3 ppm ppm^?1. On 14 June, the CO₂ concentration decreased with altitude, and the lowest value of 404 ppm occurred at 8 km where the air mass originated from the Baikal region. Interestingly, CO and CO₂ concentrations were strongly and positively correlated on 13 June and strongly and negatively correlated on 14 June. Upstream of Xilinhot, an STE event occurred on 13 June, and the influence of the event was transported to the campaign site on 14 June. Upon analysis of the vertical distribution of PTLR and the horizontal distribution of XCO₂, we found that the trajectory with a higher PTLR region, which was indicated by lower CO concentrations, passed by the region with the highest CO₂ concentration. Thus, an unusual strong negative correlation between CO and CO₂ developed in the upper troposphere on 14 June. Based on the mass balance approach, a background stratospheric airmass was transported downward, contributing 26.7% to the upper troposphere, and tropospheric air mass was transported upward, contributing 24.3% to the LS.
Furthermore, this study shows that combining in-situ CO and CO₂ profiles with backward trajectories is a useful way to investigate horizontal and vertical airmass transport and interpret the combined effect of airmass transports bringing different structures among gas species. Besides, the modified mass balance approach in specific cases can semi-quantify the contribution of the stratospheric intrusion. To fully understand the airmass transport, especially in the UTLS region, an aircore campaign designed to simultaneously measure more gas species in the Tibetan region, such as CH₄, N₂O and O₃, will also be conducted. The interrelationships among these species will help to provide more details regarding the attributes of airmass transport.
Acknowledgements. This research was supported by grants from the Strategic Priority Research Program of the Chinese Academy of Sciences (CAS) (Grant No. XDA17010100), the National Natural Science Foundation of China (Grant No. 41875043), the Youth Innovation Promotion Association, CAS, the Key Research Program of CAS (Grant No. ZDRW-ZS-2019-1), and the External Cooperation Program of CAS (Grant No. GJHZ 1802).

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Corresponding author: Yuli ZHANG,zhangyuli@mail.iap.ac.cn;