Changes in HCFC Emissions in China During 2011–2017

Abstract

Hydrochlorofluorocarbons (HCFCs), the main substitutes of chlorofluorocarbons, are regulated by the Montreal Protocol. Chinese HCFC emissions increased fast from the beginning of this century. However, limit reports based on atmospheric measurement are available for years after 2011, an important period when significant changes are expected. Combining atmospheric observations at seven sites across China with a FLEXible PARTicle dispersion model-based Bayesian inversion technique, we estimate emission magnitudes and changes of four major HCFCs in China during 2011–2017. The emissions of all four HCFCs reached peaks before 2015. Our results agreed well with the reported bottom-up inventories. The Chinese ozone depletion potential (ODP)-weighted emission of the three most abundant HCFCs accounted for 37% of global totals from 2011 to 2016. The total emission of HCFC-22 from China, the European Union, and the United States accounted approximately a half of the global totals, suggesting large HCFC emission emitted from the rest of the world.

Plain Language Summary

Hydrochlorofluorocarbons (HCFCs) are used to replace chlorofluorocarbons, or well known as Freon, a group of gases which contribute to the polar ozone hole. However, HCFCs are also important ozone depletion substances and are regulated by the Montreal Protocol. As the largest developing country, the HCFC emissions in China are of great interest. In this study, we estimate emission magnitudes and changes of four major HCFCs in China over the period 2011–2017 based on atmospheric observations at seven sites. We find the emissions of all four HCFCs reached their peaks before 2015, which generally agree with the emission inventories estimated using production and consumption information, suggesting the effectiveness of the implementation of Montreal Protocol in China. However, there is a big gap between the total HCFC-22 emission from China, the European Union, and the United States and global totals, suggesting large emissions from the rest of the world.

1 Introduction

Hydrochlorofluorocarbons (HCFCs) are a group of synthetic chemicals introduced in refrigeration, air conditioning, foam blowing, and solvent applications, as the main substitutes of chlorofluorocarbons (CFCs; Engel et al., 2018). With the phasing-out procedure of CFCs, global HCFCs mole factions and total chlorine from HCFCs kept increasing (Engel et al., 2018). Because HCFCs are also ozone-depleting substances (ODSs), they are included in the 1992 Montreal Protocol amendment. HCFC-22 (CHClF₂), HCFC-141b (CH₃CCl₂F), HCFC-142b (CH₃CClF₂), and HCFC-124 (CHClFCF₃) are the most abundant HCFCs in the atmosphere (Montzka et al., 2009; Simmonds et al., 2017). HCFC-22 is widely used in refrigeration, air conditioning, and foam blowing applications and as a chemical feedstock for producing fluoropolymers (McCulloch et al., 2003; McCulloch et al., 2006; Saikawa et al., 2012). HCFC-141b is mainly used in foams and as a solvent in electronics and precision cleaning applications. HCFC-142b is primarily used as foam blowing agents as well as an aerosol propellant and as a refrigerant (Simmonds et al., 2017; Wan et al., 2009). HCFC-124 is used in specialized air conditioning equipment, refrigerant, fire extinguishers, and as a component of sterilant mixtures (Midgley & McCulloch, 1999). The four HCFCs are also greenhouse gases with high global warming potentials (GWPs; Table S1 in the supporting information).

Referring to the Montreal Protocol and subsequently the 2007 adjustments which required an accelerated phaseout of emissive uses of HCFCs in both “non-Article 5” developed and “Article 5” developing countries, the production and consumption for the HCFCs in non-Article 5 countries have been substantially reduced since 2004 (United Nations Environmental Programme, 2008). Global HCFC-22 emissions have remained relatively unchanged between 2012 and 2016, while emissions of HCFC-141b and HCFC-142b declined during the same period, in consistent with decreased HCFC consumption after 2012 (Engel et al., 2018).

As the largest Article 5 country (developing country) under the Montreal Protocol, the HCFC emissions in China are of great interest. China's timetable of phasing-out ODS is 10 to 15 years later than in developed countries. China was obligated to freeze production and consumption of HCFCs by 2013 and to achieve a complete phaseout by 2030 with an exception of an annual average of 2.5% for servicing until 2040 (United Nations Environmental Programme, 2008, 2009). China is still allowed to produce and consume HCFCs to replace the first-generation ODSs (e.g., CFCs), leading to increased banks of HCFCs. Recent bottom-up inventory estimates showed the Chinese HCFC emissions increased fast, from 0.2 kt/year in 1990 (kt = kilotons) to 127.2 kt/year in 2014 for HCFC-22 (Li et al., 2016), from 0.8 kt/year in 2000 to 15.8 kt/year in 2013 for HCFC-141b (Wang et al., 2015), and from 0.1 kt/year in 2000 to 14.4 kt/year in 2012 for HCFC-142b (Han et al., 2014). The projected Chinese emissions of HCFC-22 and HCFC-142b have reached their peaks in 2010s, while emission of HCFC-141b will reach its peak in 2020s under Montreal Protocol phasing-out scenario (Fang et al., 2018).

In the last two decades, Chinese HCFCs emissions were estimated using inverse modeling and in situ measurement data (An et al., 2012; Liu et al., 2015; Stohl et al., 2009; Stohl et al., 2010; Vollmer et al., 2009) or tracer ratio methods and data from sampling campaigns (Fang et al., 2012; Wang et al., 2014), in situ measurements (Kim et al., 2010; Li et al., 2011; Yokouchi et al., 2006) or aircraft measurements (Blake et al., 2003; Palmer et al., 2003). However, these studies only provided estimates for periods no longer than 2 years and China's HCFC emissions after 2011 were limited. Furthermore, there is no published inventory or top-down estimates for HCFC-124.

Therefore, it is important to conduct long-term measurements of HCFCs to track their emission evolutions and thus investigate the effectiveness of China's regulation on HCFCs in the past and coming years. This study provides comprehensive emission information for four HCFCs in China using the atmospheric measurement data from seven Chinese stations during 2011–2017 and explores the HCFC emission changes in the context of fast dynamic first-generation ODS phaseout process in China.

2 Materials and Methods

2.1 Site Description

The seven sampling sites and their footprint are shown in Figure 1 and their geographic information, measurement details and representativeness are listed in Table S2. Air samples were collected at Shangdianzi (SDZ), Mt. Waliguan (WLG), Longfengshan (LFS), and Lin'an (LAN) since 2010 and at Shangri-La (XGL) since July 2011, at a sample frequency of one pair per week. To improve the representativeness of southern and southwest China, daily sampling was conducted in 2017 at the Heyuan (HYN) and Jiangjin (JGJ) stations. In situ measurement was also conducted at Shangdianzi periodically from 2010 to 2017. All of these stations were operated by the China Meteorological Administration, and they are at least 20 km away from densely populated or industrial areas to avoid closing to massive sources and ensure regional representativeness.

Figure 1

The location (white crosses) and average emission sensitivity for seven sampling sites in 2017. SDZ, WLG, LFS, LAN, XGL, HYN, JGJ represent Shangdianzi, Mt. Waliguan, Longfengshan, Lin'an, Shangri-La, Heyuan, and Jiangjin, respectively.

2.2 Periodic Sampling and In Situ Measurements

At each site, ambient air was drawn from the top of the sampling towers (80 m for WLG, SDZ, and LFS, 50 m for LAN and XGL, and 10 m for HYN and JGJ) through a sampling tube by a custom-made sampler and pressurized into 3-L stainless steel canisters (X23-2N, LabCommerce, Inc, USA). Then the canisters were shipped to the central laboratory at the Meteorological Observation Centre in Beijing for analysis within one month. In addition, pairs of parallel samples were collected at WLG, SDZ, LFS, LAN, and XGL for quality assurances. In the lab, a custom-built “Medusa” gas chromatographic (GC) system with mass spectrometric (MS) detection (Agilent 6890/5975B, USA) based on the Advanced Global Atmospheric Gases Experiment (AGAGE) technique (Miller et al., 2008) was used to measure the mole fractions of the four HCFCs. The details of sampling and lab analysis are described by Zhang et al. (2017).

At the SDZ station, atmospheric HCFCs were also measured by the in situ system in years of 2011–2012 and 2015–2017, using the Medusa GC/MS system described above. The details were reported by Yao, Vollmer, Zhou, et al. (2012). Besides, HCFC-22 and HCFC-142b were also measured periodically during 2013–2014 by an in situ two-channel electron-capture detector (ECD) gas chromatography (GC) system equipped with a custom-built sample preparation system. The details were described by Yao, Vollmer, Xia, et al. (2012) and the emissions of HCFC-22 and HCFC-142b based on the in situ measurement by GC-ECD system were reported for the year 2007 to 2010 by Vollmer et al. (2009), An et al. (2012), and Liu et al. (2015).

Each sample measurement is bracketed by a reference gas (working standard or quaternary standard), which was calibrated against a tertiary standard from AGAGE, and the results are reported as dry air mole fractions on the calibration scales developed at the Scripps Institution of Oceanography and the University of Bristol: Scripps Institution of Oceanography-05 (HCFC-22, HCFC-141b, HCFC-142b), University of Bristol-98 (HCFC-124) (Prinn et al., 2000; Prinn et al., 2018). The measurement uncertainties of ambient concentration samples were approximately 0.5% for HCFC-22, HCFC-141b, and HCFC-142b and 2% for HCFC-124. The measured mole fractions of each HCFC from each site were filtered to exclude extreme outliers using Tukey's fence approach. The high-frequency in situ measurements were averaged into daily resolution. All flask and in situ measurement data used in the emission inverse modeling are shown in Figures S1–S4 for the four HCFCs, respectively.

2.3 Inverse Modeling of Emissions

This study used the FLEXPART (“FLEXible PARTicle dispersion model”) model and a Bayesian inversion algorithm to estimate emissions. This approach has been explained in a previous study by Fang et al. (2019). Here we briefly introduce the model and inversion algorithm. FLEXPART, a Lagrangian transport and dispersion model, has been widely used for the simulation of a large range of atmospheric species and transport processes (Stohl et al., 1998; Stohl et al., 2005). In this study, the FLEXPART model was driven by meteorological data (European Centre for Medium-Range Weather Forecasts) with 1° × 1° global resolution and 3-hourly temporal resolution and run in a backward mode for 20 days in time. Forty thousand virtual particles were released from each sampling site in a 3-hr interval. The output of the FLEXPART model simulation is a source-receptor relationship matrix (H), termed “emission sensitivities” (1° × 1°; Figure 1), which is combined with a Bayesian inversion algorithm and the HCFC measurement data to derive the HCFC emission strengths in grid boxes over China continent. The equations used in this study are

Here x is the emission strength state vector, x_a is the prior emission vector, y^obs is atmospheric measurement vector. S_a and S_b are the prior and posterior emission error covariance matrices, respectively, and S_o is the observational error covariance matrix. As for the prior emission vector (x_a), this study used global total emissions for a specific HCFC in 2011(Rigby et al., 2014), the bottom-up estimates of China's national total emissions for each HCFC by Fang et al. (2018), and then disaggregated approximately the emission by the population spatial distribution (Gridded Population of the World: Future Estimates, 2005). The prior emission used (termed reference prior emissions) for China is 149 kt/year for HCFC-22, 17.8 kt/year for HCFC-141b, and 9.9 kt/year for HCFC-142b, based on the mean emissions estimated for 2011–2014 by Fang et al. (2018), while 0.85 kt/year for HCFC-124, based on the global totals and population distribution. As an example, HCFC-142b prior emission spatial map is shown in Figure S5. We used prior emissions for a specific HCFC that were unchanged during 2011−2017. The approach for determining background mole fractions: For flask sampling sites, background mole fractions were the lower value between (1) the lowest value of measured HCFC mole fractions in a 2-month moving window and (2) mole fraction that latitude-direction linearly interpolated between the HCFC monthly baseline mole fractions measured at Ragged Point, Barbados and Mace Head, Ireland (http://agage.eas.gatech.edu/data_archive/agage/); for in situ measurement, background mole fractions were filtered using the approach developed by Stohl et al. (2009). The diagonal elements of observational error covariance matrix S_o are squared σ_observation. Calculation of σ_observation follows:

Here σ_{obs_precision} represents the HCFC measurement precision, σ_{obs_representation} represents representation of observations, and this study used one-sigma standard deviation of the observations in a 2-month moving window for flask samples and one-sigma standard deviation of the in situ observations (~2-hr frequency) that were averaged in each day. In this study, the background uncertainty (σ_background ) used the 2% of the background values (described above) and σ_observation elements were assumed to be uncorrelated, because this study used either one measurement a day (flask data) or daily averages (in situ data). Thus, off-diagonal elements in S_observation are zeros. Figures S5 and S6 show the spatial prior and posterior emissions of HCFC-142b as examples, respectively. Figure S7 shows the observed and modeled mole fractions of HCFC-142b as examples.

There is no knowledge on the emission uncertainty in an individual grid cell. The prior emission uncertainty in each grid box (squared values are the diagonal elements of S_a) was set as 200%, 150%, and 100% of the corresponding emissions. Posterior emissions were derived from an ensemble of nine inversions using three prior emission fields (scaling the reference prior emissions by 150%, 100%, and 50%) multiplied by the three prior emission uncertainties (200%, 150%, and 100%). China's national emissions from the nine inversions are shown in Figures S8–S11 for the four HCFCs, respectively. The final results for China's national emissions from the ensembles are shown in Figures S12–S15 for the four HCFCs, respectively. Figures S8–S11 show that prior emission magnitudes change posterior emissions to some extent. The three levels of scaled prior emissions bracket the posterior emissions well, which suggests the prior emissions were not systematically too low or high. Tests using 200%, 150%, and 100% as prior emission uncertainty show that the derived emissions only vary by less than 12.2% in 2011 and 2017 (see Table S3). Thus, magnitudes of prior emission uncertainties do not significantly alter the posterior emissions.

3 Results

3.1 Chinese Emissions Derived From Inverse Modeling

The annual emissions for four HCFCs in China during 2011–2017 are shown in Table 1. The emissions of all four HCFCs reached peaks in this period. HCFC-22 emissions varied from 139 to 172 kt/year, with a maximum in 2013. HCFC-141b and HCFC-142b emissions were about 1 order of magnitude smaller. The HCFC-141b emission showed a maximum at 24 kt/year in 2011 and decreased to 16 kt/year in 2014 with an average annual decline rate of ~3 kt/year and then changed less than 0.5 kt/year from 2014 to 2017. The HCFC-142b emissions were relatively stable from 2011 to 2014, with a maximum at 11 kt/year in 2011 then decreased about to around 40% with 6 kt/year in 2017. This study provides China's HCFC-124 emission estimates for the first time. The HCFC-124 emissions were the smallest of the four HCFCs, with 0.7 to 0.9 kt/year, and largest emission in 2015.

Table 1. Chinese Emissions (kt/year; One-Sigma Uncertainty) of Four HCFCs Derived From Inverse Modeling Over 2011–2017

HCFC	2011	2012	2013	2014	2015	2016	2017
HCFC-22	139 ± 35	154 ± 51	172 ± 37	159 ± 340	146 ± 44	147 ± 36	147 ± 26
HCFC-141b	24 ± 5	22 ± 6	18 ± 6	16 ± 7	15 ± 6	15 ± 3	15 ± 2
HCFC-142b	11 ± 3	11 ± 4	11 ± 4	11 ± 3	9 ± 3	8 ± 2	6 ± 1
HCFC-124	0.7 ± 0.3	0.7 ± 0.2	0.8 ± 0.3	0.7 ± 0.3	0.9 ± 0.3	0.8 ± 0.2	0.8 ± 0.1

• Note. HCFC = hydrochlorofluorocarbon.

3.2 Comparisons to Previous Studies

The estimated emissions of three major HCFCs (HCFC-22, HCFC-141b, and HCFC-142b) were compared with previous studies and shown in Figure 2. Generally, the emissions based on atmospheric measurement by this study agreed with the reported results by bottom-up method, considering the relative small differences between averaged emissions during 2011–2017. As for HCFC-22, both top-down studies (An et al., 2012; Fang et al., 2012; Li et al., 2011; Stohl et al., 2010; Vollmer et al., 2009; Wang et al., 2014; Yokouchi et al., 2006) and bottom-up studies (Fang et al., 2018; Li et al., 2016) show a rapid increase in HCFC-22 emissions during 2004 to 2012 (Figure 2a). It was projected that Chinese HCFC-22 emission would reach a maximum in 2016 and then decline as a consequence of the regulations under the Montreal Protocol (Fang et al., 2018; Li et al., 2016). A similar trend was observed by this study with the peak year in 2013, 3 years ahead the projected year with maximum emission by the bottom-up method. The averaged emission from 2011 to 2017 by this study (152 kt/year) agree very well with the results by Fang et al. (2018) in the same period (157 kt/year) and are about 23% higher than the results by Li et al. (2016).

Figure 2

Comparison of Chinese hydrochlorofluorocarbon (HCFC) emissions during the period 2002–2018. For the bottom-up estimates, solid lines represent estimated historical emission while dotted lines represent projected emissions under Montreal Protocol phasing-out scenario.

Estimated Chinese HCFC-141b emissions based on the top-down method (Fang et al., 2012; Li et al., 2011; Stohl et al., 2009) agreed with the results by the bottom-up method (Fang et al., 2018; Wang et al., 2015) in the year 2008 and 2009. In the bottom-up studies the HCFC-141b emissions were increasing from 2002 to 2011 but became stable from 2011 to 2014. It is projected that HCFC-141b emissions will keep increasing until mid-2020s (Fang et al., 2018; Wang et al., 2015). However, a decline of HCFC-141b emissions was observed by this study since 2011, which is in contrast to the increasing trend projected by bottom-up studies.

From 2006 to 2011 rapid growth of Chinese HCFC-142b emissions was reported by both top-down studies (Fang et al., 2012; Li et al., 2011; Liu et al., 2015; Stohl et al., 2010; Vollmer et al., 2009) and bottom-up studies (Fang et al., 2018; Han et al., 2014). The projection that the emission should stabilize in the 2010s and then kept decreasing with the implementation of the Montreal Protocol (Han et al., 2014) was supported by this study. A moderate decrease of HCFC-142b emissions was observed by this study since 2014, and the inferred emission in 2017 was lower than the bottom-up inventories. It should be noted that the relative uncertainties of the emissions were smaller in 2017 than in 2011–2016, because in 2017 daily sampling at two more stations was added to the observation network, indicating additional measurements with a high temporal resolution helps in reducing the uncertainty of the emission estimate.

3.3 ODP-Weighted and CO₂-Equivalent Emissions and Distribution Among HCFCs

Since HCFCs are ODSs, it is important to understand the total and the selected ODP-weighted emissions of the four HCFCs. These ODP-weighted emissions were calculated by multiplying the emissions of each HCFC by their ODP (see Table S1). As shown in Figure 3a, total ODP-weighted emission of the four HCFCs in China varied from 6.9 kt/year (2017) to 8.4 kt/year (2013) with an annual average at 7.6 kt/year, with an increasing trend from 2011 to 2013 and then slightly decreased until 2017. Among the four HCFCs, HCFC-22 contributed the highest share of 68% in terms of ODP-weighted emission. HCFC-141b, HCFC-142b, and HCFC-124 contributed 24%, 7%, and 0.2% of the total ODP-weighted emission, respectively.

Figure 3

Hydrochlorofluorocarbon (HCFC) emission in terms of ozone depletion potential (ODP)-weighted (left) and CO₂-equivalent (right) emission in China during 2011 to 2017.

HCFCs are also strong greenhouse gases; thus, it is necessary to estimate the HCFC evolutions in terms of CO₂-equivalent (in abbreviation as CO₂-eq hereafter) emissions. The CO₂-eq emissions were obtained using the mass emissions of each HCFC multiplied by their GWPs at 100-year time horizon (GWP₁₀₀; see Table S1). The average of the HCFC CO₂-eq emissions from 2011 to 2017 was at 305 Mt/year (Mt = million tons; Figure 3b), with fluctuations between 288 Mt/year (2017) to 344 Mt/year (2013). The major contributor to this total was again HCFC-22, with averaged emissions of 271 CO₂-eq Mt/year, accounting for 89% of total HCFC CO₂-eq emission. The averaged CO₂-eq emissions of HCFC-142b (20 Mt/year) was larger than of HCFC-141b (14 Mt/year) because its GWP₁₀₀ value is 159% higher than for HCFC-141b. The proportion of HCFC-124 in terms of CO₂-eq emissions was quite small at only ~0.1%.

3.4 Chinese Contribution to Global Emissions

Chinese HCFC emissions are compared to the total global emissions and those from other important source regions (e.g., Europe and the United States). The global emissions of HCFC-22, HCFC-141b, and HCFC-142b during 2011–2016 were taken from Scientific Assessment of Ozone Depletion: 2018 (Engel et al., 2018), which were derived using global atmospheric mole fraction measured at the remote stations in the AGAGE network. The details are described by Rigby et al. (2014).

Global ODP-weighted emissions of the three most abundant HCFCs (HCFC-22, HCFC-141b, and HCFC-14b) were calculated by the same method as to calculate Chinese ODP-weighted HCFC emission discussed in section 3.3. As shown in Figure 4, contributions from aggregated China's ODP-weighted emissions for the three major HCFCs to the global totals fluctuated from 35% (2016) to 40% (2013). China's cumulative ODP-weighted emissions for the three HCFCs contributed 37% of global totals during 2011–2016.

Figure 4

Global ozone depletion potential (ODP)-weighted hydrochlorofluorocarbon (HCFC) emissions and China's contributions. Global emissions were taken from the Scientific Assessment of Ozone Depletion: 2018 (Engel et al., 2018).

The HCFC-22 emissions based on atmospheric observation were reported for the European Union (EU; Graziosi et al., 2015) from 2002 to 2012 and the United States (Hu et al., 2017) from 2008 to 2014. As shown in Figure S16, annual HCFC-22 emissions from the United States were 67 kt/year in 2008. As non-Article 5 countries, the emission from the United States and the EU declined continuously with the phaseout of HCFC-22. In 2012, the emissions from the United States were about 30% of that from China. The total emissions from the EU, the United States, and China were calculated and compared to the global total HCFC-22 emissions from 2011 to 2012. The global HCFC-22 emissions were relatively stable at 373 kt/year, while the total HCFC-22 emissions from the EU, the United States, and China were 203 and 209 kt/year in 2011 and 2012, respectively. Thus, the HCFC-22 emissions from the EU, the United States, and China accounted approximately a half to global totals, suggesting large HCFC emission up to approximately 170 kt/year emitted from the rest of the world.

Atmospheric HCFC measurements are limited or not reported from many regions, for example, South and Southeast Asia, Africa, and South America. Thus, it is critically important to carry out long-term atmospheric measurements of HCFCs in these regions to optimize the global observation network and better understand the global HCFC emission distribution or evaluate the overall effectiveness of the Montreal Protocol.

4 Conclusions

Measurement-based Chinese emissions of four major HCFCs (HCFC-22, HCFC-141b, HCFC-142b, and HCFC-124) all reached peaks during 2011 to 2017. Larger HCFC-22 emissions were observed in 2013. The HCFC-141b emissions decreased from 2011 to 2014 and then kept stable until 2017. The HCFC-142b emissions exhibited a decreasing trend since 2014, while the largest emissions of HCFC-124 appeared in 2015. HCFC-22 had the highest contribution of all HCFCs in terms of ODP-weighted and CO₂-eq emissions. The HCFC-141b emissions in the term of ODP-weighted emissions are more than 2 times larger than HCFC-142b, while the CO₂-equivalent emission of HCFC-142b is approximately 1/3 larger than that of HCFC-141b. China's HCFC-124 emissions are reported here for the first time. Emissions of HCFC-124 were the smallest among those of the four HCFCs, accounting for less than 1% of the all four HCFCs.

The averaged emission of the three HCFCs (HCFC-22, HCFC-141b, and HCFC-142b) generally agreed with those from reported results by the bottom-up inventory. Maximum emissions of HCFC-22 in mid-2010s were found by both top-down and bottom-up methods. Bottom-up estimates projected continuous increasing trend until 2020s of HCFC-141b after a period of relative stability in the 2010s. In contrast, the emissions of HCFC-141b revealed declines since 2011 by this study.

China contributes 37% of the world's HCFC emission in the terms of ODP-weighted emissions from 2011 to 2016. However, large gaps were found between the global HCFC-22 emissions and total HCFC-22 emissions from the EU, the United States, and China, suggesting large HCFC-22 emissions emitted from the rest of the world. Considering limited reports of the atmospheric HCFC measurements in many potentially important source regions, it is essential to carry out long-term atmospheric measurements of HCFCs in these regions, to better assess the global and regional HCFC emissions and also to better evaluate the implementation of the Montreal Protocol.

Acknowledgments

The observation work was supported by the National Natural Science Foundation of China (41575114 and 41730103). X. Fang and R. Prinn were supported by NASA Grant NNX16AC98G to MIT. We thank the stations personnel who have supported canister sampling at SDZ, WLG, LAN, LFS, XGL, JGJ, and HYN and the in situ measurement at SDZ. We thank technical assistance by the AGAGE network. We thank the Scripps Institution of Oceanography (SIO) for help with the data acquisition, processing software, and calibration standards. We also thank Dr. Matthew Rigby from the University of Bristol for providing global HCFC emissions estimates and their uncertainties.