Unexplained high and persistent methyl bromide emissions in China

Domain: earth_science
Published: 2024-10-16
Editorial outcome: minor_revision

Abstract
Methyl bromide (CH3Br) is an important ozone-depleting substance whose use is regulated under the Montreal Protocol. Quantifying emissions on the national scale is required to assess compliance with the Montreal Protocol and thereby ensure the timely recovery of the ozone layer. However, the spatial-temporal patterns of China’s national CH3Br emissions remain unclear. Here we estimate the national emissions of CH3Br in China during 2011−2020 using atmospheric observations at 10 sites across China combined with an inversion technique (top-down) and compare those with an updated inventory of identified emission sources (bottom-up). Measured CH3Br mole fractions are enhanced well above the background mole fractions, especially at sites in eastern China. Top-down emission estimates exceed bottom-up estimates by 5.5 ± 1.4 gigagrams per year, with the largest fraction (60%) of observationally derived CH3Br emissions arising from underestimated or unidentified emissions sources. This study shows the potential impacts of the unaccounted emissions on stratospheric ozone depletion, with implications for the Montreal Protocol.

Introduction
Global production, consumption (i.e., usage), and emissions of long-lived ozone-depleting substances (ODSs) such as chlorofluorocarbons (CFCs), halons, and carbon tetrachloride (CCl4) have led to the decline of the stratospheric ozone layer and contributed to global and Arctic warming1,2. To slow down and eventually reverse further depletion of the ozone layer, the production and consumption of these ODSs have been regulated since 1987 under the Montreal Protocol on Substances that Deplete the Ozone Layer and its Amendments3. Methyl bromide (CH3Br) is an important ODS, with a lifetime of 0.8 years4, an ozone depletion potential (ODP) of 0.63, and a 20-yr global warming potential (GWP) of 94. CH3Br is the single largest contributor to stratospheric bromine load, and bromine is around 60 times more efficient than chlorine in depleting ozone under current stratospheric conditions5. CH3Br from natural and anthropogenic sources contributed 20% of CFC-11-equivalent emissions of all ODSs in 2020 and is projected to increase to 39% by 2100 as other ODS emissions decline5.

Being a highly effective broad-spectrum fumigant, CH3Br was widely used as a pest-control treatment in fumigation applications including quarantine and pre-shipment (QPS), and non-QPS uses (mainly soil, post-harvest, and structure fumigation)5. CH3Br is also used as laboratory and analytical solvents and feedstocks for the manufacture of other chemicals6. Other sources, both natural and anthropogenic, also contribute to the atmospheric CH3Br budget, including the oceans7,8, biomass burning9,10, biofuel burning4, natural ecosystems, and certain crops11–15. In 1992, CH3Br was added to Annex E of the Montreal Protocol3. For non-Article 5 countries (mainly developed countries), the anthropogenic production and consumption of CH3Br were required to be frozen in 1995 and reduced by 25% in 1999, 50% in 2001, 70% in 2003, and 100% in 2005. For Article 5 countries (mainly developing countries), production and consumption were to be frozen in 2002, reduced by 20% by 2005, and eliminated by 2015, with exemptions made for QPS use3.

China is an Article 5 country under the Montreal Protocol3. China’s non-QPS and QPS CH3Br consumption peaked at 3.5 gigagrams per year (Gg yr−1) in 2000 and 2.1 Gg yr−1 in 2005, respectively (Supplementary Table 1). Although non-QPS CH3Br consumption was scheduled to be phased out by 20156,16, China obtained critical use exemptions (CUEs) of approximately 0.1 Gg yr−1 during 2015−2018 for ginger cultivation (Supplementary Table 1), thus delaying the phase-out of non-QPS consumption to 2019.

However, China’s actual national CH3Br emissions over the last decade remain unclear. Insufficient spatial coverage of the observation site (only the Gosan (GSN) site in South Korea)17–19 and the shortcomings of the interspecies correlation method (ISC)17–20 have resulted in highly uncertain emission estimates and a lack of knowledge about the spatial distribution of CH3Br emissions in China. In addition, multiyear atmospheric observation-inferred estimates of China’s CH3Br emissions are lacking. An updated and comprehensive bottom-up inventory is also necessary for comparison with the top-down estimates in China, as previous bottom-up estimates17,21 have omitted several emission sectors, such as feedstock use6, rice paddies22, salt marshes12,15, and mangrove11.

In this work, we quantify total China’s CH3Br emissions during 2011–2020 using observations of atmospheric mole fractions of CH3Br at ten sites across China and an atmospheric inversion method. We also develop an improved bottom-up emission inventory for known sources of CH3Br. This study reveals that half of China’s CH3Br emissions are concentrated in the eastern provinces of China, and over half of the national emissions remain unexplained. The potential causes for these unexplained emissions and implications for stratospheric ozone depletion and the Montreal Protocol are also discussed.

Results
Higher CH3Br mole fractions in China compared to the background atmosphere
Atmospheric mole fractions of CH3Br were measured at 10 sites across China from 2011 to 2020 (Fig. 1, Supplementary Table 2, and Supplementary Fig. 1). We estimated the baseline (i.e., background) mole fractions at our measurement sites by selecting the lowest observed concentrations in a 90-day moving time window (see Methods). The average annual mean baselines observed during 2011–2020 ranged from 7.0 parts per trillion (ppt) at Longfengshan (LFS) to 8.2 ppt at Lin’an (LAN) (Supplementary Table 3 and Supplementary Fig. 2). These concentrations are comparable to the 7.0 to 7.8 ppt CH3Br background mole fraction range observed at four Northern Hemisphere background sites within the Advanced Global Atmospheric Gases Experiment (AGAGE) network (https://agage.mit.edu/data/agage-data) that are at comparable latitudes to our sites in China (24.0°N–47.1°N): Mace Head site in Ireland (MHD hereafter, 53.3°N, 9.9°W), Trinidad Head site in California, USA (THD hereafter, 41.1°N, 124.2°W), Gosan site on Jeju Island, South Korea (GSN hereafter, 33.3°N, 126.9°E), and Ragged Point site in Barbados (RPB hereafter, 13.2°N, 59.4°W). The background mole fractions at those four AGAGE sites were determined by using AGAGE’s statistical algorithm which extracted the background observations by applying a second-order polynomial to the daily minima over a 120-day moving time window23. To ensure comparability, we verified that the background mole fractions estimated using AGAGE’s method and this study’s method were consistent (Supplementary Fig. 3).

Enhanced mole fractions above baseline values at each of the ten Chinese sites reflect emissions in China and other Asian countries surrounding China. These pollution events showed spatial heterogeneity among the ten Chinese sites, with the highest average annual mean enhanced mole fraction of 9.9 ± 1.4 ppt observed at the LAN site in eastern China and the lowest of 0.6 ± 0.8 ppt observed at the Mount Waliguan (WLG) site in northwest China (Supplementary Table 3 and Supplementary Fig. 2). The higher enhancements in the eastern provinces of China indicate potentially stronger CH3Br emissions from this region (see discussion in the next section).

Persistent CH3Br emissions in China after the 2015 phase-out
The measurements at these sites were sensitive to emissions in most of China (Fig. 1 and Supplementary Fig. 1), such that national CH3Br emissions can be quantified using an inversion of the atmospheric measurements (see Methods). This study improves on previous studies by using more sites within China’s borders, allowing a better quantification of national emissions. CH3Br emissions in China averaged 9.2 ± 1.4 Gg yr−1 during 2011−2020 (Fig. 2a). Emissions showed inter-annual variations but no significant trend (slope = 0.16 ± 0.15 Gg yr−1, p = 0.33), with a maximum of 10.5 ± 1.4 Gg yr−1 in 2014 and a minimum of 6.2 ± 1.1 Gg yr−1 in 2012 (Fig. 2a). These results are generally consistent with national emissions estimated by the interspecies ratio method (Supplementary Fig. 4), although prior results were single year estimates from the beginning of this study or earlier: ~5.5 ± 2.0 Gg yr−1 in 200818,19. Based on the recently established long-term observation network in China, this study addresses the magnitude and 2011−2020 trend of national CH3Br emissions in China.

We identified eastern China (enclosed by red lines in Fig. 2b, including the 11 provinces of Anhui, Beijing, Hebei, Jiangsu, Liaoning, Shandong, Shanghai, Tianjin, Zhejiang, Fujian, and Guangdong) as the hotspot for emissions (Fig. 2b and Supplementary Fig. 5). The CH3Br flux (emission rate per unit area) in eastern China was eight times that of the rest of China (4.0 and 0.53 kg km−2 yr−1, respectively) from 2011 to 2020 (Fig. 2b). Even though the area of eastern China accounts for only 12.5% of China’s total area, their emissions contributed about 52% (4.8 Gg yr−1) of total emissions. As shown in Supplementary Table 4, the top five CH3Br emitting provinces were Jiangsu (0.76 ± 0.16 Gg yr−1), Shandong (0.74 ± 0.12 Gg yr−1), Zhejiang (0.72 ± 0.23 Gg yr−1), Anhui (0.66 ± 0.19 Gg yr−1), and Guangdong (0.50 ± 0.17 Gg yr−1), contributing approximately 40% of China’s national CH3Br emissions. For comparison, these five provinces represent 7.3% and 32% of China’s total area and population, respectively. As shown in Supplementary Fig. 4, the emission estimates for eastern China in this study are consistent with those derived from observations at the GSN site in South Korea and the interspecies ratio method by Choi et al.17.

Accounting of CH3Br emissions from known sources in China
National bottom-up CH3Br emissions in China estimated in this study were 3.7 ± 0.2 Gg yr−1 on average during 2011−2020 (Fig. 3 and Supplementary Table 5). These were, on average, 2.8 ± 0.2 Gg yr−1 significantly higher than the fumigation sector estimates alone (the sum of QPS and non-QPS emissions based on CH3Br consumption data reported to the United Nations Environment Programme (UNEP)) and 1.2 ± 0.2 Gg yr−1 significantly higher than the total estimate (fumigation plus three non-fumigation sectors) by Choi et al.17. CH3Br emissions from fumigation (QPS + non-QPS) sectors were about 2.0 Gg yr−1 (54% of the total bottom-up emissions) on average during 2011−2020. Non-QPS fumigation emissions in this study (0.07 Gg yr−1) were consistent with amounts reported to UNEP (0.06 Gg yr−1), while the QPS emissions (1.96 Gg yr−1) were higher than reported (0.91 Gg yr−1). QPS emissions that are primarily associated with the import/export shipping industry contributed over 90% of the total fumigation emissions (Fig. 3). China’s port cargo throughput is concentrated in eastern China provinces (Supplementary Table 6 and Supplementary Fig. 6); thus, QPS emissions associated with shipping may account for some of the emission hotspots of eastern China.

Compared with Choi et al.17, seven additional sectors were considered in this study, including non-fumigation anthropogenic sectors (feedstock6,24, solvents24–26, CH3Br industrial production24) and terrestrial ecosystem sectors (rice paddies13,22, salt marshes12,15, mangroves11, and fungi27,28). CH3Br emissions from these seven sectors reached 1.0 ± 0.1 Gg yr−1 on average during 2011−2020, which accounted for 26% of the total bottom-up emissions and were equal to the sum of fumigation use (QPS and non-QPS sectors) emissions based on CH3Br consumption data reported by China to UNEP (Fig. 3c). Thus, the addition of these seven sectors substantially improves the bottom-up estimates of CH3Br emissions in China.

Unexplained high emissions of CH3Br from China and their potential causes
In total, our bottom-up emission estimates of 3.7 ± 0.2 Gg yr−1 remain 5.5 ± 1.4 Gg yr−1 lower than our top-down estimates (9.2 ± 1.4 Gg yr−1) on average during 2011−2020 (Fig. 4 and Supplementary Table 7). The gap between our top-down and bottom-up emissions estimates is large, amounting to approximately 60% of the top-down estimates. The unexplained CH3Br emissions in China may be attributed to three possible causes.

First, multiple instances of illegal production and sales were reported between 2010 and 2014 in multiple provinces29–34 (magenta triangles shown in Fig. 2b). Although the above-mentioned activities were punished and reported, multiple instances of illegal production still occurred in 2020 in the Shandong Province35,36 (yellow dots shown in Fig. 2b). The proportion of emissions from this source to the total unexplained emissions is unclear.

Second, known terrestrial sources of CH3Br may be underestimated. The emission fluxes of CH3Br from terrestrial sources (such as salt marshes, rice paddies, and rapeseed) vary with temperature37, Br content of the soil22, and plant types38. However, measurements of CH3Br emission fluxes from these sources are sparse27, limiting the accuracy of estimates for emissions from these sources. Representative CH3Br flux measurements in China need to be conducted in the future to better quantify the emissions from these terrestrial sources. Although coastal ocean waters are also a source of CH3Br (the open ocean is a net sink of CH3Br)39, China’s CH3Br emissions from coastal ocean waters are estimated at 0.05 (0.01−0.15) Gg yr−1 based on the area of China’s coastal ocean waters40 and measured emission flux rates39, so coastal ocean waters are unlikely to be major contributors to the large unexplained sources observed here.

Third, it is likely that additional sources remain to be identified. New emission sources of CH3Br are still being discovered in recent years, such as baking discovered in 201641 and copper-based pesticides discovered in 202242, reflecting our incomplete understanding of CH3Br sources. However, the emission contribution from baking is negligible (about 0.2 Gg yr−1 globally41). Using China’s CuSO4 consumption (Supplementary Table 8) and the relationship between copper(II) amendments and CH3Br emissions reported by Jiao et al.42, China’s emission from this sector is likely also negligible (0.01 ± 0.004 Gg yr−1). Note that due to the lack of China’s CuSO4 consumption for pesticide use, we use total CuSO4 consumption to estimate emissions from this sector (data and calculation shown in Supplementary Table 8). Therefore, the missing source in China cannot be well explained by these newly-identified sources but may be explained by sources yet to be identified. The emission hotspots identified via our inverse modeling may provide some implications for future work on identifying new sources. In summary, unreported production, emissions from known natural sources (if underestimated), and unidentified new sources may contribute to China’s large missing source of CH3Br.

Methods
Sampling and analysis
Atmospheric mole fractions of CH3Br were measured at ten sites across China from 2011 to 2020: Akedala (AKD), Heyuan (HYN), Jiangjin (JGJ), Jinsha (JSA), Lin’an (LAN), Longfengshan (LFS), Mount Waliguan (WLG), Xinfeng (XFG), Shangri-La (XGL), and Shangdianzi (SDZ). The detailed information on the ten sites is summarized in Supplementary Table 2. These sites were located more than 20 km from the nearest industrial and densely populated areas in order to sample air masses carrying regional emission signals48–51.

Weekly or daily sampling was conducted at all ten sites (Supplementary Table 2). The same sampling and analysis methods were used at the ten sites, as described in detail in previous studies48,50. Air samples were pumped by a membrane pump (KNF-86, KNF Neuberger, Germany) from the tops of the sampling towers through a sampling tube (10 mm OD Synflex tubing, Eaton, USA) into 3 L stainless steel canisters (X23-2N, LabCommerce, Inc., USA)50. All the flask air samples were sent to the central laboratory at the Meteorological Observation Centre in Beijing for analysis within one month49,50. At each site, pairs of parallel samples were collected concurrently for quality assurance49,50. Additionally, at the SDZ site, an in situ sampling and analysis system was operated during 2011−2020. All the flask and in situ samples were analyzed by a “Medusa” gas chromatographic system with a mass spectrometric detector (Agilent 6890/5975B, USA)50. To detect and correct for drift in detector sensitivity, each air sample measurement from canisters was bracketed by a reference gas (real-air working standard) measurement50. Atmospheric measurements of CH3Br are linked to AGAGE standard scales50,52, and the dry mole fractions of CH3Br were reported using the Scripps Institution of Oceanography 2005 (SIO-2005) calibration scale50. We performed a stability test for CH3Br as long as 112 days, and the recoveries were 101%, 101%, 102%, 101%, 102%, and 98% for Days 9, 18, 41, 65, 90, and 112, respectively. For each tested day, we analyzed four SS flasks and took the average. There was no significant drift for CH3Br measurements, with a standard deviation of the four flasks being 1−2% (Supplementary Table 9). The measurement precision of CH3Br was 1% for measurements on flask samples and 0.6% for SDZ in situ measurements50. All observation data used in the emission inversion are shown in Supplementary Fig. 7.

As shown in Fig. 1 and Supplementary Fig. 1, the total annual average emission sensitivity data (derived from FLEXPART backward simulations, see next section) of these sites (sum of averaged footprints every three hours for all sites with measurements in that year) exhibit a high spatial coverage for all of China, which ensures that the national total emissions in China can be constrained by observations at these sites. Nonetheless, adding more observational sites in regions that currently do not have sites, should help to better constrain regional emissions in the future.

FLEXPART-based Bayesian Inversion of emissions
In this study, the Bayesian inversion algorithm and FLEXPART (“FLEXible PARTicle dispersion model”) atmospheric transport model were used to estimate national CH3Br emissions in China. This framework was well-established and described in detail in previous studies48,49,53. FLEXPART is a Lagrangian transport and dispersion model (http://www.flexpart.eu/) that has been widely used in simulating the transport of various atmospheric species54,55. The three-hour temporal resolution and 1o × 1o global meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF) was used to drive the FLEXPART model. To obtain the source-receptor relationship matrix (SRRs, also called “emissions sensitivity” or “footprint”, in units of m2 s g−1), in the FLEXPART model, 40k virtual particles were released from the location of each observation site in a three-hour interval, and the model was run backward for 20 days for each atmospheric observation48,49. This matrix relates emission fluxes at the source to atmospheric mole fractions measured at the receptor (measurement site)48,49. During the 20-day backward simulation, the fraction of chemical loss to emission resulting from CH3Br lifetime (0.8 years) is approximately only 1.7% (1-exp(−5/(0.8 × 365))) considering that the enhancements measured at observation sites are typically influenced by emissions within a five-day transport of an air mass54. A previous study demonstrated that the inversion results of CHCl3 (lifetime = 0.4 years) changed by only 1% when chemical losses were included in the simulation53. Thus, the chemical losses of CH3Br were not considered in our backward simulation. Under the Bayesian inversion framework, we obtained the optimal posterior emission by minimizing the following cost function as Eq. (1):

J(x) = 1/2 (x − xa)T Sa−1 (x − xa) + 1/2 (yobs − Hx)T So−1 (yobs − Hx) (1)

The optimal x is solved at ∇ J(x) = 0 as shown in Eqs. (2) and (3):

x = xa + (HT So−1 H + Sa−1)−1 HT So−1 (yobs − Hxa) (2)

Sb = (HT So−1 H + Sa−1)−1 (3)

where x is the state vector of the posterior emission strengths in each grid box, yobs is the observed enhanced mole fraction (observations minus baselines), xa is the prior emission vector, H is the emission sensitivity matrix derived from the FLEXPART backward simulations, Sa is the prior emission error covariance matrix, and So is the observational error covariance matrix.

Choi et al.17 estimated CH3Br emissions from eastern China at 4.1 ± 1.3 Gg yr−1. Therefore, we used a constant prior for China’s CH3Br emissions of 5 Gg yr−1 during the study period and disaggregated the total emissions by population spatial distribution (Gridded Population of the World: Future Estimates, 2020). To ensure that our inversion estimates were not sensitive to the choice of the prior emission estimate, we scaled the prior emissions by factors of 0.5 and 1.5 and then repeated the inversion (Supplementary Fig. 8a). Because of the lack of uncertainty in the gridded prior emissions, we set the prior emission uncertainty in each grid to 100%, 150%, and 200% of the corresponding emissions48,49. The final posterior emission was the ensemble result of nine inversions (three prior emission fields × three prior emission uncertainties)48,49. For the flask sampling sites, background mole fractions were estimated as the lower value of (1) the lowest measurement in the 90-day moving window and (2) the latitude-direction linearly interpolated value between the monthly mean background value at the Ragged Point site (RPB, 13.17°N, 59.43°W) and Mace Head site (MHD, 53.33°N, 9.9°W)48,49. In most cases, the lowest measurement in the 90-day moving time window was chosen as the baseline. Additionally, we tested our inversion using the same baseline calculation method mentioned above but incorporated the monthly mean background value at the Trinidad Head site (THD; 124.2°W, 41.1°N) instead of the MHD site (Supplementary Fig. 8b). For the SDZ in situ site, background mole fractions were estimated using the approach of Stohl et al.54, which selects the lowest 25% of the observations in a 30-day moving time window and then subtracts prior simulated enhancements. Observational errors are represented by one-sigma standard deviations of all observation data in a year at a site48,49. To eliminate the temporal correlation of high-frequency measurements at the SDZ in situ site, the daily averages of measurements were used in our inversion48,49. The observational error covariance matrix S is a diagonal matrix, with diagonal elements representing the square of the observation error.

Bottom-up emission inventory of China’s CH3Br
We estimated China’s CH3Br emissions from four sectors: (1) fumigation, (2) CH3Br production and non-fumigation, (3) combustion, and (4) terrestrial ecosystems. The emissions from each sector were calculated as follows:

In terms of the fumigation use sector, CH3Br has been used extensively worldwide as a pest-control fumigant since the 1950s6. Fumigation uses include quarantine pre-shipment (QPS) and non-QPS applications. The emissions calculation equation is as Eq. (4):

E fumigation,t = C non-QPS,t × EF non-QPS + C QPS,t × EF QPS (4)

where E is the emissions (Gg yr−1) of the fumigation sector in year t, C non-QPS,t and C QPS,t are the consumption (Gg yr−1) of the non-QPS and QPS uses in year t, respectively, and EF non-QPS and EF QPS are the emission factors of the non-QPS and QPS uses, at 65% and 84%, respectively3. The consumption data for non-QPS and QPS are listed in Supplementary Table 10.

In terms of CH3Br production and non-fumigation use sector, considering the possibility of CH3Br leakage from industrial production, similar to the leakage calculations during CCl4 56 and CH2Cl2 51,57 production, we calculated the emissions from the CH3Br production subsector. In addition to fumigation uses, some CH3Br has been used for non-fumigation uses, including two subsectors: feedstock uses6 in the organic synthesis industry and solvents/cleaning agents26. The emissions from these three subsectors were calculated as Eq. (5):

E production and non-fumigation,t = Σ i=1 3 C i,t × EF i (5)

where E production and non-fumigation,t are the emissions (Gg yr−1) from the CH3Br production and non-fumigation use sectors in year t, i represents the number of sectors, C i is the consumption (Gg yr−1) of feedstock use, solvent/cleaning agents, or production of CH3Br in year t. The consumption and production data are listed in Supplementary Table 10. EF i is the emission factor for the three subsectors. The emission factor was 4% for the feedstock use and industrial production subsectors24. For the solvent/cleaning agent subsector, CH3Br was assumed to be completely emitted within two years (50% in each year)58 (see Supplementary Table 11).

In terms of combustion sector, we estimated the CH3Br emissions from two combustion subsectors: open biomass burning and indoor biofuel burning59. For the open biomass burning subsector, we used dry matter burned mass data from the Global Fire Assimilation System (GFAS) database60 and emission factors of six biomass types from Andreae59. The emission factor of each grid was determined by the corresponding gridded land-use and biomass types. Global land-use data were obtained from the MODIS satellite-derived product, MCD12C1. The global gridded CH3Br emissions from open biomass burning were calculated by multiplying the dry matter burned mass matrix and the emission factor matrix (Eq. 6). Detailed information regarding this method is available in our previous study61. The emission factors for each biomass type are listed in Supplementary Table 12. For the indoor biofuel burning subsector, CH3Br emissions were calculated by multiplying the burned indoor agricultural residue mass by the emission factor. The burned indoor agricultural residue masses were equal to the product of the collected agricultural residue masses, grass-to-grain ratio of each crop, dry matter ratio of each crop residue, and burning ratio of the indoor biofuel62. We calculated the CH3Br emissions from the indoor burning of the 15 main crops in China (Supplementary Table 13). Detailed information regarding the aforementioned parameters is provided in Supplementary Tables 13 and 14. The emission factor of burning for each crop was set at 0.0011 g kg−1 during the study period59. The detailed calculation formulas are as Eq. (6−8):

E biomass burning,i,j,t = DM i,j,t × Area i,j × EF i,j (6)

E indoor biofuel,t = M t × EF indoor biofuel (7)

M t = Σ m P m,t × R m × r × σ dry-matter × φ (8)

E biomass burning,i,j,t denotes the emissions (kg s−1) from biomass burning (open) of the grid (i,j) in year t, DM i,j,t is the dry matter burned mass (kg m−2 s−1) of the grid (i,j) in year t, Area i,j is the area (m2) of the grid (i,j), and EF i,j is the emission factor (g kg−1) of the grid (i,j). E indoor biofuel,t denotes the emissions (Gg yr−1) from indoor biofuel burning in year t, M t is the total mass (kg yr−1) of agricultural residue burned indoors in year t, and P m,t is the annual production (kg yr−1) of crop m in year t, as taken from the China Rural Statistical Yearbook63. R m is the grass-to-grain ratio (%) of the crop m, r is the burning ratio (%) of indoor burning, σ dry-matter is the dry matter ratio (%) of each crop residue, and φ is the combustion efficiency (%) of the indoor burning. The parameters of R m, r, and σ dry-matter can be found in our previous study62. EF indoor biofuel is the emission factor (g kg−1) of indoor biofuel burning.

In terms of terrestrial ecosystem sector, we included five terrestrial ecosystem emission subsectors (rice paddies4,13,22, rapeseed38,64, salt marshes12,15, mangroves4,11, and fungi (decomposition of dead litter))4,27 in our bottom-up inventory. We extrapolated China’s CH3Br emissions from estimates of the planting areas for these sources12,15,17. For the rice paddy subsector, the emissions equal to China’s rice planting area multiplied by the unit area emission flux (1.1 mg m−2) obtained from Redeker et al.22. Data on China’s rice-planting areas were obtained from the China Rural Statistical Yearbook63 (Supplementary Table 15). For the rapeseed subsector, emissions were calculated as the global total emissions from rapeseed (2.8 Gg yr−1 in 201864) multiplied by the ratio of China’s rapeseed planting area to the global total planting area. The rapeseed planting areas in China and global totals were obtained from the China Rural Statistical Yearbook63 (Supplementary Table 15) and the Food and Agriculture Organization (FAO, https://www.fao.org/faostat/en/#data/QCL/visualize), respectively. We scaled the corresponding global total sectoral emissions reported by WMO for salt marshes (7 (0.6−14) Gg yr−1)4 and for mangroves (1.3 (1.2−1.3) Gg yr−1)4 to China using the ratio of China’s salt marsh (3.8 × 1011 m2)15 and mangrove (2.0 × 1011 m2)11 areas to global total areas. The salt marsh and mangrove area data for China were obtained from Chen et al.65 and Wang et al.66, respectively, and are presented in Supplementary Table 16. For the fungi subsector, we roughly assumed that the decomposition mass was proportional to the vegetation area; thus, we calculated China’s CH3Br emissions from fungi decomposition activities by multiplying global fungi emissions (2.2 (1−5.7) Gg yr−1)4 and the ratio of China’s vegetation area to global vegetation area calculated by the MODIS MCD12C1 product (https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD12C1/). The equations used for the calculations are as Eqs. (9−13):

E rice paddies,t = A rice,t × F methylbromide (9)

E rapeseed,t = E global rapeseed,t × A China rapeseed,t / A global rapeseed,t (10)

E salt marsh,t = E global salt marsh × A China salt marsh,t / A global salt marsh,t (11)

E mangrove,t = E global mangrove × A China mangrove,t / A global mangrove,t (12)

E fungi,t = E global fungi × A China vegetation,t / A global vegetation,t (13)

E rice paddies,t is the emission (Gg yr−1) from the rice paddies subsector in the year t, A rice,t is China’s rice planting area (m2) in the year t, F methylbromide is the emission flux (mg m−2) of CH3Br from the rice paddies, E rapeseed,t the emission (Gg yr−1) from the rapeseed subsector in the year t. E global rapeseed,t is the global emission (Gg yr−1) from the rapeseed subsector in the year t, A China rapeseed,t and A global rapeseed,t are rapeseed planting areas (ha; 1 ha = 0.01 km2)) of China and global totals in the year t. E salt marsh,t is the emission (Gg yr−1) from the salt marsh subsector in the year t, and A China salt marsh,t and A global salt marsh,t are salt marsh areas (m2) of China and global totals in the year t, respectively. E mangrove,t is the emission (Gg yr−1) from the mangrove subsector in the year t, and A China mangrove,t and A global mangrove,t are mangrove areas (m2) of China and global totals in the year t, respectively. E fungi,t is the emission from the fungi subsector in the year t, and A China vegetation,t and A global vegetation,t are vegetation areas (m2) of China and global totals in the year t, respectively.

In this study’s bottom-up inventory estimation, a normal distribution with 10% uncertainty for CH3Br production and consumption data derived from our survey report25; a 5% uncertainty was adopted for all national statistical activity data (i.e., agricultural residue mass and rapeseed and rice cultivation areas) used in this study58. A Monte Carlo method with 100,000 samples was employed to calculate bottom-up emissions and uncertainties58.

Metric for ozone depletion
A key metric to assess the ability of a compound to deplete stratospheric ozone is ODP, which is calculated relative to a reference compound (CFC-11 with an ODP of 1). We calculated the ODP-weighted emissions (CFC-11-equivalent emission) of CH3Br by multiplying the mass emissions of CH3Br by its ODP value. Additionally, we calculated integrated ozone depletion (IOD) to quantify the extra ozone depletion resulting from China’s missing source during 2011–2050, assuming that the missing source (5.5 Gg yr−1 on average from 2011 to 2020) remains constant during 2021–2050. The time-integrated column ozone depletion can be calculated using halocarbon emissions and their total atmospheric and stratospheric lifetimes67, as shown in Eq. (14):

IOD = K E Eq (τ atmos / τ strat) (14)

Here, K = 100 ± 16 DU years per Tg Cl. E Eq is the emissions in Tg Cl, and we multiplied a bromine efficiency factor of 60 to calculate E Eq for CH3Br67. τ atmos and τ strat are total atmospheric lifetime and stratospheric lifetime of CH3Br.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This paper makes a convincing case that emissions of methyl bromide from China significantly exceed the reported national emissions and do not conform to the Montreal Protocol. The result is based on a large amount of data with appropriate data analysis and modeling. The presentation of the results is clear. This is a very good piece of work, worthy of publication. That said, there are a few areas where the manuscript could be improved (described below). I consider these minor changes. Overall I congratulate the authors on having done an important piece of work.\nDetailed comments:\nOne issue is the metrics used to quantify the impact of the unreported emissions on stratospheric ozone. The authors cite two metrics: 1) time to stratospheric ozone recovery, and 2) integrating the effects in terms of DU-years. The first of these (recovery time) is highlighted in the abstract. This metric is inherently unstable and poorly constrained. \"time to recovery\" describes the asymptotic approach to some mythical pre-ozone hole atmosphere. Because the slope near recovery is small, there are large changes in time associated with small changes in emissions. It is simply not a robust quantity. By comparison, the second metric (DU-years) is a well-defined integral effect which is robust and meaningful. I imagine the authors might say that the Stratospheric Ozone Assessment uses \"time to recovery\", so they should. I would argue that it does not make sense to encourage the use of such a poor metric. So, I would advise that they remove that metric from the abstract and the body of the paper and emphasize DU-years instead.\nThe manuscript would greatly benefit from a thorough copy editing. For example, the meaningless phrase \"This study depicts a full picture\" is in the abstract. Some of the language seems unecessarily self aggrandizing - running down prior work rather than just explaining what they did, what they found, and what it means. For example they improved the bottom up inventory by including additional sources. That's great, but is it necessary to follow this with: \"Thus, CH3Br emissions from these seven sectors must be considered, as their addition substantially improves the bottom-up estimates of CH3Br emissions in China\"?\nThere are several places where the text is just a long list of sites and statistics (lines 110-115, 120-124, 130-133). These sentences are unreadable in the normal sense and should be converted to tables. The text should be used to provide added value (information and insight), not to list numbers. Which numbers are important and why?\nline 60. This is the start of a very long and meandering paragraph that does not have a clear focus. Some of it reads like a proposal rather than a paper. I suggest that this be broken into two paragraphs - one about the history of China's methyl bromide use and one about prior studies and their limitations.\nline 70. \"Limited by the insufficient spatial coverage of observation stations and the shortcomings of the interspecies correlation method (ISC) used in previous studies, previous emission estimates may be biased and the hotspots of CH3Br emissions in China are unclear.\" I don't underatnd why they would be biased (rather than just uncertain. I also don't know what it means for a hotspot to be \"unclear\". This is not well written.\nline 91. \"The delay years of the Antarctic ozone recovery are expected to be larger if considering the unidentified sources in other countries.\" That requires proving that those unidentified sources are anthropogenic.\n\"This study advances not only for the scientific understanding of the CH3Br budget but also for the assessment of implementing the Montreal Protocol.\" I don't know what this sentence means or why it has a \"but\" in it. Perhaps \"for\" should be deleted and \"but\" replaced with \"and\"?\nline 125. This is a run-on sentence whose meaning is unclear. \"accurate\" seems like a misuse of the word. Top-down inversion is another estimate - maybe it is more accurate than bottom up but just to declare it as accurate is misleading.", "reviewer_3": "The manuscript describes the discrepancy between CH 3 Br emission estimates from China between an updated top-down approach and a new bottom-up emission inventory developed for this study, which are clearly biased-high compared to the expected phase-out of the Montreal Protocol. Despite the paper focuses on a very important issue, I regret to mention that, at least in its current stage, the work is difficult to follow and lacks of the required quality, evaluation and discussion to be accepted for publication in Nature Communications. Indeed, at least a couple of the main messages of the work (i.e., the new observational dataset from 2011 to 2020 and the large regional enhancement in CH3Br abundance over China compared with the global background at equivalent latitudes) are left out from the abstract and only briefly mentioned in the discussion. I provide below a full set of major, minor and technical comments oriented to highlight the most important and novel results presented in the manuscript and improve the overall paper organization. If the authors feel that all comments can be revised and addressed and are willing to introduce significant changes on the main text structure, I’m willing to perform a second evaluation.\nPlease see attached file with the complete evaluation.\nReview of the manuscript “Unexplained high and persistent methyl bromide emissions in China after 2015 phase-out: A concern for the ozone layer and the Montreal Protocol” by Hu et al., 2024.\nThe manuscript describes the discrepancy between CH Br emission estimates from China between an updated top-down approach and a new bottom-up emission inventory developed for this study, which are clearly biased-high compared to the expected phase-out of the Montreal Protocol. Despite the paper focuses on a very important issue, I regret to mention that, at least in its current stage, the work is difficult to follow and lacks of the required quality, evaluation and discussion to be accepted for publication in Nature Communications. Indeed, at least a couple of the main messages of the work (i.e., the new observational dataset from 2011 to 2020 and the large regional enhancement in CH3Br abundance over China compared with the global background at equivalent latitudes) are left out from the abstract and only briefly mentioned in the discussion. I provide below a full set of major, minor and technical comments oriented to highlight the most important and novel results presented in the manuscript and improve the overall paper organization. If the authors feel that all comments can be revised and addressed and are willing to introduce significant changes on the main text structure, I’m willing to perform a second evaluation.\nMajor Comments:\nS1: L96-L135: The first section of the results presents data from observations performed at 10 sites over China between 2011-2020, and compares the new dataset w.r.t. CH3Br values from the AGAGE network to estimate the enhancement in CH3Br abundance over the background.\nNone of this issues, which are the main results of this study, are mentioned in the abstract.\nThe complete text is very hard to follow, with explicit and very detailed information of the exact values and uncertainties over each observational site that makes a complex reading (which are better suited for Figures and Tables) instead presenting an expert guided description of the main patterns and variations. In addition, one of the most important results (the estimation of the regional enhancement of China over the global background) is only show in Fig. S2 in the Supplement, and only briefly discussed here.\nS2: L136-L156: The authors should clearly state that the updated top-down estimate was possible thanks to the extended observational dataset performed at 10 site in China. Most notably, the inverse method applied shows East China to be a hotspot in CH3Br emissions compared with the remaining fraction of the country (Fig. 2b) although if one compares total emissions from China and East China in Fig. 4, East China represents less than half of the total emissions (which is not discussed in the text). In addition, in the same paragraphs the author’s claim that “this is the first study able to quantify CH3Br emissions in China from 2011 to 2020” but “our emission estimates are consistent with the most previous studies”, which requires further clarification.\nS3: L157-L182: The bottom-up inventory results are presented in this section. The discrepancy between the top-down and bottom-up total emission values are discussed, focusing mostly on fumigation. First, the usage of fumigation and/or QPS/non-QPS should be unified or at least be clearly described for a wider community. Second, no information is provided about how important is the fumigation sector in east China compared to the rest of the country. Third, the discrepancy between the reported fumigation usages from China to UNEP w.r.t. the assessed values are only briefly mentioned, and should be highlighted.\nS4: 183-218: Despite the connection with illegal/unreported sales is linked with the unexplained emissions, a comprehensive assessment of which sectors are expected to be missing and/or misrepresented is missing in the text and/or mentioned superficially. Experienced scientific orientation towards which sectors should be further studied to reconcile the top-down and bottom-up approaches is expected in these types of papers to inspire future research.\nS5: L235-244: The second paragraph of Section 5, altogether with L34-L35 in the abstract, are un-proportionately highlighted in the manuscript. Most importantly, I disagree with the Methodology used to estimate the 0.7 years delay in the recovery of Antarctic ozone due to the unexplained CH3Br emissions from China found in this study. The referenced methodology used 3D global models to estimate the role of stratospheric Cl-enhancements from a global CH2CL2 emission inventory and assuming a trend in emissions until year 2050; while here the estimation is based on an proportional ozone efficiency of bromine (compared to chlorine) and a very simplified expression to estimate the global enhancement in CH3Br global abundance based on surface-only CH3Br-observationally derived emissions from China, which are scaled to whole troposphere and stratosphere, and assumed to remain constant until 2050. I agree that the stratospheric ozone implications of the well stablished enhanced emissions from China should be mentioned, and I do not expect the authors to perform global simulations to quantify these impacts, but given the weakness of the approach used for their estimation (L455-L487 in the SI), I suggest not overstating quantitatively the global impact over Antarctic ozone. In addition, depending on the section being read (abstract, introduction or Section 5) it is not clear if the ozone impacts are given for the global ozone layer or to Antarctic ozone instead, which significantly differ.\nMinor Comments:\nL30: How large is the 5.5 Gg yr-1 discrepancy in percentage terms? Providing percentage enhancement/discrepancy values will certainly help to highlight the results and implications.\nL32: Emissions hotspots were identified, but there is not mention on how did you do so in the abstract. Both the observational dataset and the method used should be mentioned.\nL58-L59: It should be useful for the general audience to briefly explain that bromine is more efficient than chlorine in destroying ozone from the very beginning.\nL69: Sentence would benefit to mention that due to its comparatively short lifetime, national/local CH3Br budgets are expected to differ for different regions.\nL87-L88: The emission hotspots are identified using the bottom-up or in the top-down approach? Or using both?\nL105-124: The text is very difficult to read. I suggest rephrasing providing a comparative description of the results without expressing so many values in the text, and focusing on the most important ones for the message that is given.\nL112 and L126: At least a brief summary of the methodology used to estimate the baseline CH3Br value and the CH3Br enhancement over China should be given in the main text, and then extended in Methods. This is not completely clear even after reading methods.\nL129-L133: Again, very hard to follow with so many acronyms and values. The writing style is more focused for a specific journal than for a general paper.\nL134: In line L108 you highlight the importance of the latitudinal CH3Br variation (which is correct), but here you highlight that the variability in the CH3Br enhancement is greater between east and west stations. Please explain the why? And also explain if a latitudinal variation could be “hidden” in the east-west variability shown.\nL153: Emissions from east China account for 40% of total China. Can you expressed the fraction of the total area and population that those provinces represent?\nL168-L171: Here you are comparing the emissions from 7 sectors from your bottom-up inventory w.r.t. the reported emissions from QPS+nonQPS to the UNEP, but no mention is given to the QPS+nonQPS estimation from your study, which is only mentioned in the next paragraph (L176). I suggest reordering and providing percentages in addition to absolute values.\nL180:182: “We highlight the large gap between our top-down and bottom-up emissions estimates in the following section (approximately 60% of the top-down estimates; see the discussion below).” This should be highlighted in the abstract. Note that it is very repetitive to the 1st sentence in next section (L185-L189).\nL210-L212: The sentence points at total CH3Br emissions or only those related to QPS?\nL212-L213: “The proportion of emissions from this source to the total provincial emissions is unclear;”and “requires further investigation”. Can you at least provide a range of estimated or reported values?\nL216 … “the unidentified new sources and emissions from known natural sources” … This sentence requires citation. One possibility is the recent SOLAS review from Tinel et al., (2023). (Tinel, L., Abbatt, J., Saltzman, E., Engel, A., Fernandez, R., Li, Q., Mahajan, A. S., Nicewonger, M., Novak, G., Saiz-Lopez, A., Schneider, S., and Wang, S.: Impacts of ocean biogeochemistry on atmospheric chemistry, Elem. Sci. Anthr., 11, 1–26, https://doi.org/10.1525/elementa.2023.00032, 2023.)\nL221-L222: The conversion of CH3Br emissions to ODP-weighted CFC-11-eq emissions should be explained somewhere in Methods.\nL227: It is not clear if the 5.0 ± 1.0 Gg yr-1 value correspond to total China or east China.\nMethods:\nL263: Only 5 (five) sites are described in ref (40). Please specify.\nL295-L297: Please revise the whole sentence. What do you mean by “obtained via 40k virtual particles released at each observation station in a three-hour interval”. Are emissions included at the same locations as the observational sites?\nL300: Please explain how do you make consistent the 1.8 years (reaction with OH) and 3.4 years (soil uptake) lifetimes with the 0.8 years global lifetime given in L407. This is of fundamental importance to ensure that the different approaches used are comparable.\nL303: What do you mean by “proportion”? Why is the exponential decay value a factor of 4 (5/20) smaller than in previous equation in L302?\nL328-L332: Is this a standard procedure to estimate the background concentration? Given the importance of the background estimation to compute the enhancement over China, further details and/or an example with specific data would help to understand if the approach used is valid.\nL458: There are newer publications than ref. 57 supporting “recent estimations”. In addition, here and elsewhere in the text, it is not clear if you are explicitly pointing at the ozone layer, or the Antarctic ozone hole. Note that the return dates as well as the influence of ODSs under a changing climate are significantly different depending on the studied region.\nL469-L474: It is not clear what is the meaning and difference between Fi and Fsurf.\nL477-L479: Rephrase the sentence and/or citations so the references support what is being said (Hossaini et al. reported …)\nL481-L483: How can you make a CH3Br increase relative to CH2Cl2 in 2050? Approaches in current work and in Hossaini are different. See my general comment above and make it clear.\nL484: Where does the (1/2) value come from? Is it because the 2 Cl atomicity in dichloromethane, which is different from Br 1 atomicity in methyl bromide?\nL486: Following my major comment above, there are no further details on how the integrated column ozone depletion change due to CH3Br is being computed. I suggest removing it.\nLanguage editing comments and Typos:\nL127: “accurate” is not the proper word here. Please refer.\nL173: “substantially improved” compared to what?\nL203: “magenta triangles” on Fig. 2b.\nL337: Do you mean the standard deviation? (1σ or 2σ?)\nL482: … in proportion to the additional “equivalent” Cl loading caused by CH3Br …\nFigures and Tables\nFigure 1: What does the map in the middle show? This is not described in the caption. In addition, why did you chose a log scale for the color contours? To highlight low values? Same applies for Fig. S2.\nFigure 2: What is the shading in panel a). Explain what do you mean by “posterior emission” in panel b) for the general reader.\nFigure 3: Usage of fumigation, QPS and non-QPS in labels and caption is confusing. Please revise and make it consistent with the text. In addition, in panel b) it is clear that Choi et al. results are lower than in this study, but Fig. S4 shows equivalent results (Choi is even larger in some years) in east China. Can you explain those differences?\nEvaluate if some of the supplementary tables can be merged/unified. If this is not possible at least use equivalent units for the emissions and/or areas. In addition, knowledge of the fraction of the total area and population from east China relative to the total China is missing.\nTable S4: Explain if the mole fractions in the tables are the enhanced values on top of the background level.\nFigure S2: This is a nice figure and should be included in the main text.", "reviewer_4": "Fang et al. estimate the national emissions of CH3Br in China from 2011 to 2020, and reveal that there is high and persistent CH3Br emissions in China compared to the background sites. Although the focus of this manuscript together with the availability of long-term observation dataset are important for us to better understand the CH3Br emissions and its impacts, I think that the current manuscript is still lacking of solid supporting evidences and implications. The writing of the manuscript is also hard to follow, therefore, requires major improvements prior to the decision for publication. My comments are as the followings:\nPage 3, Line 50-54: The authors should introduce both the anthropogenic and natural sources of CH3Br in the introduction as the general readers might not understand the origin of CH3Br.\nPage 4, Line 75: Please specify which emission sectors have been omitted.\nPage 5, Line 91: Despite the authors have justified that these 4 sites are located at similar latitudes, I am not sure how suitable is it to select these 4 sites to represent the global background. Can you further explain on this? These sites have different characteristics and some of the sites might also have influence from the anthropogenic emissions, for example the Mace Head and Gosan can also be influenced by polluted air mass. Are these 7.0 to 7.6 ppt CH3Br averaged values or being obtained with similar method to estimate baseline values in China sites? I think it is also important to look at how do the high values in China compared to the to the polluted areas around the world? Do they have similar trend?\nPage 6, Line 118: It may be true that the long-term CH3Br emission trend is a key attraction, but I cannot see further novelty was emphasized throughout manuscript. The higher CH3Br emission has been expected as indicated by previous studies (including the Li et al., 2011; Kim et al., 2010). To me, this manuscript seems like a follow-up study to the findings reported in Choi et al. (2022) and there are some similarities in the method, analysis, and results. Although some efforts have been made to compare the works, they should further distinguish the novelty of this work with the previous studies, and properly highlight the key novelty in both abstract and main text.\nPage 7, Line 139-140: Is this 1.4 Gg yr-1 statistically different? Is it within the uncertainty range? In other word, will the red and blue lines in Fig.3b overlap if the uncertainty is being considered?\nPage 7, Line 141-149: Other than the information on port cargo throughput, is there any evidence showing the shipping activities will be important for the CH3Br emission? I am not sure how can it linked to the emissions hotspot. Is the chemical ‘ingredient’ during the fumigation still contain CH3Br? If a large source of CH3Br being emitted, the bromine chemistry will properly be important in this area, thereby affecting the surrounding air quality. Is there measurement being conducted around the ports before?\nPage 8, Line 158: I am surprised that the authors did not discuss the causes/potential reasons of the big gap between top-down and bottom-up emissions in this paragraph.\nPage 8, Line 162: The discussion in the section for its potential causes seems to be a major issue. First, I am quite sceptical on linking the CH3Br emission with the provided evidence for illegal production and sales of CH3Br in Jiangsu and Shandong province. According to the provided references, the cases have been reported by the government authorities, which means action have been taken to stop these illegal production and sales of CH3Br during the release of the reports. Logically thinking, the CH3Br emission from these illegal sources will likely becoming less. Without further evidence, I have doubt that the higher CH3Br emission are from the illegal sources. Second, the discussion on the new emission sources of CH3Br are pretty simple and vague. Third, the authors have mentioned about the terrestrial sources (such as salt marshes, rice paddies, and rapeseed), can ocean emission be an important source for CH3Br too? Given the warming of the surface ocean (due to climate change) and increasing of surface ozone levels, the ocean emission of CH3Br might be important too. The authors should add this information to the discussion.\nPage 10, Line 196: A major weakness of this manuscript is the discussion on the implication of CH3Br emission. The authors have tried to estimate the integrated ozone depletion for the unaccounted emissions of CH3Br in China originate entirely from anthropogenic sources and continue to 2050. The assumption of course is interesting but lack of scientific relevant. From the data, there is no trend of increasing for CH3Br emission in China, but towards a slightly decreasing trend starting form 2019 (Fig.2). Together with the more restriction of usage, anthropogenic sources might become less important and the contribution from the natural sources might become more relevant in future. However, these are not being discuss.\nPage 15, Line 310: Briefly explain what is the approach of Stohl et al.\nPage 29, Fig.1: From the 10 sites, almost half of them have only a few years (≤4 years) of continuous data from 2011 to 2020. How to make sure that these lacking of longer period of data in a particular site will affect the conclusions of this study?\nSI-Supplementary Table 2: Please state whether the station represent urban, rural, background, etc. site to give information on the type of environment for each sampling site.\nSI-Supplementary Table 6: Typo for ‘Hainan’."}, "author_response": "Responses to Reviewer #1\nReviewer #1 (Remarks to the Author):\nThis paper makes a convincing case that emissions of methyl bromide from China\nsignificantly exceed the reported national emissions and do not conform to the\nMontreal Protocol. The result is based on a large amount of data with appropriate data\nanalysis and modeling. The presentation of the results is clear. This is a very good\npiece of work, worthy of publication. That said, there are a few areas where the\nmanuscript could be improved (described below). I consider these minor changes.\nOverall I congratulate the authors on having done an important piece of work.\nResponse:\nWe appreciate the positive remarks and many constructive suggestions. We have\nrevised our manuscript according to these comments and provide point-to-point\nresponses below.\n1. One issue is the metrics used to quantify the impact of the unreported emissions on\nstratospheric ozone. The authors cite two metrics: 1) time to stratospheric ozone\nrecovery, and 2) integrating the effects in terms of DU-years. The first of these\n(recovery time) is highlighted in the abstract. This metric is inherently unstable and\npoorly constrained. \"time to recovery\" describes the asymptotic approach to some\nmythical pre-ozone hole atmosphere. Because the slope near recovery is small, there\nare large changes in time associated with small changes in emissions. It is simply not\na robust quantity. By comparison, the second metric (DU-years) is a well-defined\nintegral effect which is robust and meaningful. I imagine the authors might say that\nthe Stratospheric Ozone Assessment uses \"time to recovery\", so they should. I would\nargue that it does not make sense to encourage the use of such a poor metric. So, I\nwould advise that they remove that metric from the abstract and the body of the paper\nand emphasize DU-years instead.\nResponse:\nThis is an excellent point. The metric of \"time to recovery\" is indeed not very robust\nbecause of its high sensitivity to emissions near recovery. Accordingly, we have\nremoved the “time to recovery” metric and only emphasize DU-years.\nOriginal text:\nLines 34-36 in the original abstract: “More worryingly, we show that the recovery\nof the ozone layer can be delayed by 0.7 years if the unexplained emissions in China\nwere anthropogenic and not mitigated by 2050.”\nRevised text:\nLines 34-35 in the revised abstract: “If the unaccounted sources of CH Br in China\n3\nare anthropogenic and continue to 2050, they will lead to an integrated ozone\ndepletion impact of approximately 20 DU years.”\n2. The manuscript would greatly benefit from a thorough copy editing. For example,\nthe meaningless phrase \"This study depicts a full picture\" is in the abstract. Some of\nthe language seems unnecessarily self-aggrandizing - running down prior work rather\nthan just explaining what they did, what they found, and what it means. For example,\nthey improved the bottom-up inventory by including additional sources. That's great,\nbut is it necessary to follow this with: \"Thus, CH Br emissions from these seven\n3\nsectors must be considered, as their addition substantially improves the bottom-up\nestimates of CH Br emissions in China\"?\nWe conducted a thorough revision to produce a more streamlined and straightforward\nmanuscript, removing extraneous commentary and contextualizing results more\nconcisely. For example, the phrases and sentences cited above have been removed.\nWe have made numerous of edits throughout the text, and we believe that this revised\nmanuscript provides increased clarity and precision in a tighter package.\n3. There are several places where the text is just a long list of sites and statistics (lines\n110-115, 120-124, 130-133). These sentences are unreadable in the normal sense and\nshould be converted to tables. The text should be used to provide added value\n(information and insight), not to list numbers. Which numbers are important and why?\nResponse:\nWe appreciate this constructive suggestion to use statistics to emphasize key findings\nrather than only list numbers. We have changed the long and detailed numbers of each\nsite to concise summaries. The detailed numbers have been presented in\nSupplementary Fig. 2 and Table 3. In the revised manuscript's main text, we\nhighlighted the numbers that clearly demonstrate the spatial heterogeneity of\nenhancements among our ten Chinese sites. For example, enhanced concentrations in\neastern China (e.g., 9.9 ± 1.4 ppt at LAN) were much greater than other regions (e.g.,\n0.6 ± 0.8 ppt at WLG). The spatial distribution of observed enhancements provided\nimplications for the emission pattern in China.\nOriginal text:\nLines 109-115 in the original manuscript: “The average annual mean baselines\nobserved at our stations (8.2 ± 0.9 ppt [parts per trillion] for Lin’an (LAN), 7.5 ± 0.3\nppt for Shangri-La (XGL), 7.3 ± 0.7 ppt for Shangdianzi (SDZ), 7.1 ± 0.3 ppt for Mt.\nWaliguan (WLG), 7.0 ± 0.4 ppt for Longfengshan (LFS), see Methods for the baseline\ncalculation) were generally close to those observed at MHD (7.6 ± 0.5 ppt during\n2011–2020), THD (7.0 ± 0.3 ppt during 2011–2020), GSN (7.8 ± 0.4 ppt during 2011–\n20198), and RPB (7.1 ± 0.2 ppt during 2011–2020) during the study period (Figure\nS2).”\nRevised text:\nLines 89-97 in the revised manuscript: “The average annual mean baselines\nobserved during 2011–2020 ranged from 7.0 ppt at Longfengshan (LFS) to 8.2 ppt at\nLin’an (LAN) (Supplementary Table 3 and Supplementary Fig. 2). These\nconcentrations are comparable to the 7.0 to 7.6 ppt CH Br background mole fraction\n3\nrange observed at four Northern Hemisphere background sites within the Advanced\nGlobal Atmospheric Gases Experiment (AGAGE) network\n(https://agage.mit.edu/data/agage-data): Mace Head site in Ireland (MHD hereafter,\n53.3° N, 9.9° W), Trinidad Head site in California, USA (THD hereafter, 41.1° N,\n124.2° W), Gosan site on Jeju Island, South Korea (GSN hereafter, 33.3° N, 126.9°\nE), and Ragged Point site in Barbados (RPB hereafter, 13.2° N, 59.4° W).”\nOriginal text:\nLines 120-124 in the original manuscript: “The average annual mean mole\nfractions of CH Br, from high to low, were 18.1 ± 1.0 ppt for LAN, 15.6 ± 2.4 ppt for\n11.7 ± 0.6 ppt for Jiangjin (JGJ), 10.3 ± 1.2 ppt for SDZ (flask), 9.3 ± 0.5 ppt for SDZ\n(in situ), 9.0 ± 1.1 ppt for XGL, 8.8 ± 0.8 ppt for LFS, 8.7 ± 0.4 ppt for Akedala\n(AKD), and 7.7 ± 0.7 ppt for WLG (Figure 1 and S2).”\nLines 129-133 in the original manuscript: “As shown in Figure 1 and S2, the\naverage annual mean enhanced mole fractions of CH Br, from high to low were 9.9 ±\n3\n1.4 ppt for LAN, 7.4 ± 3.0 ppt for XFG, 6.0 ± 0.4 ppt for JSA, 4.9 ± 0.5 ppt for JGJ,\n4.2 ± 0.2 ppt for HYN, 3.0 ± 0.8 ppt for SDZ (flask), 2.9 ± 0.4 ppt for SDZ (in situ),\n2.2 ± 0.2 ppt for AKD, 1.8 ± 0.9 ppt for LFS, 1.5 ± 1.0 ppt for XGL, and 0.6 ± 0.8 ppt\nfor WLG (Figure 1 and S2).”\nRevised text:\nLines 100-106 in the revised manuscript: “These pollution events showed spatial\nheterogeneity among the ten Chinese sites, with the highest average annual mean\nenhanced mole fraction of 9.9 ± 1.4 ppt observed at the LAN site and the lowest of 0.6\n± 0.8 ppt observed at the Mount Waliguan (WLG) site (Supplementary Table 3 and\nSupplementary Fig. 2). The higher enhancements in eastern China and lower\nenhancements in other regions of China indicate potentially stronger CH Br\n3\nemissions in eastern China (see discussion in the next section).”\nWe have moved all the detailed baseline and enhancements information for each site\nto Supplementary Table 3.\nSupplementary Table 3. Mole fractions of CH Br observed at the ten Chinese\n3\nsites and four AGAGE background sites during 2011−2020. Unit: ppt. S. D. (1\nstandard deviation) represents the uncertainty for a normal distribution. ‘-‘ indicates\nno data.\nSite Baseline All observations Enhancement\nLAN (flask) 8.3 ± 0.9 18.1 ± 1.0 9.9 ± 1.4\nXFG (flask) 8.2 ± 0.7 15.6 ± 2.4 7.4 ± 3.0\nJSA (flask) 7.9 ± 0.4 13.9 ± 0.03 6.0 ± 0.4\nHYN (flask) 7.6 ± 0.02 11.8 ± 0.2 4.2 ± 0.2\nJGJ (flask) 6.8 ± 0.2 11.7 ± 0.2 4.9 ± 0.5\nSDZ (flask) 7.3 ± 0.7 10.3 ± 1.2 2.9 ± 0.8\nSDZ (in situ) 6.4 ± 0.3 9.3 ± 0.9 2.9 ± 0.4\nXGL (flask) 7.5 ± 0.3 9.0 ± 1.0 1.5 ± 1.0\nLFS (flask) 7.0 ± 0.4 8.8 ± 0.8 1.8 ± 0.9\nAKD (flask) 6.6 ± 0.1 8.8 ± 0.4 2.2 ± 0.3\nWLG (flask) 7.1 ± 0.3 7.7 ± 0.7 0.6 ± 0.8\nMHD (in situ) 7.6 ± 0.5 - -\nTHD (in situ) 7.0± 0.3 - -\nGSN (in situ) 7.8 ± 0.4 - -\nRPB (in situ) 7.1 ± 0.2 - -\n4. line 60. This is the start of a very long and meandering paragraph that does not\nhave a clear focus. Some of it reads like a proposal rather than a paper. I suggest that\nthis be broken into two paragraphs - one about the history of China's methyl bromide\nuse and one about prior studies and their limitations.\nResponse:\nWe appreciate this constructive suggestion. We have divided this paragraph into two\nparagraphs and edited the text to be more concise. The first paragraph focuses on the\nhistory of China's methyl bromide use, and the second paragraph introduces the prior\nstudies about emission estimates and their limitations. We have removed the proposal-\nlike sentence “It is important to conduct long-term emission estimates for CH Br to\n3\nmonitor the implementation of the Montreal Protocol as well as more\ncomprehensively understand the regional CH Br budget”.\nLines 61-75 in the revised manuscript: “China is an Article 5 country under the\nMontreal Protocol3. China’s non-QPS and QPS CH Br consumption peaked at 3.5 Gg\n3\nyr-1 in 2000 and 2.1 Gg yr-1 in 2005, respectively (Supplementary Table 1, Data in\ntables | Ozone Secretariat (unep.org)). Although non-QPS CH Br consumption was\n3\nscheduled to be phased out by 20156,7, China obtained critical use exemptions (CUEs)\nof approximately 0.1 Gg yr-1 during 2015−2018 for ginger cultivation (Supplementary\nTable 1, Data in tables | Ozone Secretariat (unep.org)), thus delaying the phase-out of\nnon-QPS consumption to 2019.\nHowever, China’s actual national CH Br emissions over the last decade remain\n3\nunclear. Insufficient spatial coverage of observation sites8-10 and the shortcomings of\nthe interspecies correlation method (ISC)8-11 have resulted in highly uncertain\nemission estimates and a lack of knowledge about the spatial distribution of CH Br\n3\nemissions in China. And there are few multiyear atmospheric observation-inferred\nestimates of China’s national CH Br emissions. An updated and comprehensive\n3\nbottom-up inventory is also necessary for comparison with the top-down estimates in\nChina, as previous bottom-up estimates have omitted several emission sectors8,12.”\n5. line 70. \"Limited by the insufficient spatial coverage of observation stations and the\nshortcomings of the interspecies correlation method (ISC) used in previous studies,\nprevious emission estimates may be biased and the hotspots of CH Br emissions in\nuncertain. I also don't know what it means for a hotspot to be \"unclear\". This is not\nwell written.\nResponse:\nWe agree that “biased” does not accurately describe the limitations of previous\nestimates, so we have revised it to “uncertain”, as suggested. We meant to indicate\nthat previous studies using the ISC method were unable to reveal the spatial\ndistribution of CH Br emissions across China, and therefore the emission hotspot in\nRevised text:\nLines 69-72 in the revised manuscript: “Insufficient spatial coverage of observation\nsites8-10 and the shortcomings of the interspecies correlation method (ISC)8-11 have\nresulted in highly uncertain emission estimates and a lack of knowledge about the\nspatial distribution of CH Br emissions in China.”\n3\n6. line 91. \"The delay years of the Antarctic ozone recovery are expected to be larger\nif considering the unidentified sources in other countries.\" That requires proving that\nthose unidentified sources are anthropogenic.\nResponse:\nWe appreciate this constructive comment. Considering we have removed the metric of\n“time to recovery” as mentioned above, we have also removed this sentence.\n7. \"This study advances not only for the scientific understanding of the CH Br budget\n3\nbut also for the assessment of implementing the Montreal Protocol.\" I don't know\nwhat this sentence means or why it has a \"but\" in it. Perhaps \"for\" should be deleted\nand \"but\" replaced with \"and\"?\nResponse:\nThank you for pointing out the language issue in this sentence. We meant to use “not\nonly……but also……” to show that this study advances the two aspects (scientific\nunderstanding of the CH Br budget and assessment of implementing the Montreal\nrevised as follows.\nRevised text:\nLines 79-81 in the revised manuscript: “This study reveals unexplained high and\npersistent CH Br emission in China. A negative impact on the ozone recovery is\n3\nanticipated if these unexplained emissions are anthropogenic and not eliminated.”\n8. line 125. This is a run-on sentence whose meaning is unclear. \"accurate\" seems like\na misuse of the word. Top-down inversion is another estimate - maybe it is more\naccurate than bottom up but just to declare it as accurate is misleading.\nResponse:\nWe agree that we should avoid saying that the top-down inversion is 'accurate'. We\nhave deleted this word accordingly.\nEND OF REVIEW\nResponses to Reviewer #3\nReview of the manuscript “Unexplained high and persistent methyl bromide\nemissions in China after 2015 phase-out: A concern for the ozone layer and the\nMontreal Protocol” by Hu et al., 2024.\nReviewer #3 (Remarks to the Author):\nThe manuscript describes the discrepancy between CH Br emission estimates from\ninventory developed for this study, which are clearly biased-high compared to the\nexpected phase-out of the Montreal Protocol. Despite the paper focuses on a very\nimportant issue, I regret to mention that, at least in its current stage, the work is\ndifficult to follow and lacks of the required quality, evaluation and discussion to be\naccepted for publication in Nature Communications. Indeed, at least a couple of the\nmain messages of the work (i.e., the new observational dataset from 2011 to 2020 and\nthe large regional enhancement in CH Br abundance over China compared with the\n3\nglobal background at equivalent latitudes) are left out from the abstract and only\nbriefly mentioned in the discussion. I provide below a full set of major, minor and\ntechnical comments oriented to highlight the most important and novel results\npresented in the manuscript and improve the overall paper organization. If the authors\nfeel that all comments can be revised and addressed and are willing to introduce\nsignificant changes on the main text structure, I’m willing to perform a second\nevaluation.\nPlease see attached file with the complete evaluation.\nResponse:\nThank you very much for your professional review and comments, and our adoption\nof suggested revisions have greatly improved the organization and readability of our\nmanuscript. We have rewritten most paragraphs of the manuscript, reorganized\nvarious sections, and highlighted the key messages in the abstract. Below we provide\npoint-to-point responses to each of the suggestions and comments.\nMajor Comments:\nS1: L96-L135: The first section of the results presents data from observations\nperformed at 10 sites over China between 2011-2020, and compares the new dataset\nw.r.t. CH Br values from the AGAGE network to estimate the enhancement in CH Br\n3 3\nabundance over the background. None of these issues, which are the main results of\nthis study, are mentioned in the abstract. The complete text is very hard to follow,\nwith explicit and very detailed information of the exact values and uncertainties over\neach observational site that makes a complex reading (which are better suited for\nFigures and Tables) instead presenting an expert guided description of the main\npatterns and variations. In addition, one of the most important results (the estimation\nof the regional enhancement of China over the global background) is only show in\nFig. S2 in the Supplement, and only briefly discussed here.\nResponse:\nWe appreciate these detailed comments. We have revised the abstract to show the\nenhanced concentrations found in China that demonstrate regional sources. We have\nmoved many of the specific details to the Supplementary Table 3 and Supplementary\nFig. 2, while highlighting the key findings. We have re-organized the results section to\nmethodically present the findings: 1) Baseline concentrations in China that are\ncomparable to AGAGE; 2) Enhancements of concentrations over China that show\nregional sources with large spatial heterogeneity; 3) Results of the inverse modeling\nof observations to derive national scale emissions; and 4) Results of the inverse\nmodeling to identify potentially stronger emissions in eastern China compared with\nother regions of China.\nRevised text:\nLines 28-29 in the revised manuscript (abstract): “Measured CH Br mole fractions\n3\nare enhanced well above the background mole fractions, especially at sites in eastern\nChina.”\nLines 89-93 in the revised manuscript: “The average annual mean baselines\nobserved during 2011–2020 ranged from 7.0 ppt at Longfengshan (LFS) to 8.2 ppt at\nLin’an (LAN) (Supplementary Table 3 and Supplementary Fig. 2). These\nconcentrations are comparable to the 7.0 to 7.6 ppt CH Br background mole fraction\n3\nrange observed at four Northern Hemisphere background sites within the Advanced\nGlobal Atmospheric Gases Experiment (AGAGE) network”\nLines 100-106 in the revised manuscript: “These pollution events showed spatial\nheterogeneity among the ten Chinese sites, with the highest average annual mean\nenhanced mole fraction of 9.9 ± 1.4 ppt observed at the LAN site and the lowest of 0.6\n± 0.8 ppt observed at the Mount Waliguan (WLG) site (Supplementary Table 3 and\nSupplementary Fig. 2). The higher enhancements in eastern China and lower\nenhancements in other regions of China indicate potentially stronger CH Br\n3\nemissions in eastern China (see discussion in the next section).”\nAs suggested, we have moved all the detailed baseline and enhancements information\nfor each site to Supplementary Table 3.\nSupplementary Table 3. Mole fractions of CH Br observed at the ten Chinese\n3\nsites and four AGAGE background sites during 2011−2020. Unit: ppt. S. D. (1\nstandard deviation) represents the uncertainty for a normal distribution. ‘-‘ indicates\nno data.\nSite Baseline All observations Enhancement\nLAN (flask) 8.3 ± 0.9 18.1 ± 1.0 9.9 ± 1.4\nXFG (flask) 8.2 ± 0.7 15.6 ± 2.4 7.4 ± 3.0\nJSA (flask) 7.9 ± 0.4 13.9 ± 0.03 6.0 ± 0.4\nHYN (flask) 7.6 ± 0.02 11.8 ± 0.2 4.2 ± 0.2\nJGJ (flask) 6.8 ± 0.2 11.7 ± 0.2 4.9 ± 0.5\nSDZ (flask) 7.3 ± 0.7 10.3 ± 1.2 2.9 ± 0.8\nSDZ (in situ) 6.4 ± 0.3 9.3 ± 0.9 2.9 ± 0.4\nXGL (flask) 7.5 ± 0.3 9.0 ± 1.0 1.5 ± 1.0\nLFS (flask) 7.0 ± 0.4 8.8 ± 0.8 1.8 ± 0.9\nAKD (flask) 6.6 ± 0.1 8.8 ± 0.4 2.2 ± 0.3\nWLG (flask) 7.1 ± 0.3 7.7 ± 0.7 0.6 ± 0.8\nMHD (in situ) 7.6 ± 0.5 - -\nTHD (in situ) 7.0± 0.3 - -\nGSN (in situ) 7.8 ± 0.4 - -\nRPB (in situ) 7.1 ± 0.2 - -\nS2: L136-L156: The authors should clearly state that the updated top-down estimate\nwas possible thanks to the extended observational dataset performed at 10 sites in\nChina. Most notably, the inverse method applied shows East China to be a hotspot in\nCH Br emissions compared with the remaining fraction of the country (Fig. 2b)\n3\nalthough if one compares total emissions from China and East China in Fig. 4, East\nChina represents less than half of the total emissions (which is not discussed in the\ntext). In addition, in the same paragraphs the author’s claim that “this is the first study\nable to quantify CH Br emissions in China from 2011 to 2020” but “our emission\n3\nestimates are consistent with the most previous studies”, which requires further\nclarification.\nResponse:\nThank you for your detailed comments. In our revised manuscript, we have clearly\nstated that the updated top-down estimate was only possible due to the large\nobservational network (10 sites) in China.\nWe also clarify the definitions of “eastern China” and “emission hotspot” in the main\ntext. To ensure comparability with Choi et al.1, eastern China region defined in\nSupplementary Fig. 4 is the same as Choi et al.1 and contributed 42% to China’s total\nemissions. However, due to our extended observation network (to Choi et al.1 is based\nonly on one external site in Gosan, South Korea), an expanded eastern China region\nwas also defined in the main text that includes two additional provinces (Fujian and\nGuangdong) compare to Choi et al.1. The emissions from the expanded eastern China\nregion contributed about 52% of China’s total emission. In our revised version, we\nillustrate \"eastern China\" to compare with Choi et al.1, and the \"expanded eastern China\"\nregion to demonstrate the importance of this larger region to overall national\nemissions (Supplementary Fig. 4). The emission hotspot (kg km-2 yr-1) is defined as\nhigh emission rates per unit area in the main text. Note that the area of eastern China\ndefined in this study only account for 12.5% of China’s total area, while eastern China\ndefined in this study account for 52% of China’s total emissions. Thus, we conclude\nthat eastern China is an emission hotspot because its emission rate per unit area is\nhigher than other regions.\nPrevious studies only provided emission estimates either from a portion of China (i.e.,\neastern China by Choi et al.1) or in certain individual years (e.g., Kim et al.2 and Li et\nal.3), leaving the magnitude and long-term trend of China’s national emissions\nunknown. We extended the emission estimates to the whole of China and over a ten-\nyear period, making this the first quantification of total China’s CH Br emissions over\n3\nmultiple years. We find that our emission estimates for the same region and year\nlargely agree with previous studies, although there are some year to year differences.\nWe note the differences and consistencies between this study and previous studies in\nthe revised manuscript.\nReferences used for this response:\n1. Choi, H., Park, M.-K., Fraser, P. J., Park, H., Geum, S., Mühle, J., Kim, J., Porter,\nI., Salameh, P. K., Harth, C. M., Dunse, B. L., Krummel, P. B., Weiss, R. F.,\nO'Doherty, S., Young, D. & Park, S. Top-down and bottom-up estimates of\nanthropogenic methyl bromide emissions from eastern China. Atmos Chem Phys 22,\n5157-5173, doi:10.5194/acp-22-5157-2022 (2022).\n2. Kim, J., Li, S., Kim, K.-R., Stohl, A., Mühle, J., Kim, S.-K., Park, M.-K., Kang,\nD.-J., Lee, G., Harth, C. M., Salameh, P. K. & Weiss, R. F. Regional atmospheric\nemissions determined from measurements at Jeju Island, Korea: Halogenated\ncompounds from China. Geophys Res Lett 37, n/a-n/a, doi:10.1029/2010gl043263\n(2010).\n3. Li, S., Kim, J., Kim, K. R., Muhle, J., Kim, S. K., Park, M. K., Stohl, A., Kang,\nD. J., Arnold, T., Harth, C. M., Salameh, P. K. & Weiss, R. F. Emissions of\nhalogenated compounds in East Asia determined from measurements at Jeju Island,\nKorea. Environ Sci Technol 45, 5668-5675, doi:10.1021/es104124k (2011).\nRevised text:\nLines 101-103 in the revised Supporting Information: ““Eastern China” defined\nhere is the same as in Choi et al., while “Expanded eastern China” includes two additional\nprovinces of Fujian and Guangdong compared to “Eastern China”.”\nLines 122-126 in the revised manuscript: “The CH Br flux (emission rate per unit\n3\narea) in eastern China was eight times that of the rest of China (4.0 and 0.53 kg km-2\nyr-1, respectively) from 2011 to 2020 (Fig. 2b). Even though the area of eastern China\naccounts for only 12.5% of China’s total area, the emissions from eastern China\ncontributed about 52% (4.8 Gg yr-1) of China’s total emissions.”\nLines 114-119 in the revised manuscript: “These results are generally consistent\nwith national emissions estimated by the interspecies ratio method (Supplementary\nFig. 4), although prior results were single year estimates from the beginning of this\nstudy or earlier: ~5.5 ± 2.0 Gg yr-1 in 20089,10. Based on the observations of the\nrecently established long-term observation network in China, this study addresses the\nmagnitude and 2011−2020 trend of national CH Br emissions in China for the first\n3\ntime.”\nRevised figure:\nSupplementary Figure 1. Comparisons with previous top-down estimates. The blue line\nrepresents emission estimates for China in this study; the yellow line represents emission\nestimates for eastern China in this study; the other estimates came from previous studies10-12.\n‘ISC’ represents interspecies ratio method. For comparison, “Eastern China” defined here is\nthe same as in Choi et al., while “Expanded eastern China” includes two additional\nprovinces of Fujian and Guangdong compared to “Eastern China”.”\nS3: L157-L182: The bottom-up inventory results are presented in this section. The\ndiscrepancy between the top-down and bottom-up total emission values are discussed,\nfocusing mostly on fumigation. First, the usage of fumigation and/or QPS/non-QPS\nshould be unified or at least be clearly described for a wider community. Second, no\ninformation is provided about how important is the fumigation sector in east China\ncompared to the rest of the country. Third, the discrepancy between the reported\nfumigation usages from China to UNEP w.r.t. the assessed values are only briefly\nmentioned, and should be highlighted.\nResponse:\nWe appreciate these important comments regarding the fumigation contributions to\nCH Br emissions. We addressed the three subpoints below.\n3\n1_ “First, the usage of fumigation and/or QPS/non-QPS should be unified or at least\nbe clearly described for a wider community”.\nResponse:\nIn the Introduction, we have added details about the usage of CH Br for QPS and non-\nRevised text:\nLines 50-52 in the revised manuscript: “Being a highly effective broad-spectrum\nfumigant, CH Br was widely used as a pest-control treatment in fumigation\n3\napplications including quarantine and pre-shipment (QPS), and non-QPS uses\n(mainly soil, post-harvest, and structure fumigation)5.”\n2. :Second, no information is provided about how important is the fumigation sector\nin east China compared to the rest of the country.”\nResponse:\nUnfortunately, province-level consumption data of fumigation are not available; thus,\nwe cannot draw a quantitative conclusion on how important is the fumigation sector\nin eastern China compared to the rest of China. However, we do know that the QPS\n(quarantine and pre-shipment) emissions dominate (90%) the reported fumigation\nemissions in China with non-QPS emissions only accounting for 10%. (Fig. 3). QPS\nuse is primarily associated with the import/export shipping industry, and it may\ntherefore be positively correlated with the port cargo throughput. Therefore, we\ncollected port cargo throughput data for each province of China in 2020 to infer the\nrelative importance of fumigation emissions in each province. As shown in\nSupplementary Table 6, the port cargo throughput was dominated by eastern China\n(including provinces of Anhui, Beijing, Hebei, Jiangsu, Liaoning, Shandong,\nShanghai, Tianjin, Zhejiang, Fujian, and Guangdong). Thus, it is likely that\nfumigation emissions were higher in eastern China than the rest of China.\nRevised text:\nLines 145-149 in the revised manuscript: “QPS emissions that are primarily\nassociated with the import/export shipping industry contributed over 90% of the total\nfumigation emissions (Fig. 3). China’s port cargo throughput is concentrated in\neastern China provinces (Supplementary Table 6); thus, QPS emissions associated\nwith shipping may account for some of the emissions hotspot of eastern China.”\nSupplementary Table 6. Port cargo throughput in each province of China in 2020. The\nrank is ordered from high to low by the sum of coastal and inland river port cargo throughput.\nProvince Coastal Inland river Sum\n(104 Gg) (104 Gg) (104 Gg)\nJiangsu (E. China） 1455 0 1455\nGuangdong (E. China） 32 264 297\nZhejiang (E. China） 176 26 202\nShandong (E. China） 141 44 185\nHebei (E. China） 169 6 175\nLiaoning (E. China） 120 0 120\nShanghai (E. China） 82 0 82\nFujian (E. China） 65 6 71\nAnhui (E. China） 62 0 62\nGuangxi 0 54 54\nHubei 30 17 47\nHianan 0 38 38\nJiangxi 20 0 20\nChongqing 0 19 19\nHunan 0 16 16\nSichuan 0 14 14\nYunan 0 1 1\nHenan 0 0 0\nHeilongjiang 0 0 0\nGuizhou 0 0 0\nData source: China Port Association (http://www.port.org.cn/list/1006_1077_11.htm)\n3_ “Third, the discrepancy between the reported fumigation usages from China to\nUNEP w.r.t. the assessed values are only briefly mentioned, and should be\nhighlighted.”\nResponse:\nThe emissions reported to UNEP versus the emissions estimated in this study\n(2011−2020 average) were largely in agreement for non-QPS (phased out use),\nbut they showed a discrepancy for QPS (exempted usage). Reported versus assessed non-\nQPS estimates were 0.06 and 0.07 Gg yr-1, respectively, whereas QPS estimates were\n0.91 and 1.96 Gg yr-1, respectively. This addition of 1.1 Gg yr-1 contributed to the\ndifference between this bottom-up inventory and previous inventories. We have added\ndiscussions on the discrepancy of fumigation estimates between reported to UNEP\nand this study in our revised manuscript.\nRevised text:\nLines 141-145 in the revised manuscript: “CH Br emissions from fumigation (QPS\n3\n+ non-QPS) sectors were about 2.0 Gg yr-1 (54% of the total bottom-up emissions) on\naverage during 2011−2020. Non-QPS sector emissions in this study (0.07 Gg yr-1)\nwere consistent with amounts reported to UNEP (0.06 Gg yr-1), while the QPS\nemissions in this study (1.96 Gg yr-1) were higher than reported to UNEP (0.91 Gg yr-\n1).”\nS4: 183-218: Despite the connection with illegal/unreported sales is linked with the\nunexplained emissions, a comprehensive assessment of which sectors are expected to\nbe missing and/or misrepresented is missing in the text and/or mentioned\nsuperficially. Experienced scientific orientation towards which sectors should be\nfurther studied to reconcile the top-down and bottom-up approaches is expected in\nthese types of papers to inspire future research.\nResponse:\nWe agree that providing insights on which sectors are missing or misrepresented\ncould direct further research. According to your suggestions, we have further\ndiscussed other potential causes of missing sources to provide some guidance for\nfuture studies. First, we compiled the discovery timeline for each emission source,\nand we find that new emission sources of CH Br are still being discovered in recent\n3\nyears, such as baking discovered in 20161 and Cu2+-based pesticides discovered in\n20222, reflecting our incomplete understanding of CH Br sources. Thus, the missing\n3\nsource may come from unidentified sources. Second, the emission fluxes of CH Br\n3\nfrom terrestrial sources (such as salt marshes, rice paddies, and rapeseed) vary with\ntemperature3, Br content of the soil4, and plant types5. However, measurements of\nCH Br emission fluxes from these sources are sparse6, limiting the accuracy of\n3\nestimates of emissions from these sources. In summary, the unidentified new sources\nand emissions from known natural sources if underestimated may contribute to\nChina’s large missing source of CH Br.\n1. Thornton, B. F., Horst, A., Carrizo, D. & Holmstrand, H. Methyl chloride and methyl\nbromide emissions from baking: an unrecognized anthropogenic source. Sci Total Environ\n551-552, 327-333, doi:10.1016/j.scitotenv.2016.01.213 (2016).\n2. Jiao, Y., Zhang, W., Kim, J. Y. R., Deventer, M. J., Vollering, J. & Rhew, R. C.\nApplication of copper(II)-based chemicals induces CH(3)Br and CH(3)Cl emissions from soil\nand seawater. Nat Commun 13, 47, doi:10.1038/s41467-021-27779-3 (2022).\n3. Wishkerman, A., Gebhardt, S., McRoberts, C. W., Hamilton, J. T., Williams, J. &\nKeppler, F. Abiotic methyl bromide formation from vegetation, and its strong dependence on\ntemperature. Environ Sci Technol 42, 6837-6842, doi:10.1021/es800411j (2008).\n4. Redeker, K. R., Wang, N., Low, J. C., McMillan, A., Tyler, S. C. & Cicerone, R. J.\nEmissions of methyl halides and methane from rice paddies. Science 290, 966-969,\ndoi:10.1126/science.290.5493.966 (2000).\n5. Mead, M. I., White, I. R., Nickless, G., Wang, K.-Y. & Shallcross, D. E. An estimation of\nthe global emission of methyl bromide from rapeseed (Brassica napus) from 1961 to 2003.\nAtmos Environ 42, 337-345, doi:10.1016/j.atmosenv.2007.09.020 (2008).\n6. Drewer, J., Heal, K. V., Smith, K. A. & Heal, M. R. Methyl bromide emissions to the\natmosphere from temperate woodland ecosystems. Global Change Biology 14, 2539-2547,\ndoi:10.1111/j.1365-2486.2008.01676.x (2008).\nRevised text:\nLines 184-194 in the revised manuscript: “In addition to the reported illegal\nproduction and sales of CH Br, we suggest two possible causes for unexplained\n3 3\ndiscovered in recent years, such as baking discovered in 201631 and copper-based\npesticides discovered in 202232, reflecting our incomplete understanding of CH Br\n3\nsources. Second, the emission fluxes of CH Br from terrestrial sources (such as salt\n3\nmarshes, rice paddies, and rapeseed) vary with temperature33, Br content of the soil16,\nand plant types34. However, measurements of CH Br emission fluxes from these\n3\nsources are sparse21, limiting the accuracy of estimates for emissions from these\nsources. In summary, unidentified new sources and emissions from known natural\nsources (if underestimated) may also contribute to China’s large missing source of\nCH Br.”\nare un-proportionately highlighted in the manuscript. Most importantly, I disagree with the\nMethodology used to estimate the 0.7 years delay in the recovery of Antarctic ozone due to\nthe unexplained CH Br emissions from China found in this study. The referenced methodology\n3\nused 3D global models to estimate the role of stratospheric Cl-enhancements from a global\nCH2CL2 emission inventory and assuming a trend in emissions until year 2050; while here the\nestimation is based on an proportional ozone efficiency of bromine (compared to chlorine)\nand a very simplified expression to estimate the global enhancement in CH Br global abundance\n3\nbased on surface-only CH Br-observationally derived emissions from China, which\n3\nare scaled to whole troposphere and stratosphere, and assumed to remain constant until 2050.\nI agree that the stratospheric ozone implications of the well stablished enhanced emissions\nfrom China should be mentioned, and I do not expect the authors to perform global\nsimulations to quantify these impacts, but given the weakness of the approach used for their\nestimation (L455-L487 in the SI), I suggest not overstating quantitatively the global impact\nover Antarctic ozone. In addition, depending on the section being read (abstract, introduction\nor Section 5) it is not clear if the ozone impacts are given for the global ozone layer or to\nAntarctic ozone instead, which significantly differ.\nResponse:\nThank you for this constructive comment. We agree that the estimation method used\nhere is perhaps too simple and not robust enough. In the revised Abstract and Section\n5, we have removed the quantitative conclusion of 0.7 years, and only present the\nmetric of DU years. The ozone impacts quantified with the metric of DU years refer\nto the global ozone instead of Antarctic ozone.\nRevised text:\nLines 34-35 in the revised manuscript: “If the unaccounted sources of CH Br in\ndepletion impact of approximately 20 DU years.”\nLines 211-213 in the revised manuscript: “If the unaccounted emissions of CH Br\n3\nin China originate entirely from anthropogenic sources and continue to 2050, they\nwill amount to an integrated ozone depletion of approximately 20 DU years (see\ncalculations in Methods).”\nMinor Comments:\nL30: How large is the 5.5 Gg yr-1 discrepancy in percentage terms? Providing\npercentage enhancement/discrepancy values will certainly help to highlight the results\nand implications.\nResponse:\nThank you for your suggestion. The discrepancy of 5.5 Gg yr-1 is equal to 60% of the\ntotal emissions in China. We have added the percentage value (60%) in this sentence\naccordingly.\nRevised text:\nLines 29-31 in the revised manuscript: “Top-down emission estimates exceed\nbottom-up estimates by 5.5 ± 1.4 gigagrams per year, or 60% of the top-down\nestimate”\nL32: Emissions hotspots were identified, but there is not mention on how did you do\nso in the abstract. Both the observational dataset and the method used should be\nmentioned.\nResponse:\nWe apologize for this oversight. Emission hotspots were identified by our top-down\nmethod (inversion). We have added the descriptions about the observational dataset\nand the inversion method to our abstract.\nRevised text:\nLines 25-28 in the revised manuscript: “Here we estimate the national emissions of\nCH Br in China during 2011−2020 using atmospheric observations at 10 sites across\nupdated inventory of identified emission sources (bottom-up).”\nLines 32-33 in the revised manuscript: “Some emission hotspots identified from our\ntop-down inversions are consistent with regions where illegal production and sales of\nCH Br have been reported.”\nis more efficient than chlorine in destroying ozone from the very beginning.\nResponse:\nThank you for this suggestion. We have added explanation that bromine is around 60\ntimes more efficient than chlorine in depleting ozone in the revised Introduction\nsection accordingly.\nRevised text:\nLines 45-47 in the revised manuscript: “CH Br is the single largest contributor of\n3\nstratospheric bromine load, and bromine is around 60 times more efficient than\nchlorine in depleting ozone under current stratospheric conditions5.”\nL69: Sentence would benefit to mention that due to its comparatively short lifetime,\nnational/local CH Br budgets are expected to differ for different regions.\nThank you for this comment. This sentence has been removed according to other\nreviewer’s suggestions.\nL87-L88: The emission hotspots are identified using the bottom-up or in the top-down\napproach? Or using both?\nResponse:\nThank you for this question. The emission hotspots are identified by our top-down\ninversion approach. We have clearly clarified this in our revised manuscript.\nRevised text:\nLines 32-33 in the revised manuscript: “Some emission hotspots identified from our\ntop-down inversions are consistent with regions where illegal production and sales of\nCH Br have been reported.”\ncomparative description of the results without expressing so many values in the text,\nand focusing on the most important ones for the message that is given.\nResponse:\nThank you for this helpful suggestion. We have rewritten this paragraph, removed the\nlong list of numbers, and focused on the consistence of baseline observations between\nour sites and AGAGE background sites.\nRevised text:\nLines 89-93 in the revised manuscript: “The average annual mean baselines\nobserved during 2011–2020 ranged from 7.0 ppt at Longfengshan (LFS) to 8.2 ppt at\nLin’an (LAN) (Supplementary Table 3 and Supplementary Fig. 2). These\nconcentrations are comparable to the 7.0 to 7.6 ppt CH Br background mole fraction\n3\nrange observed at four Northern Hemisphere background sites within the Advanced\nGlobal Atmospheric Gases Experiment (AGAGE) network”\nL112 and L126: At least a brief summary of the methodology used to estimate the\nbaseline CH Br value and the CH Br enhancement over China should be given in the\n3 3\nmain text, and then extended in Methods. This is not completely clear even after\nreading methods.\nResponse:\nThank you for this comment. We have clarified the baseline calculation method in the\nrevised Methods section. And we have added a brief summary of the method here\naccording to your suggestion.\nRevised text:\nLines 302-306 in the revised manuscript: “For the flask sampling sites, background\nmole fractions were estimated as the lower value of (1) the lowest measurement in the\n90 d moving window and (2) the latitude-direction linearly interpolated value between\nthe monthly mean background value at the Ragged Point (RPB, 13.17° N, 59.43° W)\nand Mace Head (MHD, 53.33° N, 9.9° W)40,41.”\nLines 86-88 in the revised manuscript: “We estimated the baseline (i.e.,\nbackground) mole fractions at our measurement sites by selecting the lowest observed\nconcentrations in a moving time window (i.e., 90 days; see Methods).”\nL129-L133: Again, very hard to follow with so many acronyms and values. The\nwriting style is more focused for a specific journal than for a general paper.\nResponse:\nWe appreciate this helpful suggestion. We have removed the long and exact numbers\nand rewritten this paragraph to focus on the high enhancements and their spatial\nheterogeneity observed at our ten Chinese sites.\nRevised text:\nLines 100-106 in the revised manuscript: “These pollution events showed spatial\nheterogeneity among the ten Chinese sites, with the highest average annual mean\nenhanced mole fraction of 9.9 ± 1.4 ppt observed at the LAN site and the lowest of 0.6\n± 0.8 ppt observed at the Mount Waliguan (WLG) site (Supplementary Table 3 and\nSupplementary Fig. 2). The higher enhancements in eastern China and lower\nenhancements in other regions of China indicate potentially stronger CH Br\n3\nemissions in eastern China (see discussion in the next section).”\nL134: In line L108 you highlight the importance of the latitudinal CH Br variation\n3\n(which is correct), but here you highlight that the variability in the CH Br\n3\nenhancement is greater between east and west stations. Please explain the why? And\nalso explain if a latitudinal variation could be “hidden” in the east-west variability\nshown.\nResponse:\nThank you for your questions. In line L108, the baseline observed at similar latitudes\nshould be comparable given that zonal winds mix air on the scale of a couple weeks,\nmuch less than their atmospheric lifetimes. Therefore, we selected four AGAGE\nbackground sites whose latitudes are close to our ten Chinese sites, ensuring the\ncomparability of the baselines. The consistency between the Chinese sites and\ncomparative AGAGE sites for baseline concentrations, within expectation,\ndemonstrated the measurement capability of our network. In Line 134 (here),\nenhanced concentrations, which are typically influenced by emissions within a\nseveral-day transport of an air mass, reflect the regional emissions surrounding the\nmeasurement site. Unlike the well-mixed baseline, regional enhancements do not have\na latitudinal variation, and the east-west variation of enhancements have no\nrelationship with latitudinal variation but with east-west variation of emissions. In the\nrevised manuscript, we followed the logic: 1) Baselines observed at our ten Chinese\nsites and comparisons with those observed at AGAGE sites, 2) Regional\nenhancements and their spatial pattern at our ten Chinese sites to indicate the spatial\npattern of emissions in China.\nRevised text:\nLines 89-93 in the revised manuscript: “The average annual mean baselines\nobserved during 2011–2020 ranged from 7.0 ppt at Longfengshan (LFS) to 8.2 ppt at\nLin’an (LAN) (Supplementary Table 3 and Supplementary Fig. 2). These\nconcentrations are comparable to the 7.0 to 7.6 ppt CH Br background mole fraction\n3\nrange observed at four Northern Hemisphere background sites within the Advanced\nGlobal Atmospheric Gases Experiment (AGAGE) network”\nLines 100-106 in the revised manuscript: “These pollution events showed spatial\nheterogeneity among the ten Chinese sites, with the highest average annual mean\nenhanced mole fraction of 9.9 ± 1.4 ppt observed at the LAN site and the lowest of 0.6\n± 0.8 ppt observed at the Mount Waliguan (WLG) site (Supplementary Table 3 and\nSupplementary Fig. 2). The higher enhancements in eastern China and lower\nenhancements in other regions of China indicate potentially stronger CH Br\n3\nemissions in eastern China (see discussion in the next section).”\nL153: Emissions from east China account for 40% of total China. Can you expressed\nthe fraction of the total area and population that those provinces represent?\nResponse:\nWe have added the fraction of area (7.3%) and population (32%) represented by these\nprovinces.\nRevised text:\nLines 130-131 in the revised manuscript: “For comparison, these five provinces\nrepresent 7.3% and 32% of China’s total area and populations, respectively.”\nL168-L171: Here you are comparing the emissions from 7 sectors from your bottom-\nup inventory w.r.t. the reported emissions from QPS+nonQPS to the UNEP, but no\nmention is given to the QPS+nonQPS estimation from your study, which is only\nmentioned in the next paragraph (L176). I suggest reordering and providing\npercentages in addition to absolute values.\nResponse:\nThank you for your suggestions. We have added discussion on the QPS and non-QPS\nemission estimates according to your previous suggestion. We have also provided\npercentages accordingly.\nRevised text:\nLines 141-145 in the revised manuscript: “CH Br emissions from fumigation (QPS\n3\n+ non-QPS) sectors were about 2.0 Gg yr-1 (54% of the total bottom-up emissions) on\naverage during 2011−2020. Non-QPS sector emissions in this study (0.07 Gg yr-1)\nwere consistent with amounts reported to UNEP (0.06 Gg yr-1), while the QPS\nemissions in this study (1.96 Gg yr-1) were higher than reported to UNEP (0.91 Gg yr-\n1).”\nLines 153-155 in the revised manuscript: “CH Br emissions from these seven\n3\nsectors reached 1.0 ± 0.1 Gg yr-1 on average during 2011−2020, which accounted for\n26% of the total bottom-up emissions”\nL180:182: “We highlight the large gap between our top-down and bottom-up\nemissions estimates in the following section (approximately 60% of the top-down\nemissions estimates; see the discussion below).” This should be highlighted in the abstract. Note\nthat it is very repetitive to the 1st sentence in next section (L185-L189).\nResponse:\nThank you for this suggestion. We have added this conclusion to the revised abstract\naccordingly. In addition, we have removed the repetitive 1st sentence in next section\n(L185-L189) accordingly.\nRevised text:\nLines 29-31 in the revised manuscript: “Top-down emission estimates exceed\nbottom-up estimates by 5.5 ± 1.4 gigagrams per year, or 60% of the top-down\nestimate, suggesting unreported, underreported or unidentified emissions sources in\nChina.”\nL210-L212: The sentence points at total CH Br emissions or only those related to\nResponse:\nThank you for this question. The sentence points at total CH Br emissions and we\n3\nhave clarified it in the revised manuscript.\nRevised text:\nLines 179-181 in the revised manuscript: “Jiangsu and Shandong Provinces ranked\nas the top two in terms of the average annual total CH Br missions during 2011–2020\n3\n(Supplementary Table 4)”\nL212-L213: “The proportion of emissions from this source to the total provincial\nemissions is unclear;” and “requires further investigation”. Can you at least provide a\nrange of estimated or reported values?\nResponse:\nThank you for this comment. Unfortunately, the lack in quantitative data of this\nsource makes it hard for us to provide quantitative estimates for the range. Therefore,\nwe only highlight the potential contribution of this source to the total missing source.\nL216 … “the unidentified new sources and emissions from known natural sources” …\nThis sentence requires citation. One possibility is the recent SOLAS review from\nTinel et al., (2023). (Tinel, L., Abbatt, J., Saltzman, E., Engel, A., Fernandez, R.,\nLi, Q., Mahajan, A. S., Nicewonger, M., Novak, G., Saiz-Lopez, A., Schneider, S.,\nand Wang, S.: Impacts of ocean biogeochemistry on atmospheric chemistry, Elem.\nSci. Anthr., 11, 1–26, https://doi.org/10.1525/elementa.2023.00032, 2023.)\nResponse:\nThank you for this information. We have added more comprehensive discussions\nabout the possible missing source in this paragraph according to your previous\ncomments. In the revised manuscript, this sentence serves as a summary instead of a\nnew viewpoint proposed by us.\nRevised text:\nLines 184-194 in the revised manuscript: “In addition to the reported illegal\nproduction and sales of CH Br, we suggest two possible causes for unexplained\n3 3\ndiscovered in recent years, such as baking discovered in 201631 and copper-based\npesticides discovered in 202232, reflecting our incomplete understanding of CH Br\n3\nsources. Second, the emission fluxes of CH Br from terrestrial sources (such as salt\n3\nmarshes, rice paddies, and rapeseed) vary with temperature33, Br content of the soil16,\nand plant types34. However, measurements of CH Br emission fluxes from these\n3\nsources are sparse21, limiting the accuracy of estimates for emissions from these\nsources. In summary, unidentified new sources and emissions from known natural\nsources (if underestimated) may also contribute to China’s large missing source of\nCH Br.”\n3\nemissions should be explained somewhere in Methods.\nResponse:\nWe have added the calculation method of CFC-11-eq emissions in our revised\nmanuscript accordingly.\nRevised text:\nLines 197-199 in the revised manuscript: “For example, the ozone depletion\npotential-weighted emissions (CFC-11-equivalent emissions; mass emission\nmultiplied by the ozone-depleting potential) of CH Br……”\ncompound to deplete stratospheric ozone is ozone depletion potential (ODP), which is\ncalculated relative to a reference compound (CFC-11 with an OPD of 1). We\ncalculated the ODP-weighted emissions (CFC-11-equivalent emission) of CH Br by\n3\nmultiplying the mass emissions of CH Br by its ODP value.”\nChina.\nResponse:\nThank you for pointing out the unclear statement. The 5.0 ± 1.0 Gg yr-1 value\ncorrespond to eastern China. We have further clarified it in the revised manuscript.\nRevised text:\nLines 202-204 in the revised manuscript: “China’s national CH Br emissions\n3\nsurpassed eastern China’s CFC-11 emissions of 5.0 ± 1.0 Gg yr-1 in 2019, ……”\nMethods:\nL263: Only 5 (five) sites are described in ref (40). Please specify.\nResponse:\nThank you for your careful review. The same sampling and analysis methods are used\nat the ten sites, so we cite reference (40) that first introduced the five sites in detail.\nWe have revised the statement for clarity.\nRevised text:\nLines 239-240 in the revised manuscript: “The same sampling and analysis\nmethods are used at the ten sites, as described in detail in previous studies40,42”\nL295-L297: Please revise the whole sentence. What do you mean by “obtained via\n40k virtual particles released at each observation station in a three-hour interval”. Are\nemissions included at the same locations as the observational sites?\nResponse:\nThis sentence was meant to describe how simulated particles in the backward\ndispersion model FLEXPART were released from the location of each site. Emissions\nat the observational site location (gridded boxes) are included and were solved in our\ninversion. We have revised this sentence.\nRevised text:\nLines 269-273 in the revised manuscript: “To obtain the source-receptor\nrelationship matrix (SRRs, also called “emission sensitivity” or “footprint”, in units\nof m2 s g-1), in the FLEXPART model, 40k virtual particles were released from the\nlocation of each observation site in a three-hour interval, and the model was run\nbackwards for 20 days for each atmospheric observation40,41.”\nL300: Please explain how do you make consistent the 1.8 years (reaction with OH)\nand 3.4 years (soil uptake) lifetimes with the 0.8 years global lifetime given in L407.\nThis is of fundamental importance to ensure that the different approaches used are\ncomparable.\nResponse:\nThank you for these questions. We forgot to show the partial ocean lifetime of about\n3.1 years1. The total lifetime (including atmospheric OH reaction of 1.8 years, soil of\n1\n3.4 years, and ocean uptake of 3.1 years) is = 0.8 years, which is consistent\n1 1 1\n+ +\n1.8 3.4 3.1\nwith the value (0.8 years) mentioned in Introduction section. We have revised the\nlifetime used here to be consistent with the total lifetime of 0.8 years mentioned\nabove.\nReferences used for this response:\n1. WMO. Scientific Assessment of Ozone Depletion: 2022. Chapter 1: Update on\nOzone-Depleting Substances (ODSs) and Other Gases of Interest to the Montreal\nProtocol. (2022).\nRevised text:\nLines 275-281 in the revised manuscript: “During the 20 d backward simulation,\nthe fraction of chemical loss to emission resulting from CH Br lifetime (0.8 years) is\n3\napproximately only 1.7% (1-exp(-5/(0.8×365))) considering that the enhancements\nmeasured at observation sites are typically influenced by emissions within a five-day\ntransport of an air mass46. A previous study demonstrated that the inversion results of\nCHCl (lifetime = 0.4 years) changed by only 1% when chemical losses were included\n3\nin the simulation.45 Thus, the chemical losses of CH Br were not considered in our\n3\nbackward simulation.”\nL303: What do you mean by “proportion”? Why is the exponential decay value a\nfactor of 4 (5/20) smaller than in previous equation in L302?\nResponse:\nThanks for your question. The “proportion” here is not the “loss rate” (or “lifetime”).\nThe “proportion” here refers to the fraction of loss during the backward simulation to\nemission estimated in inversion. For example, a loss proportion of 10% means that\n10% of the emitted ODS was degraded during the backward simulation period. The\nvalues in original L302 and L303 were calculated by including the chemical loss\nduring 20 days and 5 days prior to the measurement, respectively; thus, the value in\noriginal L303 is smaller than that in original L302 as you see. In fact, the\nenhancement observed at each site mainly is influenced by the emissions and\ntransport within 5 days prior to the measurement, and the emissions 15 or more days\nearlier have mixed well enough to become part of the baseline, not the enhancement1.\nTherefore, 20 days represents the upper limit when calculating the loss during\nsimulation. We have removed the 20-d scenario and only presented the more realistic\n5-d scenario.\nReferences used for this response:\n1. Stohl, A., Seibert, P., Arduini, J., Eckhardt, S., Fraser, P., Greally, B. R., Lunder,\nC., Maione, M., Mühle, J., O'Doherty, S., Prinn, R. G., Reimann, S., Saito, T.,\nSchmidbauer, N., Simmonds, P. G., Vollmer, M. K., Weiss, R. F. & Yokouchi, Y. An\nanalytical inversion method for determining regional and global emissions of\ngreenhouse gases: Sensitivity studies and application to halocarbons. Atmos Chem\nPhys 9, 1597-1620, doi:10.5194/acp-9-1597-2009 (2009).\nRevised text:\nLines 275-281 in the revised manuscript: “During the 20 d backward simulation,\nthe fraction of chemical loss to emission resulting from CH Br lifetime (0.8 years) is\n3\napproximately only 1.7% (1-exp(-5/(0.8×365))) considering that the enhancements\nmeasured at observation sites are typically influenced by emissions within a five-day\ntransport of an air mass46. A previous study demonstrated that the inversion results of\nCHCl (lifetime = 0.4 years) changed by only 1% when chemical losses were included\n3\nin the simulation.45 Thus, the chemical losses of CH Br were not considered in our\n3\nbackward simulation.”\nL328-L332: Is this a standard procedure to estimate the background concentration?\nGiven the importance of the background estimation to compute the enhancement over\nChina, further details and/or an example with specific data would help to understand\nif the approach used is valid.\nResponse:\nThe baseline method used here has been applied in many previous studies1,2,3.\nAdditionally, we have proved that our inversion results are not sensitive to the choice\nof baseline methods as shown in Supplementary Fig. 7b. We have further clarified the\nbaseline calculation method in the revised Methods section.\nReferences used for this response:\n1. Thompson, R. L.; Stohl, A. FLEXINVERT: an atmospheric Bayesian inversion\nframework for determining surface fluxes of trace species using an optimized grid.\nGeoscientific Model Development 2014, 7 (5), 2223-2242. DOI: 10.5194/gmd-7-\n2223-2014.\n2. Fang, X., Yao, B., Vollmer, M. K., Reimann, S., Liu, L., Chen, L., Prinn, R. G. &\nHu, J. Changes in HCFC Emissions in China During 2011–2017. Geophys Res Lett\n46, 10034-10042, doi:10.1029/2019gl083169 (2019).\n3. Yao, B., Fang, X., Vollmer, M. K., Reimann, S., Chen, L., Fang, S. & Prinn, R. G.\nChina’s Hydrofluorocarbon Emissions for 2011–2017 Inferred from Atmospheric\nMeasurements. Environmental Science & Technology Letters 6, 479-486,\ndoi:10.1021/acs.estlett.9b00319 (2019).\nRevised text:\nLines 302-306 in the revised manuscript: “For the flask sampling sites, background\nmole fractions were estimated as the lower value of (1) the lowest measurement in the\n90 d moving window and (2) the latitude-direction linearly interpolated value between\nthe monthly mean background value at the Ragged Point (RPB, 13.17° N, 59.43° W)\nand Mace Head (MHD, 53.33° N, 9.9° W)40,41.”\nL458: There are newer publications than ref. 57 supporting “recent estimations”. In\naddition, here and elsewhere in the text, it is not clear if you are explicitly pointing at\nthe ozone layer, or the Antarctic ozone hole. Note that the return dates as well as the\ninfluence of ODSs under a changing climate are significantly different depending on\nthe studied region.\nResponse:\nThank you for your constructive comments. We agree with the reviewers that the\nestimate method for delay in ozone layer recovery is not robust enough, so we have\nremoved this part in the revised manuscript.\nL469-L474: It is not clear what is the meaning and difference between Fi and Fsurf.\nResponse:\nThe related estimate has been removed along with the calculation of “time to\nrecovery”.\nL477-L479: Rephrase the sentence and/or citations so the references support what is\nbeing said (Hossaini et al. reported …)\nResponse:\nThis paragraph has been removed.\nL481-L483: How can you make a CH Br increase relative to CH Cl in 2050?\n3 2 2\nApproaches in current work and in Hossaini are different. See my general comment\nabove and make it clear.\nResponse:\nThis paragraph has been removed.\nL484: Where does the (1/2) value come from? Is it because the 2 Cl atomicity in\ndichloromethane, which is different from Br 1 atomicity in methyl bromide?\nResponse:\nThis paragraph has been removed.\nL486: Following my major comment above, there are no further details on how the\nintegrated column ozone depletion change due to CH Br is being computed. I suggest\n3\nremoving it.\nResponse:\nWe have added more details on this calculation method in the revised Methods\nsection.\nRevised text:\nLines 435-444 in the revised manuscript: “Additionally, we calculated integrated\nozone depletion (IOD) to quantify the extra ozone depletion resulting from China’s\nmissing source during 2011–2050, assuming that the missing source (5.5 Gg yr-1 on\naverage from 2011 to 2020) remain constant during 2021–2050. The time-integrated\ncolumn ozone depletion can be calculated using halocarbon emissions and their total\natmospheric and stratospheric lifetimes59, with the equation as follows:\n𝐼𝑂𝐷 =𝐾 𝐸 (\n𝜏𝑎𝑡𝑚𝑜𝑠)……(14)\n𝐸𝑞\n𝜏𝑠𝑡𝑟𝑎𝑡\nHere, 𝐾 =100±16 𝐷𝑈 years per Tg Cl. 𝐸 is the emissions in Tg Cl, and we\n𝐸𝑞\nmultiplied a bromine efficiency factor of 60 to calculate 𝐸 for CH Br59. 𝜏 and 𝜏\n𝐸𝑞 3 𝑎𝑡𝑚𝑜𝑠 𝑠𝑡𝑟𝑎𝑡\nare total atmospheric lifetime and stratospheric lifetime of CH Br.”\nL127: “accurate” is not the proper word here. Please refer.\nResponse:\nAccepted. We have removed it.\nL173: “substantially improved” compared to what?\nResponse:\nThank you. This sentence has been removed.\nL203: “magenta triangles” on Fig. 2b.\nResponse:\nThank you. We have added it in this line accordingly.\nRevised text:\nLines 173-174 in the revised manuscript: “……magenta triangles shown in Fig.\n2b……”\nL337: Do you mean the standard deviation? (1σ or 2σ?)\nResponse:\nThank you for this comment. Yes, we mean 1σ, and we have revised it accordingly.\nRevised text:\nLines 311-312 in the revised manuscript: “Observational errors are represented by\none-sigma standard deviations of all observation data in a year at a site40,41.”\nL482: … in proportion to the additional “equivalent” Cl loading caused by CH Br …\nThank you. This sentence has been removed.\nFigures and Tables\nFigure 1: What does the map in the middle show? This is not described in the caption.\nIn addition, why did you chose a log scale for the color contours? To highlight low\nvalues? Same applies for Fig. S2.\nResponse:\nThank you for this comment. The middle map shows the locations of our sites and the\nsimulated footprint, which reflects the capability to constrain China’s emissions. We\nhave added captions to describe this accordingly. The footprint will decrease\nexponentially with the distance from the site, therefore we set a log scale for this map\nto show the full range of the footprint clearly, otherwise the low values cannot be\nshown. Prior studies also chose to use a log scale when plotting a footprint map (see\nbelow).\nRigby et al., 2019. Nature (https://doi.org/10.1038/s41467-019-1193-4)\nYi et al., 2023. ES&T (https://doi.org/10.1021/acs.est.3c00695)\nAn et al., 2022. Nature Comm (https://doi.org/10.1038/s41467-021-27592-y)\nRevised text:\nLines 690-698 in the revised manuscript: “(a) The locations (white cross) and the\nsum of annual averaged footprints from each site in 2020. Darker colors indicate\nhigher emission sensitivity. Emissions throughout most of China can be constrained\nby measurements at the ten sites. (b-i) Box-and-whisker plots of CH Br\n3\natmospheric mole fractions at each site during 2011−2020. The box and whisker\nplots depict the 10th, 25th, 50th, 75th, and 90th percentiles of the CH Br mole fractions.”\nemission” in panel b) for the general reader.\nResponse:\nThanks for your comment. The shaded area represents 1-sigma uncertainties, and we\nhave added this explanation in the revised caption. We have removed the word\n“posterior emission”.\nRevised text:\nLines 701 in the revised manuscript: “The shaded area represents 1-sigma\nuncertainties.”\nFigure 3: Usage of fumigation, QPS and non-QPS in labels and caption is confusing.\nPlease revise and make it consistent with the text. In addition, in panel b) it is clear\nthat Choi et al. results are lower than in this study, but Fig. S4 shows equivalent\nresults (Choi is even larger in some years) in east China. Can you explain those\ndifferences?\nResponse:\nThank you for these comments. Usage of fumigation includes QPS and non-QPS.\nWe have added an explanation in the revised caption. Additionally, we have added\ndescription about fumigation, QPS, and non-QPS in the beginning section of\nIntroduction according to your previous suggestion. Bottom-up estimates for China\nshown in Fig. 3 by Choi et al. are lower than those by this study, which is discussed in\nthe bottom-up section to show the improvements by this study. Top-down estimates\nfor eastern China by Choi et al. and this study are shown in Supplementary Fig. 4,\nshowing Choi et al.’s results are close to those in this study. We have added\nexplanations in the revised manuscript.\nRevised text:\nLines 50-52 in the revised manuscript: “Being a highly effective broad-spectrum\nfumigant, CH Br was widely used as a pest-control treatment in fumigation\n3\napplications including quarantine and pre-shipment (QPS), and non-QPS uses\n(mainly soil, post-harvest, and structure fumigation)5.”\nLines 715-716 in the revised manuscript: “Note that fumigation includes QPS and\nnon-QPS applications.”\nLines 131-134 in the revised manuscript: “As shown in Supplementary Fig. 4, the\nemission estimates for eastern China in this study are consistent with those derived\nfrom observations at GSN site in South Korea and the interspecies ratio method by\nChoi et al.8.”\nLines 150-153 in the revised manuscript: “Compared with Choi et al.8, seven\nadditional sectors were considered in this study, including non-fumigation\nanthropogenic sectors (feedstock6,13, solvents13-15, CH Br industrial production13) and\n3\nterrestrial ecosystem sectors (rice paddies16,17, salt marshes18,19, mangroves20, and\nfungi21,22).”\nEvaluate if some of the supplementary tables can be merged/unified. If this is not\npossible at least use equivalent units for the emissions and/or areas. In addition,\nknowledge of the fraction of the total area and population from east China relative to\nthe total China is missing.\nResponse:\nThank you for these suggestions. We have unified the units for area and emissions\nused in each table accordingly. We have added the fraction of area and population\nfrom east China relative to total China in the revised manuscript.\nRevised text:\nLines 124-126 in the revised manuscript: “Even though the area of eastern China\naccounts for only 12.5% of China’s total area, the emissions from eastern China\ncontributed about 52% (4.8 Gg yr-1) of China’s total emissions.”\nLines 130-131 in the revised manuscript: “For comparison, these five provinces\nrepresent 7.3% and 32% of China’s total area and populations, respectively.”\nTable S4: Explain if the mole fractions in the tables are the enhanced values on top of\nthe background level.\nResponse:\nThank you. Table S4 presents the top-down and bottom-up emission estimates instead\nof mole fractions.\nFigure S2: This is a nice figure and should be included in the main text.\nResponse:\nThank you very much. However, we think that the measurement information has been\nadequately presented in Fig. 1 in the main text, so we keep Supplementary Fig. 2 in\nthe Supplementary Information to avoid repetitive information.\nEND OF REVIEW\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nI think the authors have responded to the concerns raised in the initial reviews and in my opinion,\nthe manuscript is now suitable for publication. It is a significant contribution to our understanding\nof the methyl bromide budget.\nReviewer #3 (Remarks to the Author):\nThe revised manuscript has been significantly improved with respect to the original draft. I\nappreciate the author’s efforts in addressing all of the reviewers concerns (not only mine), which\ncertainly helped to improve the quality of the manuscript, and most importantly, to provide a\nclearer and more straightforward message. Therefore, I recommend publication of the manuscript\nafter the following (mostly technical and/or linguistic) issues attached have been solved.\nReviewer #4 (Remarks to the Author):\nFang et al. estimate the national emissions of CH3Br in China from 2011 to 2020, and reveal that\nthere is high and persistent CH3Br emissions in China compared to the background sites.\nAlthough the focus of this manuscript together with the availability of long-term observation dataset are\nimportant for us to better understand the CH3Br emissions and its impacts, I think that the current\nmanuscript is still lacking of solid supporting evidences and implications. The writing of the\nmanuscript is also hard to follow, therefore, requires major improvements prior to the decision for\npublication. My comments are as the followings:\nPage 3, Line 50-54: The authors should introduce both the anthropogenic and natural sources of\nCH3Br in the introduction as the general readers might not understand the origin of CH3Br.\nPage 4, Line 75: Please specify which emission sectors have been omitted.\nPage 5, Line 91: Despite the authors have justified that these 4 sites are located at similar latitudes,\nI am not sure how suitable is it to select these 4 sites to represent the global background. Can you\nfurther explain on this? These sites have different characteristics and some of the sites might also\nhave influence from the anthropogenic emissions, for example the Mace Head and Gosan can also\nbe influenced by polluted air mass. Are these 7.0 to 7.6 ppt CH3Br averaged values or being\nobtained with similar method to estimate baseline values in China sites? I think it is also important\nto look at how do the high values in China compared to the to the polluted areas around the world?\nDo they have similar trend?\nPage 6, Line 118: It may be true that the long-term CH3Br emission trend is a key attraction, but I\ncannot see further novelty was emphasized throughout manuscript. The higher CH3Br emission\nhas been expected as indicated by previous studies (including the Li et al., 2011; Kim et al., 2010).\nTo me, this manuscript seems like a follow-up study to the findings reported in Choi et al. (2022)\nand there are some similarities in the method, analysis, and results. Although some efforts have\nbeen made to compare the works, they should further distinguish the novelty of this work with the\nprevious studies, and properly highlight the key novelty in both abstract and main text.\nPage 7, Line 139-140: Is this 1.4 Gg yr-1 statistically different? Is it within the uncertainty range? In\nother word, will the red and blue lines in Fig.3b overlap if the uncertainty is being considered?\nPage 7, Line 141-149: Other than the information on port cargo throughput, is there any evidence\nshowing the shipping activities will be important for the CH3Br emission? I am not sure how can it\nlinked to the emissions hotspot. Is the chemical ‘ingredient’ during the fumigation still contain\nCH3Br? If a large source of CH3Br being emitted, the bromine chemistry will properly be important\nin this area, thereby affecting the surrounding air quality. Is there measurement being conducted\naround the ports before?\nPage 8, Line 158: I am surprised that the authors did not discuss the causes/potential reasons of\nthe big gap between top-down and bottom-up emissions in this paragraph.\nPage 8, Line 162: The discussion in the section for its potential causes seems to be a major issue.\nFirst, I am quite sceptical on linking the CH3Br emission with the provided evidence for illegal\nproduction and sales of CH3Br in Jiangsu and Shandong province. According to the provided\nreferences, the cases have been reported by the government authorities, which means action have\nbeen taken to stop these illegal production and sales of CH3Br during the release of the reports.\nLogically thinking, the CH3Br emission from these illegal sources will likely becoming less.\nWithout further evidence, I have doubt that the higher CH3Br emission are from the illegal\nsources. Second, the discussion on the new emission sources of CH3Br are pretty simple and vague.\nThird, the authors have mentioned about the terrestrial sources (such as salt marshes, rice paddies,\nand rapeseed), can ocean emission be an important source for CH3Br too? Given the warming of the\nsurface ocean (due to climate change) and increasing of surface ozone levels, the ocean emission\nof CH3Br might be important too. The authors should add this information to the discussion.\nPage 10, Line 196: A major weakness of this manuscript is the discussion on the implication of\nCH3Br emission. The authors have tried to estimate the integrated ozone depletion for the\nunaccounted emissions of CH3Br in China originate entirely from anthropogenic sources and\ncontinue to 2050. The assumption of course is interesting but lack of scientific relevant. From the\ndata, there is no trend of increasing for CH3Br emission in China, but towards a slightly decreasing\ntrend starting form 2019 (Fig.2). Together with the more restriction of usage, anthropogenic sources\nmight become less important and the contribution from the natural sources might become more\nrelevant in future. However, these are not being discuss.\nPage 15, Line 310: Briefly explain what is the approach of Stohl et al.\nPage 29, Fig.1: From the 10 sites, almost half of them have only a few years (≤4 years) of continuous\ndata from 2011 to 2020. How to make sure that these lacking of longer period of data in a particular\nsite will affect the conclusions of this study?\nSI-Supplementary Table 2: Please state whether the station represent urban, rural, background, etc.\nsite to give information on the type of environment for each sampling site.\nSI-Supplementary Table 6: Typo for ‘Hainan’.\n2nd round of Review of the manuscript “Unexplained high and persistent methyl bromide emissions\nin China after 2015 phase-out: A concern for the ozone layer and the Montreal Protocol” by\nHu et al., 2024.\nThe revised manuscript has been significantly improved with respect to the original draft. I appreciate\nthe author’s efforts in addressing all of the reviewers concerns (not only mine), which certainly helped\nto improve the quality of the manuscript, and most importantly, to provide a clearer and more\nstraightforward message. Therefore, I recommend publication of the manuscript after the following\n(mostly technical and/or linguistic) issues have been solved.\nMain:\nAbstract, L79-L81, L158-L161, L220-L222:\nIn my opinion, further polishing of how the main message of the paper is communicated can help to\nimprove its impact and visibility. For example: it is not the same to state “unexplained high emissions\nof CH3Br” that to say “the largest fraction of the CH3Br emission remains unexplained”. Despite the\nrevised manuscript now provides how large (in percentage) that discrepancy between top-down and\nbottom-up is (and also clearly points at where the missing sources may come from), the main lines\n(L#) highlighted here only say that they are “unexplained and high”, but not\n“dominant or the largest fraction”. Given this is the most important message for the\ngeneral audience, you need to strongly conclude that based on the comparison of your\nbottom-up and top-down analysis, the largest fraction of the total emission over china\nremains unexplained, which warrants further research. Having said this, after reading\nthe whole paper in detail, the message is clear … but after a quick reading of only\nthe abstract and final discussion it is not so evident (e.g., L158-L161 are hidden in the\nresults). I provide one simple example on the abstract below and leave to the leading\nauthors to decide whereas they feel comfortable with further text editing or not.\nL31: “…suggesting that the largest fraction of the observationally derived CH3Br emissions arise from\nunreported, …“\nMinor:\nL34: “If the unaccounted sources of CH3Br in China are assumed to be anthropogenic and to remain\nconstant until 2050, we estimate an integrated ozone depletion impact of approximately 20 DU years.”\nL44, L197-L198, L432: GWP is defined here and not used anymore in the text, while ODP is not defined\nbut used in many places below before it is defined in line L432. Please revise throughout the text. Also,\nplease be consistent on the usage of ozone depletion or depleting potential (e.g., L197 and elsewhere).\nMisspelling of OPD instead of ODP in L433.\nL72: “In addition, only a few multiyear atmospheric observation-inferred estimates of China’s CH3Br\nemissions are available.”\nL80: “… emissions in China, particularly from the more densely populated east coast.”\nL84: The subtitle is too long. Suggest removing “after the 2015 phase-out” which is the main focus of\nnext section.\nL117: “Based on the observation of the recently established long-term observation network …”\nL199: be consistent on the usage of ozone depletion or depleting (here and elsewhere).\nSuggestions:\nL302-L306: Which one of the two options was generally the most frequent case for low CH3Br values:\nthe 90d moving window or the linear interpolation of AGAGE? This information can be useful for\nreaders interested in the emission methodology applied.\nFig.1: I appreciate the detailed response given about the log scale used for the central “footprint”\npanel. This certainly allows capturing low values in comparison with the linear scale used in Fig2b.\nHowever, my feeling when looking at Fig. 1a is that most (not to say all) observational sites were\nlocated on top of one of the China’s hotspots. This suggest that, given that the footprint is based on\nFLEXPART back-trajectories (which in turn depend on the location of the observational sites), the final\nmap is probably missing other hotspot over China that you just cannot detect unless you\nextend even further your observational network. Doing so is certainly out of the scope\nof this paper, but at least a sentence pointing at this issue could be included in the\ndiscussion.\nFig.4: This is a nice sketch of your study. I understand the thickness of the arrow is representative of\nthe relative contribution of each sector to the total bottom-up inventory. If this is the case, this must\nbe mentioned in the caption. In addition, have you thought about including something like a bar/pie-\nchart or something equivalent with different sizes/proportion to highlight how large is the known and\nunknown (unexplained) fraction of the emission in a visual way? This could be added\nsomewhere in the top layers where the quantitative numbers are provided. Note units must be included\neither in the figure or in the caption.\nResponses to Reviewer #1\nReviewer #1 (Remarks to the Author):\nI think the authors have responded to the concerns raised in the initial reviews and in\nmy opinion, the manuscript is now suitable for publication. It is a significant\ncontribution to our understanding of the methyl bromide budget.\nResponse:\nThank you so much for your appreciation and support.\nEND OF REVIEW\nResponses to Reviewer #3\nReviewer #3 (Remarks to the Author):\nThe revised manuscript has been significantly improved with respect to the original\ndraft. I appreciate the author’s efforts in addressing all of the reviewers concerns (not\nonly mine), which certainly helped to improve the quality of the manuscript, and most\nimportantly, to provide a clearer and more straightforward message. Therefore, I\nrecommend publication of the manuscript after the following (mostly technical and/or\nlinguistic) issues attached have been solved.\nResponse:\nWe really appreciate your constructive suggestions and support. We have revised all\nthe (mostly technical and/or linguistic) issues according to your suggestions. Below\nwe provide point-to-point responses to each of your suggestions.\nMain:\nAbstract, L79-L81, L158-L161, L220-L222:\nIn my opinion, further polishing of how the main message of the paper is\ncommunicated can help to improve its impact and visibility. For example: it is not the\nsame to state “unexplained high emissions of CH Br” that to say “the largest fraction\n3\nof the CH Br emission remains unexplained”. Despite the revised manuscript now\n3\nprovides how large (in percentage) that discrepancy between top-down and bottom-up\nis (and also clearly points at where the missing sources may come from), the main\nlines (L#) highlighted here only say that they are “unexplained and high”, but not\n“dominant or the largest fraction”. Given this is the most important message for the\ngeneral audience, you need to strongly conclude that based on the comparison of your\nbottom-up and top-down analysis, the largest fraction of the total emission over china\nremains unexplained, which warrants further research. Having said this, after reading\nthe whole paper in detail, the message is clear … but after a quick reading of only\nthe abstract and final discussion it is not so evident (e.g., L158-L161 are hidden in the\nresults). I provide one simple example on the abstract below and leave to the leading\nauthors to decide whereas they feel comfortable with further text editing or not.\nL31: “…suggesting that the largest fraction of the observationally derived CH Br\n3\nemissions arise from unreported, …“\nResponse:\nThank you so much for this constructive suggestion. According to your suggestions,\nwe have highlighted the dominant role of the unexplained emissions to the total top-\ndown emissions in the revised manuscript.\nRevised text:\nLines 31-33 in the revised manuscript: “Top-down emission estimates exceed\nbottom-up estimates by 5.5 ± 1.4 gigagrams per year, with the largest fraction (60%)\nof observationally derived CH Br emissions arising from unreported, underreported\n3\nor unidentified emissions sources.”\nLines 84-86 in the revised manuscript: “This study reveals that half of China’s\nCH Br emissions are concentrated in the eastern provinces of China, and over half of\n3\nthe national emissions remain unexplained.”\nLines 240-242 in the revised manuscript: “In summary, the largest fraction of the\ntotal CH Br emissions in China remains unexplained, which poses challenges to both\n3\nthe implementation of the Montreal Protocol and the scientific understanding of the\nCH Br budget.”\nL34: “If the unaccounted sources of CH Br in China are assumed to be anthropogenic\n3\nand to remain constant until 2050, we estimate an integrated ozone depletion impact\nof approximately 20 DU years.”\nResponse:\nThank you for this suggestion. According to another reviewer’s suggestion, we have\nrevised this sentence as follows.\nRevised text:\nLines 34-35 in the revised manuscript: “This study shows the potential impacts of\nthe unaccounted emissions on stratospheric ozone depletion, with implications for the\nMontreal Protocol.”\nL44, L197-L198, L432: GWP is defined here and not used anymore in the text, while\nODP is not defined but used in many places below before it is defined in line L432.\nPlease revise throughout the text. Also, please be consistent on the usage of ozone\ndepletion or depleting potential (e.g., L197 and elsewhere). Misspelling of OPD\ninstead of ODP in L433.\nResponse:\nThank you for such careful review and revisions. We have added the ODP definition\nin the Introduction section and revised the misspelling of OPD to ODP accordingly.\nRevised text:\nLines 43-45 in the revised manuscript: “Methyl bromide (CH Br) is an important\n20-yr global warming potential (GWP) of 94.”\nLines 214-217 in the revised manuscript: “For example, the ODP-weighted\nemissions [mass emission multiplied by the ODP; ODP represents the relative amount\nof degradation to the ozone layer a compound can cause, with trichlorofluoromethane\n(CFC-11) being fixed at an ODP of 1.0; CFC-11-equivalent emissions] of CH Br in\nLines 458-459 in the revised manuscript: “A key metric to assess the ability of a\ncompound to deplete stratospheric ozone is ODP, which is calculated relative to a\nreference compound (CFC-11 with an ODP of 1).”\nL72: “In addition, only a few multiyear atmospheric observation-inferred estimates of\nChina’s CH Br emissions are available.”\nThank you for this suggestion. Since there are no multiyear atmospheric observation-\ninferred estimates of China’s CH Br emissions, we have revised this sentence as\n3\nfollows.\nRevised text:\nLines 74-75 in the revised manuscript: “In addition, multiyear atmospheric\nobservation-inferred estimates of China’s CH Br emissions are lacking.”\ncoast.”\nResponse:\nThank you for this suggestion. We have revised this sentence according to your first\ncomment to highlight the large fraction of the unexplained emissions relative to the\ntotal emissions.\nRevised text:\nLines 84-86 in the revised manuscript: “This study reveals that half of China’s\nCH Br emissions are concentrated in the eastern provinces of China, and over half of\n3\nthe national emissions remain unexplained.”\nL84: The subtitle is too long. Suggest removing “after the 2015 phase-out” which is\nthe main focus of next section.\nResponse:\nThank you for this suggestion. We have revised it accordingly.\nRevised text:\nLines 90-91 in the revised manuscript: “Higher CH Br mole fractions in China\n3\ncompared to the background atmosphere”\nL117: “Based on the observation of the recently established long-term observation\nnetwork …”\nResponse:\nThank you for this suggestion. ‘Observation’ is repeated twice here, so we removed\nthe first one.\nRevised text:\nLines 130 in the revised manuscript: “Based on the recently established long-term\nobservation network in China, …”\nL199: be consistent on the usage of ozone depletion or depleting (here and\nelsewhere).\nResponse:\nThank you for this reminder. We have revised the “ozone depleting” to “ozone\ndepletion” and we defined the ODP in the Introduction, so here we directly used\n“ODP”.\nRevised text:\nLines 43-45 in the revised manuscript: “Methyl bromide (CH Br) is an important\n20-yr global warming potential (GWP) of 94.”\nLines 214 in the revised manuscript: “For example, the ODP-weighted\nemissions……”\nSuggestions:\nL302-L306: Which one of the two options was generally the most frequent case for\nlow CH Br values: the 90d moving window or the linear interpolation of AGAGE?\napplied.\nResponse:\nThank you for this suggestion. The 90-day moving window is the most frequent case.\nWe have added this information in the revised manuscript accordingly.\nRevised text:\nLines 330-331 in the revised manuscript: “In most cases, the lowest measurement\nin the 90-day moving window was chosen as the baseline.”\nFig.1: I appreciate the detailed response given about the log scale used for the central\n“footprint” panel. This certainly allows capturing low values in comparison with the\nlinear scale used in Fig2b. However, my feeling when looking at Fig. 1a is that most\n(not to say all) observational sites were located on top of one of the China’s hotspots.\nThis suggest that, given that the footprint is based on FLEXPART back-trajectories\n(which in turn depend on the location of the observational sites), the final map is\nprobably missing other hotspot over China that you just cannot detect unless you\nextend even further your observational network. Doing so is certainly out of the scope\nof this paper, but at least a sentence pointing at this issue could be included in the\ndiscussion.\nResponse:\nThank you for this comment. We agree with you that adding more observational sites\nwill help to better identify any other emission hotspots in China. We have added a\nstatement about this issue accordingly.\nRevised text:\nLines 283-284 in the revised manuscript: “Nonetheless, adding more observational\nsites in regions that currently do not have sites, should help to better constrain\nregional emissions in the future.”\nFig.4: This is a nice sketch of your study. I understand the thickness of the arrow is\nrepresentative of the relative contribution of each sector to the total bottom-up\ninventory. If this is the case, this must be mentioned in the caption. In addition, have\nyou thought about including something like a bar/piechart or something equivalent\nwith different sizes/proportion to highlight how large is the known and unknown\n(unexplained) fraction of the emission in a visual way? This could be added\nsomewhere in the top layers where the quantitative numbers are provided. Note units\nmust be included either in the figure or in the caption.\nResponse:\nThank you for these good suggestions. We have added a description of the meaning of\nthe arrow width in the caption. In addition, we have added the unit and half-circles\nwith different sizes at the top of the figure to represent the proportions of the\nunexplained emissions more clearly.\nRevised text:\nLines 775-776 (in the caption of Figure 4) in the revised manuscript: “The\nthickness of the arrow represents the relative contribution of each emission sector to\nthe total bottom-up inventory.”\nRevised Figure:\nEND OF REVIEW\nResponses to Reviewer #4\nReviewer #4 (Remarks to the Author):\nFang et al. estimate the national emissions of CH Br in China from 2011 to 2020, and\n3\nreveal that there is high and persistent CH Br emissions in China compared to the\n3\nbackground sites. Although the focus of this manuscript together with the availability\nof long-term observation dataset are important for us to better understand the CH Br\n3\nemissions and its impacts, I think that the current manuscript is still lacking of solid\nsupporting evidences and implications. The writing of the manuscript is also hard to\nfollow, therefore, requires major improvements prior to the decision for publication.\nMy comments are as the followings:\nResponse:\nWe really appreciate your professional review and comments. We have provided\nmany supporting evidences for your major concerns. The implications for\nstratospheric ozone depletion and the Montreal Protocol have been further clarified.\nBelow we provide point-to-point responses to each of the comments and suggestions.\nPage 3, Line 50-54: The authors should introduce both the anthropogenic and natural\nsources of CH Br in the introduction as the general readers might not understand the\n3\norigin of CH Br.\nThank you for this suggestion. We have added a list of known natural sources in the\nrevised Introduction accordingly.\nRevised text:\nLines 54-56 in the revised manuscript: “Other sources, both natural and\nanthropogenic, also contribute to the atmospheric CH Br budget, including the\n3\noceans7,8, biomass burning9,10, biofuel burning4, natural ecosystems and certain\ncrops11-15.”\nPage 4, Line 75: Please specify which emission sectors have been omitted.\nResponse:\nThank you for this comment. We have specified the omitted emission sectors in this\nline accordingly.\nRevised text:\nLines 77-78 in the revised manuscript: “as previous bottom-up estimates17,21 have\nomitted several emission sectors, such as feedstock use6, rice paddies22, salt\nmarshes12,15, and mangrove11.”\nPage 5, Line 91: Despite the authors have justified that these 4 sites are located at\nsimilar latitudes, I am not sure how suitable is it to select these 4 sites to represent the\nglobal background. Can you further explain on this? These sites have different\ncharacteristics and some of the sites might also have influence from the anthropogenic\nemissions, for example the Mace Head and Gosan can also be influenced by polluted\nair mass. Are these 7.0 to 7.6 ppt CH Br averaged values or being obtained with\n3\nsimilar method to estimate baseline values in China sites? I think it is also important\nto look at how do the high values in China compared to the to the polluted areas\naround the world? Do they have similar trend?\nResponse:\nThank you for this constructive comment.\n(1) As for “I am not sure how suitable is it to select these 4 sites to represent the\nglobal background”, we agree with you that the baselines at these four sites are not\nexactly equal to the “global background” because baselines are not globally uniform\nand vary with latitudes, so the “global background” term used in the original subtitle\nis not accurate enough, and we have removed the “global” word in our revised\nmanuscript.\nOriginal text:\nLines 83-84 in the revised manuscript: “Higher CH Br mole fractions in China\n3\ncompared to the global background atmosphere after the 2015 phase-out”\nRevised text:\nLines 90-91 in the revised manuscript: “Higher CH Br mole fractions in China\n3\ncompared to the background atmosphere”\n(2) As for “These sites have different characteristics and some of the sites might also\nhave influence from the anthropogenic emissions, for example the Mace Head and\nGosan can also be influenced by polluted air mass”, we agree with you that some of\nthe four sites such as MHD, THD, and GSN can be influenced by anthropogenic\nemissions, as shown in Figure R1 below, there were some high values (pollution\nevents) observed at these three sites compared with RPB site. However, these four\nsites are remote background sites and they can capture well-mixed background air\nmass (Figure R1). In fact, in our manuscript, we used the baseline observations\nextracted using AGAGE’s method1 at these four AGAGE sites instead of the whole\nobservation datasets. High values (pollution events) caused by recently polluted air\nmasses as you mentioned were excluded. These 7.0 to 7.6 ppt values are not averaged\nmole fractions of the whole observation datasets but the averaged values of baseline\nobservations. The baselines observed at those four sites are generally consistent with\nthe range of 7.0 to 7.6 ppt on average and represent the zonally-mixed background\nlevel. In our revised manuscript, we have added the statement that we used the\nbaseline observations at those four AGAGE sites and the baseline extraction method.\nRevised text:\nLines 105-110 in the revised manuscript: “The background mole fractions at those\nfour AGAGE sites were determined by using AGAGE’s statistical algorithm which\nextracted the background observations by applying a second-order polynomial to the\ndaily minima over a 120-day moving time window23. To ensure comparability, we\nverified that the background mole fractions estimated using AGAGE’s method and\nthis study’s method were consistent (Supplementary Fig. 3).”\nFigure R1 (just for response). CH Br atmospheric mole fractions at four AGAGE\n3\nbackground sites during 2011−2020. The grey and yellow scatters represent the baseline and\npollution observations at each site, respectively.\n(3) As for “Are these 7.0 to 7.6 ppt CH Br averaged values or being obtained with\n3\nsimilar method to estimate baseline values in China sites?”, these 7.0 to 7.6 ppt values\nare not averaged mole fractions of the whole observation datasets but the averaged\nvalues of extracted baseline observations. The baseline estimation methods used for\nthese four AGAGE sites and our Chinese sites are similar in principle, which are both\nbased on statistical filtering methods by selecting the lower observations. For\nexample, as shown in Supplementary Fig. 3, the baseline estimates at LFS site (one of\nour Chinese sites) using AGAGE’s method1 and this study’s method are generally\nconsistent. We have added this validation to the revised Supplementary Information.\nSupplementary Figure 3. Annual mean baseline of CH Br at LFS (one of the Chinese\n3\nsites used in this study) using two different baseline estimate methods.\nRevised text:\nLines 108-110 in the revised manuscript: “To ensure the comparability, we verified\nthat the background mole fractions estimated using AGAGE’s method and this study’\nmethod were consistent (Supplementary Fig. 3).”\n(4) As for “how do the high values in China compared to the to the polluted areas\naround the world? Do they have similar trend?”, according to your suggestion, we\nhave compared the high values observed at our Chinese sites with those at four\nAGAGE background sites who can capture regional emissions from Europe (MHD),\nNorth America (THD), East Asia (GSN), and northern tropical regions (RPB). As\nshown in Figure R2, the magnitudes of enhanced mole fractions at the most of our\nChinese sites are significantly higher than those at MHD, THD, and RPB sites. The\nGSN site also observed many high values and this is consistent with the fact that GSN\nis also sensitive to emissions from eastern China (and other East Asia regions). The\ntrends of enhanced mole fractions at AGAGE sites are also generally stable. The\nsignificant difference between Chinese sites and AGAGE sites is the magnitude of\nenhanced mole fractions.\nFigure R2 (just for response). Box-and-whisker plots of CH Br atmospheric mole fractions\n3\nat four AGAGE background sites and Chinese sites during 2011−2020. Box plots indicate the\n25th and 75th of the CH Br mole fractions, with the median shown as a horizontal line within each\n3\nbox. The whiskers show the 10th and 90th percentiles. The difference between the lower and\nhigher percentiles indicates the magnitude of above-baseline events due to the interception of air\nmasses containing recently emitted CH Br. Note that the scale of y-axis in each subplot is not\n3\nexactly the same.\nReference used for this response:\n1. O'Doherty, S., Simmonds, P. G., Cunnold, D. M., Wang, H. J., Sturrock, G. A.,\nFraser, P. J., Ryall, D., Derwent, R. G., Weiss, R. F., Salameh, P., Miller, B. R. &\nPrinn, R. G. In situ chloroform measurements at Advanced Global Atmospheric Gases\nExperiment atmospheric research stations from 1994 to 1998. Journal of Geophysical\nResearch: Atmospheres 106, 20429-20444, doi:10.1029/2000jd900792 (2001).\nPage 6, Line 118: It may be true that the long-term CH Br emission trend is a key\n3\nattraction, but I cannot see further novelty was emphasized throughout manuscript.\nThe higher CH Br emission has been expected as indicated by previous studies\n3\n(including the Li et al., 2011; Kim et al., 2010). To me, this manuscript seems like a\nfollow-up study to the findings reported in Choi et al. (2022) and there are some\nsimilarities in the method, analysis, and results. Although some efforts have been\nmade to compare the works, they should further distinguish the novelty of this work\nwith the previous studies, and properly highlight the key novelty in both abstract and\nmain text.\nResponse:\nThank you for these insightful comments and suggestions. We summarized three key\nnovelties compared with previous studies as follows. In our revised manuscript, we\nhave highlighted the novelties of this work.\n(1) This study significantly improved the spatial and temporal coverage of\natmospheric observation network, which helps us to better constrain China’s national\nCH Br emissions than previous studies. Specifically, this study conducted ten-year\n3\natmospheric observations at ten background sites whose measurements were sensitive\nto almost the whole of China. While the emission estimates reported by Li et al., Kim\net al., and Choi et al. were based on only one site (i.e., GSN located in South Korea)\nwhich is only sensitive to emissions from eastern China, leaving the emission\nestimates from other regions of China highly uncertain.\n(2) This study employs a different emission estimate method (i.e., a Bayesian inverse\ntechnique combined with a FLEXPART transport model), based on which this study\nfor the first time presents the spatial distribution and emission hotspots of China’s\nCH Br emissions. Previous studies (i.e., Li et al., Kim et al., and Choi et al.) used an\n3\ninterspecies correlation method and were unable to reveal the spatial distribution of\nemissions. The emission hot regions identified by this work may provide implications\nfor future search for missing sources.\n(3) This study developed an updated bottom-up inventory which includes more\nemission sectors that were omitted in previous studies. Combining the improved top-\ndown and bottom-up estimates, this study for the first time reveals over half of\nChina’s CH Br emissions were unexplained and discuss the potential causes and\n3\nimplications.\nRevised text:\nLines 79-88 in the revised manuscript: “The novelties of this study are as follows:\n1) we present atmospheric observations of CH Br at ten sites in China, whose spatial\n3\ncoverages are significantly larger than the previously-used GSN site; 2) combining\nthese observations and an inverse modeling approach, we quantify for the first time\nthe total CH Br emissions from China and address their spatial-temporal patterns\n3\nduring 2011–2020; and 3) we develop an improved bottom-up emission inventory for\nknown sources of CH Br. This study reveals that half of China’s CH Br emissions are\n3 3\nconcentrated in the eastern provinces of China, and over half of the national\nemissions remain unexplained. The potential causes for these unexplained emissions\nand implications for stratospheric ozone depletion and the Montreal Protocol are also\ndiscussed.”\nLines 25-26 in the revised abstract: “However, the spatial-temporal patterns of\nChina’s national CH Br emissions remain unclear.”\nunaccounted emissions on stratospheric ozone depletion, with implications for the\nMontreal Protocol.”\nLines 122-124 in the revised manuscript: “This study improves on previous studies\nby using more sites within China’s borders, allowing a better quantification of\nnational emissions.”\nLines 170-171 in the revised manuscript: “Thus, the addition of these seven sectors\nsubstantially improves the bottom-up estimates of CH Br emissions in China.”\ninverse modeling may provide some implications for the future work on identifying\nnew sources.”\nPage 7, Line 139-140: Is this 1.4 Gg yr-1 statistically different? Is it within the\nuncertainty range? In other word, will the red and blue lines in Fig.3b overlap if the\nuncertainty is being considered?\nResponse:\nThank you for your detailed questions. We have added the uncertainties of the blue\nline (results of Choi et al.) and considered the uncertainties when comparing our\nupdated bottom-up inventory with Choi et al. according to your suggestion. As shown\nin Figure 3b, the red (this study) and blue (Choi et al.) lines do not overlap if the\nuncertainty is being considered. Thus, the difference between our updated bottom-up\nestimate and Choi et al. is significant.\nRevised text:\nLines 150-154 in the revised manuscript: “These were, on average, 2.8 ± 0.2 Gg yr-\n1 significantly higher than fumigation sector estimates alone (the sum of QPS and\nnon-QPS emissions based on CH Br consumption data reported to UNEP) and 1.2 ±\n3\n0.2 Gg yr-1 significantly higher than the total estimate (fumigation plus three non-\nfumigation sectors) by Choi et al.8.”\nRevised figure:\nFig. 3. Comparisons of bottom-up inventories of CH Br emissions from China during 2011-\n3\n2020.\nPage 7, Line 141-149: Other than the information on port cargo throughput, is there\nany evidence showing the shipping activities will be important for the CH Br\n3\nemission? I am not sure how can it linked to the emissions hotspot. Is the chemical\n‘ingredient’ during the fumigation still contain CH Br? If a large source of CH Br\n3 3\nbeing emitted, the bromine chemistry will properly be important in this area, thereby\naffecting the surrounding air quality. Is there measurement being conducted around\nthe ports before?\nResponse:\nThank you for these insightful questions. The chemical ‘ingredient’ during the\nfumigation is highly purified CH Br which is the effective ingredient to kill the\n3\nquarantine pests. For example, the lowest CH Br dose used for QPS fumigation\n3\naccepted for China is 98% purity1. For another example, the lowest CH Br dose used\n3\nfor QPS fumigation accepted for New Zealand pine logs exported to India is 99%\npurity (or 48 g m-3)2. Most (i.e., nearly 80%) of the CH Br used during the QPS\n3\nfumigation process is directly emitted to the atmosphere3. In principle, CH Br use for\nfumigation emissions of CH Br should occur in ports (mainly in eastern China).\n3\nfumigation process (or the shipping activities).\nThe main sink of CH Br in the troposphere is reaction with hydroxyl radical5, and the\n3\npartial lifetime of CH Br with hydroxyl radical is 1.8 years5 which is much longer\n3\nthan the time scale of zonal wind transport (about 2 weeks), thus, the local bromide\nchemistry and air quality surrounding the ports may not be significantly influenced by\nthe emitted CH Br. According to your suggestion, we searched the literature and\n3\nfound some reported high concentrations of CH Br in many ports. For example, Park\n3\net al.6 measured the CH Br concentrations in air sampled around Busan port, South\n3\nconcentration at various distances from fumigated objects in Busan port and various\ntimes after the start of degassing. For example, they reported that the mean\nconcentrations of CH Br at 1-m distance from the fumigated objects ranged from 44.9\n3\nto 267.3 ppm6, which even exceeds the US OSHA workplace limits of 20 ppm7. For\nanother example, at the Port of Tauranga in New Zealand, the 1-hour maximum\nCH Br concentration was measured at 0.34 ppm and the fluctuations in methyl\n3\nbromide were directly related to fumigation activities8 (Figure R3). Measurements at\nChinese ports are lacking and need to be conducted in the future.\nTable R1 (just for response). Mean CH Br concentrations at various distances from the\n3\nfumigated objects during both injection and degassing and at various elapsed times after the\nstart of degassing. This table was taken form Park et al.6\nFigure 3 (just for response). Time series plot comparison of the concentrations of methyl\nbromide and Total Volatile Organic Compounds (TVOC) measured with PID 1 and PID 2.\nThis figure was taken from EPA8.\nReferences used for this response:\n1. Inspection and Quarantine of the People's Republic of China. Professional Standard\nof Entry-Exit Inspection and Quarantine of the People’s Republic of China.\nhttps://cceeccic.org/1125404949.html.\n2. New Zealand Ministry for Primary Industries (NZMPI). Forest Products Export\nStandards—Phytosanitary Requirements of India.\nhttps://www.mpi.govt.nz/export/export-requirements/icpr-importing-countries-\nphytosanitary-requirements/forestry-icprs/india/.\n3. MBTOC. Methyl Bromide Technical Options Committee: Report of the Methyl\nBromide Technical Options Committee: 2018 Assessment, United Nations\nEnvironment Program, Nairobi, Kenya.\n4. https://safety4sea.com/fumigation-of-cargo-with-methyl-bromide/.\n5. Saltzman, E. S., Nicewonger, M. R., Montzka, S. A. & Yvon‐Lewis, S. A. A Post‐\nPhaseout Retrospective Reassessment of the Global Methyl Bromide Budget. Journal\nof Geophysical Research: Atmospheres 127, doi:10.1029/2021jd035567 (2022).\nhttps://ozone.unep.org/sites/default/files/2019-04/MBTOC-assessment-report-\n2018_1.pdf (2018).\n6. Park, M. G., Hong, Y. S., Park, C. G., Gu, D. C. & Mo, H. H. Variations in methyl\nbromide concentration with distance and time during quarantine fumigation. Environ\nMonit Assess 193, 397, doi:10.1007/s10661-021-09154-3 (2021).\n7. US OSHA. OSHA Occupational Chemical Database METHYL BROMIDE,\nhttps://www.osha.gov/chemicaldata/552.\n8. EPA. Methyl bromide and total volatile organic compounds concentrations\nmeasured at the Port of Tauranga. https://www.epa.govt.nz/assets/FileAPI/hsno-\nar/APP203660/Ecocific-Env-WS02-2020.08.09.pdf.\nPage 8, Line 158: I am surprised that the authors did not discuss the causes/potential\nreasons of the big gap between top-down and bottom-up emissions in this paragraph.\nResponse:\nThank you for this comment. We focused on the bottom-up estimates for known\nsources in this section titled “Accounting of CH Br emissions from known sources in\n“Unexplained high emissions of CH Br from China and its potential causes”. We have\n3\nmoved this paragraph to the next section.\nRevised text:\nLines 172-177 in the revised manuscript:\n“Unexplained high emissions of CH Br from China and its potential causes\n1 lower than our top-down estimates (9.2 ± 1.4 Gg yr-1) on average during 2011−2020\n(Fig. 4 and Supplementary Table 7). The gap between our top-down and bottom-up\nemissions estimates is large, amounting to approximately 60% of the top-down\nemissions estimates.”\nPage 8, Line 162: The discussion in the section for its potential causes seems to be a\nmajor issue. First, I am quite sceptical on linking the CH Br emission with the\n3\nprovided evidence for illegal production and sales of CH Br in Jiangsu and Shandong\n3\nprovince. According to the provided references, the cases have been reported by the\ngovernment authorities, which means action have been taken to stop these illegal\nproduction and sales of CH Br during the release of the reports. Logically thinking,\n3\nthe CH Br emission from these illegal sources will likely becoming less. Without\n3\nfurther evidence, I have doubt that the higher CH Br emission are from the illegal\n3\nsources. Second, the discussion on the new emission sources of CH Br are pretty\n3\nsimple and vague. Third, the authors have mentioned about the terrestrial sources\n(such as salt marshes, rice paddies, and rapeseed), can ocean emission be an important\nsource for CH Br too? Given the warming of the surface ocean (due to climate\n3\nchange) and increasing of surface ozone levels, the ocean emission of CH Br might be\n3\nimportant too. The authors should add this information to the discussion.\nResponse:\nThank you for these insightful comments. We have made many revisions on these\nthree points.\n(1) As for the “illegal production and sales of CH Br”, we agree with you that the\n3\nemissions from the reported illegal production and sales listed in the main text may\nhave been generally stopped by the government. Thus, it might not be suitable to\nmake a strong link between the high emissions to the reported illegal production and\nsales. In our revised manuscript, we have removed the statements about the strong\nlink between the reported illegal trades and the high emissions. However, it’s\nimportant to note that although illegal production and sales were punished in 2010 by\nthe government1-6, new illegal production and sales in 2020 still occurred7,8, almost\nalways in particular provinces (e.g., Shandong province). This indicates that it is\ndifficult to completely avoid and stop the illegal production and sales. Therefore,\nillegal production and sales of CH Br is still a noteworthy issue and may contribute to\n3\nthe high emissions, although we cannot quantitively estimate their contributions.\nRevised text:\nLines 179-184 in the revised manuscript: “First, illegal production and sales of\nCH Br may still be occurring in China. Multiple instances of illegal production and\n3\nsales were reported between 2010 and 2014 in multiple provinces29-34 (magenta\ntriangles shown in Fig. 2b). Although the above-mentioned activities were punished\nand reported, multiple instances of illegal production still occurred in 2020 in the\nShandong Province35,36 (yellow dots shown in Fig. 2b). The proportion of emissions\nfrom this source to the total unexplained emissions is unclear.”\nReferences used for this response:\n1. People's court of Anqiu City. A First instance criminal judgment of illegal business\n(in Chinese). https://www.lawtime.cn/caipan/1292254.html (2015).\n2. Ministry of Ecology and Environment of the People's Republic of China . The\nMinistry of Environmental Protection announced the handling of key environmental\ncases in October 2014 (in Chinese).\nhttps://www.mee.gov.cn/gkml/sthjbgw/qt/201411/t20141117_291515_wh.htm (2014).\n3. Ministry of Ecology and Environment of the People's Republic of China . The\nMinistry of Environmental Protection announced the handling of key environmental\ncases in August 2014 (in Chinese).\nhttps://www.gov.cn/foot/site1/20140929/782bcb888c4d15934c8201.pdf (2014).\n4. People's Court of Shandong Province. First instance criminal judgment of illegal\nbusiness (in Chinese).\nhttps://susong.tianyancha.com/3328c9f9a18d4fe3a9d2a258472075b4 People's Court\nof Shandong Province (2016).\n5. People's court of Anqiu City. First instance criminal judgment of illegal business (in\nChinese). https://susong.tianyancha.com/e258227bdc66420b8c7915daa704f7eb\n(2016).\n6. Aiqicha. Legal document of illegal business operation crime (in Chinese).\nhttps://aiqicha.baidu.com/nwenshu?wenshuId=01f0479a572a266cd4cc8b0cb0222c27\nc6967937 (2016).\n7. Sohu. Four men were prosecuted in Rizhao on suspicion of illegal trafficking of\ndrug products, environmental pollution and counterfeiting of registered trademarks (in\nChinese). https://www.sohu.com/a/519602203_121123881. (2022).\n8. Sohu. A fine of 100,000! Lizin this aging fertilizer plant inside (in Chinese).\nhttps://www.sohu.com/a/439647511_670376 (2020).\n(2) As for the “the discussion on the new emission sources of CH Br”, we have added\n3\nfurther calculation and discussion on the new emission sources. The emissions of\nCH Br from baking are negligible (about 0.2 Gg yr-1 globally1). We collected China’s\n3\nconsumption of CuSO and estimated China’s emissions from this sector at about 0.01\n4\n± 0.004 Gg yr-1 following the method used in Jiao et al.2. Therefore, emissions from\nthese two newly-identified sources cannot explained the gap between top-down and\nbottom-up emission estimates for China. The detailed discussion and calculation have\nbeen added to our revised manuscript as follows.\nRevised text:\nLines 196-207 in the revised manuscript: “Third, it is likely that additional sources\nremain to be identified. New emission sources of CH Br are still being discovered in\n3\nrecent years, such as baking discovered in 201641 and copper-based pesticides\ndiscovered in 202242, reflecting our incomplete understanding of CH Br sources.\nglobally41). Using China’s CuSO consumption (Supplementary Table 8) and the\n4\nrelationship between copper (II) amendments and CH Br emissions reported by Jiao\n3\net al.42, China’s emission from this sector is likely also negligible (0.01 ± 0.004 Gg yr-\n1). Note that due to the lack of China’s CuSO consumption for pesticide use, we use\n4\ntotal CuSO consumption to estimate emissions from this sector (data and calculation\n4\nshown in Supplementary Table 8). Therefore, the missing source in China cannot be\nwell explained by these newly-identified sources, but may be explained by sources yet\nto be identified.”\nSupplementary Table 8 in the revised Supplementary Information. CuSO\n4\nproduction, export, import, and consumption in China. Unit: Gg yr-1.\nYear Productiona Exporta Importa Consumptiona\n2010 213.4 19 3.3 198\n2011 252.6 21 1.6 233\n2012 270.7 17 1.9 256\n2013 292.2 13 3.1 282\n2014 329.2 15 1.4 316\n2015 362.4 16 1.1 348\n2016 391.5 12 1.6 381\n2017 425.1 15 1.9 412\n2018 471.9 15 1.3 458\naData source: https://www.chyxx.com/industry/201907/766127.html\nCH Br emission = 1656 ± 752 [ng CH Br] ÷ 0.0005 [mol Cu amended] × (45.8×1010 g ÷ 159.6 g mol-1\n3 3\nCuSO ) ÷ 1018 [ng Gg-1] = 0.01 ± 0.004 Gg yr-1\n3\n3) As for the “can ocean emission be an important source for CH Br too?”, open\n3\nocean is ne net sink and coastal ocean is a source of CH Br3. In our revised\n3\nmanuscript, based on the area of China’s coastal ocean waters (3.7×1011 m2)4 and the\nmeasured emission flux rates [3.7 (0.9−12) nmol m-2 d-1]3, we added the calculation of\nthe CH Br emissions from China’s coastal ocean waters at 3.7 nmol m-2 d-1 × (3.7 ×\n3\n1011 m2) × 365.5 d yr-1 × (94.94 × 10-9 g nmol-1) × (10-9 Gg g-1) = 0.05 Gg yr-1.\nTherefore, coastal ocean waters are unlikely to be major contributors to the large\nunexplained sources observed here.\nRevised text:\nLines 191-195 in the revised manuscript: “Although coastal ocean waters are also\na source of CH Br (open ocean is a net sink of CH Br), China’s CH Br emissions\n3 3 3\nfrom coastal ocean waters are estimated at 0.05 (0.01−0.15) Gg yr-1 based on the\narea of China’s coastal ocean waters40 and measured emission flux rates39, so coastal\nocean waters are unlikely to be major contributors to the large unexplained sources\nobserved here.”\nReferences used for this response:\n1. Thornton, B. F., Horst, A., Carrizo, D. & Holmstrand, H. Methyl chloride and\nmethyl bromide emissions from baking: an unrecognized anthropogenic source. Sci\nTotal Environ 551-552, 327-333, doi:10.1016/j.scitotenv.2016.01.213 (2016).\n2. Jiao, Y., Zhang, W., Kim, J. Y. R., Deventer, M. J., Vollering, J. & Rhew, R. C.\nApplication of copper(II)-based chemicals induces CH(3)Br and CH(3)Cl emissions\nfrom soil and seawater. Nat Commun 13, 47, doi:10.1038/s41467-021-27779-3\n(2022).\n3. Hu, L., Yvon-Lewis, S. A., Liu, Y., Salisbury, J. E. & O'Hern, J. E. Coastal\nemissions of methyl bromide and methyl chloride along the eastern Gulf of Mexico\nand the east coast of the United States. Global Biogeochemical Cycles 24, n/a-n/a,\ndoi:10.1029/2009gb003514 (2010).\n4. Ministry of Ecology and Environment of the People's Republic of China. Bulletin\nof Environmental Quality in China's coastal waters (in Chinese).\nhttps://www.mee.gov.cn/hjzl/sthjzk/jagb/ (2002).\nPage 10, Line 196: A major weakness of this manuscript is the discussion on the\nimplication of CH Br emission. The authors have tried to estimate the integrated\n3\nozone depletion for the unaccounted emissions of CH Br in China originate entirely\n3\nfrom anthropogenic sources and continue to 2050. The assumption of course is\ninteresting but lack of scientific relevant. From the data, there is no trend of increasing\nfor CH Br emission in China, but towards a slightly decreasing trend starting form\n3\n2019 (Fig.2). Together with the more restriction of usage, anthropogenic sources\nmight become less important and the contribution from the natural sources might\nbecome more relevant in future. However, these are not being discuss.\nResponse:\nThank you for this constructive discussion. As you commented, the calculated\nintegrated ozone depletion (IOD) depends on the future evolution of these\nunidentified emissions. We acknowledge that the future unaccounted CH Br\n3\nemissions may differ with the average level during 2011−2020, so we stated the\nlimitation of this assumption: “Note that this calculated IOD depends on the future\nevolution of CH Br emissions” in our revised manuscript.\ndifference is that if these emissions are natural, they cannot be regulated by Montreal\nProtocol; but if they are anthropogenic, they can be regulated by the Montreal\nProtocol. Therefore, if these unexplained emissions are anthropogenic, they will pose\na challenge for the Montreal Protocol. That is why we only discuss the scenario that\nthese emissions are anthropogenic. We have revised the abstract and main text as\nfollows to highlight the potential implications of these unexplained emissions for the\nMontreal Protocol and the ozone depletion.\nRevised text:\nLines 229-234 in the revised manuscript: “If the unaccounted emissions of CH Br\n3\nin China continue to 2050, they will amount to an integrated ozone depletion of\napproximately 20 DU years (see calculations in Methods). Note that this calculated\nIOD depends on the future evolution of CH Br emissions. It is important to figure out\n3\nhow much of the unaccounted emissions of CH Br are anthropogenic and to\n3\ndetermine their future evolution in order to assess compliance with the Montreal\nProtocol.”\nLines 33-35 in the revised abstract: “This study shows the potential impacts of the\nunaccounted emissions on stratospheric ozone depletion, with implications for the\nMontreal Protocol.”\nPage 15, Line 310: Briefly explain what is the approach of Stohl et al.\nResponse:\nThank you for this suggestion. We have added explanations about the Stohl’s\napproach in the revised manuscript.\nRevised text:\nLines 335-337 in the revised manuscript: “For the SDZ in situ site, background\nmole fractions were estimated using the approach of Stohl et al.54, which selects the\nlowest 25% of the observations in a 30-day moving time window and then subtracts\nprior simulated enhancements.”\nPage 29, Fig.1: From the 10 sites, almost half of them have only a few years (≤4\nyears) of continuous data from 2011 to 2020. How to make sure that these lacking of\nlonger period of data in a particular site will affect the conclusions of this study?\nResponse:\nThank you for this question. As shown in Figure R4 and Figure 5, our recent study of\nHCFC-141b1 and previous study of CH2Cl22 emission inversion using the same\nobservational network have shown that the derived top-down emissions are relatively\ninsensitive to the number of observational sites used in inversion. While more\nmeasurement sites in the latter years could lead to a more comprehensive sensitivity\ncoverage, the measurements in the earlier years appear to be sufficient to capture the\nemissions from China relatively well (see Supplement Fig. 1, the sensitivity maps\ncover most of the key emission regions of China). In our revised manuscript, we have\nadded one sentence to state that more observational sites help to better constrain the\ntop-down emissions.\nRevised text:\nLines 283-284 in the revised “Methods”: “Nonetheless, adding more observational\nsites in regions that currently do not have sites, should help to better constrain\nregional emissions in the future.”\nFigure R4 (just for response). Derived HCFC-141b emissions for China using different\nmeasurement datasets.\nSun et al., 2023. ES&T (https://doi.org/10.1021/acs.est.3c04881)1\nFigure 5 (just for response). Derived CH Cl emissions for China using different\n2 2\nmeasurement datasets.\nAn et al., 2021. Nature Commun. (https://doi.org/10.1038/s41467-021-27592-y)2\nReferences used for this response:\n1. Sun, Y., Yao, B., Hu, X., Yang, Y., Li, B., Ma, M., Chi, W., Du, Q., Hu, J. & Fang,\nX. Inverse Modeling Revealed Reversed Trends in HCFC-141b Emissions for China\nduring 2018–2020. Environmental Science & Technology 57, 19557-19564,\ndoi:10.1021/acs.est.3c04881 (2023).\n2. An, M., Western, L. M., Say, D., Chen, L., Claxton, T., Ganesan, A. L., Hossaini,\nR., Krummel, P. B., Manning, A. J., Muhle, J., O'Doherty, S., Prinn, R. G., Weiss, R.\nF., Young, D., Hu, J., Yao, B. & Rigby, M. Rapid increase in dichloromethane\nemissions from China inferred through atmospheric observations. Nat Commun 12,\n7279, doi:10.1038/s41467-021-27592-y (2021).\nSI-Supplementary Table 2: Please state whether the station represent urban, rural,\nbackground, etc. site to give information on the type of environment for each\nsampling site.\nResponse:\nThank you for this suggestion. The ten Chinese sites are background sites with no\nindustries or dense populations within 20 km of these sites. We have added this\ninformation in the revised manuscript and Supplementary Table 2 accordingly.\nRevised text:\nLines 252-254 in the revised manuscript: “These sites were located more than 20\nkm from the nearest industrial and densely populated areas in order to sample air\nmasses carrying regional emission signals48-51.”\nLines 29-30 in the revised Supplementary Information: “These ten sites are\nbackground sites which are at least 20 km away from the industrialized and densely\npopulated areas to avoid the influences from local pollution.”\nSI-Supplementary Table 6: Typo for ‘Hainan’.\nResponse:\nThank you for such careful review. We have revised it to “Hainan”.\nEND OF REVIEW\nREVIEWERS' COMMENTS\nReviewer #4 (Remarks to the Author):\nI have read the authors response to my comments and those of the other reviewer and find that\nthey have done a good job of addressing all of the comments and concerns raised in the reviews. I\nappreciate the effort they put into revising the manuscript, and think that the current manuscript\nhas been improved significantly."}]

Decision letter