Estimate of Hydrofluorocarbon Emissions for 2012–16in the Yangtze River Delta, China
Jingjiao PU1, Honghui XU1, Bo YAO*2, Yan YU1, Yujun JIANG1,3, Qianli MA3, and Liqu CHEN2
1Zhejiang Meteorological Science Institute, Hangzhou 310008, China2Meteorological Observation Center of China Meteorological Administration, Beijing 100081, China
3Zhejiang Lin'an Atmospheric Background National Observation and Research Station, Hangzhou 311307, China
(Received 12 November 2019; revised 13 January 2020; accepted 26 February 2020)
ABSTRACT
Hydrofluorocarbons (HFCs) have been widely used in China as substitutes for ozone-depleting substances, theproduction and use of which are being phased out under the Montreal Protocol. China is a major consumer of HFCs aroundthe world, with its HFC emissions in CO2-equivalent contributing to about 18% of the global emissions for the period2012–16. Three methods are widely used to estimate the emissions of HFCs—namely, the bottom-up method, top-downmethod and tracer ratio method. In this study, the tracer ratio method was adopted to estimate HFC emissions in theYangtze River Delta (YRD), using CO as a tracer. The YRD region might make a significant contribution to Chinese totalsowing to its rapid economic growth. Weekly flask measurements for ten HFCs (HFC-23, HFC-32, HFC-125, HFC-134a,HFC-143a, HFC-152a, HFC-227ea, HFC-236fa, HFC-245fa and HFC-365mfc) were conducted at Lin’an RegionalBackground Station in the YRD over the period 2012–16, and the HFC emissions were 2.4±1.4 Gg yr−1 for HFC-23, 2.8±1.2 Gg yr−1 for HFC-32, 2.2±1.2 Gg yr−1 for HFC-125, 4.8±4.8 Gg yr−1 for HFC-134a, 0.9±0.6 Gg yr−1 for HFC-152a, 0.3±0.3 Gg yr for HFC-227ea and 0.3±0.2 Gg yr for HFC-245fa. The YRD total HFC emissions reached 53 Tg CO -e yr ,−1 −1
2−1
contributing 34% of the national total. The per capita HFC CO -equivalent emissions rate was 240 Tg yr , while the values2−1
of per unit area emissions and per million GDP emissions reached 150 Mg km−2 yr−1 and 3500 kg yr−1 (million CNYGDP)−1, which were much higher than national or global levels.
Key words: hydrofluorocarbons, emissions, Yangtze River Delta, tracer ratio method
Citation: Pu, J. J., H. H. Xu, B. Yao, Y. Yu, Y. J. Jiang, Q. L. Ma, and L. Q. Chen, 2020: Estimate of hydrofluorocarbonemissions for 2012–16 in the Yangtze River Delta, China. Adv. Atmos. Sci., 37(6), 576−585, https://doi.org/10.1007/s00376-020-9242-3.
Article Highlights:
• Emissions of seven HFCs from 2012 to 2016 were estimated in the YRD region of China using the tracer ratio method.• HFC-23 emissions contributed to approximately two thirds of total CO-equivalent HFC emissions in the YRD.• The total HFC CO-equivalent emissions of the YRD contributed around one third of the national total.• The emissions intensity of HFCs in the YRD was higher than both national and global levels, in terms of per capita/unitarea/unit GDP measurement.
1. Introduction
Hydrofluorocarbons (HFCs), since containing no ozone-depleting chlorine or bromine, have been widely used inChina as substitutes for ozone-depleting substances (ODSs),the production and use of which are being phased out underthe Montreal Protocol. However, HFCs are also long-livedpotent greenhouse gases with global warming potentials(GWPs) as high as ozone-depleting chlorofluorocarbons
(CFCs) and halons (IPCC, 2005). Consequently, HFCs areregulated under both the 1997 Kyoto Protocol and the 2016Kigali Amendment to the Montreal Protocol (WMO, 2018).According to the Advanced Global Atmospheric Gases Exper-iment (AGAGE) network, the global surface mean mixingratios of HFCs in the atmosphere increased from 2012 to2016 by average rates of 1.6 parts per trillion (ppt) yr−1 forHFC-32 (CH2F2), 2.1 ppt yr−1 for HFC-125 (CHF2CF3), 5.6ppt yr−1 for HFC-134a (CH2FCF3), and 1.5 ppt yr−1 forHFC-143a (CH3CF3), which were larger than the meanincreases respectively reported for 2008–12 (WMO, 2018).As emission sources of HFCs are mainly from industrial sec-
tors, such as foam blowing, household/commercial refrigera-tion, fire extinguishing, etc. (Fang et al., 2018), theincreased mixing ratios of HFCs in the atmosphere can beattributed to anthropogenic emissions (Forster et al., 2007).Therefore, many recent studies have focused on estimatinganthropogenic HFC emissions.
Three methods are widely used to estimate the emis-sions of halocarbons including HFCs. The bottom-upmethod is based on the data of production and consumptionfrom various sectors, as well as empirical emission factors(IPCC, 2005). China’s halocarbon emission inventorieshave been reported by using this approach, e.g., China’s his-torical emissions of ODSs until 2014 (Fang et al., 2018),HFC emissions in China for 2005–13 (Fang et al., 2016),China’s halocarbon emissions for 1995–2004 (Wan et al.,2009), and HFC-410A emissions from the room air-condition-ing sector in China for 2006–17 (Liu et al., 2019). The top-down method combines atmospheric measurements andinverse models to simulate the potential sources to the meas-urement sites and geographic distribution of emission intensit-ies. This approach has been used in estimating the HCFCand HFC emissions in East Asia for the year 2008 (Stohl etal., 2010), CFC-11 emissions from eastern Asia for2008–17 (Rigby et al., 2019), and HFC and HCFC emis-sions from China for 2011–17 (Fang et al., 2019; Yao et al.,2019). The third method is the tracer ratio method, which isbased on the ratios of measured halocarbons to selectedtracers with known emissions, such as CO or HCFC-22. Ithas been used to infer halocarbon emissions in the PearlRiver Delta (PRD) (Shao et al., 2011; Wu et al., 2014),HFC and PFC emissions from the North China Plain (Yaoet al., 2012), and anthropogenic halocarbon emissions fromChina (Fang et al., 2012a).
The Yangtze River Delta (YRD) is a fast-growingregion in China with rapid urbanization and industrializa-tion. The region accounted for 16.1% of China’s populationand 23.5% of its Gross Domestic Product (GDP) from 2012to 2016 (National Bureau of Statistics of China, 2013a,2014a, 2015a, 2016a, 2017a). Rapid economic growth hasbeen partly driven by the expanding manufacturing sector,including the fluorine chemical industry, production of elec-tronics, air conditioners, refrigerators and automobiles,which would result in a large amount of HFC emissions. Pre-vious studies have reported that HFC emissions from Chinagrew rapidly since 2005 due to the phase-out of ODSs, andChina has become a major producer and consumer of HFCsaround the world (Zhang and Wang, 2014; Fang et al.,2016). Mixing ratios of HFCs have been reported in China,as well as in a few specific regions in China, including theYRD (Barletta et al., 2006; Fang et al., 2012b; Zhang et al.,2017). However, studies on China’s HFC emissions or theiremission sources have mainly been conducted in the PRD(Wu et al., 2014), Yellow River Delta (Zheng et al., 2019),North China Plain (Yao et al., 2012), and the entire country(Yao et al., 2012, 2019), while few studies have been conduc-ted in the YRD, an area that might contribute significantlyto China’s total HFC emissions (Li et al., 2014). In this
study, weekly flask measurements for 10 HFCs (HFC-23,HFC-32, HFC-125, HFC-134a, HFC-143a, HFC-152a,HFC-227ea, HFC-236fa, HFC-245fa and HFC-365mfc)were performed at Lin’an Regional Background (LAN) sta-tion in the YRD over the period 2012–16. The correlationbetween HFC and CO enhanced mixing ratios was ana-lyzed and HFC emissions in the YRD were further inferredby the tracer ratio method. The results were compared withthose derived by both the inverse modeling method (FLEX-PART-model-based Bayesian inverse modeling) and bot-tom-up method. Finally, the contribution of HFCs in termsof CO2-equivalent emissions from the YRD to the nationaltotal was evaluated to inform understanding of the regionalsignificance.
2. Methods
2.1. Sampling site
The sampling site was at LAN station [(30.30°N,119.73°E), 138.6MSL, as shown in Fig. 1], which is loc-ated in the south of the YRD region and is about 60 km tothe west of Hangzhou and about 195 km to the southwest ofShanghai. The station is well vegetated, surrounded by hillylands, forest and farmland. The prevailing wind directionsare northeasterly and southwesterly (seen in Fig. A1 inAppendix), with distinct meteorological characteristics of sub-tropical monsoon climate. According to previous studies,LAN station can represent the background circumstanceswell in the YRD region (Yan et al., 2012; Feng et al., 2015;Deng et al., 2018).
The areas that might contribute significant emissions toLAN station were identified by backward trajectory calcula-tions using the Lagrangian particle dispersion model FLEX-PART (V9.01; Stohl et al., 2005). The model was driven byECMWF (European Centre for Medium range Weather Fore-casts) Operational Analysis Data, with a global resolution of1° × 1° and regional resolution of 0.2° × 0.2° over easternChina. Ten-day air mass backward trajectories were calcu-lated at the sampling time. The derived source receptor rela-tionships (SRRs) (Seibert and Frank, 2004) demonstratedthe sensitivity of the mixing ratio observations at LAN toemissions on the grid. The total SRR calculated for HFC pol-lution events at LAN station from 2012 to 2016 revealedthat the potential source area with significant influence wasconcentrated in four provinces of the YRD (Anhui, Jiangsu,Shanghai and Zhejiang).
2.2. Experimental method
The sampling time was 1400–1430 LST, when the atmo-sphere was well mixed, every Wednesday, over the period2012–16. The ambient air was drawn from the top of a 50-m-high tower and pressurized into two 3-L canisters thatwere connected in series. The air samples were shipped tothe Greenhouse Gases Laboratory of the MeteorologicalObservation Center of the China Meteorological Administra-tion (MOC/CMA) in Beijing, where the mixing ratios of the
JUNE 2020 PU ET AL. 577
10 HFCs (HFC-23, HFC-32, HFC-125, HFC-134a, HFC-143a, HFC-152a, HFC-227ea, HFC-236fa, HFC-245fa andHFC-365mfc) were measured by the Medusa GC-MS tech-nique developed by AGAGE. The relative measurement preci-sions were typically < 3% for HFC-365mfc and < 1% forother HFCs. The system was calibrated by standards tracedto AGAGE reference standards and the HFC mixing ratioswere reported on the primary calibration scales developed atthe Scripps Institution of Oceanography. More detailedinformation on the sampling, instruments and quality con-trol was provided in previous studies (Zhang et al., 2017;Yao et al., 2019).
CO was observed in-situ by a cavity ring-down spectro-scopy (CRDS) analyzer (G2401, Picarro Inc., Califonia,USA). The air sample was collected from the same inlet asthe HFC samples, and delivered to the analyzer by a mem-brane pump. After being filtered, the air samples were driedto a dew point of approximately −60°C. The precision ofCO measured with this technique is < 2 parts per billion(ppb). The system was calibrated by standard gases thatwere traceable to WMO/GAW primary standards every 6 h.The observing method was described in detail in Fang et al.(2013). The 5-min average CO concentration closest to theHFC sampling time was chosen, and the time intervalbetween the corresponding samples of the two observationsshould be no more than 1 h.
2.3. Data analysis
The mixing ratios of HFCs were distinguished as“baseline level” and “pollution level” by sequentially apply-ing the “robust extraction of baseline signal” filter (REBS;Ruckstuhl et al., 2012) and a background wind sectormethod. Firstly, the REBS technique was applied to filterthe observation data iteratively so as to fit a local regres-
sion curve, and the outliers outside the 1σ range around thecurrent baseline were excluded iteratively until all the datawere within the ± 1σ range of the baseline, which could beflagged as “background values”. Secondly, the pollution val-ues were identified by a meteorological data filter, when theairflow came from polluted wind sectors. The backgroundand polluted wind sectors were defined by local pollutionsources and the characteristics of other tracers such as CO(Zhou et al., 2003, 2004). The filtered results can be seen inFig. A2. Finally, the mixing ratio enhancements of HFCswere determined by the absolute value of the polluted mix-ing ratios minus the background mixing ratios. Consideringthe lack of background values at LAN, where anthropo-genic emissions render significant influence, the back-ground mixing ratios of HFCs in this study were employedvia the measurements at Shangri-la (XGL) station[(28°01′N, 99°26′E), 3580.0 MSL], with similar latitude andlocated far away from human habitat. The air was sampledat XGL with the same method and analyzed with the sameinstrument type in the lab at MOC/CMA (Zhang et al.,2017; Yao et al., 2019). The background mixing ratio atXGL observed on the same date as that at LAN was chosenfirst, and if it was missing, the monthly average at XGL wasused instead. In-situ CO concentrations were filtered by theREBS filter method (Ruckstuhl et al., 2012).
2.4. Emissions estimation
This study adopted the tracer ratio method, which hasbeen widely used in estimating halocarbon emissions. COwas chosen as a tracer since its anthropogenic emissionscould be better known than HCFC-22. Many previous stud-ies have focused on CO emissions (Ohara et al., 2007;Zhang et al., 2009; Li et al., 2017; Zheng et al., 2018a,2018b). The CO emissions of the YRD (including Shang-
Fig. 1. Location of sampling site and land coverage around the station. The images are derived from GlobCoverproducts provided by ESA (http://due.esrin.esa.int/page_globcover.php) and GlobeLand30 (http://www.globallandcover.com/).
578 ESTIMATE OF HFC EMISSIONS FOR 2012-2016 IN YRD VOLUME 37
hai, Zhejiang, Jiangsu and Anhui provinces) were derivedfrom the CO anthropogenic emissions inventory of MEIC(Multi-resolution Emissions Inventory for China) based onthe years 2010 and 2016 (Li et al., 2017), with values of22.4 and 19.6 Tg yr−1, respectively. The interannual trend ofCO emissions in the YRD over the period 2012–15 wasdetermined according to a −2% yr−1 decrease in totalChinese CO emissions (Zheng et al., 2018a, 2018b) and theannual growth rate of smoke and dust emissions from theYRD (National Bureau of Statistics of China, 2013a, 2014a,2015a, 2016a, 2017a), resulting in annual CO emissions of23.1, 24.5, 35.9 and 30.6 Tg yr−1 from 2012 to 2015. Thus,the average CO emissions rate of the YRD was about 26.7Tg yr−1 over the period 2012–16. The uncertainty of CO emis-sions was assumed to be 35%, as reported in previous stud-ies (Zhang et al., 2009; Li et al., 2017).
The correlations of mixing ratio enhancements betweenspecific HFCs and CO were analyzed in order to assess theapplicability of the tracer ratio method to estimate HFC emis-sions, because a reliable tracer should have significant correla-tion with most other compounds (Wang et al., 2014). Theemissions of the target HFC, Ex (Gg yr−1), can be calcu-lated by its mixing ratio enhancement (ΔCx) and the mixingratio enhancement of CO (ΔCCO) as follows:
Ex = ECO∆Cx
∆CCO
Mx
MCO, (1)
where Ex and ECO represent the total emissions of targetHFC and that of CO, respectively. Mx and MCO are themolecular weight of the target HFC and CO, respectively.The uncertainty of the emissions estimate was calculated byerror propagation, as below:
σEx = Ex
√(σb
b
)2+
(σEco
ECO
)2
, (2)
where b is the mixing ratio enhancement slope; and σb andσEco are the uncertainties of b and ECO, respectively. Finally,the HFC CO2-equivalent emissions were calculated usingthe emissions of each HFC multiplied by their 100-yrGWPs (Forster et al., 2007), to evaluate the contribution ofthe greenhouse effect of HFC emissions in the YRD to thatof China.
3. Results and discussion
3.1. HFC mixing ratios
The mixing ratios of HFCs at LAN from 4 January2012 to 28 December 2016 are illustrated in Table 1 (exceptfor the observation of HFC-365mfc, which started from 6August 2014), and five-year time series for HFC mixingratios are presented in Fig. A2. The background mixingratios of both HFC-23 and HFC-32 accounted for less than5%, while the background values of HFC-125, HFC-134a,HFC-152a and HFC-245fa took percentages of 10%–20%.Therefore, the background mixing ratios of all 10 HFCs atXGL were instead considered. The relative errors betweenthe background mixing ratios of HFCs at LAN and at XGLwere 3.8% (HFC-23), 23.0% (HFC-32), 3.9% (HFC-125),5.2% (HFC-134a), 6.0% (HFC-143a), 31.8% (HFC-152a),0.0% (HFC-227ea), 7.1% (HFC-236fa), 10.3% (HFC-245fa) and 10.6% (HFC-365mfc), which could be mainlyexplained by the asynchronous sampling time of the back-ground samples at these two stations. Also, they were much
Table 1. Mixing ratios of HFCs measured at LAN and XGL during 2012–16.
CompoundObserving period(YYYY.MM.DD)
LAN XGL
GWP100(Forster etal., 2007)
Numberof air
samples
Percentageof
background
Mixing ratioenhancement
(ppt)
Numberof air
samples
Percentageof
background
Backgroundmixing
ratio(ppt)
HFC-23 2012.01.04–2016.12.28
230 3.9% 12.3 176 90.9% 27.8 14800
HFC-32 2012.01.04–2016.12.28
233 2.6% 19.0 184 75.0% 10.6 675
HFC-125 2012.01.04–2016.12.28
223 12.1% 10.4 179 95.5% 17.3 3500
HFC-134a 2012.01.04–2016.12.28
180 16.7% 32.4 177 84.7% 81.1 1430
HFC-143a 2012.01.04–2016.12.28
227 44.1% 5.3 187 96.3% 16.7 4470
HFC-152a 2012.01.04–2016.12.28
227 17.2% 7.2 158 80.4% 7.1 124
HFC-227ea 2012.01.04–2016.12.28
219 21.5% 0.95 161 94.4% 1.1 3220
HFC-236fa 2012.01.04–2016.12.28
232 41.8% 1.2 181 90.6% 0.13 9810
HFC-245fa 2012.01.04–2016.12.28
235 17.4% 0.79 188 74.5% 2.2 1030
HFC-365mfc 2014.08.06–2016.12.28
107 43.0% 0.44 96 79.2% 1.0 794
JUNE 2020 PU ET AL. 579
lower than the relative differences between background mix-ing ratios and pollution mixing ratios of HFCs at LAN,except for HFC-152a, for the mixing ratio of HFC-152a prob-ably has a non-negligible latitudinal gradient (Zhang et al.,2017). Overall, it was feasible to employ the background mix-ing ratios of HFCs at XGL to represent those at LAN to calcu-late the mixing ratio enhancements.
The pollution mixing ratios of HFCs at LAN weremuch higher than the background values observed at XGLover the period 2012–16. The enhancements between mix-ing ratios measured at these two stations were 30%–50%(HFC-23, HFC-134a, HFC-143a, HFC-245fa and HFC-365mfc), 61% (HFC-125), 87% (HFC-227ea), 102% (HFC-152a), 179% (HFC-32) and 931% (HFC-236fa).
3.2. Interspecies correlations of HFCs and CO
The interspecies correlations of enhanced mixing ratiosof the 10 HFCs versus CO are shown in Table 2 and Fig. 2.HFC-23, HFC-32, HFC-125, HFC-152a and HFC-245fapresented significant correlations with the tracer CO (p<0.001), showing Pearson correlation coefficients larger
than 0.31. HFC-134a and HFC-227ea also displayed signific-ant but slightly worse correlations (p <0.025), with the correla-tion coefficients between 0.22 and 0.23. The enhanced mix-ing ratios of HFC-143a, HFC-236fa and HFC-365mfc didnot significantly correlate with those of CO, which might bepartly explained by less polluted samples compared to otherHFCs (Table 2), and China’s emissions of these three HFCswere relatively small among all HFCs in previous studies(Kim et al., 2010; Yao et al., 2019). Therefore, the emis-sions of HFC-143a, HFC-236fa and HFC-365mfc are not dis-cussed in this paper.
3.3. HFC emissions of the YRD
As listed in Table 3, the estimated total emissions ofHFCs in the YRD from 2012 to 2016 were 2.4±1.4 Gg yr−1
for HFC-23, 2.8±1.2 Gg yr−1 for HFC-32, 2.2±1.2 Gg yr−1 forHFC-125, 4.8±4.8 Gg yr−1 for HFC-134a, 0.9±0.6 Gg yr−1
for HFC-152a, 0.3±0.3 Gg yr−1 for HFC-227ea and 0.3±0.2Gg yr−1 for HFC-245fa, respectively. As shown in Fig. 3,among these seven HFCs, HFC-134a, HFC-32, HFC-23 andHFC-125 were the four main HFCs in the YRD, with propor-
Table 2. Pearson correlation coefficient (R) and regression slope (S) of mixing ratio enhancements between HFCs and CO, with 95%confidence bounds, over the period 2012–16.
*Correlation is significant at the 0.001 level (one-tailed).**Correlation is significant at the 0.025 level (one-tailed).
Fig. 2. Correlation coefficient matrix between observed CO and HFC mixing ratio enhancements (a), and regressionplots of mixing ratio enhancement of HFC-32 and CO as an example (b).
580 ESTIMATE OF HFC EMISSIONS FOR 2012-2016 IN YRD VOLUME 37
tions of 35%, 21%, 18% and 16%, respectively, while thetotal emissions of the other three HFCs shared less than11%.
In terms of CO2-equivalent emissions, HFC-23 contrib-uted about two thirds to the total CO2-equivalent emissionsdue to its high GWP (GWP100=14800) among all 10 of theHFCs in this study. The contribution of HFC-125 or HFC-134a to total CO2-equivalent HFC emissions exceeded 10%,and HFC-32 emissions contributed 3.6%, while the otherthree HFCs in total contributed less than 3%. Thus, themajor HFC compounds in the YRD were HFC-134a, HFC-23, HFC-125 and HFC-32, with both largest mass emis-sions and CO2-equivalent emissions, and HFC-23 was theprimary HFC considering CO2-equivalent emissions. Thetotal CO2-equivalent emissions of HFCs reached 53 Gg yr−1
in the YRD, accounting for 2.3% of the CO2 emissionswithout landuse, land-use change and forestry in this region(CCGGWP, 2019).
HFC emissions in this study were also compared with res-
ults reported by previous studies using the bottom-upmethod, as listed in Table 3. The HFC emissions of thewhole of China are listed because studies of the YRD are lim-ited. HFC-23 and HFC-134a emissions in this study andthose using the bottom-up method (CCGGWP, 2019)differed relatively little, at 4.2% and 14.5%, respectively.HFC-23 is mainly emitted as a byproduct of HCFC-22 produc-tion (Miller et al., 2010). There are nine fluorine chemistryplants producing HCFC-22 in the YRD, of which three arelocated in Jiangsu Province (contributing 18% of HFC-23emissions) and six in Zhejiang Province (contributing 82%of HFC-23 emissions). HFC-134a is mainly used as a substi-tute for CFC-12 in the automobile air-conditioning sector(Hu et al., 2010). Over the period 2012–16, the HFC-134aemissions in the YRD derived from the tracer ratio methodcomprised 18.6% of those in China by the inverse model-ing method, which was consistent with the percentage(approximately 20%) of vehicle numbers in the YRD of thewhole country (National Bureau of Statistics of China,
Table 3. Emissions (Gg yr−1) of each HFC from the YRD estimated by the CO tracer ratio method from 2012 to 2016 and comparisonwith previous studies.
Compound
Emissions byCO tracer ratio Emissions by bottom-up method
a Data from CCGGWP(2019); b Data from Fang et al. (2016); c Data from National Development and Reform Commission (2016); d Datafrom MEE (2019); e Data from Yao et al. (2019); f Here, only the consumption of HFC-410A in the room air-conditioning sector wasconsidered.
Fig. 3. HFC emission proportions in the YRD over the period 2012–16: (a) mass emissions; (b) CO2-equivalentemissions.
JUNE 2020 PU ET AL. 581
2013a, 2014a, 2015a, 2016a, 2017a). There were understand-able differences in HFC-125 and HFC-32 emissionsbetween this study and those using the bottom-up method(CCGGWP, 2019) because only their consumption asmixed-blend HFC-410A from the room air-conditioning sec-tor was considered by the bottom-up method. Besides theirprimary usage, HFC-125 and HFC-32 are also used as R-32or other mixed blends, such as R-404a and R-507a (Li et al.,2011). The ratios of HFC-410A emissions (sum of HFC-32emissions and HFC-125 emissions) by the bottom-upmethod (CCGGWP, 2019) to the sum of HFC-32 and HFC-125 emissions by the tracer ratio method or top-downmethod were all around 0.5, both in the YRD and at thenational scale, indicating that half of HFC-32 and HFC-125might be used as HFC-410A in the room air-conditioning sec-tor in China.
It should be noted that up-to-date HFC emissions inChina have been reported by a few different studies in thepast two years (MEE, 2018; CCGGWP, 2019; Yao et al.,2019). However, there were significantly large differences(as large as 2 to 90 times, depending on specific HFC spe-cies) among the different studies, which could hardly beexplained by their different time scales. Further studies areneeded to reduce these discrepancies.
3.4. The YRD’s HFC emissions contribution to China
The proportion of HFC emissions in the YRD tonational totals reflects the regional significance. Here, theemissions using the top-down method for the same period(Yao et al., 2019) and HFC-23 emissions in 2015 byCCGGWP (2019) were chosen to represent national levels.Therefore, the HFC emissions in the YRD counted for 46%(HFC-23), 38% (HFC-32), 23% (HFC-125), 19% (HFC-134a), 18% (HFC-152a), 36% (HFC-227ea) and 27%(HFC-245fa) of national totals. The total CO2-equivalentemissions of these seven HFCs in the YRD contributed 34%of the total HFC emissions in China. In comparison with pre-vious studies that were carried out in other regions of China,the HFC-134a in the PRD accounted for only about 8% ofnational total emissions in 2010 (Wu et al., 2014), and theper capita HFC-134a emissions rate was 12.5 g yr−1, whichis much lower than that in the YRD at 18.7 g yr−1. There-fore, the YRD constitutes a significant emissions source ofHFCs in China.
The CO2-equivalent emission intensities of HFCs areillustrated in Fig. 4. Here, global total CO2-equivalent emis-sions were based on emissions derived from observations atremote AGAGE stations (Rigby et al., 2014; Engel et al.,2018), and the global population and GDP were derivedfrom the International Statistical Yearbook (National Bur-eau of Statistics of China, 2013b, 2014b, 2015b, 2016b,2017b). The national population and GDP data were fromthe China Statistical Yearbook (National Bureau of Statist-ics of China, 2013a, 2014a, 2015a, 2016a, 2017a). Com-pared with either the national or global emissions intensity,the YRD displayed as a higher HFC emitter. The per capitaHFC CO2-equivalent emissions intensity of the YRD was
nearly twice the national or global levels, at 240 kg per cap-ita per year. In terms of emissions per unit area, the emis-sions intensity of the YRD was about 24 times the globalvalue and 8 times the national value, amounting to morethan 150 Mg km−2 yr−1. The emissions rate per million GDPin Chinese Yuan (CNY) was 3500 kg yr−1, twice the globalvalue. In conclusion, the emissions intensity of HFCs in theYRD was notably high, whether in terms of per capita orper unit area or per unit GDP. It should be noted that HFC-23 emissions in the YRD contributed around two thirds tototal HFC emissions in the YRD, or more than 1/5 to thenational HFC emissions, in terms of CO2-equivalent.Hence, if HFC-23 emissions were totally eliminated, the emis-sions intensity of the YRD would be lower than nationaland global levels, and thus HFC-23 is the key HFC specieswhen considering the mitigation potential of HFCs in theYRD, or even in China as a whole.
4. Conclusions
Based on co-located atmospheric measurements of 10HFCs and CO at LAN in the YRD from 2012 to 2016, signi-ficant correlations were found between the enhanced mix-ing ratio of CO and those of seven HFCs, which were HFC-23, HFC-32, HFC-125, HFC-134a, HFC-152a, HFC-227eaand HFC-245fa. The emissions of these HFCs were estim-ated by the tracer ratio method. Among these seven HFCs,HFC-134a, HFC-23, HFC-32 and HFC-125 contributedmore than 89% of the total emissions, while in terms ofCO2-equivalent emissions, HFC-23 contributed approxim-ately two thirds of all HFCs.
HFC-23 and HFC-134a emissions in this study wereestimated to be quite close to those using the bottom-upmethod. However, there were large discrepancies among dif-ferent studies in terms of national-scale estimation.
Fig. 4. Comparison of total HFC CO2-equivalent emissionintensities of the YRD, China and global levels from 2012 to2016. National CO2-equivalent emissions of HFC-23 werederived from the bottom-up method (CCGGWP, 2019), andother HFC emissions were from the inverse modeling method(Yao et al., 2019). Global total CO2-equivalent emissions werebased on emissions derived from observations at remoteAGAGE stations (Rigby et al., 2014; Engel et al., 2018).
582 ESTIMATE OF HFC EMISSIONS FOR 2012-2016 IN YRD VOLUME 37
The total HFC CO2-equivalent emissions of the YRD con-tributed 34% of the national total, and the HFC emissionsintensity of the YRD was much larger than the national orglobal level in terms of per capita, or per unit area, or perunit GDP. Therefore, the YRD region is a significant sourcearea for HFC emissions in China, indicating the consider-able mitigation potential that could be achieved by regulat-ing HFC-23 in the YRD region.
Acknowledgements. This study was supported by theNational Natural Science Foundation of China (Grant Nos.41575114 and 41730103), the Zhejiang Provincial Natural Sci-ence Foundation (Grant No. LY19D050002) and the Meteorolo-gical Science and Technology Program of Zhejiang Province(Grant No. 2019ZD12). We thank the station personnel who havesupported canister sampling at XGL. We also thank the AGAGE net-work for its technical assistance and the Scripps Institution of Ocean-ography for help with the technique transfer, processing softwareand calibration standards.
APPENDIX
TIME SERIES of HFC MIXING RATIOS at LAN
Figure A2 shows the time series of the HFC mixingratios observed at LAN from 2012 to 2016. The progress-ive increase of eight HFC (HFC-23, HFC-32, HFC-125,HFC-134a, HFC-143a, HFC-227ea, HFC-245fa, and HFC-
365mfc) mixing ratios at LAN can be seen, while the annualaverage mixing ratios of HFC-152a and HFC-236fa fluctu-ated without rapid increase at LAN from 2012 to 2016. Com-pared to the annual mean growth rates of HFCs observed atSDZ station in the North China Plain from 2010 to 2011 (Yao,et al, 2012), the values at LAN were much higher for HFC-23, HFC-32, HFC-125, and HFC-134a, but not HFC-152a.
Fig. A1. Wind rose at LAN station from January 2012 toDecember 2016 based on hourly data.
Fig. A2. Time series of HFC mixing ratios at LAN station from January 2012 to December 2016.
JUNE 2020 PU ET AL. 583
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