Implication for Fossil Fuel CO2 Inputs

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Observations of Atmospheric Δ14CO2 at the Global and Regional Background Sites in China: Implication for Fossil Fuel CO2 Inputs Zhenchuan Niu,†,‡ Weijian Zhou,*,†,‡,§ Peng Cheng,†,‡ Shugang Wu,†,‡ Xuefeng Lu,†,‡ Xiaohu Xiong,†,‡ Hua Du,†,‡ and Yunchong Fu†,‡ †

State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an, China Shaanxi Provincial Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi’an AMS Center, Xi’an, China § Beijing Normal University, Beijing, China ‡

S Supporting Information *

ABSTRACT: Six months to more than one year of atmospheric Δ14CO2 were measured in 2014−2015 at one global background site in Waliguan (WLG) and four regional background sites at Shangdianzi (SDZ), Lin’an (LAN), Longfengshan (LFS) and Luhuitou (LHT), China. The objectives of the study are to document the Δ14CO2 levels at each site and to trace the variations in fossil fuel CO2 (CO2ff) inputs at regional background sites. Δ14CO2 at WLG varied from 7.1 ± 2.9‰ to 32.0 ± 3.2‰ (average 17.1 ± 6.8‰) in 2015, with high values generally in autumn/summer and low values in winter/spring. During the same period, Δ14CO2 values at the regional background sites were found to be significantly (p < 0.05) lower than those at WLG, indicating different levels of CO2ff inputs at those sites. CO2ff concentrations at LAN (12.7 ± 9.6 ppm) and SDZ (11.5 ± 8.2 ppm) were significantly (p < 0.05) higher than those at LHT (4.6 ± 4.3 ppm) in 2015. There were no significant (p > 0.05) seasonal differences in CO2ff concentrations for the regional sites. Regional sources contributed in part to the CO2ff inputs at LAN and SDZ, while local sources dominated the trend observed at LHT. These data provide a preliminary understanding of atmospheric Δ14CO2 and CO2ff inputs for a range of Chinese background sites.

of nuclear weapons tests, atmospheric Δ14CO2 decreased rapidly between 1963 and 1990, mainly driven by exchanges between the atmosphere, and biosphere and oceans. From 1990 onward, atmospheric Δ14CO2 has decreased slowly mainly due to the CO2ff emissions.3,5 The recent decrease of Δ14CO2 resulted principally from the CO2ff emissions, and 1 ppm of CO2ff emitted to the atmospheric CO2 level of 380 ppm will result in a decrease of ∼2.8‰ for Δ14C.9 Thus, the measurement of Δ14CO2 in the atmosphere can provide a quantitative record of atmospheric CO2ff concentration, which is important for the understanding of the increase of atmospheric CO2 concentration, and for the formulation of CO2ff reduction strategies to mitigate this increase. With the rapid economic growth in recent decades, several economic regions have been established in China, and atmospheric CO2 concentrations at some regional background sites were reported to be influenced by fossil fuel emissions in adjacent economic regions.10−12 So, what are the levels of atmospheric CO2ff inputs at those regional background sites in

INTRODUCTION Radiocarbon (14C) has a radioactive half-life of 5730 years,1 and it is naturally produced in the atmosphere by the cosmic-ray neutron interactions with nitrogen nuclei: 14N(n, p)14C. Once produced, 14C is rapidly oxidized to 14CO2 and is rapidly distributed around the globe. The levels of 14C in CO2 are reported as Δ14C, that is, the per mil (‰) deviation from the absolute radiocarbon reference standard corrected for fractionation and decay.2 ⎤ ⎡ (14C /12C) Δ14 C = ⎢ 14 12 SN − 1⎥ × 1000‰ ⎦ ⎣ ( C / C)ABS 14



(1) 12

In this equation, ( C/ C)SN is the C/ C ratio of the sample normalized to a conventional δ13C value of −25‰, and (14C/12C)ABS is the absolute radiocarbon reference standard. The level of Δ14CO2 in the atmosphere has been disturbed by the ongoing input of fossil fuel CO2 (CO2ff) at least since 1890, and by a series of atmospheric nuclear weapons tests in the 1950−60s. To study the disturbance, atmospheric Δ14CO2 has been measured at some background sites.3−8 The long-term measurements at these sites indicate that atmospheric Δ14CO2 values were depressed to about −25‰ at the beginning of 1950 due to CO2ff emissions, and subsequently increased drastically due to the addition of 14C produced by aboveground nuclear weapons tests in the 1950−60s. After the cease © 2016 American Chemical Society

Received: Revised: Accepted: Published: 12122

June 6, 2016 October 20, 2016 October 25, 2016 October 25, 2016 DOI: 10.1021/acs.est.6b02814 Environ. Sci. Technol. 2016, 50, 12122−12128


Environmental Science & Technology

Figure 1. Locations of the four regional background sites at Longfengshan (LFS), Shangdianzi (SDZ), Lin’an (LAN) and Luhuitou (LHT), and the global background site at Waliguan (WLG). Green circle: sampling sites; red star: capital; black cross: cities.

China? To answer this question it is first necessary to ascertain background atmospheric Δ14CO2 levels across China. Currently the available data are limited to some recent measurements of Δ14C in plant material and atmospheric Δ14CO2 in several cities.13−16 This sparse background Δ14CO2 data set12 hinders our broader understanding of atmospheric CO2ff values in China. In addition,, background Δ14CO2 values are also important for carbonaceous aerosol apportionment studies using the 14C method.17−20 Thus, six months to more than one year of atmospheric Δ14CO2 measurements were carried out at one global background site and four regional background sites in China from 2014−2015. The objectives of the work include (1) to clarify the levels and temporal variations in atmospheric Δ14CO2 at global and regional background sites; (2) to trace the variations in CO2ff inputs at regional background sites; (3) to determine the influences of local and regional emissions on these variations.

atmospheric background information on the Beijing-TianjinHebei Economic Region.10,11 Lin’an (LAN) regional background station (30.30° N, 119.73° E, 139 m a.s.l.) is located on the top of a small hill about 6 km northeast of Lin’an county, Zhejiang Province, East China. This site is about 40 km from the center of Hangzhou, capital of Zhejiang Province, and 190 km from the center of Shanghai, the largest economic center in China (Figure 1). This mountainous area is covered by woodlands and rice paddies, with a subtropical monsoon climate. It represents the atmospheric background information on Yangtze River Delta Economic Region.10,11 Longfengshan (LFS) regional background station (44.73° N, 127.60° E, 331 m a.s.l.) is located on the top of a hill about 40 km southeast of Wuchang county, 140 km the southeast of Harbin, capital of Heilongjiang Province, Northeast China (Figure 1). The area has a temperate continental monsoon climate, covered by woodlands and rice paddies. There is a reservoir with an area of about 20 km2 on the northeast side of this station and small villages within several kilometers of it. The station represents the atmospheric background information on the Northeast Old Industrial Bases.10,11 Luhuitou (LHT) (18.22° N, 109.48° E, 10 m a.s.l.) is a coastal station located at the southwest tip of the Luhuitou peninsula in Sanya, Hainan Province, South China (Figure 1). This station is on the southernmost perimeter of Hainan Island, about 200 km from the capital city of Haikou, more than 600 km southwest of the Pearl River Delta Economic Region. This area has a tropical oceanic monsoon climate, with luxuriant tropical vegetation. Sample Collection. The air samplings were carried out from September 2014 to December 2015 at SDZ and LAN, from September 2014 to February 2015 at LFS, and from January 2015 to December 2015 at LHT and WLG. The air samplings at each site were generally arranged at about 10:00 AM (local time) on the 10th and 25th of each month, and sometimes the samplings were postponed or advanced about

MATERIALS AND METHODS Site Description. Waliguan (WLG) Global Atmosphere Watch (GAW) station (36.28° N, 100.9° E, 3816 m a.s.l.) is located in the northeast part of Qinghai-Tibet Plateau in Qinghai Province, western China (Figure 1). This site is about 100 km southwest of Xining, capital of Qinghai Province, far from industrial and populated centers. There are no inhabitants within 10 km of this station. This region has a continental plateau climate, covered by arid and semiarid desert meadow. This station provides background atmospheric data for the Eurasian continent.21 Shangdianzi (SDZ) regional background station (40.65° N, 117.12° E, 287 m a.s.l.) is situated on a mountainside about 100 km northeast of Beijing, North China (Figure 1). This mountainous area has a semihumid continental monsoon climate, covered by woodlands and crops. A small village is located to the south (about 0.8 km) of this site, and a railway runs from the southwest to northwest direction (about 0.6 km). The observation at this site was used to delegate the 12123

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Environmental Science & Technology

An aliquot of standard air with Δ14C value of 6.7 ± 2.3‰ obtained from the Chinese Academy of Meteorological Sciences was periodically (about two months) used to assess the uncertainty for chemical processing, with the same treatment processing as the bag air samples, and an average uncertainty of 2.3‰ was obtained. This value will result in an uncertainty of about 1.3 ppm in the CO2ff calculations. The 14C levels in the air samples were measured using a 3 MV accelerator mass spectrometer (AMS) in Xi’an, China. Each batch contains forty-eight targets, including thirty-eight air samples, six OX-II samples as primary standards, two Chinese sugar carbon (CSC) samples as secondary standards, and two anthracite coal samples as blanks. They were arranged in order into a sample-holding wheel, and then placed into the AMS ion source for 14C measurement. Each sample recorded 300 000− 400 000 14C counts, and online δ13C measurements were used for isotopic fractionation corrections. The precision of a typical 14 C measurement was 3‰.27 The 14C levels in the air samples are expressed as Δ14C values at each site in Table S1. Calculation of CO2ff. To quantify the inputs of CO2ff to atmospheric CO2 at the regional sites, CO2ff concentrations at SDZ, LAN, LHT and LFS were calculated according to the equations below. CO2 in the air sample (CO2a) is thought to be a mixture of background CO2 (CO2bg), CO2ff, and other CO2 (CO2other), and the Δ14C values for CO2a, CO2bg, CO2other, and CO2ff are expressed as Δa, Δbg, Δother, and Δff (−1000‰), respectively. Two following equations were obtained according to the mass balance of CO2 and 14C.28

one or 2 days when rainy or snowy days were encountered. Additionally, to study the CO2ff variations at different times of a day at the regional sites, air samples at SDZ, LFS, LHT and LAN were collected at about 10:00, 18:00, and 22:00 on two continuous days during both the summer and winter. Ambient air was collected in two 10 L aluminum foil sampling bags (Delin Gas Packing Co., Ltd., Dalian, China) at WLG, using pumps for approximately 10 min, whereas 5 L sampling bags were used at the regional sites. Meteorological parameters were recorded during sampling. The bag sampling method has been proven in former studies,16,22 and has little influence on CO2ff calculations.16 Before samples were collected, the bags were flushed out with ambient air three times. The operators held their breath when turning on and off the switch and maintained a distance from the apparatus during the collection. After the collection, the bags were sent to the laboratory immediately. A total of 144 air samples were obtained. The bagged air samples were first measured for CO2 concentration, and then for 14C analysis. CO2 Concentration Measurement. The CO2 concentrations of air samples were measured by a Picarro G2131-I CO2 Isotopic Analyzer (Picarro Inc.). This type of equipment employs a cavity ring-down spectroscopy (CRDS) technology, with high linearity, precision and stability for CO2 measurement. A cavity ring-down spectrometer is made up of a laser, a high finesse optical cavity consisting of two or more mirrors, and a photodetector. The “ring-down” measurement is made by rapidly turning off the laser and measuring the time constant of the light intensity as it exponentially decays.23,24 Briefly, the ambient air in the bag was filtered, dried in an ethanol-liquid nitrogen cold trap (−90 °C), and then introduced into a high-finesse optical cavity. The optical absorbance of the sample, a function of CO2 concentration, was determined by the light dissipation rate in the optical cavity. Each sample was measured for 6 min. Because of the dead volumes when switching to a new sample, only the data in the last 4 min was averaged for a sample. The data of12 CO2_dry and13CO2_dry were summed to get the total CO2 concentration of an air sample. The instrument was calibrated by a standard gas (395.49 ± 0.02 ppm) obtained from the Chinese Academy of Meteorological Sciences. This standard gas is pressurized in a 29.5 L treated aluminum alloy cylinder (Scott-Marrin Inc., California) fitted with high-purity, two-stage gas regulator, and calibrated with cylinders assigned by the WMO/GAW CO2 Central Calibration Laboratory operated by NOAA/ESRL. The precision of CO2 measurements in this study was below 0.1 ppm. Purification, Graphitization, and 14C Measurement. In order to get pure CO2 samples, the air in the bag was first passed through a liquid nitrogen trap (−196 °C) in a vacuum system at a flow rate of about 200 mL min−1 to trap CO2 and water, and then the trapped water was removed with an ethanol-liquid nitrogen trap (−90 °C).8 A zinc−iron method was used for the graphitization of CO2, with zinc particles and iron powder as reductant and catalyst, respectively.25,26 Then the obtained graphite (1.0−1.2 mg) from ambient air samples was pressed into aluminum target holders for 14C measurement. Additionally, after combustion with excess CuO powder, the gases produced from standards and anthracite coal blanks were processed using the same procedure as the ambient air samples. A vacuum system blank (−998.4 ± 0.1‰) was obtained.

CO2a = CO2bg + CO2other + CO2ff


CO2a Δa = CO2bg Δbg + CO2other Δother + CO2ff Δff


From eq 2 and eq 3, CO2ff can be calculated with the following equation: CO2ff =

CO2a (Δbg − Δa ) Δbg − Δff


CO2other (Δother − Δbg ) Δbg − Δff (4)

The second term on the right-hand-side of eq 4 is a small bias (β) from other small sources of 14C mainly from the heterotrophic respiration and nuclear industry. CO2ff bias from the heterotrophic respiration will be underestimated by 0.2−0.3 ppm during the winter and 0.4−0.8 ppm during the summer.9,28,29 CO2ff bias resulted from nuclear power plants (NPP) is more than −0.25 ppm over large regions, and up to several ppm near to nuclear sites.30,31 A small correction (−0.25 ∼ −0.5 ppm) was used for CO2ff calculation at LAN regional site, about 120 km to the west of Qinshan NPP, for the following reasons. 14C is mainly released as 14CH4 from the Pressurized Water Reactors (PWRs) in Qinshan NPP with a low 14CO2 emission factor, and Graven and Gruber (2011) showed that the CO2ff bias around the LAN site was low.30 Additionally, previous study using moss and pine needles around the Qinshan NPP showed that the 14C specific activity decreases with increasing distance from the NPP, and reaches a background value (223.8 Bq/kg C) at a distance of 6.5 km.32 Back-Trajectory Analysis. A Hysplit Trajectory Model33 was used to study the influence of air mass transport on Δ14CO2/CO2ff temporal variations at each sampling site. A Global Data Assimilation System (GDAS, 2006−present) meteorological data set with a spatial resolution of 1° × 1° and temporal resolution of 3 h, was used in the model, with a 12124

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Xining, capital of Qinghai Province, lies to the east of this site, as well as the more developed and densely populated region with relatively strong CO2 emissions from fuel combustion, while the region to the west of this site is sparsely populated with weak CO2 emissions from fuel combustion.38 The calculation of CO2ff concentrations is influenced by the choice of background. The high altitude mountain site is an approximation of the background. Because of the influence of local or regional fossil fuel sources on mountain sites, there is about a 2‰ difference in Δ14CO2 between the free tropospheric background and high-altitude mountain background,28 and this difference might bring out a bias of about 0.8 ppm in CO2ff calculations. Although previous measurements at WLG around 2005 showed that the values of Δ14CO2 at this site were similar to those at Ulaan Uul, Mongolia (UUM, 44.45° N, 111.10° E, 914 m a.s.l.) and Niwot Ridge, Colorado (NWR, 40.05° N, 105.58° W, 3526 m a.s.l.),12 Δ14CO2 data at WLG for this study still require filtering according to wind directions and CO values to remove nonbackground influences. The wind direction of NE−ENE−E in all seasons is regarded as the major nonbackground section of atmospheric CO2 at WLG,10,36 and our data generally did not occur in that direction. Additionally, CO values at this site39 were used to filter obvious nonbackground data. After this filtering, seasonal averages were used as the background for CO2ff calculations at the regional sites. Δ14CO2 Variations at the Regional Background Sites. As shown in Figure 2, Δ14CO2 values vary highly during the sampling periods at the four regional background sites. Δ14CO2 values were in the ranges of −53.0 ± 3.4‰ ∼ 32.6 ± 3.0‰ (average −6.8 ± 21.1‰) at SDZ, −8.3 ± 3.0‰ ∼ 24.1 ± 2.8‰ (average 7.2 ± 11.9‰) at LFS, − 4.6 ± 2.9‰ ∼ 31.8 ± 2.8‰ (average 10.5 ± 10.3‰) at LHT, and −66.1 ± 3.0‰ ∼ 27.4 ± 2.8‰ (average −12.1 ± 24.2‰) at LAN. Previous observations at SDZ in around 2010 also showed high variations (about −48−50‰) in Δ14CO2.12 Additionally, one abnormal value (173.5 ± 3.3‰) was observed on November 26th, 2014 at LAN, about eight times the average background value. It is difficult to deem this single abnormal value to be related to the Qinshan NPP, based on the following several reasons: (1) the 14CO2 emission factor is low for Qinshan NPP,30 because 14C released from PWRs is mainly in the form of 14CH4. (2) 14C specific activity reaches a background level at a distance of 6.5 km to Qinshan NPP.32 (3) That sampling day had a wind direction of NNE and a low wind speed (0.8 m s−1), and LAN is located about 120 km west of the Qinshan NPP. Because of the indefinable reasons for that sample, its abnormal value was removed. A similar abnormal value (100.7 ± 2.2‰) was reported by Turnbull et al.12 for the observation at Tae−Ahn Peninsula, South Korea, and she hypothesized that this data represented an unidentified analytical problem and excluded the data. At SDZ and LHT, the seasonal averages of Δ14CO2 in summer/autumn are not significantly different from those in winter/spring (p > 0.05), while the seasonal average in summer was significantly (p < 0.05) higher than that in winter/spring at LAN. For the LFS site, the seasonal Δ14CO2 average in autumn was significantly (p < 0.05) higher than that in winter, due to the substantial fossil fuel consumption for heating during the severe cold wintertime in Northeast China and the low vertical mixing height in winter.37 The averages at LHT (10.5 ± 10.3‰), SDZ (−5.8 ± 21.2‰) and LAN (−9.1 ± 24.3‰) in 2015 were significantly (p < 0.05) lower than that at WLG. The

total run time of 72 h. The heights of 100 m AGL and 1000 m AGL were chosen as the typical heights of the atmospheric surface layer and the planetary boundary layer (PBL), respectively, and the height of 500 m AGL was chosen to provide more information. The start time (UTC) in this model was 8 h later than the local time. Data Analysis. Variance analysis of Δ14CO2 or CO2ff concentrations were performed by ANOVA/Duncan’s test using a SPSS statistical software (V. 17),34 and values of p < 0.05 were considered to be statistically significant.

RESULTS AND DISCUSSION Δ14CO2 Variations at WLG Global Background Site. Figure 2A shows Δ14CO2 variations at the WLG global

Figure 2. Δ14CO2 variations at WLG (A) global background site, and the regional background sites: SDZ (B), LFS (C), LHT (D), and LAN (E) during the sampling period.

background site in 2015, and two values (−0.3 ± 2.8‰ and −61.5 ± 3.2‰) were removed as obvious nonbackground samples. Δ14CO2 at this site varied from 7.1 ± 2.9‰ to 32.0 ± 3.2‰, with an average of 17.1 ± 6.8‰. Generally, high values were observed in autumn (September−November)/summer (June−August) months and low values were observed in winter (January, February, and December)/spring (March−May) months. These seasonal features have also been observed at other global background sites.3,4,8,35 Back-trajectory analyses indicate that the air masses during the winter and spring sampling periods mainly pass over the northern part of China (Figure S1). Thus, fossil fuel consumption for heating in the northern part of China and even in the range of middle to high latitudes in the Northern Hemisphere36 might be related to the relatively low values in winter and spring. Additionally, the seasonal changes in atmospheric vertical mixing height also contributed to the relatively low values in winter and spring.37 As a summer resort in China, many people travel to Qinghai Province by car, and their fossil fuel emissions could potentially reduce the atmospheric Δ14CO2 values recorded at WLG in the summer. From the wind-rose distribution patterns of Δ14CO2 along 16 directions (Figure S2), it can be seen that high values generally occur along the SW-NNW sector and low values along the NSSE sector. This distribution can be explained as follows: 12125

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SDZ are located in the Yangtze River Delta Economic Region and Beijing-Tianjin-Hebei Economic Region, respectively, and strong CO2 emissions from fuel combustions in these two most developed regions38 in China could result in the high CO2ff concentrations at LAN and SDZ. The megacities and industrial sources in the two regions were also regarded as the main reasons for the high atmospheric CO2 values at LAN and SDZ.10,11 However, the low CO2ff concentrations at LHT might be related to advantageous atmospheric diffusion (with generally high wind speeds of 3.4−7.9 m s−1) for this coastal site, no fossil fuel consumption for heating during winter in Sanya, and a smaller number of heavy industries in this tourist city. Reduced CO2 emissions from fuel combustions in Hainan Island are supported by the study of Wang et al. (2013).38 Temporal CO2ff Variations. No significant (p > 0.05) differences in CO2ff concentrations were found among different seasons at SDZ, LHT, and LAN (Figure S3). Additionally, no significant (p > 0.05) differences in CO2ff concentrations were found according to the time of day (10:00, 18:00, and 22:00) at SDZ, LFS, LHT, and LAN (Figure S4). Evaluation of Local and Regional Emissions on CO2ff Variations. Figure 4 shows CO2ff concentrations along 16 directions at SDZ, LAN, and LHT. This analysis was not carried out for LFS due to the short observation period. It clearly shows that CO2ff at SDZ, LAN, and LHT occurred with wind directions from the NNE−WSW sector, N−WSW sector and N−SW sector, respectively. To further ascertain whether CO2ff inputs at these sites were influenced primarily by local sources (≤∼ 10 km) or by regional sources (>∼ 10 km), CO2ff concentrations were divided according to the method used by Fang et al. (2014) based on long time series observations at these regional background sites.10 They identified the locations and directions of the primary fossil fuel emission sources around these background sites, and defined a local event when wind passed those sources. Additionally, they ascribed CO2 concentrations at low wind speeds (70‰).42 For 2015, the average contributions of CO2ff to the annual ΔCO2 offsets are 34.7 ± 26.4% at LHT, 61.7 ± 25.6% at SDZ, and 56.7 ± 38.0% at LAN. A ΔCO2 offset indicates differences in CO2 concentrations between the regional sites and the WLG site (401.0 ± 3.5 ppm in 2015).43 The annual average CO2ff concentrations at LAN (12.7 ± 9.6 ppm) and SDZ (11.5 ± 8.2 ppm) were significantly (p < 0.05) higher than those at LHT (4.6 ± 4.3 ppm) in 2015. LAN and

Figure 4. CO2ff variations along 16 horizontal wind directions at SDZ, LAN, and LHT. 12126

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(2) Stuiver, M.; Polach, H. A. Discussion: reporting of 14C data. Radiocarbon 1977, 19, 355−363. (3) Currie, K. I.; Brailsford, G.; Nichol, S.; Gomez, A.; Sparks, R.; Lassey, K. R.; Riedel, K. Tropospheric 14CO2 at Wellington, New Zealand: the world’s longest record. Biogeochemistry 2011, 104, 5−22. (4) Graven, H. D.; Guilderson, T. P.; Keeling, R. F. Observations of radiocarbon in CO2 at seven global sampling sites in the Scripps flask network: Analysis of spatial gradients and seasonal cycles. J. Geophys. Res. 2012, 117, D02303. (5) Levin, I.; Kromer, B. The tropospheric 14CO2 level in midlatitudes of the Northern Hemisphere (1959−2003). Radiocarbon 2004, 46, 1261−1272. (6) Levin, I.; Kromer, B.; Hammer, S. Atmospheric Δ14CO2 trend in Western European background air from 2000 to 2012. Tellus, Ser. B 2013, 65, 20092. (7) Rafter, T. A.; Fergusson, G. J. Atom bomb effect-recent increase of carbon-14 content of the atmosphere and biosphere. Science 1957, 126, 566−578. (8) Turnbull, J. C.; Lehman, S. J.; Miller, J. B.; Sparks, R. J.; Southon, J. R.; Tans, P. P. A new high precision 14CO2 time series for North American continental air. J. Geophys. Res. 2007, 112, D11310. (9) Turnbull, J. C.; Miller, J. B.; Lehman, S. J.; Tans, P. P.; Sparks, R. J.; Southon, J. Comparison of 14CO2, CO, and SF6 as tracers for recently added fossil fuel CO2 in the atmosphere and implications for biological CO2 exchange. Geophys. Res. Lett. 2006, 33, L01817. (10) Fang, S. X.; Zhou, L. X.; Tans, P. P.; Ciais, P.; Steinbacher, M.; Xu, L.; Luan, T. In situ measurement of atmospheric CO2 at the four WMO/GAW stations in China. Atmos. Chem. Phys. 2014, 14, 2541− 2554. (11) Liu, L.; Zhou, L.; Zhang, X.; Wen, M.; Zhang, F.; Yao, B.; Fang, S. The characteristics of atmospheric CO2 concentration variation of the four national background stations in China. Sci. China, Ser. D: Earth Sci. 2009, 52, 1857−1863. (12) Turnbull, J. C.; Tans, P. P.; Lehman, S. J.; Baker, D.; Conway, T. J.; Chung, Y. S.; Gregg, J.; Miller, J. B.; Southon, J. R.; Zhou, L.-X. Atmospheric observations of carbon monoxide and fossil fuel CO2 emissions from East Asia. J. Geophys. Res. 2011, 116, D24306. (13) Xi, X.; Ding, X.; Fu, D.; Zhou, L.; Liu, K. Regional Δ14C patterns and fossil fuel derived CO2 distribution in the Beijing area using annual plants. Chin. Sci. Bull. 2011, 56, 1721−1726. (14) Zhou, W.; Wu, S.; Huo, W.; Xiong, X.; Cheng, P.; Lu, X.; Niu, Z. Tracing fossil fuel CO2 using Δ14C in Xi’an City, China. Atmos. Environ. 2014, 94, 538−545. (15) Niu, Z.; Zhou, W.; Zhang, X.; Wang, S.; Zhang, D.; Lu, X.; Cheng, P.; Wu, S.; Xiong, X.; Du, H.; Fu, Y. The spatial distribution of fossil fuel CO2 traced by Δ14C in the leaves of gingko (Ginkgo biloba L.) in Beijing City, China. Environ. Sci. Pollut. Res. 2016, 23, 556−562. (16) Niu, Z.; Zhou, W.; Wu, S.; Cheng, P.; Lu, X.; Xiong, X.; Du, H.; Fu, Y.; Wang, G. Atmospheric fossil fuel CO2 traced by Δ14C in Beijing and Xiamen, China: temporal variations, inland/coastal differences and influencing factors. Environ. Sci. Technol. 2016, 50, 5474−5480. (17) Bernardoni, V.; Calzolai, G.; Chiari, M.; Fedi, M.; Lucarelli, F.; Nava, S.; Piazzalunga, A.; Riccobono, F.; Taccetti, F.; Valli, G.; Vecchi, R. Radiocarbon analysis on organic and elemental carbon in aerosol samples and source apportionment at an urban site in Northern Italy. J. Aerosol Sci. 2013, 56, 88−99. (18) Genberg, J.; Hyder, M.; Stenström, K.; Bergström, R.; Simpson, D.; Fors, E. O.; Jönsson, J. Å.; Swietlicki, E. Source apportionment of carbonaceous aerosol in southern Sweden. Atmos. Chem. Phys. 2011, 11, 11387−11400. (19) Niu, Z.; Wang, S.; Chen, J.; Zhang, F.; Chen, X.; He, C.; Lin, L.; Yin, L.; Xu, L. Source contributions to carbonaceous species in PM2.5 and their uncertainty analysis at typical urban, peri-urban and background sites in southeast China. Environ. Pollut. 2013, 181, 107−114. (20) Szidat, S.; Jenk, T. M.; Synal, H.; Kalberer, M.; Wacker, L.; Hajdas, I.; Kasper-Giebl, A.; Baltensperger, U. Contributions of fossil

divisions indicate that CO2ff concentrations in local events (17.0 ± 8.0 ppm) were significantly (p < 0.05) higher than those from regional events (8.8 ± 8.7 ppm) at LAN, with the occurrence rates of 56.5% for local events and 43.5% for regional events. During the regional events at LAN, CO2ff concentrations for the samples within the NE−E sector (16.2 ± 5.8 ppm) were significantly (p < 0.05) higher than those along the WSW−WNW sector (2.0 ± 1.9 ppm), because air masses for the samples with wind direction from NE−E sector passed through the Yangtze River Delta Economic Region (Figure S5), while air masses for the samples with wind direction from WSW−WNW sector passed through the less developed and populated mountainous region in Zhejiang Province and Fujian Province (Figure S6). At SDZ, CO2ff concentrations associated with local events (16.0 ± 7.6 ppm) were significantly (p < 0.05) higher than those for regional events (7.6 ± 6.8 ppm), with the occurrence rates of 47.8% for local events and 52.2% for regional events. During the regional events at SDZ, low CO2ff values were generally presented when air masses passed through the less developed and populated regions in Neimenggu Province and Northeast China (Figure S7), with relatively low CO2 emissions from fuel combustion.38 CO2ff concentrations at LHT were predominately influenced by local sources in Sanya, and low values were generally observed as the air masses came from the open sea, to the southwest (Figure S8).


S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.6b02814. Additional details, including one table and eight figures (PDF)


Corresponding Author

*Phone: +86-29-62336203; fax: +86-29-62336234; e-mail: [email protected] Notes

The authors declare no competing financial interest.

ACKNOWLEDGMENTS We express our great thanks to the staff at Waliguan and Lin’an stations who have contributed to the sample collections. We also thank Dr. George Burr from the University of Arizona for polishing the English of this paper. This work was jointly supported by the National Natural Science Foundation of China (No 41573136, 41303072); CAS “Light of West China” Program (XAB2015A02); Ministry of Science and Technology of the People’s Republic of China, the MOST special fund for State Key Laboratory of Loess and Quaternary Geology (LQ1301); Chinese Academy of Sciences (ZDBS-SSWDQC001); Youth Innovation Promotion Association CAS (2016360); the Young scholar project of the Institute of Earth Environment, CAS (Y354011480, SKLLQGPY1610); and the Natural Science Foundation of Shaanxi Province, China (2014JQ2-4018). The anonymous reviewers are acknowledged for their valuable comments.


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DOI: 10.1021/acs.est.6b02814 Environ. Sci. Technol. 2016, 50, 12122−12128


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DOI: 10.1021/acs.est.6b02814 Environ. Sci. Technol. 2016, 50, 12122−12128

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