Increasing synoptic scale variability in atmospheric CO2 at Hateruma Island

Increasing synoptic scale variability in atmospheric CO2 at Hateruma Island associated with increasing East Asian emissions Y. Tohjima, H. Mukai, S. Hashimoto, and P. K. Patra Atmospheric Environment Division, National Institute for Environmental Studies, Tsukuba, Japan Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan Research Institute for Global Change, JAMSTEC, Yokohama, Japan Received: 9 July 2009 – Accepted: 15 July 2009 – Published: 24 July 2009 Correspondence to: Y. Tohjima (tohjima@nies.go.jp) Published by Copernicus Publications on behalf of the European Geosciences Union.


Introduction
Increase in carbon dioxide (CO 2 ) emission from fossil fuel consumption, cement manufacturing, and decomposition of biomass and soil organic matter associated with landuse changes has contributed to the observed rise in atmospheric CO 2 since the industrial revolution.Although on average, more than half of the anthropogenic CO 2 has been taken up by the land biosphere and the ocean, the recent growth rate of atmospheric CO 2 shows a gradual increasing trend mainly due to the continuous increase in fossil fuel consumption (e.g.Keeling et al., 1995;Patra et al., 2005).Although there are international efforts to reduce the greenhouse gas emissions, the global CO 2 emission from fossil fuel consumption and cement manufacturing derived from the Carbon Dioxide Information Analysis Center (CDIAC) database (Marland et al., 2007) shows an unprecedented accelerated growth during the period of 2002-2005.This rapid Introduction

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Full Screen / Esc Printer-friendly Version Interactive Discussion emission growth has been attributed to the accelerating emissions from the developing countries (Raupach et al., 2007), especially China (Gregg et al., 2008).Increasing fossil fuel CO 2 emissions elevate not only the overall global atmospheric burden but also enhance the local atmospheric concentrations relative to the surrounding regions.Thus, a greater emission intensity will produce larger concentration gradient in the downwind region, resulting in a greater synoptic scale variation (SSV) in the CO 2 concentration when synoptic winds change directions.For example, the Chinese CO 2 emission data from the CDIAC database indicate a rapid increase from 0.9 Pg C in 2000 to 1.5 Pg C in 2005, which could affect the SSVs in the East Asian regions.Since the amplitude of SSVs will likely change as a function of the source-receptor distance and the source strength, a SSV ratio of two chemical tracers (such as CO 2 and CH 4 employed in this study) with a similar emission pattern and long lifetime (∼month-year) would conserve the ratio of the source strengths robustly.
The National Institute for Environmental Studies (NIES) has been carrying out in-situ measurements of atmospheric greenhouse gases, including CO 2 and methane (CH 4 ), at Hateruma Island (HAT, 24.05 • N, 123.80 • E), which is located in the East Asian continental margin.The observations at HAT often show pollution events influenced by the continental emissions during the period from the late fall to early spring each year (Tohjima et al., 2000(Tohjima et al., , 2002;;Yokouchi et al., 2006).Recently, analyses of the SSVs have been found to be useful for validating regional fluxes with the help of a chemical transport model (Patra et al., 2009).In this paper, we examine the temporal changes in atmospheric CO 2 SSVs observed at HAT during 1996-2007 and investigate its relationship with the continental fossil CO 2 emissions.The CO 2 SSVs are usually associated with similar SSVs in CH 4 observed at HAT.Therefore, the ratio of CO 2 and CH 4 SSVs is used to construct a conservative tracer for tracking emission changes over the source regions.Introduction

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Data and methods
We use daily averages of the atmospheric CO 2 and CH 4 concentrations observed at HAT.The CO 2 concentrations were continuously measured by a nondispersive infrared analyzer (NDIR) (Mukai et al., 2001) and the CH 4 concentrations were semicontinuously measured by a gas chromatography equipped with an FID (Tohjima et al., 2002).To characterize the air mass transport to HAT, we calculate kinematic 3-day backward trajectories with arrival time of 0600 UTC (1500 JST) and starting altitude of 500 m a.s.l. by using the METEX (METeorological data EXplorer, http://db.cger.nies.go.jp/metex/) program developed by Zeng et al. (2003).
The observed CO 2 and CH 4 variations include not only SSVs but also long-term trends, regular and irregular seasonal variations.Thus, we first obtain smooth-curve fits to the data following the methods of Thoning et al. (1989) with a cut-off frequency of 4.6 cylces yr −1 , roughly corresponding to a 40-day running average.Then we subtract the smooth-curve fits from the original time series to extract the SSV components, which are denoted by the ∆ notation as ∆CO 2 and ∆CH 4 (similar to that used in Patra et al., 2008).Figure 1 depicts the time series of ∆CO 2 and ∆CH 4 in 2000 as a typical example.It should be noted that these time series show noticeably similar variations each other during the periods from January to April and from November to December.Annual standard deviations of ∆CO 2 and ∆CH 4 (defined as σ CO 2 and σ CH 4 ) are calculated using the data from January to April and from November to December.The data for the period May to October are not used in this study.We also investigate the ratio of σ CO 2 to σ CH 4 .Note that the daily data are applied to these analyses only when both CO 2 and CH 4 data exist.
We extend the analysis of the observed SSVs by simulating the daily averages of CO 2 and CH 4 at HAT with a chemistry-transport model (ACTM) possessing a horizontal resolution of T42 spectral truncation (∼2.8 • ×2.8 • ) and 67 sigma-pressure vertical layers.The transport model is driven by an atmospheric general circulation model (AGCM).The capability of the ACTM to simulation CO 2 and CH 4 has been investi-Introduction

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Full Screen / Esc Printer-friendly Version Interactive Discussion gated elsewhere (Patra et al., 2008(Patra et al., , 2009)).We use the CH 4 emission scenario (E2 scenario) developed in Patra et al. (2009) that optimally fits the interhemispheric gradient and seasonal cycles at most sites around the globe to within about 10 ppb on an average.For the CO 2 simulation, annually balanced terrestrial ecosystem flux (Randerson et al., 1997), oceanic exchange (Takahashi et al., 2008) and fossil fuel emission (Olivier and Berdowski, 2001) are used in simultaneously.While the monthly-mean terrestrial and oceanic fluxes are repeated every year, the annual-mean fossil flux is increased/decreased year-to-year as dictated by the CDIAC trends database for individual countries (Marland et al., 2007).

Results
The backward trajectories of the air masses arriving at HAT in 2000 during the 6-month period (January-April and November-December) are depicted in Fig. 2.During this period, observations at HAT are dominantly influenced by the air masses transported from the East Asian continental regions.On the other hand, the maritime air masses over the Pacific Ocean are dominantly transported to the site during the period from May to October (trajectories not shown).Such clear transport patterns are caused by the East Asian winter monsoon, and are climatologically characteristic of this region.
Because the November-April period is biologically dormant, limiting our analysis to this period has an advantage of reduced, if not negligible, influence from interannual variations in the land biosphere-atmosphere CO 2 exchange.A more detailed investigation of the backward trajectories shows that the observation at HAT is affected by the emissions from the provinces around Beijing (21%), along the east coast of China around Shanghai (17%), Korea (12%), and southern part of Japan (12%).The leading edge of the CO 2 SSV peak is produced mostly when the air mass is directly transported from the source regions, while the trailing edge is associated with the air mass that travels longer over the ocean, circling clockwise around the site.Similar conditions characterize the atmospheric CH 4 SSV peaks throughout the year since CH 4 has Introduction

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Full Figure 4 shows a time variation in the σ CO 2 /σ CH 4 ratio as a robust estimation of relative change in emissions.For instance, slower or faster transport from the source region to the measurement site will decrease or increase the SSV peak magnitudes, respectively.By normalizing σ CO 2 with respect to σ CH 4 such transport effect due to climate variations would be eliminated.However, disproportional changes in the emission ratio of CO 2 and CH 4 would still show up, likely contributing to the differences in the SSV increase for CH 4 and CO 2 in 1998 and 2003, or the appearance of interannual variations in the σ CO 2 /σ CH 4 ratio time series (given the fact that the emission distribution of the two species are not exactly the same).The interannual variability in the ratio is substantially reduced in comparison with σ CO 2 , and the ratio clearly shows a steadily increasing trend.For comparison, annual time series of national carbon emissions from fossil fuel combustion and cement production for China, Japan, and Korea taken from the CDIAC database (1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005) and the US Department of Energy Energy Information Administration (EIA, http://www.eia.doe.gov)database (1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006) are also plotted in Fig. 4. Note that the carbon emissions from cement production in the CDIAC dataset are added to the EIA dataset and that the emissions from Japan and Korea shown in Fig. 4 are multiplied by a factor of 5.The national emissions from CDIAC and EIA agree with each other to within ∼7% for China, ∼5% for Japan, and ∼15% for Korea.There is a good agreement between the temporal changes in the σ CO 2 /σ  1.Most of the correlations are statistically significant.As for the σ CO 2 /σ CH 4 ratio, the emission from China for 1996-2005 based on both the CDIAC and EIA data accounts for the highest portion of the temporal variation.However, when the emission for 2006 is included in the EIA data, correlation coefficients between the σ CO 2 /σ CH 4 ratio and the emission from China is slightly reduced because of the sudden decrease in the σ CO 2 /σ CH 4 ratio and the continued increase in the emission in 2006.On the other hand, although the temporal changes in the σ CO 2 values also show the highest correlation with the emission from China, the correlation coefficient is much lower than those for the σ in the national emission ratio (CO 2 /CH 4 ) for China against the σ CO 2 /σ CH 4 ratio is almost constant (∼1) during 1996-2005, while those for Japan and Korea show a gradual decrease (Fig. 5).These results strongly suggest that the SSVs at HAT are affected predominantly by the emissions from China.

Discussion
The years of 1997/1998 and 2002/2003 correspond to strong and moderate El Nino periods, respectively.El Nino events alter wind and radiation (outgoing long-wave readiation (OLR), for example) patterns (Fig. 6), causing anomalous transport and anomalous enhancement of CO 2 and CH 4 concentrations in the source region that could explain the enhanced variability in CO 2 and CH 4 at HAT observed in 1998 and 2003.Indeed, a relatively good qualitative agreement between the ACTM simulated and observed variations in σ CH 4 at HAT (Fig. 3) is indicative of the significant role the interannual transport variation plays in causing the observed interannual synoptic-scale variation, since nearly constant CH 4 emissions are used in the model, as well as the neglect of the interannual variation in OH (Patra et al., 2009).The σ CO 2 /σ CH 4 ratio reduces this transport effect, as noted earlier.We also contend that, within the confines of our study, any change in the σ CO 2 /σ CH 4 ratio is mostly reflective of a change in the fossil fuel CO 2 emission.Although interannual climate variations in such parameters as land temperature and precipitation, or in biomass burning can lead to disproportionate release/uptake of CO 2 and CH 4 due to differences in the emission factors associated with different land surfaces (e.g., wetland area, agricultural land), ecosystem types (e.g., grassland, savannah, tree), and processes involved (Andreae and Merlet, 2001), we will argue below that these have minimal effects on our results.Past El Nino events have certainly influenced the global sources of CH 4 and CO 2 in various ways.For example, unusually large boreal forest fires in eastern Russia from May to October in 1998and 2002/2003(Kasischke et al., 2005) would have contributed to the enhancement of σ CO 2 and σ CH 4 , but since these events occurred outside of the 6-Introduction

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Full month period under study, the impact of the biomass burning on our study result regarding the σ CO 2 /σ CH 4 ratio is minimal.Similarly, the CH 4 emissions from seasonal sources including wetlands and rice fields in East Asia during the analysis period (November-April) are much smaller than the emissions from the year-round non-seasonal sources including livestock, energy use (coal and natural gas) and landfills.For example, CH 4 emission from Chinese rice fields occurs from April to November, with maximum emission observed in August and more than 70% of the total CH 4 is emitted between June and August (Yan et al., 2003).In addition, the growth rate of the global atmospheric CH 4 burden showed a rapid decreasing trend after 1980, reaching ±5 ppb/yr during 1996-2005 (with the exception of 1998) (Simpson et al., 2006), unlike the rapidly increasing CO 2 from fossil fuel sources.A forward model simulation shows that a nearly constant global CH 4 emission during 1995-2006 is able to reproduce the observed atmospheric CH 4 change with a fixed OH distribution (Patra et al., 2009), supporting the recent stable CH 4 source strength.Anthropogenic CH 4 emission estimates from REAS 1.11 (Regional Emission inventory in ASia) also show that the variability in the estimated yearly anthropogenic CH 4 emission from China is less than ±3%.Furthermore, there is little contribution of the photosynthetic uptake to the CO 2 emission from East Asian continent during the yearly 6-month period under study; heterotrophic respiration is also relatively small during the colder 6-month period compared to the rest of the year (Ito, 2008).It is our contention that the above discussion lend sufficient support to our assumption that the observed σ CO 2 /σ CH 4 ratio for the seasonal period of November to April at HAT is predominantly reflective of the changes in fossil CO 2 emissions in East Asia.
To investigate the influence of the regional CO 2 emission variation to the SSVs at HAT, we categorize the origins of the air masses arriving at HAT into 4 regions (China (CH), Japan and Korea (JK), the subtropics (ST), and the Pacific Ocean (PO)) by using the 3-day backward trajectories.We designate the trajectory as CH, JK, and ST when the backward pathway first across the corresponding regional boundaries.The remaining trajectories are designated as PO.In this study the regional boundaries for CH and Introduction

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Full JK are the borders of the corresponding countries with resolution of 1 • ×1 • degree, and for ST the border of Taiwan and latitude of 20 • N. The results of the categorization of the backward trajectories for 2000 are also illustrated by different colors in Fig. 2. The percentages of the trajectories occurring in these categorized origins are about 38%, 24%, 9%, and 29% for CH, JK, ST, and PO, respectively.
Temporal variation in σ CO 2 associated with each of the geographical categories is plotted in Fig. 7, together with that derived from all ∆CO 2 .The changes observed in σ CO 2 for CH and PO show an increasing trend that is similar to the overall trend.The large variability in σ CO 2 for ST is attributed to occasional transport of highly polluted air.On the other hand, the σ CO 2 time series for JK shows nearly no trend during the entire 12-year period.These results are consistent with the trend of the recent fossil CO 2 emission from China, Japan, and Korea, suggesting that the air masses originated from JK region do not significantly contribute to the increase in the SSVs in CO 2 at HAT.The increasing trend in PO σ CO 2 is likely due to the transport of maritime air mass contaminated by continental air from China.
The footprint of the backward trajectories reaching HAT effectively covers the CO 2 emission centers in China, including the provinces around Beijing and along the east coast of China (Gregg et al., 2008).This may be the reason why the σ CO 2 /σ CH 4 ratio at HAT appears to closely track the pattern of the CO 2 emission trend from China during the period from 1996 to 2005, as indicated in the recently revised version of the CDIAC data used in this study (Marland et al., 2007).In the previous version of the CDIAC data, the emission from China decreased by about 20% during 1996-2000, which was mainly based on the official Chinese statistics reporting substantial reduction in fuel consumption, coal consumption in particular, during the aforementioned period.Several researchers questioned the official statistics based on the investigations of various energy statistics and the satellite observations of NO x over China (Akimoto et al., 2006;Zhang et al., 2007).The gradual increase during 1996-2002 and the rapid increase thereafter in the σ CO 2 /σ CH 4 ratio at HAT support the recently revised Chinese emission reflected in the CDIAC data.Introduction

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The values of the σ CO 2 /σ CH 4 ratio at HAT in 2006 and 2007 are considerably lower than and similar to the ratio observed in 2005, respectively.These temporal changes seem to suggest that the increasing rate of fossil CO 2 from China slowed down.However, plotting the values of the σ CO 2 /σ CH 4 ratio, excluding those associated with air masses originating from JK and ST, as shown in Fig. 4, we find that the σ CO 2 /σ CH 4 ratio for 2007 is higher than that for 2005 although the dip in 2006 is still present.We believe that the selected σ CO 2 /σ CH 4 ratio values better reflect the emissions from China than the unselected ratio values.In addition, since σ CO 2 shows the highest value in 2007 (Fig. 3), it likely that the increasing trend of the fossil CO 2 emission from China continued through 2007 although the sharp dip in the σ CO 2 /σ CH 4 ratio in 2006 still difficult to explain at this time.
Our simple study presented in this paper has shown that the synoptic scale variations in CO 2 and CH 4 observed at HAT can be used to obtain a better estimate of changes in emission from East Asia, especially China.This is important because there is still more than 15% uncertainty associated with the present estimate of the fossil CO 2 emission from China (Gregg et al., 2008).Recently, Stohl et al. (2009) have developed a new inversion method based on a Lagrangian particle dispersion model to estimate regional and global emissions and applied to in-situ measurements of halocarbons from several globally distributed sites.They have found that the emission from China is well constrained by the measurements at HAT.In a similar vein, such inversion method could be applied to our CO 2 data to obtain quantitative fossil CO 2 emission estimation for China during the Asian winter monsoon seasons.
in σ CO 2 and σ CH 4 are shown in Fig.3.There are large interannual variations in both σ timeseries; especially the simultaneous abrupt enhancements in 1998 and 2003 are noteworthy.However, if we exclude the anomalously high σ CO 2 values in 1998 and 2003, the temporal change shows an apparent secular increase over the whole period, that is, a gradual increase during 1996-2002 and a sharp rise during 2002-2007, resembling the growth rate of estimated annual-total fossil CO 2 emission from China (see Fig.4).On the other hand, the temporal changes in σ CH 4 do not show a clear increasing or decreasing trend, even after the anomalous σ CH 4 in 1998 and 2003 are removed.
CO 2 /σ CH 4 ratio.However, if the anomalous values of 1998 and 2003 are removed, the correlation between the σ CO 2 values and the emission from China increases to 0.92 even if the σ CO 2 value in 2006 is included.Furthermore, the national emission ratio of CO 2 to CH 4 for China, based on the November-April monthly fluxes used in the model simulation, is almost identical to, but those for Japan and Korea are more than double, the σ CO 2 /σ CH 4 ratio at HAT.Moreover, the relative change
carbon emission from China: both temporal changes show a gradual increase during1996-2002 and a rapid increase during 2002-2005, especiallyin 2004.While the EIA dataset for China still shows growing emissions in 2006, the observed σ CO 2 /σ CH 4 ratio shows a considerable decrease in 2006.The time series of σ CO 2 and σ CH 4 and the σ CO 2 /σ CH 4 ratio based on the simulated CO 2 and CH 4 are also depicted in Figs. 3 and 4, respectively, as open symbols with broken lines.The temporal changes in σ CO 2 and σ CH 4 produced by the model simulation also show anomalies in 1998 and 2003, although the amplitudes of the both CO 2 and CH 4 variations are smaller in 2003 in comparison with the observation.The temporal changes in the σ CO 2 /σ CH 4 ratio show a better correspondence between the model simulation and the observation than those for σ CO 2 and σ CH 4 .This result suggests the effectiveness of the normalization of σ CO 2 with respect to σ CH 4 to reduce the transport effect.Squared Pearson correlation coefficients (r 2 ) of the observed σ CO 2 /σ CH 4 ratio and the σ CO 2 values with the reported fossil carbon emissions from China, Japan and Korea are summarized in Table

Table 1 .
Summary of squared correlation coefficients (r 2 ) of σ CO 2 /σ CH 4 and σ CO 2 with the national carbon emissions.