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A21H0248$ Diurnal and Seasonal Attribution of ......-10 0 10 20 30 40 50 CO 2 m) midday-10 0 10 20...

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-10 0 10 20 30 40 50 CO 2 (ppm) midday -10 0 10 20 30 40 50 60 CO 2 (ppm) gasoline natural gas biosphere morning -10 0 10 20 30 40 50 7/1 10/1 1/1 4/1 7/1 10/1 1/1 4/1 7/1 CO 2 (ppm) date 2013 2014 evening 2015 -0.2 0 0.2 0.4 0.6 0.8 fraction in CO 2 xs midday -0.2 0 0.2 0.4 0.6 0.8 1 fraction in CO 2 xs gasoline natural gas biosphere morning -0.2 0 0.2 0.4 0.6 0.8 7/1 10/1 1/1 4/1 7/1 10/1 1/1 4/1 7/1 fraction in CO 2 xs date 2013 2014 evening 2015 -80 -60 -40 -20 0 δ 13 C (‰) -80 -60 -40 -20 0 7/1 10/1 1/1 4/1 7/1 10/1 1/1 4/1 7/1 δ 13 C (‰) date morning midday evening 2013 2014 2015 R 2 > 0.9 Diurnal and Seasonal Attribution of Anthropogenic CO 2 Emissions Over Two Years in the Los Angeles Megacity Sally Newman 1 , Xiaomei Xu 2 , Ying K. Hsu 3 , Arlyn Andrews 4 , and Yuk L. Yung 1 1 California Institute of Technology, Pasadena, CA; 2 University of California, Irvine, CA; 3 California Air Resources Board, Sacramento, CA; 4 NOAA, Boulder, CO IV. Conclusions The rela2ve propor2ons of the different emission sources for CO 2 may not be the same at different 2mes of day. At least during the summer, this is not obviously due to diurnal changes in wind direc2on bringing emissions from different regions. In the megacity of Los Angeles, the rela2ve contribu2on from natural gas combus2on is higher during the summers and lower during the winter at midday and during the evenings, when orbi2ng satellites take measurements, but is higher in winter spring than in summer during mornings. This is probably because of shiEing wind direc2ons seasonally. The biosphere’s contribu2on is higher during the cooler months than during the warmer months for all 2mes of day, as expected for this low midla2tude semiarid region. However, the early mornings always have the highest biospheric contribu2ons of the day. Emissions from gasoline combus2on do not have a clear seasonal cycle for these two years, during midday and evening. To improve this analysis, we must determine the emission ra2o (RCO/CO 2 ff) for different 2mes of day. We must also improve modeling at 2mes other than midday, in order to quan2ta2vely account for transport of emissions. References: Draxler, R.R. and Rolph, G.D. HYSPLIT (HYbrid SinglePar2cle Lagrangian Integrated Trajectory) Model access via NOAA ARL READY Website (hYp://www.arl.noaa.gov/HYSPLIT.php). NOAA Air Resources Laboratory, College Park, MD. Eldering, A.; Boland, S. W.; Bowman, K. W.; Crisp, D.; Duren, R. M.; Fisher, J. B.; Frankenberg, C.; Gunson, M. R.; Menemenlis, D.; Miller, C. E.; Kaki, S., Eos AGU Abstract, A51J04, 2012. Eldering, A., Kaki, S., Crisp, D., and Gunson, M.R., Eos AGU Abstract A21G0134, 2013. Keeling, C. D., Geochim Cosmochim Acta, 13(4), 322–334, 1958. Keeling, C., Geochim Cosmochim Acta, 24, 277–298, 1961. Levin, I., Kromer, B., Schmidt, M. and Sartorius, H., Geophys Res LeY, 30(23), 2194, 2003. Miller, J. B., Lehman, S. J., Montzka, S. A., Sweeney, C., Miller, B. R., Karion, A., Wolak, C., Dlugokencky, E. J., Southon, J., Turnbull, J. C. and Tans, P. P., J. Geophys. Res, 117, 2012. Newman, S., Xu, X., Gurney, K. R., Hsu, Y. K., Li, K. F., Jiang, X., Keeling, R., Feng, S., O'Keefe, D., Patarasuk, R., Wong, K. W., Rao, P., Fischer, M. L., and Y. L. Yung, Y.,, Atmos Chem Phys Discuss, 15(20), 29591–29638, doi:10.5194/acpd15295912015, 2015. Turnbull, J., Miller, J., Lehman, S., Tans, P., Sparks, R. and Southon, J., Geophys Res LeY, 33(1), L01817, 2006. Turnbull, J. C., Karion, A., Fischer, M. L., Faloona, I., Guilderson, T., Lehman, S. J., Miller, B. R., Miller, J. B., Montzka, S., Sherwood, T., Saripalli, S., Sweeney, C. and Tans, P. P., Atmos Chem Phys, 11(2), 705–721, 2011. Vogel, F. R., Hammer, S., Steinhof, A., Kromer, B. and Levin, I., Tellus B, 62(5), 512–520, 2010. Xi, X., Natraj, V., Shia, R.L., Luo, M., Zhang, Q., Newman, S., Sander, S., and Yung, Y., Atmos Meas Tech Discuss, 8(6), 5809–5846, doi:10.5194/amtd858092015.. Contact informa2on: S. Newman: [email protected] Figure 2. Examples of diurnal paYerns (leE column) and Keeling plots for morning, midday, and evening on individual days (right column). Keeling plot intercepts and correla2on coefficients are shown for each correla2on line. Ver2cal lines on the diurnal plots indicate the 2mes chosen between morning and midday and evening. 118°30 118°0 117°30 34°0’N 33°30’N 118°30 118°0 117°0’W 117°30 33°30’N 34°0’N San Gabriel Mountains Santa Monica Mountains San Gabriel Valley Hills Puente Santa Ana Mountains Santa Catalina Island Palos Verdes Peninsula Los Angeles Basin Pasadena 117°0’W I. Introduc2on In order to understand the role of anthropogenic greenhouse gases (GHGs), of which CO 2 is the most abundant, in climate change we must understand their sources. Since ci2es produce >70% of the anthropogenic GHGs, large signals there can be used to study the details of emission paYerns. Trea2es are being signed to regulate emissions, and there must be verifica2on of compliance. The easiest way to get a broad picture of the distribu2on of CO 2 and its changes through 2me is to collect measurements of total column concentra2ons from space. Satelliteborne instruments measure during midday, but is the distribu2on of emissions among the sources the same at all 2mes of day for all 2mes of year? Understanding the diurnal varia2on of the sources is important for comparison with boYomup inventories, modeling, and results from new instruments such as OCO3 (Eldering et al., 2012, 2013) and the Geosta2onary Carbon Process Inves2ga2on (Xi et al., 2014) which will see more of a diurnal cycle. We have shown that CO 2 13 C, and ∆ 14 C can be used to dis2nguish among gasoline combus2on, natural gas combus2on, and biosphere contribu2ons to CO 2 in the atmosphere (Newman et al., 2015) in a topdown approach. Here we present in situ data for different 2mes of day from the megacity of Los Angeles, CA, specifically from the Caltech campus in Pasadena (Figure 1), in order to understand this diurnal varia2on using this method with CO as a proxy for 14 C, for morning, midday, and evening for June 2013 through May 2015. Figure 1. Map showing the loca2on of the Pasadena site in the Los Angeles basin II. Data and Methods The data sets involved in this study include con2nuous measurements of CO 2 and δ 13 C (Picarro Isotopic CO 2 Analyzer) and CO (LGR N 2 O/CO EP Monitor) in Pasadena and background measurements on Mt. Wilson (CO, CO 2 ; flasks). ∆ 14 C composi2ons are determined for flask samples collected on alternate aEernoons at 14:00 PST in Pasadena. We use mul2ple mass balance calcula2ons on monthly averages to dis2nguish among the sources: fossil fuel combus2on (CO 2 ff), including gasoline (CO 2 pet) and natural gas (CO 2 ng), and the biosphere (CO 2 bio). The ∆ 14 C values of the flask samples give the frac2on of CO 2 ff vs CO 2 bio in the total local enhancement over background (CO 2 xs) (Levin et al., 2003). We use the CO 2 ff/CO 2 xs from the flask ∆ 14 C measurements and COxs/CO 2 xs from the con2nuous measurements for 13:0015:00 to determine the emission ra2o, RCO/CO 2 ff, values for each month (Figure 4; e.g., Turnbull et al., 2006, 2011; Vogel et al., 2010; Miller et al., 2012). This assumes that RCOxs/CO 2 ff does not vary diurnally, but only seasonally. The yintercept of correla2ons between δ 13 C and 1000/CO 2 (Figure 2; Keeling plots; Keeling, 1958, 1961) provide the composi2on of the highCO 2 , local enhancement of the CO 2 . The summary of the daily morning, midday, and evening intercepts are shown in Figure 3. Since these can be quite scaYered we filter the data by rejec2ng intercepts from correla2ons with R 2 < 0.90. Monthly averages of the retained intercepts are shown in Figure 5. The stable isotopic composi2on of the carbon in the CO 2 13 C, ‰ rela2ve to the standard VPDB) is then used to dis2nguish between gasoline and natural gas combus2on within CO 2 ff. Figure 3. Top: all of the Keeling plot intercepts determined for Pasadena; morning values for correla2ons for hourly averages during 0:008:00, midday for 9:0016:00, and evening for 17:0023:00. BoYom: Keeling plot intercepts from the top panel that have been filtered by removing all results from correla2ons with R 2 < 0.9. Figure 5. Monthly averages of the Keeling plot intercepts for morning, midday, and evening on individual days. The isotopic signatures of natural gas and petroleum/ biosphere are labeled to the right of the plot. Figure 4. Monthly averages of COxs/CO 2 xs for morning, midday, and evening on individual days (colored dots) and of emission ra2os (RCO/CO 2 ff; +) from ∆ 14 C data from midday flasks. Figure 6. Source alloca2on as frac2on of CO 2 pet, CO 2 ng, and CO 2 bio in CO 2 xs (leE column) and as CO 2 (ppm; right column) contributed to the local atmosphere. III. Results The monthly averages of the Keeling plot intercepts (Figure 5) show significantly different paYerns at different 2mes of day, especially between early mornings and later. The lowest values of δ 13 C are centered on warmer months during midday and evening, whereas they are centered in the fall in the morning. This suggests that gasoline combus2on or the biosphere dominate the signal at different 2mes of day. When these δ 13 C values are combined with values of the frac2on of CO 2 from fossil fuels in CO 2 xs, this dichotomy propagates through to different paYerns for the propor2ons of natural gas and gasoline combus2on of total CO 2 xs at different 2mes of day (Figure 6 leE). Although natural gas is the dominant source of local CO 2 emissions during the summer middays, when the satelliteborne instruments observe, gasoline combus2on is the dominant source during summer mornings and evenings. Winter early morning emissions are mostly from the biosphere, very different from midday, when the biosphere contributes at most ~20%. As expected, the biosphere is a sink for CO 2 during the spring and summer, although this sink is much less intense than elsewhere. The absolute contribu2ons in CO 2 ppm (Figure 6 right) are very similar to the paYerns for the frac2ons for the morning period, but are higher for mornings and evenings than for middays, when the atmosphere is most wellmixed and therefore mixing ra2os are closest to the background values, resul2ng in lower CO 2 xs. The seasonal paYern for the evening absolute contribu2ons is similar for all three sources. We have shown that the paYern of higher fossil fuel emissions observed in Pasadena during summer is due to the annual wind direc2on paYern (Newman et al., 2015). However, the different paYerns for different 2mes of day during the summer cannot be due to the winds, since the wind direc2ons are the same at all 2me of day. A21H0248 -15 -14 -13 -12 -11 -10 -9 -8 δ 13 C (‰) 6-6-13 morning: -11.9 ± 12.7 ppm; R 2 = 0.01 midday: -29.7 ± 5.4 ppm; R 2 = 0.67 evening: -15.0 ± 18.4 ppm; R 2 = 0.02 400 450 500 550 600 -15 -14 -13 -12 -11 -10 -9 -8 6-6-13 CO 2 (ppm) δ 13 C (‰) Diurnal Plots Keeling Plots 400 420 440 460 480 500 -15 -14 -13 -12 -11 -10 -9 0 4 8 12 16 20 24 12-1-13 CO 2 (ppm) δ 13 C (‰) hour 400 450 500 550 -15 -14 -13 -12 -11 -10 -9 8-15-13 CO 2 (ppm) δ 13 C (‰) 400 450 500 550 -15 -14 -13 -12 -11 -10 -9 6-28-13 CO 2 (ppm) δ 13 C (‰) -15 -14 -13 -12 -11 -10 -9 1.7 1.8 1.9 2 2.1 2.2 2.3 2.4 2.5 δ 13 C (‰) 1000/CO2 (ppm -1 ) 12-1-13 morning: -28.8 ± 1.0 ppm; R 2 = 0.98 midday: -18.3 ± 9.0 ppm; R 2 = 0.18 evening: -30.5 ± 1.0 ppm; R 2 = 0.99 -15 -14 -13 -12 -11 -10 -9 δ 13 C (‰) morning: -24.5 ± 2.1 ppm; R 2 = 0.87 midday: -32.4 ± 1.4 ppm; R 2 = 0.94 evening: -39.0 ± 2.3 ppm; R 2 = 0.96 8-15-13 -15 -14 -13 -12 -11 -10 -9 δ 13 C (‰) 6-28-13 morning: -29.1 ± 0.5 ppm; R 2 = 0.994 midday: -31.8 ± 0.5 ppm; R 2 = 0.997 evening: -26.9 ± 0.4 ppm; R 2 = 0.996 Figure 7. Wind back trajectories calculated using HYSPLIT (Draxler and Rolph, 2015) at different 2mes of day showing seasonal, but not significant diurnal, varia2ons in the source regions. The red dots indicate the loca2on of Pasadena. Funded in part by California Air Resources Board Contract 13329, and a grant from the W. M. Keck Ins2tute for Space Science. January 2014 10 m ending in Pasadena at 0400 PST 24hr 0400 PST January 2014 January 2014 10 m ending in Pasadena at 1200 PST 24hr 1200 PST January 2014 10 m ending in Pasadena at 2000 PST 24hr 2000 PST July 2013 10 m ending in Pasadena at 0400 PST 24hr 0400 PST July 2013 10 m ending in Pasadena at 1200 PST 24hr 1200 PST July 2013 10 m ending in Pasadena at 2000 PST 24hr 2000 PST July 2013 March 2014 10 m ending in Pasadena at 0400 PST 24hr 0400 PST March 2014 10 m ending in Pasadena at 1200 PST 24hr 1200 PST March 2014 10 m ending in Pasadena at 2000 PST 24hr 2000 PST March 2014 0 0.005 0.01 0.015 7/1 10/1 1/1 4/1 7/1 10/1 1/1 4/1 7/1 COxs/CO 2 xs date morning midday evening RCOxs/CO2ff 2013 2015 2014 -40 -35 -30 -25 5/1 11/1 5/1 11/1 5/1 δ 13 C (‰) date morning midday evening gasoline combustion/ biosphere natural gas combustion 2015 2013 2014
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Diurnal and Seasonal Attribution of Anthropogenic CO2 Emissions Over Two Years in the Los Angeles Megacity���Sally Newman1, Xiaomei Xu2, Ying K. Hsu3, Arlyn Andrews4, and Yuk L. Yung1

1California Institute of Technology, Pasadena, CA; 2University of California, Irvine, CA; 3California Air Resources Board, Sacramento, CA; 4NOAA, Boulder, CO

IV.  Conclusions  •  The  rela2ve  propor2ons  of  the  different  emission  sources  for  CO2  may  not  be  the  same  at  different  2mes  of  day.  At  least  

during  the  summer,  this  is  not  obviously  due  to  diurnal  changes  in  wind  direc2on  bringing  emissions  from  different  regions.  •  In  the  megacity  of  Los  Angeles,  the  rela2ve  contribu2on  from  natural  gas  combus2on  is  higher  during  the  summers  and  lower  

during  the  winter  at  midday  and  during  the  evenings,  when  orbi2ng  satellites  take  measurements,  but  is  higher  in  winter-­‐spring  than  in  summer  during  mornings.    This  is  probably  because  of  shiEing  wind  direc2ons  seasonally.  

•  The  biosphere’s  contribu2on  is  higher  during  the  cooler  months  than  during  the  warmer  months  for  all  2mes  of  day,  as  expected  for  this  low  mid-­‐la2tude  semi-­‐arid  region.    However,  the  early  mornings  always  have  the  highest  biospheric  contribu2ons  of  the  day.  

•  Emissions  from  gasoline  combus2on  do  not  have  a  clear  seasonal  cycle  for  these  two  years,  during  midday  and  evening.  •  To  improve  this  analysis,  we  must  determine  the  emission  ra2o  (RCO/CO2ff)  for  different  2mes  of  day.    We  must  also  improve  

modeling  at  2mes  other  than  mid-­‐day,  in  order  to  quan2ta2vely  account  for  transport  of  emissions.    

References:  Draxler,  R.R.  and  Rolph,  G.D.  HYSPLIT  (HYbrid  Single-­‐Par2cle  Lagrangian  Integrated  Trajectory)  Model  access  via  NOAA  ARL  READY  Website  (hYp://www.arl.noaa.gov/HYSPLIT.php).  NOAA  Air  Resources  Laboratory,  College  Park,  MD.    Eldering,  A.;  Boland,  S.  W.;  Bowman,  K.  W.;  Crisp,  D.;  Duren,  R.  M.;  Fisher,  J.  B.;  Frankenberg,  C.;  Gunson,  M.  R.;  Menemenlis,  D.;  Miller,  C.  E.;  Kaki,  S.,  Eos  AGU  Abstract,  A51J-­‐04,  2012.  Eldering,  A.,  Kaki,  S.,  Crisp,  D.,  and  Gunson,  M.R.,  Eos  AGU  Abstract  A21G-­‐0134,  2013.  Keeling,  C.  D.,  Geochim  Cosmochim  Acta,  13(4),  322–334,  1958.  Keeling,  C.,  Geochim  Cosmochim  Acta,  24,  277–298,  1961.  Levin,  I.,  Kromer,  B.,  Schmidt,  M.  and  Sartorius,  H.,  Geophys  Res  LeY,  30(23),  2194,  2003.  Miller,  J.  B.,  Lehman,  S.  J.,  Montzka,  S.  A.,  Sweeney,  C.,  Miller,  B.  R.,  Karion,  A.,  Wolak,  C.,  Dlugokencky,  E.  J.,  Southon,  J.,  Turnbull,  J.  C.  and  Tans,  P.  P.,  J.  Geophys.  Res,  117,  2012.  Newman,  S.,  Xu,  X.,  Gurney,  K.  R.,  Hsu,  Y.  K.,  Li,  K.  F.,  Jiang,  X.,  Keeling,  R.,  Feng,  S.,  O'Keefe,  D.,  Patarasuk,  R.,  Wong,  K.  W.,  Rao,  P.,  Fischer,  M.  L.,  and  Y.  L.  Yung,  Y.,,  Atmos  Chem  Phys  Discuss,  15(20),  29591–29638,  doi:10.5194/acpd-­‐15-­‐29591-­‐2015,  2015.  Turnbull,  J.,  Miller,  J.,  Lehman,  S.,  Tans,  P.,  Sparks,  R.  and  Southon,  J.,  Geophys  Res  LeY,  33(1),  L01817,  2006.  Turnbull,  J.  C.,  Karion,  A.,  Fischer,  M.  L.,  Faloona,  I.,  Guilderson,  T.,  Lehman,  S.  J.,  Miller,  B.  R.,  Miller,  J.  B.,  Montzka,  S.,  Sherwood,  T.,  Saripalli,  S.,  Sweeney,  C.  and  Tans,  P.  P.,  Atmos  Chem  Phys,  11(2),  705–721,  2011.  Vogel,  F.  R.,  Hammer,  S.,  Steinhof,  A.,  Kromer,  B.  and  Levin,  I.,  Tellus  B,  62(5),  512–520,  2010.  Xi,  X.,  Natraj,  V.,  Shia,  R.-­‐L.,  Luo,  M.,  Zhang,  Q.,  Newman,  S.,  Sander,  S.,  and  Yung,  Y.,  Atmos  Meas  Tech  Discuss,  8(6),  5809–5846,  doi:10.5194/amtd-­‐8-­‐5809-­‐2015..    

Contact  informa2on:  S.  Newman:  [email protected]    

Figure  2.    Examples  of  diurnal  paYerns  (leE  column)  and  Keeling  plots  for  morning,  midday,  and  evening  on  individual  days  (right  column).    Keeling  plot  intercepts  and  correla2on  coefficients  are  shown  for  each  correla2on  line.    Ver2cal  lines  on  the  diurnal  plots  indicate  the  2mes  chosen  between  morning  and  midday  and  evening.  

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I.    Introduc2on  In  order  to  understand  the  role  of  anthropogenic  greenhouse  gases  (GHGs),  of  which  CO2  is  the  most  abundant,  in  climate  change  we  must  understand  their  sources.    Since  ci2es  produce  >70%  of  the  anthropogenic  GHGs,  large  signals  there  can  be  used  to  study  the  details  of  emission  paYerns.    Trea2es  are  being  signed  to  regulate  emissions,  and  there  must  be  verifica2on  of  compliance.    The  easiest  way  to  get  a  broad  picture  of  the  distribu2on  of  CO2  and  its  changes  through  2me  is  to  collect  measurements  of  total  column  concentra2ons  from  space.    Satellite-­‐borne  instruments  measure  during  midday,  but  is  the  distribu2on  of  emissions  among  the  sources  the  same  at  all  2mes  of  day  for  all  2mes  of  year?  Understanding  the  diurnal  varia2on  of  the  sources  is  important  for  comparison  with  boYom-­‐up  inventories,  modeling,  and  results  from  new  instruments  such  as  OCO-­‐3  (Eldering  et  al.,  2012,  2013)  and  the  Geosta2onary  Carbon  Process  Inves2ga2on  (Xi  et  al.,  2014)  which  will  see  more  of  a  diurnal  cycle.    We  have  shown  that  CO2,  δ13C,  and  ∆14C  can  be  used  to  dis2nguish  among  gasoline  combus2on,  natural  gas  combus2on,  and  biosphere  contribu2ons  to  CO2  in  the  atmosphere  (Newman  et  al.,  2015)  in  a  top-­‐down  approach.    Here  we  present  in  situ  data  for  different  2mes  of  day  from  the  megacity  of  Los  Angeles,  CA,  specifically  from  the  Caltech  campus  in  Pasadena  (Figure  1),  in  order  to  understand  this  diurnal  varia2on  using  this  method  with  CO  as  a  proxy  for  ∆14C,  for  morning,  midday,  and  evening  for  June  2013  through  May  2015.  

Figure  1.    Map  showing  the  loca2on  of  the  Pasadena  site  in  the  Los  Angeles  basin  

II.    Data  and  Methods  •  The  data  sets  involved  in  this  study  include  con2nuous  measurements  of  CO2  and  δ13C  (Picarro  Isotopic  CO2  Analyzer)  and  CO  (LGR  N2O/CO  EP  Monitor)  in  Pasadena  and  

background  measurements  on  Mt.  Wilson  (CO,  CO2;  flasks).    ∆14C  composi2ons  are  determined  for  flask  samples  collected  on  alternate  aEernoons  at  14:00  PST  in  Pasadena.      •  We  use  mul2ple  mass  balance  calcula2ons  on  monthly  averages  to  dis2nguish  among  the  sources:  fossil  fuel  combus2on  (CO2ff),  including  gasoline  (CO2pet)  and  natural  gas  

(CO2ng),  and  the  biosphere  (CO2bio).      •  The  ∆14C  values  of  the  flask  samples  give  the  frac2on  of  CO2ff  vs  CO2bio  in  the  total  local  enhancement  over  background  (CO2xs)  (Levin  et  al.,  2003).  •  We  use  the  CO2ff/CO2xs  from  the  flask  ∆14C  measurements  and  COxs/CO2xs  from  the  con2nuous  measurements  for  13:00-­‐15:00  to  determine  the  emission  ra2o,  RCO/CO2ff,  

values  for  each  month  (Figure  4;  e.g.,  Turnbull  et  al.,  2006,  2011;  Vogel  et  al.,  2010;  Miller  et  al.,  2012).    This  assumes  that  RCOxs/CO2ff  does  not  vary  diurnally,  but  only  seasonally.  

•  The  y-­‐intercept  of  correla2ons  between  δ13C  and  1000/CO2  (Figure  2;  Keeling  plots;  Keeling,  1958,  1961)  provide  the  composi2on  of  the  high-­‐CO2,  local  enhancement  of  the  CO2.    The  summary  of  the  daily  morning,  midday,  and  evening  intercepts  are  shown  in  Figure  3.    Since  these  can  be  quite  scaYered  we  filter  the  data  by  rejec2ng  intercepts  from  correla2ons  with  R2  <  0.90.    Monthly  averages  of  the  retained  intercepts  are  shown  in  Figure  5.    

•  The  stable  isotopic  composi2on  of  the  carbon  in  the  CO2  (δ13C,  ‰  rela2ve  to  the  standard  VPDB)  is  then  used  to  dis2nguish  between  gasoline  and  natural  gas  combus2on  within  CO2ff.  

Figure  3.    Top:  all  of  the  Keeling  plot  intercepts  determined  for  Pasadena;  morning  values  for  correla2ons  for  hourly  averages  during  0:00-­‐8:00,  midday  for  9:00-­‐16:00,  and  evening  for  17:00-­‐23:00.    BoYom:  Keeling  plot  intercepts  from  the  top  panel  that  have  been  filtered  by  removing  all  results  from  correla2ons  with  R2  <  0.9.  

Figure  5.    Monthly  averages  of  the  Keeling  plot  intercepts  for  morning,  midday,  and  evening  on  individual  days.  The  isotopic  signatures  of  natural  gas  and  petroleum/biosphere  are  labeled  to  the  right  of  the  plot.  

Figure  4.    Monthly  averages  of  COxs/CO2xs  for  morning,  midday,  and  evening  on  individual  days  (colored  dots)  and  of  emission  ra2os  (RCO/CO2ff;  +)  from  ∆14C  data  from  midday  flasks.      

Figure  6.    Source  alloca2on  as  frac2on  of  CO2pet,  CO2ng,  and  CO2bio  in  CO2xs  (leE  column)  and  as  CO2  (ppm;  right  column)  contributed  to  the  local  atmosphere.    

III.    Results  •  The  monthly  averages  of  the  Keeling  plot  intercepts  (Figure  5)  show  significantly  different  paYerns  at  different  2mes  of  day,  especially  between  early  mornings  and  later.    

The  lowest  values  of  δ13C  are  centered  on  warmer  months  during  midday  and  evening,  whereas  they  are  centered  in  the  fall  in  the  morning.    This  suggests  that  gasoline  combus2on  or  the  biosphere  dominate  the  signal  at  different  2mes  of  day.      

•  When  these  δ13C  values  are  combined  with  values  of  the  frac2on  of  CO2  from  fossil  fuels  in  CO2xs,  this  dichotomy  propagates  through  to  different  paYerns  for  the  propor2ons  of  natural  gas  and  gasoline  combus2on  of  total  CO2xs  at  different  2mes  of  day  (Figure  6  leE).    Although  natural  gas  is  the  dominant  source  of  local  CO2  emissions  during  the  summer  middays,  when  the  satellite-­‐borne  instruments  observe,  gasoline  combus2on  is  the  dominant  source  during  summer  mornings  and  evenings.    Winter  early  morning  emissions  are  mostly  from  the  biosphere,  very  different  from  midday,  when  the  biosphere  contributes  at  most  ~20%.    As  expected,  the  biosphere  is  a  sink  for  CO2  during  the  spring  and  summer,  although  this  sink  is  much  less  intense  than  elsewhere.    

•  The  absolute  contribu2ons  in  CO2  ppm  (Figure  6  right)  are  very  similar  to  the  paYerns  for  the  frac2ons  for  the  morning  period,  but  are  higher  for  mornings  and  evenings  than  for  middays,  when  the  atmosphere  is  most  well-­‐mixed  and  therefore  mixing  ra2os  are  closest  to  the  background  values,  resul2ng  in  lower  CO2xs.    The  seasonal  paYern  for  the  evening  absolute  contribu2ons  is  similar  for  all  three  sources.      

•  We  have  shown  that  the  paYern  of  higher  fossil  fuel  emissions  observed  in  Pasadena  during  summer  is  due  to  the  annual  wind  direc2on  paYern  (Newman  et  al.,  2015).    However,  the  different  paYerns  for  different  2mes  of  day  during  the  summer  cannot  be  due  to  the  winds,  since  the  wind  direc2ons  are  the  same  at  all  2me  of  day.  

A21H-­‐0248  

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δ13C

(‰)

6-6-13

morning: -11.9 ± 12.7 ppm; R2 = 0.01

midday: -29.7 ± 5.4 ppm; R2 = 0.67

evening: -15.0 ± 18.4 ppm; R2 = 0.02400

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CO

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CO

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δ13C

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1000/CO2 (ppm-1)

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morning: -28.8 ± 1.0 ppm; R2 = 0.98

midday: -18.3 ± 9.0 ppm; R2 = 0.18

evening: -30.5 ± 1.0 ppm; R2 = 0.99

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δ13C

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morning: -24.5 ± 2.1 ppm; R2 = 0.87

midday: -32.4 ± 1.4 ppm; R2 = 0.94

evening: -39.0 ± 2.3 ppm; R2 = 0.96

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δ13C

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6-28-13

morning: -29.1 ± 0.5 ppm; R2 = 0.994

midday: -31.8 ± 0.5 ppm; R2 = 0.997

evening: -26.9 ± 0.4 ppm; R2 = 0.996

Figure  7.    Wind  back  trajectories  calculated  using  HYSPLIT  (Draxler  and  Rolph,  2015)  at  different  2mes  of  day  showing  seasonal,  but  not  significant  diurnal,  varia2ons  in  the  source  regions.    The  red  dots  indicate  the  loca2on  of  Pasadena.  

Funded  in  part  by  California  Air  Resources  Board  Contract  13-­‐329,  and  a  grant  from  the  W.  M.  Keck  Ins2tute  for  Space  Science.    

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0

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7/1 10/1 1/1 4/1 7/1 10/1 1/1 4/1 7/1

COxs

/CO

2xs

date

morning midday evening RCOxs/CO2ff

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δ13C

(‰)

date

morning midday evening

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gasoline combustion/biosphere

natural gascombustion

each data set fit to 2-3° sine curves

2015  2013   2014  

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