Application of SCIAMACHY and MOPITT CO total column measurements to evaluate model results over biomass burning regions and Eastern China

Liu, C.; Beirle, Steffen; Butler, Tim; Liu, J.; Hoor, Peter; Jöckel, Patrick; Vries, Marloes Penning de; Pozzer, Andrea; Frankenberg, Christian; Lawrence, M. G.; Lelieveld, Jos; Platt, U.; Wagner, Thomas

doi:10.5194/acp-11-6083-2011

Cited by 39 publications

(50 citation statements)

References 68 publications

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“…Additionally, the biomass burning emissions of BC and POM in the inventory (2.12 and 18.45 Tg yr −1 , respectively) may be underestimated, as they are lower than what is suggested in the literature (3.1 and 34.7 Tg yr −1 , respectively, Dentener et al, 2006). The underestimations of the biomass burning sources has been noticed for the same simulation also for other emitted compounds (CO, Liu et al, 2011) when compared to satellite observations. The underestimation could possibly produce a bias in the AOD estimates by the model, which results in an underestimation of AOD when compared with MODIS and MISR, as observed e.g.…”

Section: Comparison With Satellite Observationssupporting

confidence: 54%

Distributions and regional budgets of aerosols and their precursors simulated with the EMAC chemistry-climate model

et al. 2012

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Abstract.The new global anthropogenic emission inventory (EDGAR-CIRCE) of gas and aerosol pollutants has been incorporated in the chemistry general circulation model EMAC (ECHAM5/MESSy Atmospheric Chemistry). A relatively high horizontal resolution simulation is performed for the years [2005][2006][2007][2008] to evaluate the capability of the model and the emissions to reproduce observed aerosol concentrations and aerosol optical depth (AOD) values. Model output is compared with observations from different measurement networks (CASTNET, EMEP and EANET) and AODs from remote sensing instruments (MODIS and MISR). A good spatial agreement of the distribution of sulfate and ammonium aerosol is found when compared to observations, while calculated nitrate aerosol concentrations show some discrepancies. The simulated temporal development of the inorganic aerosols is in line with measurements of sulfate and nitrate aerosol, while for ammonium aerosol some deviations from observations occur over the USA, due to the wrong temporal distribution of ammonia gas emissions. The calculated AODs agree well with the satellite observations in most regions, while negative biases are found for the equatorial area and in the dust outflow regions (i.e. Central Atlantic and Northern Indian Ocean), due to an underestimation of biomass burning and aeolian dust emissions, respectively. Aerosols and precursors budgets for five different regions (North America, Europe, East Asia, Central Africa and South America) are calculated. Over East-Asia most of the emitted aerosols (precursors) are also deposited within the region, while in North America and Europe transport plays a larger role. Further, it is shown that a simulation with monthly varying anthropogenic emissions typically improves the temporal correlation by 5-10 % compared to one with constant annual emissions.

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Section: Comparison With Satellite Observationssupporting

confidence: 54%

Distributions and regional budgets of aerosols and their precursors simulated with the EMAC chemistry-climate model

et al. 2012

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“…In recent publications of Liu et al (2011), satellite measurements and model simulations showed that monthly mean of CO vertical column density had a maximum in winter and minimum in summer in the eastern area of China Diurnal variation can be obtained by analysing data on a daily timescale. 24 October 2014 is selected because the data sampled on this clear-sky day cover long daylight hours and are continuous.…”

Section: Variation Of Xco 2 and Xcomentioning

confidence: 99%

Investigating the performance of a greenhouse gas observatory in Hefei, China

et al. 2017

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Abstract. A ground-based high-resolution Fourier transform spectrometer (FTS) station has been established in Hefei, China to remotely measure CO 2 , CO and other greenhouse gases based on near-infrared solar absorption spectra. Total column measurements of atmospheric CO 2 and CO were successfully obtained from July 2014 to April 2016. The spectra collected with an InSb detector in the first year were compared with those collected by an InGaAs detector from July 2015, demonstrating that InGaAs spectra have better signal-to-noise ratios and rms of spectral fitting residuals relative to InSb spectra. Consequently, the measurement precision of the retrieved XCO 2 and XCO for InGaAs spectra is superior to InSb spectra, with about 0.04 and 0.09 % for XCO 2 , and 1.07 and 2.00 % for XCO within clear-sky days respectively. Daily and monthly averages of columnaveraged dry air mole fraction of CO 2 show a clear seasonal cycle, while the daily and monthly averages of XCO displayed no seasonal variation. Also, we analysed the relationship of the anomalies of XCO and XCO 2 , found that the correlations are only observable for individual days, and the data under different prevailing wind conditions during the observations displayed weak correlation. The observations based on the high-resolution FTS were also compared with the temporally coinciding measurements taken with a low-resolution solar FTS instrument, the EM27/SUN. Ratioing the daily averaged XCO 2 of EM27 and FTS gives an overall calibration factor of 0.996 ± 0.001. We also compared ground-based observations from the Tsukuba TCCON station with our observations, the results showing that the variation in phase and seasonal amplitude of XCO 2 are similar to our results, but the variation of XCO in Tsukuba is quite different from our data in Hefei. To further evaluate our retrieved data, we made use of satellite measurements. The direct comparison of our observations with the Greenhouse Gases Observing Satellite (GOSAT) data shows good agreement of daily median XCO 2 , with a bias of −0.52 ppm and standard deviation of 1.63 ppm. The correlation coefficient (R 2 ) is 0.79 for daily median XCO 2 between our FTS and GOSAT observations. Daily median Orbiting Carbon Observatory 2 (OCO-2) data produce a positive bias of 0.81 ppm and standard deviation of 1.73 ppm relative to our ground-based data. Our daily median XCO 2 also show strong correlation with OCO-2 data, with correlation coefficient (R 2 ) of 0.83. Although there were a limited number of data during the observations due to instrument downtime and adverse weather, the results confirm the suitability of the observatory for ground-based long-term measurements of greenhouse gases with high precision and

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“…The oxidation of CO also leads to the formation of carbon dioxide (CO 2 ) and tropospheric ozone (O 3 ) (Crutzen and Gidel, 1983;Fishman and Crutzen, 1978;Burrows et al, 1995). Because of its moderately long lifetime (weeks to months) and inhomogeneous distribution in the troposphere, CO is an ideal tracer for monitoring the air pollution sources and transports (Cicerone, 1988;Logan et al, 1981;Shindell et al, 2006;Lelieveld et al, 2001;Hoor et al, 2005;Edwards et al, 2004Edwards et al, , 2006Pan et al, 1995;Worden et al, 2013a;Liu et al, 2011Liu et al, , 2013.…”

Section: Introductionmentioning

confidence: 99%

Technical Note: Temporal change in averaging kernels as a source of uncertainty in trend estimates of carbon monoxide retrieved from MOPITT

et al. 2013

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Abstract.It has become possible to retrieve the global, longterm trends of trace gases that are important to atmospheric chemistry, climate, and air quality from satellite data records that span more than a decade. However, many of the satellite remote sensing techniques produce measurements that have variable sensitivity to the vertical profiles of atmospheric gases. In the case of constrained retrievals like optimal estimation, this leads to a varying amount of a priori information in the retrieval and is represented by an averaging kernel (AK). In this study, we investigate to what extent the estimation of trends from retrieved data can be biased by temporal changes of averaging kernels used in the retrieval algorithm. In particular, the surface carbon monoxide data retrieved from the Measurements Of Pollution In The Troposphere (MOPITT) instrument from 2001 to 2010 were analyzed. As a practical example based on the MOPITT data, we show that if the true atmospheric mixing ratio is continuously 50 % higher or lower than the a priori state, the temporal change of the averaging kernel at the surface level gives rise to an artificial trend in retrieved surface carbon monoxide, ranging from −10.71 to +13.21 ppbv yr −1 (−5.68 to +8.84 % yr −1 ) depending on location. Therefore, in the case of surface (or near-surface level) CO derived from MOPITT, the AKs trends multiplied by the difference between true and a priori states must be quantified in order to estimate trend biases.

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Application of SCIAMACHY and MOPITT CO total column measurements to evaluate model results over biomass burning regions and Eastern China

Cited by 39 publications

References 68 publications

Distributions and regional budgets of aerosols and their precursors simulated with the EMAC chemistry-climate model

Distributions and regional budgets of aerosols and their precursors simulated with the EMAC chemistry-climate model

Investigating the performance of a greenhouse gas observatory in Hefei, China

Technical Note: Temporal change in averaging kernels as a source of uncertainty in trend estimates of carbon monoxide retrieved from MOPITT

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