scholarly journals Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES)

2009 ◽  
Vol 9 (5) ◽  
pp. 19967-20018 ◽  
Author(s):  
M. Kopacz ◽  
D. J. Jacob ◽  
J. A. Fisher ◽  
J. A. Logan ◽  
L. Zhang ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Transport Model ◽  
Large Fraction ◽  
A Priori ◽  
A Posteriori ◽  
Chemical Transport Model ◽  
In Situ Data ◽  
Global Emission ◽  
Cold Starts

Abstract. We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004–April 2005) global inversion of CO sources at 4°×5° spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM) and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and aircraft (MOZAIC) are used for evaluation of the a posteriori solution. Global intercomparison of the different satellite datasets using GEOS-Chem as a common intercomparison platform shows consistency between the satellite datasets and with the in situ data. The majority of the differences between the datasets can be explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a−1, with an additional 217 Tg a−1 from oxidation of co-emitted VOCs. This is much higher than current bottom-up emission inventories. Consistent with both the satellite and in situ data, a large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. A posteriori emissions also indicate a general underestimation of biomass burning relative to the GFED2 inventory. However, the tropical biomass burning constraints are not consistent across the different datasets. Although the datasets reveal regional inconsistencies over tropical biomass burning regions, we find the global emission estimates to be a balance of information from all three instruments.

scholarly journals Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES)

2010 ◽  
Vol 10 (3) ◽  
pp. 855-876 ◽  
Author(s):  
M. Kopacz ◽  
D. J. Jacob ◽  
J. A. Fisher ◽  
J. A. Logan ◽  
L. Zhang ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Transport Model ◽  
Large Fraction ◽  
A Priori ◽  
A Posteriori ◽  
Chemical Transport Model ◽  
In Situ Data ◽  
Global Consistency ◽  
Priori Information ◽  
Cold Starts

Abstract. We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004–April 2005) global inversion of CO sources at 4°×5° spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM) and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and aircraft (MOZAIC) are used for evaluation of the a posteriori solution. Using GEOS-Chem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a−1. This is much higher than current bottom-up emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A posteriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.

Global Methane Emissions Through an Isotopic Lens

2020 ◽  
Author(s):  
Alice Drinkwater ◽  
Tim Arnold ◽  
Paul Palmer
Keyword(s):  
Transport Model ◽  
Global Climate ◽  
Agricultural Practices ◽  
Isotope Ratios ◽  
Atmospheric Methane ◽  
Source Attribution ◽  
Chemical Transport Model ◽  
Magnitude Distribution ◽  
In Situ Data

<p>Changes in atmospheric methane (CH<sub>4</sub>) are mainly driven by natural, anthropogenic and pyrogenic emissions and oxidation by OH.</p><p>There is no consensus about the underlying explanations about hemispheric-scale changes in atmospheric methane (CH<sub>4</sub>). This is partly due to sparse data that do not exclusively identify individual changes in surface emissions and surface and atmospheric losses of CH<sub>4</sub>. This challenge represents a major scientific weakness in our understanding of this potent greenhouse gas, with implications for meeting global climate policy obligations.  A confounding challenge is that the regional importance of individual emission sources change with time due to, for example, innovations in agricultural practices, climate-sensitive wetlands, and political decisions associated with climate friendlier transitional fuels.  </p><p><br>Here we use bulk isotope ratios δ<sup>13</sup>C and δD of CH<sub>4</sub> that have been previously shown to provide effective constraints on source apportionment: different CH<sub>4</sub> sources have characteristic isotope ratios. One of the key challenges associated with using these data is that region-specific isotope ratios change with time due to varying source prevalance, in addition to source signatures having inherent uncertainties. We use the GEOS-Chem global 3-D chemical transport model to describe the spatial and temporal isotopic behaviour of atmospheric CH<sub>4</sub>. We develop a Maximum A-Posteriori inverse method to simultaneously infer time dependent CH<sub>4</sub> emissions and isotope ratios from in situ data. </p><p>We will report the magnitude, distribution and source attribution of CH<sub>4</sub> emissions from 2004 to 2017, inferred from in situ measurements of total atmospheric CH<sub>4</sub> mole fraction and the corresponding measurements of δ<sup>13</sup>C and δD. We will compare our results with previous studies.</p>

Comparison of TROPOMI/Sentinel-5 Precursor NO2 product with ground-based observations in Helsinki and first societal applications

2020 ◽  
Author(s):  
Iolanda Ialongo ◽  
Henrik Virta ◽  
Henk Eskes ◽  
Jari Hovila ◽  
John Douros
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
A Priori ◽  
Urban Air Quality ◽  
Oil Refinery ◽  
Urban Air ◽  
Chemical Transport Model ◽  
Weekly Cycle ◽  
Oil Refineries

<p>We evaluate the satellite-based TROPOMI (TROPOspheric Monitoring Instrument) NO2 products against ground-based observations in Helsinki (Finland). TROPOMI NO2 total (summed) columns are compared with the measurements performed by the Pandora spectrometer during April–September 2018. The mean relative and absolute bias between the TROPOMI and Pandora NO2 total columns is about 10 % and 0.12 × 10<sup>15</sup> molec. cm<sup>-2</sup> respectively.<span> </span></p><p>We find high correlation (r = 0.68) between satellite- and ground-based data, but also that TROPOMI total columns underestimate ground-based observations for relatively large Pandora NO2 total columns, corresponding to episodes of relatively elevated pollution. This is expected because of the relatively large size of the TROPOMI ground pixel (3.5 × 7 km) and the a priori used in the retrieval compared to the relatively small field-of-view of the Pandora instrument. On the other hand, TROPOMI slightly overestimates relatively small NO2 total columns. Replacing the coarse a priori NO2 profiles with high-resolution profiles from the CAMS chemical transport model improves the agreement between TROPOMI and Pandora total columns for episodes of NO2 enhancement.<span> </span></p><p>In order to evaluate the capability of TROPOMI observation for monitoring urban air quality, we also analyse the consistency between satellite-based data and NO2 surface concentrations from the local air quality station. We find similar day-to-day variability between TROPOMI and in situ measurements, with NO2 enhancements observed during the same days. Both satellite- and ground-based data show a similar weekly cycle, with lower NO2 levels during the weekend compared to the weekdays as a result of reduced emissions from traffic and industrial activities (as expected in urban sites). The TROPOMI NO2 maps reveal also spatial features, such as the main traffic ways, the airport and other industrial areas, as well as the effect of the prevailing south-west wind patterns.<span> </span></p><p>These first results confirm that TROPOMI NO2 products are valuable to complement the traditional ground-based in situ data for monitoring urban air quality and are already tested by local and national authorities as well as private companies to monitor pollution sources in the Helsinki region (e.g., emissions from traffic, energy production or oil refineries). For example, TROPOMI NO2 products are already used by the oil refinery company NESTE in their sustainability report and by the Finnish Ministry of Environment to map the air pollution levels in Finland.</p><p>Ialongo, I., Virta, H., Eskes, H., Hovila, J., and Douros, J.: Comparison of TROPOMI/Sentinel 5 Precursor NO2 observations with ground-based measurements in Helsinki, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-329, accepted for publication, 2020.</p>

scholarly journals Top-down estimates of black carbon emissions at high latitudes using an atmospheric transport model and a Bayesian inversion framework

2018 ◽  
Vol 18 (20) ◽  
pp. 15307-15327 ◽  
Author(s):  
Nikolaos Evangeliou ◽  
Rona L. Thompson ◽  
Sabine Eckhardt ◽  
Andreas Stohl
Keyword(s):  
North America ◽  
Biomass Burning ◽  
Oil And Gas ◽  
Transport Model ◽  
Atmospheric Transport ◽  
A Priori ◽  
Gas Production ◽  
Anthropogenic Sources ◽  
A Posteriori ◽  
Northern Latitudes

Abstract. This paper presents the results of BC inversions at high northern latitudes (> 50° N) for the 2013–2015 period. A sensitivity analysis was performed to select the best representative species for BC and the best a priori emission dataset. The same model ensemble was used to assess the uncertainty of the a posteriori emissions of BC due to scavenging and removal and due to the use of different a priori emission inventory. A posteriori concentrations of BC simulated over Arctic regions were compared with independent observations from flight and ship campaigns showing, in all cases, smaller bias, which in turn witnesses the success of the inversion. The annual a posteriori emissions of BC at latitudes above 50° N were estimated as 560±171 kt yr−1, significantly smaller than in ECLIPSEv5 (745 kt yr−1), which was used and the a priori information in the inversions of BC. The average relative uncertainty of the inversions was estimated to be 30 %.A posteriori emissions of BC in North America are driven by anthropogenic sources, while biomass burning appeared to be less significant as it is also confirmed by satellite products. In northern Europe, a posteriori emissions were estimated to be half compared to the a priori ones, with the highest releases to be in megacities and due to biomass burning in eastern Europe. The largest emissions of BC in Siberia were calculated along the transect between Yekaterinsburg and Chelyabinsk. The optimised emissions of BC were high close to the gas flaring regions in Russia and in western Canada (Alberta), where numerous power and oil and gas production industries operate. Flaring emissions in Nenets–Komi oblast (Russia) were estimated to be much lower than in the a priori emissions, while in Khanty-Mansiysk (Russia) they remained the same after the inversions of BC. Increased emissions at the borders between Russia and Mongolia are probably due to biomass burning in villages along the Trans-Siberian Railway. The maximum BC emissions in high northern latitudes (> 50° N) were calculated for summer months due to biomass burning and they are controlled by seasonal variations in Europe and Asia, while North America showed a much smaller variability.

scholarly journals Validation of satellite formaldehyde (HCHO) retrievals using observations from 12 aircraft campaigns

2020 ◽  
Author(s):  
Lei Zhu ◽  
Gonzalo González Abad ◽  
Caroline R. Nowlan ◽  
Christopher Chan Miller ◽  
Kelly Chance ◽  
...  
Keyword(s):  
Transport Model ◽  
A Priori ◽  
Chemical Transport Model ◽  
Shape Factors ◽  
Atmospheric Lifetime ◽  
Volatile Organic ◽  
Satellite Sensors ◽  
Systematic Biases ◽  
In Situ Observations

Abstract. Formaldehyde (HCHO) has been measured from space for more than two decades. Owing to its short atmospheric lifetime, satellite HCHO data are used widely as a proxy of volatile organic compounds (VOCs; please refer to Appendix A for abbreviations and acronyms), providing constraints on underlying emissions and chemistry. However, satellite HCHO products from different satellite sensors using different algorithms have received little validation so far. The accuracy and consistency of HCHO retrievals remain largely unclear. Here we develop a global validation platform for satellite HCHO retrievals using in situ observations from 12 aircraft campaigns with a chemical transport model (GEOS-Chem) as the intercomparison method. Application to the NASA operational OMI HCHO product indicates slight biases (−30.9 % to +16.0 %) under high-HCHO conditions partially caused by a priori shape factors used in the retrievals, while high biases (+113.9 % to +194.6 %) under low-HCHO conditions due mainly to slant column fitting and radiance reference sector correction. By providing quick assessment to systematic biases in satellite products over large domains, the platform facilitates, in an iterative process, optimization of retrieval settings and the minimization of retrieval biases. It is also complementary to localized validation efforts based on ground observations and aircraft spirals.

scholarly journals Intercomparison methods for satellite measurements of atmospheric composition: application to tropospheric ozone from TES and OMI

2010 ◽  
Vol 10 (1) ◽  
pp. 1417-1456 ◽  
Author(s):  
L. Zhang ◽  
D. J. Jacob ◽  
X. Liu ◽  
J. A. Logan ◽  
K. Chance ◽  
...  
Keyword(s):  
Tropospheric Ozone ◽  
Kernel Smoothing ◽  
Transport Model ◽  
Atmospheric Composition ◽  
Chemical Transport Model ◽  
Ozone Monitoring Instrument ◽  
Satellite Measurements ◽  
In Situ Data ◽  
In Situ Method

Abstract. We analyze three different methods to validate and intercompare satellite measurements of atmospheric composition, and apply them to tropospheric ozone retrievals from the Tropospheric Emission Spectrometer (TES) and the Ozone Monitoring Instrument (OMI). The first method (in situ method) uses in situ vertical profiles for absolute instrument validation; it is limited by the sparseness of in situ data. The second method (CTM method) uses a chemical transport model (CTM) as an intercomparison platform; it provides a globally complete intercomparison with relatively small noise added by model error. The third method (averaging kernel smoothing method) involves smoothing the retrieved profile from one instrument with the averaging kernel matrix of the other; it also provides a global intercomparison but dampens the actual difference between instruments and adds noise from the a priori. Application to a full year (2006) of TES and OMI data shows mean positive biases of 5.3 parts per billion volume (ppbv) (10%) for TES and 2.8 ppbv (5%) for OMI at 500 hPa relative to in situ data from ozonesondes. We show that the CTM method (using the GEOS-Chem CTM) closely approximates results from the in situ method while providing global coverage. It reveals that differences between TES and OMI are generally less than 10 ppbv (18%), except at northern mid-latitudes in summer and over tropical continents. The CTM method allows for well-constrained CTM evaluation in places where the satellite observations are consistent. We thus find that GEOS-Chem underestimates tropospheric ozone in the tropics, reflecting a combination of possible factors, and overestimates ozone in the northern subtropics and southern mid-latitudes, likely because of excessive stratospheric influx.

scholarly journals Comparison of TROPOMI/Sentinel-5 Precursor NO<sub>2</sub> observations with ground-based measurements in Helsinki

2020 ◽  
Vol 13 (1) ◽  
pp. 205-218 ◽  
Author(s):  
Iolanda Ialongo ◽  
Henrik Virta ◽  
Henk Eskes ◽  
Jari Hovila ◽  
John Douros
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
A Priori ◽  
Quality Data ◽  
High Temporal Resolution ◽  
Chemical Transport Model ◽  
Early Evaluation ◽  
The Mean ◽  
Urban Sites

Abstract. We present a comparison between satellite-based TROPOMI (TROPOspheric Monitoring Instrument) NO2 products and ground-based observations in Helsinki (Finland). TROPOMI NO2 total (summed) columns are compared with the measurements performed by the Pandora spectrometer between April and September 2018. The mean relative and absolute bias between the TROPOMI and Pandora NO2 total columns is about 10 % and 0.12×1015 molec. cm−2 respectively. The dispersion of these differences (estimated as their standard deviation) is 2.2×1015 molec. cm−2. We find high correlation (r = 0.68) between satellite- and ground-based data, but also that TROPOMI total columns underestimate ground-based observations for relatively large Pandora NO2 total columns, corresponding to episodes of relatively elevated pollution. This is expected because of the relatively large size of the TROPOMI ground pixel (3.5×7 km) and the a priori used in the retrieval compared to the relatively small field-of-view of the Pandora instrument. On the other hand, TROPOMI slightly overestimates (within the retrieval uncertainties) relatively small NO2 total columns. Replacing the coarse a priori NO2 profiles with high-resolution profiles from the CAMS chemical transport model improves the agreement between TROPOMI and Pandora total columns for episodes of NO2 enhancement. When only the low values of NO2 total columns or the whole dataset are taken into account, the mean bias slightly increases. The change in bias remains mostly within the uncertainties. We also analyse the consistency between satellite-based data and in situ NO2 surface concentrations measured at the Helsinki–Kumpula air quality station (located a few metres from the Pandora spectrometer). We find similar day-to-day variability between TROPOMI, Pandora and in situ measurements, with NO2 enhancements observed during the same days. Both satellite- and ground-based data show a similar weekly cycle, with lower NO2 levels during the weekend compared to the weekdays as a result of reduced emissions from traffic and industrial activities (as expected in urban sites). The TROPOMI NO2 maps reveal also spatial features, such as the main traffic ways and the airport area, as well as the effect of the prevailing south-west wind patterns. This is one of the first works in which TROPOMI NO2 retrievals are validated against ground-based observations and the results provide an early evaluation of their applicability for monitoring pollution levels in urban sites. Overall, TROPOMI retrievals are valuable to complement the ground-based air quality data (available with high temporal resolution) for describing the spatio-temporal variability of NO2, even in a relatively small city like Helsinki.

scholarly journals Top-down estimates of biomass burning emissions of black carbon in the Western United States

2014 ◽  
Vol 14 (14) ◽  
pp. 7195-7211 ◽  
Author(s):  
Y. H. Mao ◽  
Q. B. Li ◽  
D. Chen ◽  
L. Zhang ◽  
W.-M. Hao ◽  
...  
Keyword(s):  
Black Carbon ◽  
Pacific Northwest ◽  
Biomass Burning ◽  
Transport Model ◽  
Early Summer ◽  
A Posteriori ◽  
Chemical Transport Model ◽  
Fire Emissions ◽  
Active Fire ◽  
Skill Scores

Abstract. We estimate biomass burning and anthropogenic emissions of black carbon (BC) in the western US for May–October 2006 by inverting surface BC concentrations from the Interagency Monitoring of PROtected Visual Environment (IMPROVE) network using a global chemical transport model. We first use active fire counts from the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve the spatiotemporal distributions of the biomass burning BC emissions from the Global Fire Emissions Database (GFEDv2). The adjustment primarily shifts emissions from late to middle and early summer (a 33% decrease in September–October and a 56% increase in June–August) and leads to appreciable increases in modeled surface BC concentrations in early and middle summer, especially at the 1–2 and 2–3 km altitude ranges. We then conduct analytical inversions at both 2° × 2.5° and 0.5° × 0.667° (nested over North America) horizontal resolutions. The a posteriori biomass burning BC emissions for July–September are 31.7 Gg at 2° × 2.5° (an increase by a factor of 4.7) and 19.2 Gg at 0.5° × 0.667° (an increase by a factor of 2.8). The inversion results are rather sensitive to model resolution. The a posteriori biomass burning emissions at the two model resolutions differ by a factor of ~6 in California and the Southwest and by a factor of 2 in the Pacific Northwest. The corresponding a posteriori anthropogenic BC emissions are 9.1 Gg at 2° × 2.5° (a decrease of 48%) and 11.2 Gg at 0.5° × 0.667° (a decrease of 36%). Simulated surface BC concentrations with the a posteriori emissions capture the observed major fire episodes at most sites and the substantial enhancements at the 1–2 and 2–3 km altitude ranges. The a posteriori emissions also lead to large bias reductions (by ~30% on average at both model resolutions) in modeled surface BC concentrations and significantly better agreement with observations (increases in Taylor skill scores of 95% at 2° × 2.5° and 42 % at 0.5° × 0.667°).

scholarly journals The zonal structure of tropical O<sub>3</sub> and CO as observed by the Tropospheric Emission Spectrometer in November 2004 – Part 1: Inverse modeling of CO emissions

2009 ◽  
Vol 9 (11) ◽  
pp. 3547-3562 ◽  
Author(s):  
D. B. A. Jones ◽  
K. W. Bowman ◽  
J. A. Logan ◽  
C. L. Heald ◽  
J. Liu ◽  
...  
Keyword(s):  
Inverse Modeling ◽  
Transport Model ◽  
A Priori ◽  
Systematic Errors ◽  
A Posteriori ◽  
Chemical Transport Model ◽  
Australian Region ◽  
Equatorial Africa ◽  
Modeling Analysis ◽  
The Tropics

Abstract. We conduct an inverse modeling analysis of measurements of atmospheric CO from the TES and MOPITT satellite instruments using the GEOS-Chem global chemical transport model to quantify emissions of CO in the tropics in November 2004. We also assess the consistency of the information provided by TES and MOPITT on surface emissions of CO. We focus on the tropics in November 2004, during the biomass burning season, because TES observations of CO and O3 and MOPITT observations of CO reveal significantly greater abundances of these gases than simulated by the GEOS-Chem model during that period. We find that both datasets suggest substantially greater emissions of CO from sub-equatorial Africa and the Indonesian/Australian region than in the climatological emissions in the model. The a posteriori emissions from sub-equatorial Africa based on TES and MOPITT data were 173 Tg CO/yr and 184 Tg CO/yr, respectively, compared to the a priori of 95 Tg CO/yr. In the Indonesian/Australian region, the a posteriori emissions inferred from TES and MOPITT data were 155 Tg CO/yr and 185 Tg CO/yr, respectively, whereas the a priori was 69 Tg CO/yr. The differences between the a posteriori emission estimates obtained from the two datasets are generally less than 20%. The a posteriori emissions significantly improve the simulated distribution of CO, however, large regional residuals remain, and are likely due to systematic errors in the analysis. Reducing these residuals and improving the accuracy of top-down emission estimates will require better characterization of systematic errors in the observations and the model (chemistry and transport).

scholarly journals Estimates of black carbon emissions in the western United States using the GEOS-Chem adjoint model

2015 ◽  
Vol 15 (13) ◽  
pp. 7685-7702 ◽  
Author(s):  
Y. H. Mao ◽  
Q. B. Li ◽  
D. K. Henze ◽  
Z. Jiang ◽  
D. B. A. Jones ◽  
...  
Keyword(s):  
United States ◽  
Black Carbon ◽  
Biomass Burning ◽  
Transport Model ◽  
A Priori ◽  
Western United States ◽  
Sufficient Information ◽  
Chemical Transport Model ◽  
Global Chemical Transport Model ◽  
Substantial Bias

Abstract. We estimate black carbon (BC) emissions in the western United States for July–September 2006 by inverting surface BC concentrations from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network using a global chemical transport model (GEOS-Chem) and its adjoint. Our best estimate of the BC emissions is 49.9 Gg at 2° × 2.5° (a factor of 2.1 increase) and 47.3 Gg at 0.5° × 0.667° (1.9 times increase). Model results now capture the observed major fire episodes with substantial bias reductions (~ 35 % at 2° × 2.5° and ~ 15 % at 0.5° × 0.667°). The emissions are ~ 20–50 % larger than those from our earlier analytical inversions (Mao et al., 2014). The discrepancy is especially drastic in the partitioning of anthropogenic versus biomass burning emissions. The August biomass burning BC emissions are 4.6–6.5 Gg and anthropogenic BC emissions 8.6–12.8 Gg, varying with the model resolution, error specifications, and subsets of observations used. On average both anthropogenic and biomass burning emissions in the adjoint inversions increase 2-fold relative to the respective {a priori} emissions, in distinct contrast to the halving of the anthropogenic and tripling of the biomass burning emissions in the analytical inversions. We attribute these discrepancies to the inability of the adjoint inversion system, with limited spatiotemporal coverage of the IMPROVE observations, to effectively distinguish collocated anthropogenic and biomass burning emissions on model grid scales. This calls for concurrent measurements of other tracers of biomass burning and fossil fuel combustion (e.g., carbon monoxide and carbon isotopes). We find that the adjoint inversion system as is has sufficient information content to constrain the total emissions of BC on the model grid scales.

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