scholarly journals Satellite measurement based estimates of decadal changes in European nitrogen oxides emissions

2008 ◽  
Vol 8 (1) ◽  
pp. 2013-2059 ◽  
Author(s):  
I. B. Konovalov ◽  
M. Beekmann ◽  
J. P. Burrows ◽  
A. Richter
Keyword(s):  
Great Britain ◽  
Nitrogen Oxides ◽  
Nox Emissions ◽  
Satellite Measurements ◽  
Data Set ◽  
Bottom Up ◽  
Model Calculations ◽  
Near Surface ◽  
Continental Scale ◽  
General Decline

Abstract. Long-term satellite measurements of nitrogen dioxide in the troposphere are used in combination with a continental scale air quality model in order to verify and improve available estimates of multi-annual changes of emissions of nitrogen oxides (NOx) in Europe and the Mediterranean area between 1996 and 2005. As a result, a measurement-based data set of NOx emissions on a 1° by 1° grid and averaged over summer months is elaborated. The results are compared with emission data based on the EMEP emission inventory. Our data are in agreement with the EMEP estimates suggesting a general decline in the level of NOx emissions in Western and Central European countries (France, Germany, Great Britain and Poland). Over Southern Europe and for shipping emissions, neutral to positive trends are found both for the inverted and bottom-up emissions. In contrast, considerable differences between both data sets are found in some other countries. In particular, significant negative trends instead of the positive ones in the "bottom-up" inventory are found for the Balkan countries, Russia and Turkey. The NOx emission trends derived from satellite measurements demonstrate larger spatial heterogeneity than those calculated with the EMEP data, especially in Russia and Ukraine. The obtained estimates of the decadal trends in NOx emissions for Great Britain are found to be consistent with independent data from the U.K. Automatic Urban and Rural Network (AURN). It is also found that using our emission estimates yields better agreement of model calculations with near-surface ozone measurements of the European EMEP network.

scholarly journals Satellite measurement based estimates of decadal changes in European nitrogen oxides emissions

2008 ◽  
Vol 8 (10) ◽  
pp. 2623-2641 ◽  
Author(s):  
I. B. Konovalov ◽  
M. Beekmann ◽  
J. P. Burrows ◽  
A. Richter
Keyword(s):  
Great Britain ◽  
Nitrogen Oxides ◽  
Nox Emissions ◽  
Satellite Measurements ◽  
Data Set ◽  
Bottom Up ◽  
Model Calculations ◽  
Near Surface ◽  
Continental Scale ◽  
General Decline

Abstract. Long-term satellite measurements of nitrogen dioxide in the troposphere are used in combination with a continental scale air quality model in order to verify and improve available estimates of multi-annual changes of emissions of nitrogen oxides (NOx) in Europe and the Mediterranean area between 1996 and 2005. As a result, a measurement-based data set of NOx emissions on a 1° by 1° grid and averaged over summer months is elaborated. The results are compared with emission data based on the EMEP emission inventory. Our data are in agreement with the EMEP estimates suggesting a general decline in the level of NOx emissions in Western and Central European countries (France, Germany, Great Britain and Poland). Over Southern Europe and for shipping emissions, neutral to positive trends are found both for the inverted and bottom-up emissions. In contrast, considerable differences between both data sets are found in some other countries. In particular, significant negative trends instead of the positive ones in the "bottom-up" inventory are found for the Balkan countries, Russia and Turkey. The NOx emission trends derived from satellite measurements demonstrate larger spatial heterogeneity than those calculated with the EMEP data, especially in Russia and Ukraine. The obtained estimates of the decadal trends in NOx emissions for Great Britain are found to be consistent with independent data from the U.K. Automatic Urban and Rural Network (AURN). It is also found that using our emission estimates yields better agreement of model calculations with near-surface ozone measurements of the European EMEP network.

scholarly journals Emissions of nitrogen oxides from US urban areas: estimation from Ozone Monitoring Instrument retrievals for 2005–2014

2015 ◽  
Vol 15 (18) ◽  
pp. 10367-10383 ◽  
Author(s):  
Z. Lu ◽  
D. G. Streets ◽  
B. de Foy ◽  
L. N. Lamsal ◽  
B. N. Duncan ◽  
...  
Keyword(s):  
Nitrogen Oxides ◽  
Urban Areas ◽  
Nox Emission ◽  
Nox Emissions ◽  
Strong Wind ◽  
Ozone Monitoring Instrument ◽  
Bottom Up ◽  
Monitoring Instrument ◽  
Ozone Monitoring ◽  
Weak Wind

Abstract. Satellite remote sensing of tropospheric nitrogen dioxide (NO2) can provide valuable information for estimating surface nitrogen oxides (NOx) emissions. Using an exponentially modified Gaussian (EMG) method and taking into account the effect of wind on observed NO2 distributions, we estimate 3-year moving-average emissions of summertime NOx from 35 US (United States) urban areas directly from NO2 retrievals of the Ozone Monitoring Instrument (OMI) during 2005–2014. Following conclusions of previous studies that the EMG method provides robust and accurate emission estimates under strong-wind conditions, we derive top-down NOx emissions from each urban area by applying the EMG method to OMI data with wind speeds greater than 3–5 m s−1. Meanwhile, we find that OMI NO2 observations under weak-wind conditions (i.e., < 3 m s−1) are qualitatively better correlated to the surface NOx source strength in comparison to all-wind OMI maps; therefore, we use them to calculate the satellite-observed NO2 burdens of urban areas and compare with NOx emission estimates. The EMG results show that OMI-derived NOx emissions are highly correlated (R > 0.93) with weak-wind OMI NO2 burdens as well as with bottom-up NOx emission estimates over 35 urban areas, implying a linear response of the OMI observations to surface emissions under weak-wind conditions. The simultaneous EMG-obtained effective NO2 lifetimes (~ 3.5 ± 1.3 h), however, are biased low in comparison to the summertime NO2 chemical lifetimes. In general, isolated urban areas with NOx emission intensities greater than ~ 2 Mg h−1 produce statistically significant weak-wind signals in 3-year average OMI data. From 2005 to 2014, we estimate that total OMI-derived NOx emissions over all selected US urban areas decreased by 49 %, consistent with reductions of 43, 47, 49, and 44 % in the total bottom-up NOx emissions, the sum of weak-wind OMI NO2 columns, the total weak-wind OMI NO2 burdens, and the averaged NO2 concentrations, respectively, reflecting the success of NOx control programs for both mobile sources and power plants. The decrease rates of these NOx-related quantities are found to be faster (i.e., −6.8 to −9.3 % yr−1) before 2010 and slower (i.e., −3.4 to −4.9 % yr−1) after 2010. For individual urban areas, we calculate the R values of pair-wise trends among the OMI-derived and bottom-up NOx emissions, the weak-wind OMI NO2 burdens, and ground-based NO2 measurements, and high correlations are found for all urban areas (median R= 0.8), particularly large ones (R up to 0.97). The results of the current work indicate that using the EMG method and considering the wind effect, the OMI data allow for the estimation of NOx emissions from urban areas and the direct constraint of emission trends with reasonable accuracy.

scholarly journals North American CO<sub>2</sub> exchange: inter-comparison of modeled estimates with results from a fine-scale atmospheric inversion

2012 ◽  
Vol 9 (1) ◽  
pp. 457-475 ◽  
Author(s):  
S. M. Gourdji ◽  
K. L. Mueller ◽  
V. Yadav ◽  
D. N. Huntzinger ◽  
A. E. Andrews ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
North American ◽  
Co2 Fluxes ◽  
Fine Scale ◽  
Bottom Up ◽  
Near Surface ◽  
Continental Scale ◽  
The North ◽  
Atmospheric Observations ◽  
Atmospheric Inversion

Abstract. Atmospheric inversion models have the potential to quantify CO2 fluxes at regional, sub-continental scales by taking advantage of near-surface CO2 mixing ratio observations collected in areas with high flux variability. This study presents results from a series of regional geostatistical inverse models (GIM) over North America for 2004, and uses them as the basis for an inter-comparison to other inversion studies and estimates from biospheric models collected through the North American Carbon Program Regional and Continental Interim Synthesis. Because the GIM approach does not require explicit prior flux estimates and resolves fluxes at fine spatiotemporal scales (i.e. 1° × 1°, 3-hourly in this study), it avoids temporal and spatial aggregation errors and allows for the recovery of realistic spatial patterns from the atmospheric data relative to previous inversion studies. Results from a GIM inversion using only available atmospheric observations and a fine-scale fossil fuel inventory were used to confirm the quality of the inventory and inversion setup. An inversion additionally including auxiliary variables from the North American Regional Reanalysis found inferred relationships with flux consistent with physiological understanding of the biospheric carbon cycle. Comparison of GIM results with bottom-up biospheric models showed stronger agreement during the growing relative to the dormant season, in part because most of the biospheric models do not fully represent agricultural land-management practices and the fate of both residual biomass and harvested products. Comparison to earlier inversion studies pointed to aggregation errors as a likely source of bias in previous sub-continental scale flux estimates, particularly for inversions that adjust fluxes at the coarsest scales and use atmospheric observations averaged over long periods. Finally, whereas the continental CO2 boundary conditions used in the GIM inversions have a minor impact on spatial patterns, they have a substantial impact on the continental carbon budget, with a difference of 0.8 PgC yr−1 in the total continental flux resulting from the use of two plausible sets of boundary CO2 mixing ratios. Overall, this inter-comparison study helps to assess the state of the science in estimating regional-scale CO2 fluxes, while pointing towards the path forward for improvements in future top-down and bottom-up modeling efforts.

scholarly journals Inverse modelling of the spatial distribution of NO<sub>x</sub> emissions on a continental scale using satellite data

2006 ◽  
Vol 6 (7) ◽  
pp. 1747-1770 ◽  
Author(s):  
I. B. Konovalov ◽  
M. Beekmann ◽  
A. Richter ◽  
J. P. Burrows
Keyword(s):  
Spatial Distribution ◽  
Satellite Data ◽  
A Priori ◽  
Inverse Modelling ◽  
Geometric Standard Deviation ◽  
Nox Emissions ◽  
A Posteriori ◽  
Near Surface ◽  
Continental Scale ◽  
Tropospheric No2

Abstract. The recent important developments in satellite measurements of the composition of the lower atmosphere open the challenging perspective to use such measurements as independent information on sources and sinks of atmospheric pollutants. This study explores the possibility to improve estimates of gridded NOx emissions used in a continental scale chemistry transport model (CTM), CHIMERE, by employing measurements performed by the GOME and SCIAMACHY instruments. We set-up an original inverse modelling scheme that not only enables a computationally efficient optimisation of the spatial distribution of seasonally averaged NOx emissions (during summertime), but also allows estimating uncertainties in input data and a priori emissions. The key features of our method are (i) replacement of the CTM by a set of empirical models describing the relationships between tropospheric NO2 columns and NOx emissions with sufficient accuracy, (ii) combination of satellite data for tropospheric NO2 columns with ground based measurements of near surface NO2 concentrations, and (iii) evaluation of uncertainties in a posteriori emissions by means of a special Bayesian Monte-Carlo experiment which is based on random sampling of errors of both NO2 columns and emission rates. We have estimated the uncertainty in a priori emissions based on the EMEP emission inventory to be about 1.9 (in terms of geometric standard deviation) and found the uncertainty in a posteriori emissions obtained from our inverse modelling scheme to be significantly lower (about 1.4). It is found also that a priori NOx emission estimates are probable to be persistently biased in many regions of Western Europe, and that the use of a posteriori emissions in the CTM improves the agreement between the modelled and measured data.

scholarly journals Inverse modelling of the spatial distribution of NO<sub>x</sub> emissions on a continental scale using satellite data

2005 ◽  
Vol 5 (6) ◽  
pp. 12641-12695 ◽  
Author(s):  
I. B. Konovalov ◽  
M. Beekmann ◽  
A. Richter ◽  
J. P. Burrows
Keyword(s):  
Spatial Distribution ◽  
Satellite Data ◽  
A Priori ◽  
Inverse Modelling ◽  
Geometric Standard Deviation ◽  
Nox Emissions ◽  
A Posteriori ◽  
Near Surface ◽  
Continental Scale ◽  
Tropospheric No2

Abstract. The recent important developments in satellite measurements of the composition of the lower atmosphere open the challenging perspective to use such measurements as independent information on sources and sinks of atmospheric pollutants. This study explores the possibility to improve estimates of gridded NOx emissions used in a continental scale chemistry transport model (CTM), CHIMERE, by employing measurements performed by the GOME and SCIAMACHY instruments. We set-up an original inverse modelling scheme that not only enables a computationally efficient optimisation of the spatial distribution of seasonally averaged NOx emissions (during summertime), but also allows estimating uncertainties of input data and a priori emissions. The key features of our method are (i) replacement of the CTM by a set of empirical models describing the relationships between tropospheric NO2 columns and NOx emissions with sufficient accuracy, (ii) combination of satellite data for tropospheric NO2 columns with ground based measurements of near surface NO2 concentrations, and (iii) evaluation of uncertainties of the a posteriori emissions by means of a special Bayesian Monte-Carlo experiment which is based on random sampling of errors of both NO2 columns and emission rates. We have estimated the uncertainty in a priori emissions based on the EMEP emission inventory to be about 1.9 (in terms of the geometric standard deviation) and found the uncertainty in a posteriori emissions obtained from our inverse modelling scheme to be significantly lower (about 1.4). It is found also that a priori NOx emission estimates are probable to be persistently biased in many regions of Western Europe, and that the use of a posteriori emissions in the CTM improves the agreement between the modelled and measured data.

scholarly journals Emissions of nitrogen oxides from US urban areas: estimation from Ozone Monitoring Instrument retrievals for 2005–2014

2015 ◽  
Vol 15 (10) ◽  
pp. 14961-15003 ◽  
Author(s):  
Z. Lu ◽  
D. G. Streets ◽  
B. de Foy ◽  
L. N. Lamsal ◽  
B. N. Duncan ◽  
...  
Keyword(s):  
Nitrogen Oxides ◽  
Urban Areas ◽  
Nox Emission ◽  
Nox Emissions ◽  
Strong Wind ◽  
Ozone Monitoring Instrument ◽  
Bottom Up ◽  
Monitoring Instrument ◽  
Ozone Monitoring ◽  
Weak Wind

Abstract. Satellite remote sensing of tropospheric nitrogen dioxide (NO2) can provide valuable information for estimating surface nitrogen oxides (NOx) emissions. Using an exponentially-modified Gaussian (EMG) method and taking into account the effect of wind on observed NO2 distributions, we estimate three-year moving-average emissions of summertime NOx from 35 US urban areas directly from NO2 retrievals of the Ozone Monitoring Instrument (OMI) during 2005–2014. Following the conclusions of previous studies that the EMG method provides robust and accurate emission estimates under strong-wind conditions, we derive top-down NOx emissions from each urban area by applying the EMG method to OMI data with wind speeds greater than 3–5 m s−1. Meanwhile, we find that OMI NO2 observations under weak-wind conditions (i.e., < 3 m s−1) are qualitatively better correlated with the surface NOx source strength in comparison to all-wind OMI maps; and therefore we use them to calculate the satellite-observed NO2 burdens of urban areas and compare with NOx emission estimates. The EMG results show that OMI-derived NOx emissions are highly correlated (R > 0.93) with weak-wind OMI NO2 burdens as well as bottom-up NOx emission estimates over 35 urban areas, implying a linear response of the OMI observations to surface emissions under weak-wind conditions. The simultaneous, EMG-obtained, effective NO2 lifetimes (~3.5 ± 1.3 h), however, are biased low in comparison to the summertime NO2 chemical lifetimes. In general, isolated urban areas with NOx emission intensities greater than ~ 2 Mg h−1 produce statistically significant weak-wind signals in three-year average OMI data. From 2005 to 2014, we estimate that total OMI-derived NOx emissions over all selected US urban areas decreased by 49%, consistent with reductions of 43, 47, 49, and 44% in the total bottom-up NOx emissions, the sum of weak-wind OMI NO2 columns, the total weak-wind OMI NO2 burdens, and the averaged NO2 concentrations, respectively, reflecting the success of NOx control programs for both mobile sources and power plants. The decrease rates of these NOx-related quantities are found to be faster (i.e., −6.8 to −9.3% yr−1) before 2010 and slower (i.e., −3.4 to −4.9% yr−1) after 2010. For individual urban areas, we calculate the R values of pair-wise trends among the OMI-derived and bottom-up NOx emissions, the weak-wind OMI NO2 burdens, and ground-based NO2 measurements; and high correlations are found for all urban areas (median R = 0.8), particularly large ones (R up to 0.97). The results of the current work indicate that using the EMG method and considering the wind effect, the OMI data allow for the estimation of NOx emissions from urban areas and the direct constraint of emission trends with reasonable accuracy.

Regularization and datuming of seismic data by weighted, damped least squares

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. U67-U76 ◽  
Author(s):  
Robert J. Ferguson
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Synthetic Data ◽  
Real Data ◽  
Structural Data ◽  
Irregular Sampling ◽  
Data Set ◽  
Near Surface ◽  
Damped Least Squares ◽  
Wavefield Extrapolation

The possibility of improving regularization/datuming of seismic data is investigated by treating wavefield extrapolation as an inversion problem. Weighted, damped least squares is then used to produce the regularized/datumed wavefield. Regularization/datuming is extremely costly because of computing the Hessian, so an efficient approximation is introduced. Approximation is achieved by computing a limited number of diagonals in the operators involved. Real and synthetic data examples demonstrate the utility of this approach. For synthetic data, regularization/datuming is demonstrated for large extrapolation distances using a highly irregular recording array. Without approximation, regularization/datuming returns a regularized wavefield with reduced operator artifacts when compared to a nonregularizing method such as generalized phase shift plus interpolation (PSPI). Approximate regularization/datuming returns a regularized wavefield for approximately two orders of magnitude less in cost; but it is dip limited, though in a controllable way, compared to the full method. The Foothills structural data set, a freely available data set from the Rocky Mountains of Canada, demonstrates application to real data. The data have highly irregular sampling along the shot coordinate, and they suffer from significant near-surface effects. Approximate regularization/datuming returns common receiver data that are superior in appearance compared to conventional datuming.

scholarly journals MAX-DOAS observations of aerosols, formaldehyde and nitrogen dioxide in the Beijing area: comparison of two profile retrieval approaches

2015 ◽  
Vol 8 (2) ◽  
pp. 941-963 ◽  
Author(s):  
T. Vlemmix ◽  
F. Hendrick ◽  
G. Pinardi ◽  
I. De Smedt ◽  
C. Fayt ◽  
...  
Keyword(s):  
Standard Deviation ◽  
A Priori ◽  
Systematic Bias ◽  
Aerosol Extinction ◽  
Data Set ◽  
Near Surface ◽  
Beijing Area ◽  
Least Squares Fit ◽  
Relative Differences ◽  
Good Agreement

Abstract. A 4-year data set of MAX-DOAS observations in the Beijing area (2008–2012) is analysed with a focus on NO2, HCHO and aerosols. Two very different retrieval methods are applied. Method A describes the tropospheric profile with 13 layers and makes use of the optimal estimation method. Method B uses 2–4 parameters to describe the tropospheric profile and an inversion based on a least-squares fit. For each constituent (NO2, HCHO and aerosols) the retrieval outcomes are compared in terms of tropospheric column densities, surface concentrations and "characteristic profile heights" (i.e. the height below which 75% of the vertically integrated tropospheric column density resides). We find best agreement between the two methods for tropospheric NO2 column densities, with a standard deviation of relative differences below 10%, a correlation of 0.99 and a linear regression with a slope of 1.03. For tropospheric HCHO column densities we find a similar slope, but also a systematic bias of almost 10% which is likely related to differences in profile height. Aerosol optical depths (AODs) retrieved with method B are 20% high compared to method A. They are more in agreement with AERONET measurements, which are on average only 5% lower, however with considerable relative differences (standard deviation ~ 25%). With respect to near-surface volume mixing ratios and aerosol extinction we find considerably larger relative differences: 10 ± 30, −23 ± 28 and −8 ± 33% for aerosols, HCHO and NO2 respectively. The frequency distributions of these near-surface concentrations show however a quite good agreement, and this indicates that near-surface concentrations derived from MAX-DOAS are certainly useful in a climatological sense. A major difference between the two methods is the dynamic range of retrieved characteristic profile heights which is larger for method B than for method A. This effect is most pronounced for HCHO, where retrieved profile shapes with method A are very close to the a priori, and moderate for NO2 and aerosol extinction which on average show quite good agreement for characteristic profile heights below 1.5 km. One of the main advantages of method A is the stability, even under suboptimal conditions (e.g. in the presence of clouds). Method B is generally more unstable and this explains probably a substantial part of the quite large relative differences between the two methods. However, despite a relatively low precision for individual profile retrievals it appears as if seasonally averaged profile heights retrieved with method B are less biased towards a priori assumptions than those retrieved with method A. This gives confidence in the result obtained with method B, namely that aerosol extinction profiles tend on average to be higher than NO2 profiles in spring and summer, whereas they seem on average to be of the same height in winter, a result which is especially relevant in relation to the validation of satellite retrievals.

A hybrid regularization scheme for the inversion of magnetotelluric data from natural and controlled sources to layer and distortion parameters

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. E301-E315 ◽  
Author(s):  
Thomas Kalscheuer ◽  
Juliane Hübert ◽  
Alexey Kuvshinov ◽  
Tobias Lochbühler ◽  
Laust B. Pedersen
Keyword(s):  
Transfer Functions ◽  
Homogeneous Distribution ◽  
Stable Configuration ◽  
Inversion Algorithm ◽  
Magnetotelluric Data ◽  
Data Set ◽  
Near Surface ◽  
Minimum Solution ◽  
Magnetic Transfer ◽  
Distortion Parameters

Magnetotelluric (MT), radiomagnetotelluric (RMT), and, in particular, controlled-source audiomagnetotelluric (CSAMT) data are often heavily distorted by near-surface inhomogeneities. We developed a novel scheme to invert MT, RMT, and CSAMT data in the form of scalar or tensorial impedances and vertical magnetic transfer functions simultaneously for layer resistivities and electric and magnetic galvanic distortion parameters. The inversion scheme uses smoothness constraints to regularize layer resistivities and either Marquardt-Levenberg damping or the minimum-solution length criterion to regularize distortion parameters. A depth of investigation range is estimated by comparing layered model sections derived from first- and second-order smoothness constraints. Synthetic examples demonstrate that earth models are reconstructed properly for distorted and undistorted tensorial CSAMT data. In the inversion of scalar CSAMT data, such as the determinant impedance or individual tensor elements, the reduced number of transfer functions inevitably leads to increased ambiguity for distortion parameters. As a consequence of this ambiguity for scalar data, distortion parameters often grow over the iterations to unrealistic absolute values when regularized with the Marquardt-Levenberg scheme. Essentially, compensating relationships between terms containing electric and/or magnetic distortion are used in this growth. In a regularization with the minimum solution length criterion, the distortion parameters converge into a stable configuration after several iterations and attain reasonable values. The inversion algorithm was applied to a CSAMT field data set collected along a profile over a tunnel construction site at Hallandsåsen, Sweden. To avoid erroneous inverse models from strong anthropogenic effects on the data, two scalar transfer functions (one scalar impedance and one scalar vertical magnetic transfer function) were selected for inversion. Compared with a regularization of distortion parameters with the Marquardt-Levenberg method, the minimum-solution length criterion yielded smaller absolute values of distortion parameters and a horizontally more homogeneous distribution of electrical conductivity.

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