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Satellite and aircraft observations made during the 2006 Texas Air Quality Study (TexAQS) detected strong urban, industrial and power plant plumes in Texas. We simulated these plumes using the Weather Research and Forecasting-Chemistry (WRF-Chem) model with input from the US EPA's 2005 National Emission Inventory (NEI-2005), in order to evaluate emissions of nitrogen oxides (NOx = NO + NO2) and volatile organic compounds (VOCs) in the cities of Houston and Dallas-Fort Worth. We compared the model results with satellite retrievals of tropospheric nitrogen dioxide (NO2) columns and airborne in-situ observations of several trace gases including NOx and a number of VOCs. The model and satellite NO2 columns agree well for regions with large power plants and for urban areas that are dominated by mobile sources, such as Dallas. However, in Houston, where significant mobile, industrial, and in-port marine vessel sources contribute to NOx emissions, the model NO2 columns are approximately 50%–70% higher than the satellite columns. Similar conclusions are drawn from comparisons of the model results with the TexAQS 2006 aircraft observations in Dallas and Houston. For Dallas plumes, the model-simulated NO2 showed good agreement with the aircraft observations. In contrast, the model-simulated NO2 is ~60% higher than the aircraft observations in the Houston plumes. Further analysis indicates that the NEI-2005 NOx emissions over the Houston Ship Channel area are overestimated while the urban Houston NOx emissions are reasonably represented. The comparisons of model and aircraft observations confirm that highly reactive VOC emissions originating from industrial sources in Houston are underestimated in NEI-2005. The update of VOC emissions based on Solar Occultation Flux measurements during the field campaign leads to improved model simulations of ethylene, propylene, and formaldehyde. Reducing NOx emissions in the Houston Ship Channel and increasing highly reactive VOC emissions from the point sources in Houston improve the model's capability of simulating ozone (O3) plumes observed by the NOAA WP-3D aircraft, although the deficiencies in the model O3 simulations indicate that many challenges remain for a full understanding of the O3 formation mechanisms in Houston.

Methods for the determination of ship fuel sulphur content and NOx emission factors based on remote measurements have been compared in the harbour of Rotterdam and compared to direct stack emission measurements on the ferry Stena Hollandica. The methods were selected based on a review of the available literature on ship emission measurements. They were either optical (LIDAR, Differential Optical Absorption Spectroscopy (DOAS), UV camera), combined with model-based estimates of fuel consumption, or based on the so called "sniffer" principle, where SO2 or NOx emission factors are determined from simultaneous measurement of the increase of CO2 and SO2 or NOx concentrations in the plume of the ship compared to the background. The measurements were performed from stations at land, from a boat and from a helicopter. Mobile measurement platforms were found to have important advantages compared to the land-based ones because they allow optimizing the sampling conditions and sampling from ships on the open sea. Although optical methods can provide reliable results it was found that at the state of the art level, the "sniffer" approach is the most convenient technique for determining both SO2 and NOx emission factors remotely. The average random error on the determination of SO2 emission factors comparing two identical instrumental set-ups was 6%. However, it was found that apparently minor differences in the instrumental characteristics, such as response time, could cause significant differences between the emission factors determined. Direct stack measurements showed that about 14% of the fuel sulphur content was not emitted as SO2. This was supported by the remote measurements and is in agreement with the results of other field studies.

A unique methodology to measure gas fluxes of SO2 and NO2 from ships has been developed in a Swedish national project using optical remote sensing. The measurement system is based on Differential Optical Absor ption Spectroscopy using reflected skylight from the water surface as light source. A grating spectrometer records spectra around 311 nm and 440 nm, respectively, with the telescope pointed downward at a 30 degree angle from the horizon. The mass column values of SO2 and NO2 are retrieved from each spectrum and integrated across the plume. To obtain the total emission in kg h−1 the resulting total mass across the plume is multiplied with the apparent wind, i.e. a dilution factor corresponding to the vector between the wind and the ship speed. The system was tested in two feasibility studies in the Baltic Sea and Kattegat, from a CASA-212 air plane in 2008 and in the Nor th Sea outside Rotterdam from a Dauphin helicopter in an EU campaign in 2009. In the Baltic Sea the average SO2 emission out of 22 ships was (54 ± 13) kg h− , and the average NO2 emission was (33± 8) kg h−1out of 13 ships. In the Nor th Sea the average SO2 emission out of 21 ships was 15 (42 ± 11) kg h−, NO2 was not measured here. The system was able to detect plumes of SO2 in 60 % of the measurements when the described method was used. The optical measurement carried out on a passenger ferr y on two consecutive days was compared to onboard emission data obtained from analysed fuel content and power consumption. The comparison shows agreement of (−30 ± 14) % and 20 (−41 ± 11) %, respectively, for two days, with equal measurement precision of about 20%, this indicates the presence of systematic error sources that are yet unaccounted for when deriving the flux. Two such error sources are the difficulty in estimating the optical path of the ocean scattered light due to waves, and direct and multiple scattering in the exhaust plume. Rough estimates of these sources have been accounted for in the total uncer tainty, 30–45 %. A ship emission model, FMI-STEAM, has been compared to the optical measurements showing a 18 % overestimation and a correlation coefficient (R 2 ) of 0.6. It is AMTD shown that a combination of the optical method with modelled power consumption can estimate the sulphur fuel content within 40 %, which would be sufficient to detect the difference between ships running at 1 % and at 0.1 %, limits applicable within the IMO regulated areas., JRC.H.2-Air and Climate

Trends in the CO and C2H6 partial columns (~0–15 km) have been estimated from four European groundbasedsolar FTIR (Fourier Transform InfraRed) stations for the 1996–2006 time period. The CO trends from the four stations Jungfraujoch, Zugspitze, Harestua and Kiruna have been estimated to −0.45±0.16%yr−1, −1.00 ± 0.24%yr−1, −0.62±0.19%yr−1 and −0.61±0.16%yr−1, respectively. The corresponding trends for C2H6 are−1.51±0.23%yr−1, −2.11±0.30%yr−1, −1.09±0.25%yr−1 and −1.14±0.18%yr−1. All trends are presented with their 2-σ confidence intervals. To find possible reasons for the CO trends, the global-scale EMEP MSC-W chemical transport model has been used in a series of sensitivity scenarios. It is shown that the trends are consistent with the combination of a 20% decrease in the anthropogenic CO emissions seen in Europe and North America during the 1996–2006 period and a 20% increase in the anthropogenic CO emissions in East Asia, during the same time period. The possible impacts of CH4 and biogenic volatile organic compounds (BVOCs) are also considered. The European and global-scale EMEP models have been evaluated against the measured CO and C2H6 partial columns from Jungfraujoch, Zugspitze, Bremen, Harestua, Kiruna and Ny-Ålesund. The European model reproduces, on average the measurements at the different sites fairly well and within 10–22% deviation for CO and 14–31% deviation for C2H6. Their seasonal amplitude is captured within 6–35% and 9–124% for CO and C2H6, respectively. However, 61–98% of the CO and C2H6 partial columns in the European model are shown to arise from the boundary conditions, making the globalscale model a more suitable alternative when modeling these two species. In the evaluation of the global model the average partial columns for 2006 are shown to be within 1–9% and 37–50% of the measurements for CO and C2H6, respectively. The global model sensitivity for assumptions made in this paper is also analyzed.

Total columns measured with the ground-based solar FTIR technique are highly variable in time due to atmospheric chemistry and dynamics in the atmosphere above the measurement station. In this paper, a multiple regression model with anomalies of air pressure, total columns of hydrogen fluoride (HF) and carbon monoxide (CO) and tropopause height are used to reduce the variability in the methane (CH4) and nitrous oxide (N2O) total columns to estimate reliable linear trends with as small uncertainties as possible. The method is developed at the Harestua station (60°N, 11°E, 600ma.s.l.) and used on three other European FTIR stations, i.e. Jungfraujoch (47°N, 8°E, 3600ma.s.l.), Zugspitze (47°N, 11°E, 3000ma.s.l.), and Kiruna (68°N, 20°E, 400ma.s.l.). Linear CH4 trends between 0.13±0.01-0.25±0.02%yr−1 were estimated for all stations in the 1996-2009 period. A piecewise model with three separate linear trends, connected at change points, was used to estimate the short term fluctuations in the CH4 total columns. This model shows a growth in 1996–1999 followed by a period of steady state until 2007. From 2007 until 2009 the atmospheric CH4 amount increases between 0.57±0.22–1.15±0.17%yr−1. Linear N2O trends between 0.19±0.01–0.40±0.02%yr−1 were estimated for all stations in the 1996-2007 period, here with the strongest trend at Harestua and Kiruna and the lowest at the Alp stations. From the N2O total columns crude tropospheric and stratospheric partial columns were derived, indicating that the observed difference in the N2O trends between the FTIR sites is of stratospheric origin. This agrees well with the N2O measurements by the SMR instrument onboard the Odin satellite showing the highest trends at Harestua, 0.98±0.28%yr−1, and considerably smaller trends at lower latitudes, 0.27±0.25%yr−1. The multiple regression model was compared with two other trend methods, the ordinary linear regression and a Bootstrap algorithm. The multiple regression model estimated CH4 and N2O trends that differed up to 31% compared to the other two methods and had uncertainties that were up to 300% lower. Since the multiple regression method were carefully validated this stresses the importance to account for variability in the total columns when estimating trend from solar FTIR data.

International audience; The Atmospheric Chemistry Experiment (ACE), also known as SCISAT, was launched on 12 August 2003, carrying two instruments that measure vertical profiles of atmospheric constituents using the solar occultation technique. One of these instruments, the ACE Fourier Transform Spectrometer (ACE-FTS), is measuring volume mixing ratio (VMR) profiles of nitrous oxide (N2O) from the upper troposphere to the lower mesosphere at a vertical resolution of about 3–4 km. In this study, the quality of the ACE-FTS version 2.2 N2O data is assessed through comparisons with coincident measurements made by other satellite, balloon-borne, aircraft, and ground-based instruments. These consist of vertical profile comparisons with the SMR, MLS, and MIPAS satellite instruments, multiple aircraft flights of ASUR, and single balloon flights of SPIRALE and FIRS-2, and partial column comparisons with a network of ground-based Fourier Transform InfraRed spectrometers (FTIRs). Overall, the quality of the ACE-FTS version 2.2 N2O VMR profiles is good over the entire altitude range from 5 to 60 km. Between 6 and 30 km, the mean absolute differences for the satellite comparisons lie between -42 ppbv and +17 ppbv, with most within ±20 ppbv. This corresponds to relative deviations from the mean that are within ±15%, except for comparisons with MIPAS near 30 km, for which they are as large as 22.5%. Between 18 and 30 km, the mean absolute differences are generally within ±10 ppbv, again excluding the aircraft and balloon comparisons. From 30 to 60 km, the mean absolute differences are within ±4 ppbv, and are mostly between -2 and +1 ppbv. Given the small N2O VMR in this region, the relative deviations from the mean are therefore large at these altitudes, with most suggesting a negative bias in the ACE-FTS data between 30 and 50 km. In the comparisons with the FTIRs, the mean relative differences between the ACE-FTS and FTIR partial columns are within ±6.6% for eleven of the twelve contributing stations. This mean relative difference is negative at ten stations, suggesting a small negative bias in the ACE-FTS partial columns over the altitude regions compared. Excellent correlation (R=0.964) is observed between the ACE-FTS and FTIR partial columns, with a slope of 1.01 and an intercept of -0.20 on the line fitted to the data.

This paper describes the statistical analysis of annual trends in long term datasets of greenhouse gas measurements taken over ten or more years. The analysis technique employs a bootstrap resampling method to determine both the long-term and intra-annual variability of the datasets, together with the uncertainties on the trend values. The method has been applied to data from a European network of ground-based solar FTIR instruments to determine the trends in the tropospheric, stratospheric and total columns of ozone, nitrous oxide, carbon monoxide, methane, ethane and HCFC-22. The suitability of the method has been demonstrated through statistical validation of the technique, and comparison with ground-based in-situ measurements and 3-D atmospheric models.

Altitude profiles of ClONO2 retrieved with the IMK (Institut für Meteorologie und Klimaforschung) science-oriented data processor from MIPAS/Envisat (Michelson Interferometer for Passive Atmospheric Sounding on Envisat) mid-infrared limb emission measurements between July 2002 and March 2004 have been validated by comparison with balloon-borne (Mark IV, FIRS2, MIPAS-B), airborne (MIPAS-STR), ground-based (Spitsbergen, Thule, Kiruna, Harestua, Jungfraujoch, Izaña, Wollongong, Lauder), and spaceborne (ACE-FTS) observations. With few exceptions we found very good agreement between these instruments and MIPAS with no evidence for any bias in most cases and altitude regions. For balloon-borne measurements typical absolute mean differences are below 0.05 ppbv over the whole altitude range from 10 to 39 km. In case of ACE-FTS observations mean differences are below 0.03 ppbv for observations below 26 km. Above this altitude the comparison with ACE-FTS is affected by the photochemically induced diurnal variation of ClONO2. Correction for this by use of a chemical transport model led to an overcompensation of the photochemical effect by up to 0.1 ppbv at altitudes of 30–35 km in case of MIPAS-ACE-FTS comparisons while for the balloon-borne observations no such inconsistency has been detected. The comparison of MIPAS derived total column amounts with ground-based observations revealed no significant bias in the MIPAS data. Mean differences between MIPAS and FTIR column abundances are 0.11±0.12×1014 cm−2 (1.0±1.1%) and −0.09±0.19×1014 cm−2 (−0.8±1.7%), depending on the coincidence criterion applied. χ2 tests have been performed to assess the combined precision estimates of MIPAS and the related instruments. When no exact coincidences were available as in case of MIPAS – FTIR or MIPAS – ACE-FTS comparisons it has been necessary to take into consideration a coincidence error term to account for χ2 deviations. From the resulting χ2 profiles there is no evidence for a systematic over/underestimation of the MIPAS random error analysis.

International audience; Emissions of air pollutants in and around urban areas lead to negative health impacts on the population. To estimate these impacts, it is important to know the sources and transport mechanisms of the pollutants accurately. Mexico City has a large urban fleet in a topographically constrained basin leading to high levels of carbon monoxide (CO). Large point sources of sulfur dioxide (SO2) surrounding the basin lead to episodes with high concentrations. An Eulerian grid model (CAMx) and a particle trajectory model (FLEXPART) are used to evaluate the estimates of CO and SO2 in the current emission inventory using mesoscale meteorological simulations from MM5. Vertical column measurements of CO are used to constrain the total amount of emitted CO in the model and to identify the most appropriate vertical diffusion scheme. Zenith sky UV spectroscopy is used to estimate the emissions of SO2 from a large power plant and the Popocatépetl volcano. Results suggest that the models are able to identify correctly large point sources and that both the power plant and the volcano impact the MCMA. Modelled concentrations of CO based on the current emission inventory match observations suggesting that the current total emissions estimate is correct. Possible adjustments to the spatial and temporal distribution can be inferred from model results. Accurate source and dispersion modelling provides feedback for development of the emission inventory, verification of transport processes in air quality models and guidance for policy decisions.

International audience; Total column amounts of CO, CH4, CO2 and N2O retrieved from SCIAMACHY nadir observations in its near-infrared channels have been compared to data from a ground-based quasi-global network of Fourier-transform infrared (FTIR) spectrometers. The SCIAMACHY data considered here have been produced by three different retrieval algorithms, WFM-DOAS (version 0.5 for CO and CH4 and version 0.4 for CO2 and N2O), IMAP-DOAS (version 1.1 and 0.9 (for CO)) and IMLM (version 6.3) and cover the January to December 2003 time period. Comparisons have been made for individual data, as well as for monthly averages. To maximize the number of reliable coincidences that satisfy the temporal and spatial collocation criteria, the SCIAMACHY data have been compared with a temporal 3rd order polynomial interpolation of the ground-based data. Particular attention has been given to the question whether SCIAMACHY observes correctly the seasonal and latitudinal variability of the target species. The present results indicate that the individual SCIAMACHY data obtained with the actual versions of the algorithms have been significantly improved, but that the quality requirements, for estimating emissions on regional scales, are not yet met. Nevertheless, possible directions for further algorithm upgrades have been identified which should result in more reliable data products in a near future.

Total column amounts of CO, CH4, CO2 and N2O retrieved from SCIAMACHY nadir observations in ist near-infrared channels have been compared to data from a ground-based quasi-global network of Fourier-transform infrared (FTIR) spectrometers. The SCIAMACHY data considered here have been produced by three different retrieval algorithms, WFM-DOAS (version 0.5 for CO and CH4 and version 0.4 for CO2 and N2O), IMAP-DOAS (version 1.1 and 0.9 (for CO)) and IMLM (version 6.3) and cover the January to December 2003 time period. Comparisons have been made for individual data, as well as for monthly averages. To maximize the number of reliable coincidences that satisfy the temporal and spatial collocation criteria, the SCIAMACHY data have been compared with a temporal 3rd order polynomial interpolation of the ground-based data. Particular attention has been given to the question whether SCIAMACHY observes correctly the seasonal and latitudinal variability of the target species. The present results indicate that the individual SCIAMACHY data obtained with the actual versions of the algorithms have been significantly improved, but that the quality requirements, for estimating emissions on regional scales, are not yet met. Nevertheless, possible directions for further algorithm upgrades have been identified which should result in more reliable data products in a near future.

International audience; Total column amounts of CO, CH4, CO2 and N2O retrieved from SCIAMACHY nadir observations in its near-infrared channels have been compared to data from a ground-based quasi-global network of Fourier-transform infrared (FTIR) spectrometers. The SCIAMACHY data considered here have been produced by three different retrieval algorithms, WFM-DOAS (version 0.4, 0.41 for CH4), IMAP-DOAS (version 0.9) and IMLM (version 5.5) and cover the January to December 2003 time period. Comparisons have been made for individual data, as well as for monthly averages. To maximize the number of reliable coincidences that satisfy the temporal and spatial collocation criteria, the SCIAMACHY data have been compared with a temporal 3rd order polynomial interpolation of the ground-based data. Particular attention has been given to the question whether SCIAMACHY observes correctly the seasonal and latitudinal variability of the target species. The ensemble of comparisons, discussed in this paper, demonstrate the capability of SCIAMACHY, using any of the three algorithms, to deliver products for the target species under consideration, which are already useful for qualitative geophysical studies on a global scale. It is expected that the remaining uncertainties in the data products will decrease in future versions of the algorithm to also allow more quantitative investigations on a regional scale.