I. De Smedt

Trends, seasonal variability and dominant NOx source derived from a ten year record of NO2 measured from space

[1] For the period 1996–2006, global distributions of tropospheric nitrogen dioxide (NO2) have been derived from radiances measured with the satellite instruments GOME (Global Ozone Monitoring Experiment) and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY). A statistical analysis is applied to derive trends and seasonal variability for this period on a global scale. The time series of the monthly NO2 columns for these ten years have been fitted with a linear function superposed on an annual seasonal cycle on a grid with a spatial resolution of 1 by 1 .W e see significant reductions (up to 7% per year) in NO2 in Europe and parts of the eastern United States, and a strong increase in Asia, most particularly in China (up to 29% per year) but also in Iran and Russia. By comparing the data with the cloud information derived from the same satellite observations, the contribution of lightning to the total column of NO2 is estimated. The estimated NO2 from lightning is, especially in the tropics, in good agreement with lightning flash rate observations from space. The satellite observed seasonal variability of NO2 generally correlates well with independent observations and estimates of the seasonal cycle of specific NOx sources. Source categories considered are anthropogenic (fossil fuel and biofuel), biomass burning, soil emissions and lightning. Using the characteristics of the seasonal variability of these source categories, the dominant source of NOx emissions has been identified on a global scale and on a 1 by 1 grid.

Intercomparison of SCIAMACHY nitrogen dioxide observations, in situ measurements and air quality modeling results over Western Europe

[1] The Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) satellite spectrometer provides detailed information on the nitrogen dioxide (NO 2) content in the planetary boundary layer. NO 2 tropospheric column retrievals of SCIAMACHY and its predecessor Global Ozone Monitoring Experiment are characterized by errors of the order of 40%. We present here a new SCIAMACHY tropospheric retrieval data set for the year 2003. The cloud free satellite observations are compared to surface measurements and simulations over western Europe performed with the regional air-quality model CHIMERE. The model has a resolution of 50 km similar to the satellite observations. For these comparisons, averaging kernels are applied to the collocated model profiles to remove the dependency of the comparison on a priori NO 2 profile information used in the retrieval. The consistency of both SCIAMACHY and CHIMERE outputs over sites where surface measurements are available allows us to be confident in evaluation of the model over large areas not covered by surface observations. CHIMERE underestimates surface NO 2 concentrations for urban and suburban stations which we mainly attribute to the low representativeness of point observations. No such bias is found for rural locations. The yearly average SCIAMACHY and CHIMERE spatial NO 2 distributions show a high degree of quantitative agreement over rural and urban sites: a bias of 5% (relative to the retrievals) and a correlation coefficient of 0.87 (n = 2003). On a seasonal basis, biases are smaller than 20% and correlation coefficients are larger than 0.75. Spatial correlations between both the model and satellite columns and the European Monitoring and Evaluation Program (EMEP) emission inventory are high in summer (r = 0.74, n = 1779) and low in winter (r = 0.48, n = 1078), related to seasonal changes in lifetime and transport. On the other hand, CHIMERE and SCIAMACHY columns are mutually consistent in summer (r = 0.82) and in winter (r = 0.79). This shows that CHIMERE simulates the transport and chemical processes with a reasonable accuracy. The NO 2 columns show a high daily variability. The daily NO 2 pollution plumes observed by SCIAMACHY are often well described by CHIMERE both in extent and in location. This result demonstrates the capabilities of a satellite instrument such as SCIAMACHY to monitor the NO 2 concentrations over large areas on a daily basis. It provides evidence that present and future satellite missions, in combination with CTM and surface data, will contribute to improve quantitative air quality analyses at a continental scale. Citation: Blond, N., K. F. Boersma, H. J. Eskes, R. J. van der A, M. Van Roozendael, I. De Smedt, G. Bergametti, and R. Vautard (2007), Intercomparison of SCIAMACHY nitrogen dioxide observations, in situ measurements and air quality modeling results over Western Europe,

Reductions of NO2 detected from space during the 2008 Beijing Olympic Games

During the 2008 Olympic and Paralympic Games in Beijing (from 8 August to 17 September), local authorities enforced strong measures to reduce air pollution during the events. To evaluate the direct effect of these measures, we use the tropospheric NO2 column observations from the satellite instruments GOME-2 and OMI. We interpret these data against simulations from the regional chemistry transport model CHIMERE, based on a 2006 emission inventory, and find a reduction of NO2 concentrations of approximately 60% above Beijing during the Olympic period. The air quality measures were especially effective in the Beijing area, but also noticeable in surrounding cities of Tianjin (30% reduction) and Shijiazhuang (20% reduction). Copyright 2009 by the American Geophysical Union.

Sulfur dioxide vertical column DOAS retrievals from the Ozone Monitoring Instrument: Global observations and comparison to ground-based and satellite data

We present a new data set of sulfur dioxide (SO2) vertical columns from observations of the Ozone Monitoring Instrument (OMI)/AURA instrument between 2004 and 2013. The retrieval algorithm used is an advanced Differential Optical Absorption Spectroscopy (DOAS) scheme combined with radiative transfer calculation. It is developed in preparation for the operational processing of SO2 data product for the upcoming TROPOspheric Monitoring Instrument/Sentinel 5 Precursor mission. We evaluate the SO2 column results with those inferred from other satellite retrievals such as Infrared Atmospheric Sounding Interferometer and OMI (Linear Fit and Principal Component Analysis algorithms). A general good agreement between the different data sets is found for both volcanic and anthropogenic SO2 emission scenarios. We show that our algorithm produces SO2 columns with low noise and is able to provide accurate estimates of SO2. This conclusion is supported by important validation results over the heavily polluted site of Xianghe (China). Nearly 4 years of OMI and ground-based multiaxis DOAS SO2 columns are compared, and an excellent match is found. We also highlight the improved performance of the algorithm in capturing weak SO2 sources by detecting shipping SO2 emissions in long-term averaged data, an unreported measurement from space.

Substantial Underestimation of Post-Harvest Burning Emissions in the North China Plain Revealed by Multi-Species Space Observations

The large-scale burning of crop residues in the North China Plain (NCP), one of the most densely populated world regions, was recently recognized to cause severe air pollution and harmful health effects. A reliable quantification of the magnitude of these fires is needed to assess regional air quality. Here, we use an eight-year record (2005–2012) of formaldehyde measurements from space to constrain the emissions of volatile organic compounds (VOCs) in this region. Using inverse modelling, we derive that satellite-based post-harvest burning fluxes are, on average, at least a factor of 2 higher than state-of-the-art bottom-up statistical estimates, although with significant interannual variability. Crop burning is calculated to cause important increases in surface ozone (+7%) and fine aerosol concentrations (+18%) in the North China Plain in June. The impact of crop fires is also found in satellite observations of other species, glyoxal, nitrogen dioxide and methanol, and we show that those measurements validate the magnitude of the top-down fluxes. Our study indicates that the top-down crop burning fluxes of VOCs in June exceed by almost a factor of 2 the combined emissions from other anthropogenic activities in this region, underscoring the need for targeted actions towards changes in agricultural management practices.

Impact of Short‐Term Climate Variability on Volatile Organic Compounds Emissions Assessed Using OMI Satellite Formaldehyde Observations

A major feedback between climate and atmospheric chemistry lies in the meteorological dependence of the emissions of biogenic volatile organic compounds (BVOCs), precursors of important climate forcers, aerosols, and ozone. Whereas the short‐term response of BVOC emissions to meteorological drivers is fairly well simulated by current emission models, it is yet unclear whether models can faithfully predict their response to climate change, given the scarcity of long observation records of BVOC fluxes. Here we take advantage of the high yield of formaldehyde (HCHO) in the oxidation of VOCs and use a long‐term spaceborne record of HCHO observations in combination with model simulations to show that (i) HCHO interannual variability is primarily driven by climate through its impacts on photochemistry, vegetation fire occurrence, and above all, biogenic emissions and (ii) the HCHO record validates the interannual variability of biogenic emissions calculated by the state‐of‐the‐art Model of Emissions of Gases and Aerosols from Nature (MEGAN) emission model in vegetated regions.

Investigating the Impact of the Economic Recession Over Mediterranean Urban Regions on Satellite-Based Formaldehyde Columns; Comparison with Chemistry Transport Model Results

Formaldehyde (CH2O) is an important indicator of tropospheric hydrocarbon emissions and photochemical activity. CH2O is a high-yield intermediate product from the oxidation of Non-Methane Volatile Organic Compounds (NMVOCs) emitted by anthropogenic, biogenic, and biomass burning activities. For the past 30 years CH2O can be measured from space in the near-UV by solar backscatter instruments. An increased trend in CH2O over big cities around the Mediterranean has been observed from space since the beginning of the financial crisis. This fact could be associated with the enhanced use of wood and pellets for domestic/central heating during cold days, diesel being over-taxed and hence too expensive. This change on the fuel type, apart from more frequent PM10 episodes, is also reflected in CH2O emissions. We use satellite measurements to study the temporal variability of the winter-months CH2O column in order to ascertain the increased biomass burning emissions in urban areas which contribute to elevated levels of smog. We also validate the satellite retrievals using a chemistry transport model and test the ability of observations to reproduce geographical and seasonal variability in CH2O emissions over the Southern Europe.