Nitrogen dioxide (NO2) and Formaldehyde (CH2O)
introduction

• Support to Air pollution monitoring
  • Global tropospheric NO2
  • Global tropospheric CH2O

• Nitrogen dioxide and Formaldehyde
• Observing NO2 and CH2O from space
• Uncertainties in retrieval
• Retrieval of tropospheric NO2 and CH2O

Nitrogen dioxide and Formaldehyde

• NOx and volatile organic compounds are emitted in large quantities due to human activities such as traffic and industry. In the summer months this mixture produces photochemical smog.

• The chemical budget of ozone in the troposphere is largely determined by the concentration of NOx. The knowledge of the ozone distribution and its budgets is strongly limited by a severe lack of observations of NO and NO2 in the troposphere.

• The variability of NOx concentrations in the lower troposphere in industrialised areas and near biomass burning sites is very large. The few available point observations of NOx, on the ground or from aircraft measurements, are therefore difficult to translate to regional scale concentrations.

  The residence time of NOx in the lower troposphere is short. Therefore observations of boundary layer NOx contain important information on the emissions of nitric oxide, and the trends in these emissions.

• The free troposphere is also of great importance for the ozone budget, and for CH4 and CO oxidation processes. Again these budgets are uncertain due to a limited knowledge of NOx. The degree of NOx transfer from the boundary layer is difficult to model, and NOx emissions from lightning are very uncertain.

Formaldehyde (CH2O) is a major intermediate gas in the oxydation of methane and many other hydrocarbons. The lifetime of formaldehyde is short, and the photolysis reactions and reaction with OH form a major source of CO. Because of the short lifetime of several hours, the presence of formaldehyde signals hydrocarbon emission areas. Formaldehyde is important, since it is a measure of the total amount of oxidised hydrocarbons, and together with NOx quantifies the chemical ozone production. The presence of elevated levels of CH2O is related to the release of hydrocarbons (e.g. ethene, isoprene, and methane) by forests, biomass burning, traffic and industrial emissions.
 

Observing NO2 and CH2O from space

Good signal-to-noise ratio's (of about 20) are obtained for NO2 with the Differential Optical Absorption Spectroscopy (DOAS) retrieval technique. This is related to the absence of strong other absorbers (e.g. ozone) in this spectral interval. GOME has also demonstrated the ability to observe boundary layer NO2: on top of a stratospheric background enhanced column NO2 amounts are observed that correlate well with known industrialised areas. GOME has also detected NO2 plumes originating from biomass burning events and enhanced CH2O concentrations over forests. Furthermore, there are signatures of lightning-produced NO2 in the GOME data set.

Vertical column of NO2 for the month March 1997, derived from the measurements of GOME. The blue/green background is of stratospheric origin. On top of this, the tropospheric concentrations related to emissions in industrialised regions are clearly visible as red areas.

Uncertainties in retrieval

1. The largest uncertainties are due to clouds, as they will shield near-surface NO2 and CH2O from the view of the satellite. The retrieval depends very sensitively on the presence of clouds, and even small coud fractions (between 5 to 20%) have a major impact. High quality observations of the cloud properties (at least cloud fraction and cloud top height) are necessary for a quantitative retrieval.

2. The surface albedo directly influences the sensitivity of GOME for boundary layer NO2 and CH2O. High quality albedo maps in the relevant spectral range are essential.

3. Profiles of NO2 are characterised by a large range of variability. At emission areas the NO2 concentration will peak at the surface, while downstream of such areas the pollution plume will peak at higher altitudes. The profile of NO2 will be determined by aspects like the distribution of emission sources, the stability and height of the boudary layer, wet removal of nitric acid, deep convection and long-range transport by the wind. All these aspects are strongly varying in time and space.

4. The NO2 columns measured by GOME consist of comparable stratospheric and tropospheric contributions. The stratospheric background has to be quantified carefully in order to derive the tropospheric column. Atmospheric dynamics is well known to generate significant variability in stratospheric tracer amounts, consistent with for instance HALOE observations of NO2. A standard approach applied to GOME is based on the assumption that stratospheric NO2 is zonally uniform, or at least has only a small longitudinal variation. Such simplification makes the retrieval of small tropospheric NO2 columns practically impossible.

5. Another source of uncertainty are aerosols. Thick aerosol layers influence the radiation field and the sensitivity of GOME for near-surface NO2 and CH2O.

One important improvement of SCIAMACHY as compared to GOME is the smaller ground pixel size. In this way the variability of NO2 and CH2O can be better resolved, and the fraction of cloud-free pixels will be larger, improving the quality of the retrieval.
 

Retrieval of tropospheric NO2 and CH2O

These model forecast fields will be collocated with the GOME/SCIAMACHY observations, and the radiative transfer modelling in the retrieval will be performed based on the model trace gas profile and temperature profiles. The modelled stratospheric NO2 distribution will be employed to derive a tropospheric column by subtracting the modelled (assimilated) stratosphere from the measured column. The retrieval is coupled to cloud top height and cloud fraction retrievals derived from the GOME/SCIAMACHY data, and the retrieval will be coupled to high quality albedo maps.

The approach has been implemented and is applied to the GOME data. As an example the monthly-mean NO2 map for March 1997 is shown above. This map is derived based on the GOME Data Processor version 2.7 slant column amounts, profile estimates from the TM3 chemistry-transport model and cloud fraction and cloud top pressures from the Fresco algorithm.