Supplementary Discussion for Richter et al., Significant Increase in Tropospheric Nitrogen
Dioxide Over China Observed from Space, Nature 2005
Error estimates for changes in tropospheric NO2 columns as derived from satellite
measurements.
The error budget of satellite measurements of tropospheric NO2 columns has been discussed
in detail in several publications (Richter et al. (2002), Martin et al. (2003), Boersma et al.
(2004)). Here, some points specific to this study are discussed, mainly based on questions and
comments of 4 anonymous reviewers.
Overall Error budget:
Briefly, the main contributions to the error are
 random fitting uncertainties (small)
 uncertainties related to the subtraction of the stratospheric contributions (relatively
small)
 uncertainties from residual clouds (significant)
 uncertainties from satellite sampling (significant if number of measurements small due
to clouds)
 uncertainties of the airmass factor (dominant)
An overall assessment of errors leads to numbers of 5E14-1E15 molec/cm2 for the absolute
error and 40 - 60% relative errors for monthly averages over polluted areas (Richter et al.
(2002), Martin et al. (2003), Boersma et al. (2004)). Many of the uncertainties in the airmass
factor (AMF) are systematic (e.g. profile shape, surface reflectivity, aerosol estimate). If the
same airmass factor is used for each year as in this study, for a trend analysis only the changes
in these parameters contribute to the error. Thus, the error in the relative change of NO2
column over a given location is much smaller than the absolute error on the column. Based on
the detailed studies listed above, we estimate the errors on the annual relative changes to be
 negligible from fitting uncertainties
 negligible from stratospheric correction
 < 5% from changes in profile shape
 < 5% from changes in surface reflectivity
 < 5% from changes in aerosols (except for China, where 10% are estimated, see
below)
 <10% from clouds and sampling
Assuming that the errors act independently, the overall error of the annual change in NO2
column over polluted areas is estimated to be 13% over Europe and the US and 16% over
China.
Estimation of detection limit for annual changes
The detection limit of the satellite measurements is determined by many different factors,
including
 fitting error
 errors in stratospheric correction
 errors in radiative transfer
Here, we have only treated the additive part of the error which is dominated by fitting errors
and the error in stratospheric correction and is about 0.5-1.0 10E15 molec/cm2 for an
individual measurement. With roughly 50 measurements per year in a 0.5° x 0.5° grid box,
and assuming random errors, this corresponds to 0.7 -1.4 10E14 molec/cm2 detection limit for
an annual mean.
Impact of possible changes in surface reflectivity
Changes in surface reflectivity could potentially explain part of the observed increase in NO2
columns over China. However,
 the NO2 column changes are consistent between summer and winter which makes
changes in winter surface reflectance an unlikely explanation for the observations
 snow covered scenes are identified by the FRESCO cloud retrieval algorithm and are
not used in the analysis
 GOME intensities show only an increase of < 5% from 1996 to 2001 over China, most
of it between 1997 and 1998 with little changes afterwards. This behaviour is quite
different from the exponential increase in NO2 columns observed over the same area.
 we do not know of any measurements indicating that surface reflectivity has
systematically increased in China from 1996 to 2002 while at the same time surface
reflectivity over Europe has decreased
We therefore conclude that interannual changes in surface reflectivity contribute to the overall
uncertainty in the measurements, but are a very unlikely explanation of the systematic NO2
column changes observed over China and Europe.
Impact of possible changes in aerosol loading
Trends in aerosol loading could also influence the observed NO2 columns. Depending on the
type of aerosol (absorbing black carbon or reflecting sulphate or sand) and the relative vertical
distributions of NO2 and aerosols, an increase in aerosol loading could both lead to an
increase or decrease in the observed NO2 signal. In most cases, an increasing aerosol content
will reduce the observed signal as part of the NO2 is “hidden” below the aerosol layer which
has a similar effect as a thin cloud. Under these circumstances, the observed change in NO2
columns would be a lower estimate of the real change.
Whether or not aerosol loading has at all increased over China from 1996 to 2002 is not clear.
While TOMS data show a clear increase in UV absorbing aerosol optical depth from 1980 to
2000, there is no trend in the data after 1996 (Massie et al., 2004). In an inventory study,
Streets et al 2003 estimate that both Sulphur Dioxide and Black Carbon emissions in China
were significantly lower in 2000 than in 1995 which would result in a decreased aerosol load.
On the other hand, we don’t know of any study reporting on measured aerosol trends from
1996 to 2002 over China in spite of many reports of severe aerosol loading in the
industrialised parts of China.
As the information on aerosol trends over China is inconclusive, it is difficult to quantitatively
estimate the impact of aerosols on the NO2 column changes observed. As a conservative
limit, we assume that the impact of a possible change in aerosols over China from 1996 to
2002 is no larger than the total impact of aerosols on NO2 retrieval over the US, which was
estimated to be 5 - 10% in a study by Martin et al. (2003).
Impact of using an airmass factor that does not account for changes in emissions
Changes in emissions as suggested over China will change the atmospheric profiles of NO2
and thereby also the measurement sensitivity or airmass factors. It should however be noted,
that the airmass factor does not depend on the absolute amount of NO2 in the boundary layer
but rather on the relative vertical distribution. If only the absolute numbers are changed, the
AMF remains constant, at least in an optically thin atmosphere.
If however the vertical distribution changes, for example by large emissions in an area which
used to have background conditions, using a time invariant AMF will lead to a systematic
underestimation of the NO2 column. Similarly, any region in which the model used for the
AMF calculation has too large surface sources of NOx, the column will be overestimated.
For the trends over China analysed here, use of a constant AMF leads to a systematic
underestimation, making the assessment a conservative lower limit. On the other hand,
implementation of an AMF with increasing emissions over China would create an increasing
trend in GOME NO2 even if the atmospheric NO2 column remained the same. We therefore
believe that our approach is to be preferred if the focus is on trend determination from the
measurements.
References
Boersma, K. F., Eskes, H. J. & Brinksma E. J., Error Analysis for Tropospheric NO 2 Retrieval from Space, J.
Geophys. Res., 109, doi:10.1029/2003JD003962, (2004).
Martin, R. V., Jacob, D. J., Chance, K., Kurosu, T. P., Palmer P. I. & Evans, M. J., Global inventory of nitrogen
oxide emissions constrained by space-based observations of NO2 columns, J. Geophys. Res., 108, 4537-4548,
(2003).
Massie, S. T., Torres, O. &Smith, S. J., Total Ozone Mapping Spectrometer (TOMS) observations of increases
in Asian aerosol in winter from 1979 to 2000, J. Geophys. Res., 109, D18211, doi:10.1029/2004JD004620,
(2004).
Richter, A. & Burrows, J. P., Retrieval of Tropospheric NO2 from GOME measurements, Adv. Space Res., 29,
16673-1683, (2002).
Streets D. G., et al., An inventory of gaseous and primary aerosol emissions in Asia in the year 2000, J.
Geophys. Res., 108 (D21), 8809, doi:10.1029/2002JD003093, (2003).