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Tropospheric Composition Reactive Gases

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The main UV-absorbing aerosol types occurring over Africa are desert dust and biomass burning aerosols. Their abundances can be characterised by using Absorbing Aerosol Index (AAI) data from GOME and SCIAMACHY. Time series of regionally averaged AAI from 1995 to 2008 show the seasonal variations of aerosols in Africa. When relating the zonally averaged daily AAI to monthly mean precipitation data, they indicate monsoon-controlled atmospheric aerosol loadings, which are different for the West African and East African monsoons owing to their different dynamics caused by the asymmetric distribution of land masses around the equator. Fig. 3-5 clearly shows that the seasonal variation of the aerosol distribution is linked to the seasonal cycle of the monsoonal wet and dry periods in both areas. During dry periods, the AAI varies freely, driven by emissions from deserts and biomass burning events. During wet periods the AAI depends linearly on the amount of precipitation due to scavenging of aerosols and the prevention of aerosol emissions from wet surfaces. (see fig. 3-5)

3.2 Tropospheric Composition – Reactive Gases

Emissions of greenhouse gases are not the only anthropogenic impact onto the lowest layer of the Earth’s atmosphere. Pollution and air quality have become a major concern in an ever increasing industrialised world. SCIAMACHY is able to detect and monitor the global, regional and local signatures of trace gases contributing to air pollution and to follow how emissions evolve with time.

Nitrogen Dioxide – NO2

NO2 is an important indicator of air pollution and a cause of summer smog. NO2 catalyses ozone production contributes to acidification and also adds to radiative forcing. The main sources of NO2 are anthropogenic in origin, e.g. power plants, vehicular traffic, forced biomass burning and both heavy and agricultural industry. Other but slightly less important sources comprise natural biomass burning, lightning and microbiological soil activity. NO2 emissions have increased by more than a factor of 6 since pre-industrial times, with concentrations being highest in large urban areas.Global monitoring of tropospheric NO2 emissions is a crucial task. SCIAMACHY’s predecessor GOME has already demonstrated the unique ability to monitor tropospheric air pollution. Fig. 3-6 shows a global survey of tropospheric NO2 as seen by SCIAMACHY. The inset in Fig. 3-6 presents a time series of these concentrations over China. The periodic trend in NO2 columns each year can mainly be explained by seasonal variations in energy consumption while the overall increase in tropospheric NO2 over China is a result of the increase in industrial activity (Richter et al. 2005a). The inset also demonstrates how well SCIAMACHY matches with GOME and GOME-2. NO2 vertical columns of both instruments perfectly overlap around the turn of the year 2002 and from 2007 onwards.


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fig. 3-6

Global survey of tropospheric vertical column (VC) NO2 for 2009. Clearly visible are the industrialised regions in the northern hemisphere and the regions of biomass burning in the southern hemisphere. The inset illustrates how NO2 concentrations have risen in China from 1996-2009. The trend analysis uses data from GOME (1996-2002) and SCIAMACHY (2003-2009). While 'old' industrialised countries were able to stop the increase of NO2 emissions, the economical growth in China turns out to be a strong motor for pollution. (Graphics: A. Richter, IUP-IFE, University of Bremen)

Due to its higher spatial resolution (60 km ´ 30 km as compared to 320 km ´ 40 km for GOME), SCIAMACHY enables very detailed observations of polluted regions. As a result of these new datasets, individual cities (Beirle et al. 2004) and even large power plants (Kim et al. 2009) can be identified. Similar small scale structure in NO2 emissions can also be detected over the oceans. The high sensitivity and spatial resolution of the SCIAMACHY measurements permits localising frequently used ship routes (Richter et al. 2004). Using data from GOME, SCIAMACHY and GOME-2, Franke et al. (2009) could even derive temporal changes in these ‘tiny’ signatures of anthropogenic activity.

Particularly interesting are studies concerning the global trend in NO2 concentrations (Richter et al. 2005a, Stavrakou et al. 2008, van der A et al. 2008). By combining SCIAMACHY results with those of previous missions, e.g. GOME, it is possible to investigate how the tropospheric NO2 load has changed over the past decade. A strong increase in nitrogen dioxide is observed by SCIAMACHY in countries and areas with a booming economy, particularly in China (see inset Fig. 3-6), while in Europe, SCIAMACHY has observed a stabilisation of NO2 levels which is attributed partly to slightly increased traffic emissions after a period of reducing nitrogen dioxide levels in the 1990’s as a result of EU regulations. For the US, SCIAMACHY results indicate a decrease in NO2 emissions related to the recent implementation of pollution controls for power plants (Kim et al. 2006).

The spatial and temporal characteristics of a multi-year dataset provide much improved constraints for attempts to identify main emission sources and to quantify emission strengths by inverse modelling. It also facilitates the derivation of independent top-down estimates of emissions not only on a country-by-country basis but even on regional scales. Konovalov et al. (2008, 2010) investigated such trends within Europe for a 10 year time period showing that while emissions are decreasing in many countries, emissions have increased especially in the Mediterranean area, along the coastlines, as well as in Eastern Europe. Van der A et al. (2008) analysed the spatial and temporal patterns in a multi-year dataset of GOME and SCIAMACHY tropospheric NO2 and identified the most dominating emission sources (fig. 3-7) from this data. Whereas in the northern hemisphere, the NO2 mainly stems from anthropogenic sources and from soils, biomass burning is the dominating origin of tropospheric NO2 in the southern hemisphere.


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fig. 3-7

Dominant NOx source identification based on analyses of the time series of measured tropospheric NO2 from GOME and SCIAMACHY satellite observations (1996-2006). (Graphics: van der A et al. 2008, reproduced by permission of the American Geophysical Union)

By combining SCIAMACHY NO2 observations at 10:00 local time with NO2 observations from OMI at 13:30 local time, it even becomes possible to get a first glimpse on the diurnal variations of tropospheric chemistry and emissions from space. These measurements suggest a decrease in tropospheric NO2 between 10:00 and 13:30 over fossil fuel source regions due to photochemical loss. Over tropical biomass burning regions, the opposite effect – an increase due to a midday peak in emissions - is obvious (Boersma et al. 2008).


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