Satellite observations of ozone and nitrogen dioxide : from retrievals to emission estimates

B. Mijling

Research output: ThesisPhd Thesis 1 (Research TU/e / Graduation TU/e)

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Abstract

In the last decades, measurements of atmospheric composition from satellites have become very important for scientific research as well as applications for monitoring and forecasting the state of the atmosphere. Instruments such as GOME-2, and OMI look at backscattered sunlight in nadir view, measuring the ultraviolet and visible spectrum in high resolution. Launched in a sun-synchronous orbit at ??800 km altitude, they scan the Earth’s surface daily in 14–15 orbits, providing a homogeneous dataset with (almost) daily global coverage. Combining the spectral measurements with radiative transport models, concentrations can be inferred for important trace gases such as ozone (O3) and nitrogen dioxide (NO2). Chemical transport models can be used to calculate the strength and location of the underlying emissions. Long time series of satellite retrievals give insight on how human activity contributes to changes of atmospheric composition, affecting health and climate. Information in the vertical distribution of ozone can be retrieved from the sharp decrease in the ozone absorption cross-section in the ultraviolet spectrum. Chapter 2 deals with the question how the performance of the ozone profile retrieval algorithm (OPERA) can be improved. To produce consistent global datasets, the algorithm needs to have good global performance, while short computation time facilitates the use of the algorithm in near real time applications. Because the retrieval is ill-posed (in the sense that many profiles give similar simulated spectra within the measurement errors), the solution depends on a priori (climatological) ozone profiles. The non-linearity of the problem asks for an iteration scheme to find the best fitting solution numerically. We use the convergence behaviour of the iteration as a diagnostic tool for the ozone profile retrievals from the GOME instrument for February and October 1998. In this way, we reveal several retrieval problems of different origin, and we improve issues related to the Southern Atlantic Anomaly, low cloud fractions e.g. above deserts, and ozone cross sections. The a priori ozone climatology and its associated variability is also an important source for retrieval problems. By using a priori ozone profiles that are selected on the expected total ozone column, retrieval problems due to anomalous ozone distributions (such as in the ozone hole) can be avoided. Applying the algorithm adaptations improve the convergence statistics considerably, not only increasing the number of successful retrievals, but also reducing the average computation time, due to less iteration steps per retrieval. For February 1998, non-convergence was brought down from 10.7% to 2.1%, while the mean number of iteration steps (which dominates the computational time) dropped 26% from 5.11 to 3.79. Total nitrogen dioxide columns can be retrieved from space in the 405–465 nm window, but the NO2 spectrum does not contain any significant height information. Instead, data assimilation techniques can be used to distinguish the tropospheric part from the stratospheric part, which gives valuable information of NO2 in the lowest part of the atmosphere. Here it acts as an air pollutant, often from man-made origin. The case study in Chapter 3 evaluates how NO2 air pollution can be controlled with air quality measures. Due to strong economic growth in the last decades, air pollution in large Chinese megacities has become a serious issue. In reparation for the Olympic Games in Beijing in 2008, extensive air quality measures were taken to improve air quality during the event, affecting traffic, industry and power production. We evaluate the effect of the air quality measures on reducing air pollution, by analysing the tropospheric NO2 retrievals over the greater Beijing area before, during and after the Olympic Games. To compensate for the strong variability due to meteorology, we compare the observations with model simulations from the regional chemistry transport model CHIMERE based on a pre-Olympic emission inventory. The relative change between observation and simulation shows that the measures caused a reduction of tropospheric NO2 column 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). In the months after the Olympic events, NOx emissions in Beijing show a slow recovery towards pre-Olympic levels. In a next step, we use the difference between NO2 observations and simulations to adjust the emission inventory used by the model. Emission inventories of air pollutants are crucial information for policy makers and form important input data for air quality models. Chapter 4 presents a new algorithm specifically designed to use daily satellite observations of column concentrations for fast updates of emission estimates of short-lived atmospheric constituents on a mesoscopic scale (??25??25 km2). The algorithm needs only one forward model run from a chemical transport model to calculate the sensitivity of concentration to emission, using trajectory analysis to account for transport away from the source. By using a Kalman filter in the inverse step, optimal use of the a priori knowledge and the newly observed data is made. We apply the algorithm for NOx emission estimates of East China, using the CHIMERE model on a 0.25 degree resolution together with tropospheric NO2 column retrievals of the OMI and GOME-2 satellite instruments. Closed loop tests show that the algorithm is capable of reproducing new emission scenarios. Applied with real satellite data, the algorithm is able to detect emerging sources (e.g. new power plants), and improves emission information for areas where proxy data are not or badly known (e.g. shipping emissions). It is shown that chemical transport model runs with the daily updated emission estimates provide better spatial and temporal agreement between observed and simulated NO2 concentrations, which facilitates an improved air quality forecast for East China. Monthly emission estimates give valuable insight in changing biogenic and anthropogenic activity. In Chapter 5, the emission estimation algorithm is used to construct a monthly NOx emission time series for 2007–2010 from tropospheric NO2 observations of GOME-2 over East Asia. Most Chinese provinces show a strong positive trend during this period, related to the country’s economic development. Negative emission trends are found in Japan and South Korea, which can be attributed to a combined effect of local environmental policy and global economic crises. The algorithm is also used to quantify the direct effect of regional NOx emissions on tropospheric NO2 concentrations elsewhere. Due to transport of air pollution, high NOx emissions not only affect local air quality, but also contribute significantly to tropospheric NO2 in remote downwind areas.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Applied Physics
Supervisors/Advisors
  • Kelder, Hennie, Promotor
  • Levelt, Pieternel, Promotor
  • A, van der, R.J., Copromotor, External person
Award date11 Oct 2012
Place of PublicationEindhoven
Publisher
Print ISBNs978-94-6191-411-8
DOIs
Publication statusPublished - 2012

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