Emissions estimation from satellite retrievals: A review of current capability

TLDR: In this article, a comprehensive literature review and comprising input by both satellite experts and emission inventory specialists, the review identifies several targets that seem promising: large point sources of NOx and SO2, species that are difficult to measure by other means (NH3 and CH4, for example), area sources that cannot easily be quantified by traditional bottom-up methods (such as unconventional oil and gas extraction, shipping, biomass burning, and biogenic sources), and the temporal variation of emissions (seasonal, diurnal, episodic).

About: This article is published in Atmospheric Environment.The article was published on 2013-10-01 and is currently open access. It has received 338 citations till now. The article focuses on the topics: Satellite & Temporal resolution.

Figures

Fig. 1. Methane concentrations over North America in JuneeAugust 2004 as observed by SCIAMACHY (column mixing ratios) and INTEX-A (mixing ratios below 700 hPa). The middle panels show the corresponding GEOS-Chem model values, and the bottom panels show the observed-model differences.

Fig. 6. Comparison of MOPITT, AIRS, TES, and IASI retrieved annual average CO column amounts for the period 2002e2012 over four different world regions: E. China, E. USA, Europe, and India (adapted from Worden et al., 2013).

Fig. 8. Modeled and measured boundary-layer SO2 tropospheric lifetimes over the eastern U.S. and global lifetimes of SO2 using a combination of numerical modeling as well as in situ and remote observations (adapted from Lee et al., 2011a). This material is reproduced with permission of John Wiley & Sons, Inc.

Fig. 2. Flight paths of the CalNex aircraft campaign in California in AprileJune 2010 and the locations of TES and GOSAT satellite observations during this period.

Fig. 9. NO2 columns for the month of July 2011 over the Mid-Atlantic states during DISCOVER-AQ. The CMAQmodel matches urban observations well but underestimates rural NO2. Increasing the photolysis rate of alkyl nitrates in CB05 improves model-measurement agreement.

Fig. 5. Spatial distributions of anthropogenic NOx emissions at 1% #1.25%: bottom-up inventory for the year 2005 (top); inventory predicted from OMI NO2 observations for the year 2010 (middle). Inventory totals refer to colored regions only. The difference between the OMI-derived emissions for 2010 minus the bottom-up emissions for 2005 is shown at the bottom (adapted from Lamsal et al., 2011).

Frequently asked questions

Q1. What are the contributions mentioned in the paper "Emissions estimation from satellite retrievals: a review of current capability" ?

This review article addresses the question of how well the authors can relate the satellite measurements to quantification of primary emissions and what advances are needed to improve the usability of the measurements by U. S. air quality managers. Techniques that enhance the usefulness of current retrievals ( data assimilation, oversampling, multi-species retrievals, improved vertical profiles, etc. ) are discussed. Finally, the authors point out the value of having new geostationary satellites like GEO-CAPE and TEMPO over North America that could provide measurements at high spatial ( few km ) and temporal ( hourly ) resolution. Built on a comprehensive literature review and comprising input by both satellite experts and emission inventory specialists, the review identifies several targets that seem promising: large point sources of NOx and SO2, species that are difficult to measure by other means ( NH3 and CH4, for example ), area sources that can not easily be quantified by traditional bottom-up methods ( such as unconventional oil and gas extraction, shipping, biomass burning, and biogenic sources ), and the temporal variation of emissions ( seasonal, diurnal, episodic ). 

Q2. What are the future works mentioned in the paper "Emissions estimation from satellite retrievals: a review of current capability" ?

This is possible with further collaboration between emission inventory developers and the satellite research communities. For example, given the lower tropospheric lifetime of fine PM ( a couple of days to a week ), a satellite must be able to achieve a return frequency of 1e2 days in order to study air pollution episodes related to wildfires, dust storms, and heavy haze. Identification of the practical problems faced routinely by emission inventory developers can be used to guide further interaction between the communities. If the detection limit for such emissions could be improved, there is great potential to enhance the conventional bottom-up inventory methods. 

Q3. What techniques can be used to evaluate the Jacobian?

Moreefficient sensitivity techniques, such as direct decoupled or adjoint methods, may also be used to evaluate the Jacobian (e.g., Napelenok et al., 2008). 

Q4. What is the name of the class of atmospheric species that is implicated in environmental problems?

Nitrogen oxides (NOx) are an important class of atmospheric species that are implicated in a number of environmental problems, including the formation of tropospheric ozone and aerosols, acidification, eutrophication, and human health effects. 

Q5. Why is the SO2 signal readily detectable by several instruments?

Because the volcanic source strength is great, the SO2 signal is readily detectable by several instruments and more easily converted to an estimate of emissions than the SO2 released by anthropogenic sources. 

Q6. What is the only satellite instrument to demonstrate the instantaneous multispectral retrievals necessary?

MOPITT is the only satellite instrument to demonstrate the instantaneous multispectral retrievals necessary for an independent measurement of a trace-gas concentration in the lowermost troposphere (Worden et al., 2010). 

Q7. What is the largest source of error?

The largest source of error appears to be the “smearing” associated with the time delay between isoprene emission and HCHO formation (Marais et al., 2012). 

Q8. What is the common method of detecting chemical species in the atmosphere?

Chemical species in the atmosphere are detected by the absorption, or attenuation, of radiation of specific wavelengths along the path that the radiation travels through the atmosphere. 

Q9. What can be used to guide further interaction between the communities?

Identification of the practical problems faced routinely by emission inventory developers can be used to guide further interaction between the communities. 

Q10. What are the two instruments that are particularly valuable in an air pollution context?

Two Aura instruments are particularly valuable in an air pollution context: the Ozone Monitoring Instrument (OMI) (Levelt et al., 2006) and the Tropospheric Emission Spectrometer (TES) (Beer et al., 2001). 

Q11. What is the role of CO in controlling OH levels?

CO is the dominant sink for the hydroxyl radical (OH), and as such plays a critical role in controlling OH levels with implications for a wide range of atmospheric gases. 

Q12. What is the role of the anthropogenic point sources in the U.S. air quality?

The ability to detect changing emissions from these types of sources has the potential to aid in the verification of region-wide pollution control policies and in determining the compliance of individual point sources with emission control requirements. 

Q13. What is the effect of modernization on the emission rate of the two smelters?

Annual SO2 emissions from the larger of the two smelters, Ilo, were estimated at 0.3 (0.2e0.5) Tg. Interestingly, the emission rate appeared to decrease by about 40% between late 2004 and early 2005, which the authors of the paper speculate may have been caused by modernization of the plant and an increase in the SO2 capture rate. 

Q14. What are the main types of sources that are important to characterize?

There are several types of natural area sources that are important to characterize from the perspectives of assessing the contribution of anthropogenic emissions to total emissions, understanding atmospheric chemistry and the production of secondary species, and assembling complete emissions datasets to run CTMs and other atmospheric models. 

Q15. What is the process of generating an estimate of production efficiency?

The analytical process involves generating an estimate of production efficiency (number of molecules produced per flash) and then multiplying that by an estimate of the number of flashes in a given time period over a given area to yield an estimate of the NOx produced. 

Q16. What are the types of emissions sources that are submitted to the EIS?

Based on the AERR requirements, S/L/T agencies submit emissions of point, nonpoint, on-road mobile, nonroadmobile, and fires emissions sources. 

Q17. What are the methods for reducing emissions of NOx and SO2 from stationary sources?

There are a number of methods for significantly reducing emissions of NOx and SO2 from the effluent of stationary sources, most importantly Selective Catalytic Reduction (SCR) for NOx and flue-gas desulfurization (FGD) for SO2. 

Q18. How did Zhang et al. (2012) study the extent of the highly polluted regions?

They observed that the highly polluted regions (areasdominated by anthropogenic emissions) in China have expanded from the east to the central and the west, and new highly polluted regions have formed throughout the nation in the past 15 years. 

Q19. What was the reason for the use of satellites to study SO2 emissions?

Despite the coarse spatial resolution of GOME and the relatively large uncertainties for individual observations, it was felt at that time that there was potential for being able to derive rough estimates of SO2 emissions from satellite retrievals. 

Q20. What is the need for a national approach to estimating biomass burning activities?

And there is a continued need in the regulatory community for satellite products that allow estimation of biomass burning activities using software such as SMARTFIRE to support a nationally consistent approach that brings together the best of the satellite and on-the-ground information for a robust inventory.