• Ricardo study shows satellite data can provide critical insight in designing pollution emission management strategy in UK cities

Industrial Emissions

Ricardo study shows satellite data can provide critical insight in designing pollution emission management strategy in UK cities

Ricardo emission and air quality modelling specialists have developed an improved method for the quantification of air pollutant emissions utilising satellite observation data. The novel approach provides better insight into total annual nitrogen oxides (NOx) emissions, average nitrogen dioxide (NO2) lifetime levels, seasonal variation, and estimated weekday/weekend concentrations.

In testing the methodology, Ricardo estimated annual NOx emissions and their temporal variation for three highly densified cities in the UK (London, Manchester and Birmingham), for 2019. As a control measure, findings were then compared with figures recorded via the UK National Atmospheric Emissions Inventory (NAEI) for the same year. The study found findings calculated using satellite data (TROPOMI) were more consistent with NAEI figures than that of another recent study conducted for the same year, using other pollution quantification methods. In some instances, discrepancies between nationally recorded levels and findings from the alternate study were as high as 105% variation. This is in stark contrast to the findings produced using satellite data which were found to have a much better correlation with national standards, with the biggest discrepancy recorded coming in at 33% variation.

In addition to an improvement in annual values, the study demonstrated that satellite data is also useful in understanding the temporal variation (seasonal climatic changes) of emissions and lifetime (residual) estimates, especially regarding variations in pollution quantities between seasons and on a day-to-day basis e.g. weekdays vs. weekends. 

Such insight into ambient pollution changes is helpful to understand the knock-on effects on personal pollution exposure and where to target local mitigation efforts to be most effective. For instance, findings from Ricardo’s study suggest that the mitigation of NO2 concentrations in Manchester could require a different emission management strategy than London and Birmingham. Policies in Manchester could be focussed in a targeted manner on reducing weekend emissions (where both emission rate and NO2 lifetime are longest), whereas in London and Birmingham focussing mitigation action on weekday emissions may be more beneficial to lowering pollution levels, as there is less seasonal variation in emissions and weekday emissions are much greater than weekend levels.

Matthieu Pommier, Principal Consultant in Ricardo’s air quality modelling team commented, ‘This work highlights the high potential in the use of satellite observations in designing more effective emission management strategy. For example, in Manchester, a seasonal approach can be beneficial to reach different objectives i.e., targeting summer emissions might help to reduce the number of consecutive hours of exposure to NO2 exceedance caused by an increased presence of NO2 in the air, as found in this study. Similarly, targeting the reduction of autumnal emissions might help decrease NO2 concentrations given average NOx emissions tend to be higher around this time compared to other seasons.

Ricardo’s study illustrates that satellite instruments are key observers of the changes in emitting activities and the data collected can allow quantification of the changes in emissions.

Alternative approaches to quantifying emissions are usually limited to calculating annual values only for pollutant emissions. Ricardo’s satellite data method opens the door for more granular reporting and improved insight into emissions concentrations that can be used to better inform pollution abatement strategies in future.

For full details of the study, please see here.

For more information on satellite data observations or how our emissions team can support your organisation, please contact Ricardo.


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