Shipping Emissions in Rapidly Growing Seaports in Africa Determined with TROPOMI

Lu, Gongda; Marais, Eloïse A.; Vohra, K.G.; Zhu, Lei

doi:10.1002/essoar.10505854.1

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thanks to high spatial resolution, satellite sensors play a vital role as an alternative (to bottom-up estimations) means for estimating industrial emissions from large power plants, e.g., India [18], Greece [19], and South Africa [20], as well as from big cities in Mexico [21], France [22], and the USA [23]. Due to high spatial resolution, TROPOMI revealed information on emitters that was previously considered as challenging to estimate, e.g., compressor stations in Siberia [24], shipping emissions in African harbours [25], and ONG exploration in Canada [26].…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variation of NO2 Vertical Column Densities (VCDs) over Poland: Comparison of the Sentinel-5P TROPOMI Observations and the GEM-AQ Model Simulations

2021

View full text Add to dashboard Cite

The TROPOMI instrument aboard Sentinel-5P is a relatively new, high-resolution source of information about atmosphere composition. One of the primary atmospheric trace gases that we can observe is nitrogen dioxide. Thanks to TROPOMI capabilities (high resolution and short revisit time), one can describe regional and seasonal NO2 concentration patterns. Thus far, such patterns have been analysed by either ground measurements (which have been limited to specific locations and only to the near-surface troposphere layer) or numerical models. This paper compares the TROPOMI and GEM-AQ derived vertical column densities (VCD) over Poland, focusing on large point sources. Although well established in atmospheric science, the GEM-AQ simulations are always based on emission data, which in the case of the energy sector were reported by stack operators. In addition, we checked how cloudy conditions influence TROPOMI results. Finally, we tried to link the NO2 column number densities with surface concentration using boundary layer height as an additional explanatory variable. Our results showed a general underestimation of NO2 tropospheric column number density by the GEM-AQ model (compared to the TROPOMI). However, for the locations of the most significant point sources, we noticed a systematic overestimation by the GEM-AQ model (excluding spring and summer months when TROPOMI presents larger NO2 VCDs than GEM-AQ). For the winter months, we have found TROPOMI NO2 VCD results highly dependent on the choice of qa_value threshold.

show abstract