Conference Agenda

Three-dimensional (3-D) radiative transfer effects of clouds on trace gases and aerosols have been studied extensively using satellite products and model simulations. In the vicinity of clouds, satellite measured reflectances are higher than the cloud-free scenes at the bright side of clouds and lower in the shadows. In order to understand the 3-D effects of clouds, we have developed a 3-D Monte Carlo radiative transfer model at KNMI (called MONKI). MONKI has been used to simulate TROPOMI measurements at UV wavelengths with polarization.

TROPOMI is a satellite spectrometer with a spatial resolution of 3.5 km x 5.5 km. The objective of TROPOMI is to provide accurate atmospheric composition products. We have used MONKI to simulate the TROPOMI NO₂ airmass factors and reflectances at 340 and 380 nm at different cloudy scenes. Various cloud optical thickness, cloud heights, and surface albedo values are specified in the simulations. Then Absorbing Aerosol Index (AAI) values are calculated for the simulated scenes using TROPOMI AAI algorithm. Based on the AAI features in the simulated scenes, we re-analysed the AAI data in the TROPOMI product in the shadows. For the NO₂ products, we simulated the NO₂ airmass factors using MONKI and compared with NO₂ airmass factor calculated using 1-D model simulations. Finally we analysed the TROPOMI NO₂ products in the shadowed pixels and in the cloud-free, shadow-free pixels to quantify the impacts of shadows on the NO₂ product.

Shadows from clouds and buildings present in high spatial resolution satellite imagery are typically filtered out in image processing. However, the shadows can be used to retrieve aerosol and surface properties simultaneously. In a new retrieval algorithm, the aerosol optical thickness is retrieved using the contrast between shadowed pixels and bright pixels and compared with AERONET data.

In the presentation we will report the progresses on the 3-D model simulations of AAI, NO₂ AMFs, impacts of shadows on NO₂ products, and the aerosol retrievals using shadows.

Northern Ireland's contribution to the UK's fifth carbon budget mandates a reduction in emissions of at least 35% by 2030 compared to the 1990 level. In comparison to the rest of the United Kingdom, Northern Ireland has relatively high percentages per capita emission in the agricultural, transportation, residential, LULUCF (land use, land use change, and forestry) and power sector. The electricity generated by the renewable energy is increasing since 2003 significantly. The increasing rate is nearly three times for the N. Ireland than the UK. In the year 2021, the electricity generated by the wind has increased to 47% (Figure 1). In this project we have conducted investigations into the current status of carbon emission in Northern Ireland (NI) along with the electricity generation situation through the renewable energy like wind and solar energy applications. Further more the types of renewable energy sources have been analysed. As comparison, the CO2 emission distribution in the NI has been observed by the GHGSat and a program has been developed to carry on analysis with the CO2 emission data collected during the past ten years. This developed tool will help us to study the effect of using the renewable energy for the power generation with the CO2 distribution in the atmosphere in the N.Ireland. It is also, the analysis will help us to understand the influence of different types of renewable energy to the CO2 reduction.

Figure 1 shows the total electricity energy consumption in N. Ireland along with the increased portion of electricity generated by the renewable energy since 2008. The electricity consumption in the past 15 year is reducing while the percentage of the electricity generated by the renewable energy is continuing increased from 6% in 2008 to 47% in 2022.

The Figure 2 shows the renewable energy applications since 1990 to 2022 with capacity up to 48MW. The installation of the renewable energy sites is continuing over time. It is aiming to find out the effect of CO2 reduction with the geo-distribution of the renewable applications.

Figure 3 shows the mirror image of the CO2 distribution in the N. Ireland in the past ten years.