Conference Agenda

Earth’s climate is influenced profoundly by anthropogenic greenhouse gas (GHG) emissions. The lack of available global CO₂ and CH₄ measurements makes it difficult to estimate their emissions accurately. Satellite measurements would be very helpful for understanding the global CO₂ and CH₄ flux distribution if CO₂ and CH₄ column-averaged dry air mole fractions (XCO₂ and XCH₄) could be measured with a precision of better than 2 ppm. To this point, one of our main objectives of this research is to use a combination of ground-based measurements of CO₂ and CH₄ and data from current satellite observations (TanSat, GOSAT/-2, OCO-2/-3 and TROPOMI) to validate and evaluate satellite retrievals with retrieval inter-comparisons, to assess them against model calculations and to ingest them into inverse methods to assess surface flux estimates of CO₂ and CH₄.

The aim of Global Stocktakes requires more accurate and larger coverage measurement in future missions. The next generation of TanSat mission, known as TanSat-2 mission kicked-off two years ago. To improve the measurement coverage and repeat frequency, TanSat-2 satellite will sample atmosphere at 1500 km wide across-track swaths, with a footprint size of 3 km ×3 km and hence the measurement covers the global in daily flight. The NIR/SWIR hyperspectral measurement on backscattered sunlight by the spectrometers onboard TanSat-2 includes 0.4 um (ultraviolet), 0.76 um (O₂ A), 1.61 um (CO₂) and 2.0 um (CO₂) bands. There will also be an aerosol optical property to improve the XCO₂ and XCH₄ accuracy. The TanSat-2 XCO₂ measurement precision is designed to be better than 1 ppm for each pixel.

The preliminary OSSE on global and regional scale indicates high efficiency for the TanSat 2 emission in error reduction for top-down flux estimation. We also develop a new method to separate the ecosystem and anthropogenic emission which will be helpful for atmospheric inversion method toward the Global Stocktake. The TanSat mission has been used in city carbon emission signature investigation, which show the capability of TanSat-2 to detect the anthropogenic emission signals.

To evaluate TanSat-2 potential for estimating surface CH₄ fluxes at a weekly scale, we designed a series of observing system simulation experiments (OSSEs) using an existing Ensemble Kalman Filter framework. These experiments focused on the sensitivity of flux estimates to systematic errors (μ) and random errors (σ) in XCH₄ measurements, as well as the impact of satellite swath width. Our findings indicate that with a target precision of 8 ppb, the globally inverted CH₄ flux exhibits an accuracy of 5.1 ± 1.7%, with a reduction of 86.6 ± 11.2% in the a priori uncertainties. The accuracy in the Northern Hemisphere mid-latitudes reaches at 1.9 ± 1.6%. Increasing temporal resolution from 1-month to 1-week reduces flux discrepancies in most regions, except Africa, which is also highly sensitive to XCH₄ bias. In particular, the accuracy of inverted CH₄ fluxes in North Africa declines by 20.4% for each ppb increase in global μ levels. It leads to a 2.3% rise (~11 Tg/yr) in the global total discrepancy. The σ value affects both the accuracy and precision of optimized fluxes, especially in North American Boreal and Tropical Asia, but these effects can be mitigated by expanding the satellite swath width from 1,000 to 3,000 pixels. CH₄ fluxes in Eurasia Temperate and North America Temperate show higher reliability and resilience to variations in swath width and measurement uncertainties. For μ-sensitive regions like Africa, expanding swath width alone offers limited improvements, highlighting the need for complementary observations from other platforms.

To understand the hot-spot emission measurement capability of TanSat-2 mission, we developed a parametric model and a database to swift assess the quantification capability of satellites and configure satellite technique characteristic for certain detection goal. we get the detection thresholds of several satellites and find that the high spatial resolution is much more important to monitor CH₄ emissions than measurement precision. For quantifying emissions, improving measurement precision is a more effective way. A more accurate simulation model and estimation method are needed for the assessment of the quantified capacity of satellites for low-intensity emissions.

The Climate Change Act (Northern Ireland) 2022 (Act) sets a target of an at least 100% reduction in net zero greenhouse gas (GHG) emissions by 2050 (i.e., net zero emissions by 2050) for Northern Ireland compared to baseline, along with interim targets including an at least 48% reduction in net emissions by 2030. The greenhouse gases include carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6) and nitrogen trifluoride (NF3). There is greater difference around emissions in Northern Ireland / Ireland compared to other parts of the United Kingdom due to the relative importance of methane and nitrous oxide emissions in the agriculture sector (Figure 1). In the Northern Ireland, the GHG emissions are mainly from agriculture, buildings, transport and power generation (Figure 2). The fossil fuel has been replaced by renewable energy eventually for the carbon emission reduction.

Figure 1. Composition of emissions between Northern Ireland and UK in 2022.

Figure 2. Greenhouse gas emissions by sector in Northern Ireland, 2022

Figure 3. Change in emissions by sector from base year -2022 in Northern Ireland

Comparing with the other sectors the GHG emissions from the agricuture has increased 15% with the baseline in 1990 (Figure 3). The GHG emissions from the agricultural takes 29.1% compared to the other sector and methane (26%) is mainly produced by livestock (Figure 3). It needs to find out the GHG emissions in agricultural sector in more detailed.

Globally, methane is the second most important greenhouse gas (GHG). Its contribution to global warming is estimated at 27 times that of carbon dioxide, over a 100 year period. Biogenic methane (methane produced by animals and plants) is one of the predominant GHG emissions emitted from global agricultural, the majority of which is originates from ruminant livestock as enteric or manure methane. The agricultural sector has a target to reduce its greenhouse gas emissions by 25% by the year 2030, relative to 2018 levels, developing strategies to reduce enteric methane will be crucial to meeting Ireland’s agricultural climate targets. A 500 kg beef animal on a high concentrate diet produces 230 g methane per day and a 550 kg dairy cow grazing on pasture emits about 320-330 grams of methane per day. Methane associated with ruminant livestock production accounts for three-quarters (74%) of Irish agricultural GHG emissions. As a result, reducing the volume of methane produced by ruminant livestock, will be critical to achieving the agricultural sectors 2030 GHG emissions reduction target.
Figure 4. Methane emission through the year from 2009 to 2022 in Ireland

Emissions of methane are more difficult to estimate than carbon dioxide, and the agriculture sector makes up a larger share of Northern Ireland’s emissions than in other parts of the UK. This greenhouse gas emission estimates are based on a wide range of data sources and sources of uncertainty include statistical differences, assumptions, proxy datasets and expert judgement. In addition, the natural variability in the processes that are being modelled introduce uncertainty. The uncertainties presented are a close approximation of the 95% confidence interval. For the percentage reduction between the base year and 2022, the uncertainty interval ranges from 20% to 37%. Therefore, data from satellite will be used to support the analysis with verified accuracy. The GHG production monitored by the Satellites are retrieved and validated by the project partner from China from the year 1990 to 2022 on the geolocation of Ireland, N. Ireland and Island (Figure 4). From the data analysis, it has found that the differential between them is less than 2%. Detailed emission on CO2 and CH4 will be analysed along with the emission through the agriculture applications.

Aerosols and clouds are important factors affecting radiative forcing and climate change, and improving the ability to observe high-precision profiles of their optical properties will reduce uncertainties in climate model simulations and forecasting systems. High spectral atmospheric detection lidar is capable of wide-area, continuous, dynamic, and full-time integrated monitoring of aerosols and clouds. Three-dimensional wind field data with high spatial and temporal resolution is an important observational basis for an in-depth understanding of the structure and evolutionary characteristics of the atmospheric boundary layer, and the heat-momentum-matter exchange and equilibrium process between the upper and lower troposphere. In order to achieve global high-precision wind field and aerosol profile observations by satellite-borne Doppler wind measurement lidar and high spectral resolution lidar, it is necessary to carry out long-term and rigorous calibration and verification.

The Chinese atmospheric environment monitoring satellite DQ-1 has been successfully launched on 16 April 2022. As an integrated detection scientific research satellite, it will serve as an important part of Chinese atmospheric environment monitoring system. The DQ-1 equips five sensors including an a Particulate Observing Scanning Polarimeter (POSP), a Directional Polarization Camera (DPC), an Environmental trace gas Monitoring Instrument (EMI) and a Wide Swath Imaging system (WSI). As the primary payload, Aerosol and Carbon Detection Lidar (ACDL) is a high spectral resolution lidar (HSRL) with two-wavelength polarization detection, that can be utilized to derive the aerosol optical properties. In this study, we develop radiation calibration and optical parameter retrieval algorithms for ACDL channels in daytime and nighttime scenarios, and carry out cloud phase classification and aerosol classification studies through layer identification and scene classification algorithms. The aerosol and cloud optical properties products of the ACDL include total depolarization ratio, backscatter coefficient, extinction coefficient, lidar ratio and color ratio. After the calibration and comparison iterations, the high-resolution standardized data products of the ACDL aerosol channel developed in this study are widely used in joint multi-sensor observations and meteorological and environmental monitoring.

The ESA’s EarthCARE satellite was launched in May 2024. The HSRL payload ATLID will provide vertical profiles of aerosols and thin clouds. It will operate at a wavelength of 355 nm and have a high-spectral resolution receiver and depolarization channel. In this study, after temporal and spatial matching and quality control of the ACDL and ATLID on-orbit observation data products, synchronized observations are carried out for the scenarios of dust, cirrus clouds and polar stratospheric clouds. Through the establishment of a worldwide comparison and validation process for satellite-ground and satellite-satellite observations, the two lidars are jointly compared on optical parameters such as attenuation backscatter coefficient and depolarization ratio. The observation capability and data accuracy of the spaceborne high spectral resolution lidar are verified, and iterative optimization directions are provided for the calibration program and data processing algorithms.

Aeolus was the first satellite mission to acquire profiles of Earth’s wind on a global scale. It was launched on 22 August 2018 and finished its nominal lifetime on 30 April 2023 before an assisted re-entry on 28 July 2023. The Aeolus satellite’s only payload is a direct detection DWL ALADIN. During its lifetime, it has measured the global wind profiles and aerosol profiles simultaneously and continuously for more than 4 years. In order to guarantee the data quality and improve the inversion algorithm, the reprocessing of the Aeolus data products to improve data quality will continue in the next 5 years during phase F. This research utilizes the China Coherent Doppler Lidar Network (CDLnet) to assess the reprocessed data from Aeolus, and evaluating and analyzing the data quality.

In this study, we performed a detailed analysis of the ionospheric zonal currents from equator to middle latitudes during the recent intense geomagnetic storm on 10-12 May 2024. Magnetic measurements from two ground stations in the America sector, as well as that from the Swarm satellites have been used. Extreme intensified eastward and westward EEJ values, reaching 300 mA/m and -400 mA/m have been observed during the storm main and recovery phases, respectively. Such intense EEJ values have never been observed during the past 11-year flying period of Swarm mission. In addition, the storm responses of zonal currents at low and middle latitudes have been analyzed, by using the vertical magnetic field component from Swarm. These zonal currents showed quite prominent dependences on magnetic local time. In the noon sector, eastward currents were dominated under both quiet and storm conditions, with slightly intensification during storm. Conversely, the zonal currents in the dawn and dusk sectors displayed abrupt current reversals within 30 minutes after the sudden storm commencement, characterized by sustained eastward (dawn) and westward (dusk) perturbations persisting for the rest one and a half days. Most interestingly, two eastward zonal current jets were found located at ±25º magnetic latitudes at the dusk sector, emerged with westward zonal currents at other low and middle latitudes. To our knowledge, this is the first time to report such narrow current jets at middle latitudes during storms.