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ASSESSING EFFECT OF CARBON EMISSION REDUCTION WITH INTEGRATING RENEWABLE ENERGY IN URBAN
RANGE ENERGY GENERATION SYSTEMS
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The growth rate of atmospheric carbon dioxide (CO2) reflects the net effect of emissions and uptake resulting from anthropogenic and natural carbon sources and sinks. The anthropogenic emissions of CO2 are primarily generated by human [...] |
Dr. Ming Jun HUANG, Ulster University, UK |
Dr. Xingying Zhang, China Meteorological Administration, CHINA |
Atmosphere |
The growth rate of atmospheric carbon dioxide (CO2) reflects the net effect of emissions and uptake resulting from anthropogenic and natural carbon sources and sinks. The anthropogenic emissions of CO2 are primarily generated by human activities, including fossil fuel combustion, energy used in transport sectors, etc. In the urban, energy used in domestic and transport sectors takes more than 80% of the total energy consumption in the UK. In the past decade, renewable energy (RE) technologies, such as solar and wind power, geothermal and hydro power, have gradually been deployed in domestic buildings for heating and electricity. However global fossil CO2 emissions are still more than 4% higher in 2019 compared with those in 2015. In the UK, the recent campaign of CO2 reductions has proposed a policy of the phase-out of coal, and by 2050, the gas boiler could be as obsolete as the coal fire in UK homes. Although many policies for decarbonisation, like the Paris Agreement and integrating REs into urban buildings have been introduced, it is not clear what is the contribution of REs to CO2 reduction. Therefore it is imperative to study the impact of REs integration with existing power generations on the CO2 reduction by using satellite monitoring, analysing the REs supply with on-site response and artificial intelligent technology. Since 1983, the World Meteorological Organization (WMO) has established various Global Atmosphere Watch stations worldwide in different latitudes and longitudes to continuously monitor changes of atmospheric CO2 and CH4 concentrations at near-surface level. To understand the transport mechanisms of global greenhouse gases (GHG), JAXA launched Greenhouse gases Observing Satellite (GOSAT) and GOSAT-2 in 2009 and 2018 for clarifying the sources and sinks of CO2. NASA put the OCO-2 and OCO-3 satellites to operation in 2014 and 2019 for quantifying variations in the column averaged atmospheric CO2 dry air mole fraction, namely XCO2. Chinese carbon dioxide observation satellite (TanSat) was launched on 22 Dec 2016. These satellites provide the ability to retrieve XCO2, and their XCO2 data products have been used to improve our knowledge of natural and anthropogenic CO2 sources and sinks. The synergistic use of complementary measurements is not only addressing the carbon cycles, but also opens a unique opportunity to address some of the main knowledge gaps in atmospheric CO2 for the urban with the prevision of integration of REs into buildings for electricity and heating. The project aims at exploiting the synergic measurements together with REs technology and advanced AI to quantify the effect of REs in the terrestrial carbon cycle. Specifically the key objectives include: • Develop fusion algorithms for combining measurements from different satellites on required spatial and temporal scales for the urbans. • Develop retrieve algorithms of CO2 from satellite and combined measurements • Validate and apply GHG products of satellites to estimate CO2 concentration and distribution • Investigate the energy demand and the energy contribution of RE integration in the urban regions for heating and transportation. • Develop the methods of studying the effect of integrating the REs into urbans to reduce CO2 emission. • Provide policy makers with the evidence of CO2 reduction over regions that have integrated REs as energy suppliers. The proposed project involves a collaboration between the Sustainable Technology Centre at Ulster University, UK and the National Satellite Meteorological Centre (NSMC) at China Meteorological Administration (CMA). Work conducted by both teams are part of their respective research commitments, hence limited funding will be used to support this cooperation research. It is also expected the Dragon 5 program would provide certain amount of funding to support EU partners for attending symposia and for young scientists to carry out the project research.
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EXPLOITATION OF SATELLITE REMOTE SENSING TO IMPROVE OUR UNDERSTANDING OF THE MECHANISMS AND PROCESSES AFFECTING AIR QUALITY IN CHINA (EMPAC)
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This proposal addresses different aspects related to the air quality (AQ) over China: aerosols, trace gases and their interaction through different processes, including effects of radiation and meteorological, geographical and topographical [...] |
Prof.. Ronald van der A, The Royal Netherlands Meteorological Institute (KNMI), NETHERLANDS |
Prof.. Jianhui Bai, Institute of Atmospheric Physiscs, Chinese Academy of Sciences, CHINA |
Atmosphere |
This proposal addresses different aspects related to the air quality (AQ) over China: aerosols, trace gases and their interaction through different processes, including effects of radiation and meteorological, geographical and topographical influences. Detailed in situ measurements are combined with ground-based and satellite remote sensing which together provide complimentary information on the contributions from different sources and processes affecting AQ, with scales varying from the whole of China to local studies and from the surface to the top of the boundary layer and above. Different species contributing to air quality will be studied, i.e. aerosols, in AQ studies often represented as PM2.5 (mass of dry particles with in situ diameter smaller than 2.5 µm), trace gases such as NO2, NH3, Volatile Organic Compounds (VOCs) and O3. The primary source of information in these studies is the use of a variety of satellite-based instruments providing data on atmospheric composition using different techniques. Concentrations of atmospheric components are either retrieved by the EMPAC consortium or downloaded from public data services such as COPERNICUS. They are validated using reference data sets and evaluated by comparison with other satellite data over areas where no reference data are available. For the interpretation of satellite data and their use to AQ studies, a wide variety of data from other types of observations is used, providing complementary information on the species measured from satellites, as well as meteorological information and large-scale phenomena. In particular this proposal focuses on the relationship between satellite-based column-integrated properties and near-surface concentrations important for AQ which would allow for the use of satellites to provide AQ information on large spatial scales. To understand the satellite/surface relationships, detailed process studies will be undertaken, using ground/based in situ measurements, instrumented towers and drones, as well as remote sensing using lidar and Max-DOAS. A unique source of information on the vertical variation of NO2, O3, PM2.5 and BC is obtained from the use of an instrumented drone. The proposal is structured along three related topics: Aerosols, Trace Gases and biosphere/atmosphere interactions.
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GEOPHYSICAL AND ATMOSPHERIC RETRIEVAL FROM SAR DATA STACKS OVER NATURAL SCENARIOS
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The aim of this project consists in the development and application of processing methodologies to address two specific Sub-topics relevant for stack-based spaceborne applications. Sub-topic 1 concerns the internal structure of natural media, [...] |
Prof.. Stefano Tebaldini, Politecnico di Milano, ITALY |
Prof.. Mingsheng Liao, LIESMARS, Wuhan University, CHINA |
Atmosphere |
The aim of this project consists in the development and application of processing methodologies to address two specific Sub-topics relevant for stack-based spaceborne applications. Sub-topic 1 concerns the internal structure of natural media, and it is mapped to Dragon topic Solid Earth – Subsurface target detection. Sub-topic 2 concerns joint estimation of deformation and water vapour maps, and it is mapped to Dragon topic Solid Earth – Monitoring of surface deformation of large landslides. The topics above are of fundamental importance in the context of present and future spaceborne missions, which will allow increasingly more systematic use of multiple acquisitions thanks to improved hardware stability and orbital control. Indeed, the proposed activities are intended to support use of multi-pass data stacks from:o the upcoming P-Band mission BIOMASS. o future L-Band missions, such as the SAOCOM constellation, the upcoming Chinese L-Band bistatic Mission Lu-Tan1, and potentially Tandem-L and Rose-L.o the C-Band Sentinel Missions.Sub-topic 1 will consider as test sites a forested area in North-West Germany and a desert area in Namibia, which are under study in the context of the ESA campaigns TomoSense and DesertSAR. The activities will focus on processing SAR image stacks to extract information about forest structure and sub-surface terrain topography on forested areas, and about the internal structure of sand dunes and surface topography on desert areas. Estimation and compensation of ionospheric and tropospheric propagation effects will be considered as well. Given the availability of a large amount of reference data at both sites, the success of this study will be assessed by direct validation against reference data from in-situ measurements and products from airborne Tomography. During the first years of this study, the activities will proceed based on stacks of ALOS SAR images, which are currently available as archive products.Sub-topic 2 will consider two test sites: Kenya, of interest for retrieval of water-vapor and deformation over large scale, and Xilodou dam, characterized by on-going deformation, and at the same time, very humid and heavily vegetated conditions and rugged terrain. The objective is two-fold. For the generation of tropospheric products, for meteorological application, the synergic exploitation of distributed and permanent scatterers, is still an open issue, where the retrieval of absolute phase screen needs merging with GNSS and meteorological maps (ERA5, GACOS), where timeliness and efficiency is a must. The integration of DS and PS will in parallel by tested on difficult sites with fast and high resolution deformations in Xilodou.DeliverablesD1: Dragon symposium 2021: attendance and presentationsD2: Dragon symposium 2022: attendance, presentations, and journal papersD3: Dragon symposium 2023: attendance and presentationsD4: Dragon symposium 2024: attendance, presentations, and journal papersFundingThe activities are planned to start with two European Young Scientists from Politecnico di Milano:o Ing. Marco Manzoni, currently pursuing his PhD at PoliMi under ministerial funding granted until end of 2021. o Dr. Mauro Mariotti dÔÇÖAlessandro, working in the SAR group at PoliMi as Post-Doc research fellow under internal funding granted until end of 2021.A YS from University of Pisa, Dr. Claudia Zoppetti, Post-Doc collaborator under funding granted until January 2021, is also availableIt is important to note that the duration of the Dragon programme is significantly longer than the average time a University is able to grant funding for young researchers (PhD are given within a 3 year programme, research funding are typically granted on yearly basis). If the project is granted, future PhD students and Research Fellows from both PoliMi and University of Pisa will be involved in the proposed Dragon project in the next years.
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MONITORING GREENHOUSE GASES FROM SPACE
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EarthÔÇÖs climate is influenced Prof.oundly by anthropogenic greenhouse gas (GHG) emissions. Climate forecasts are needed so that we can prepare, mitigate and adapt to the changing climate. The forecasts require accurate information about the [...] |
Prof.. Hartmut Boesch, University of Leicester, Department of Physics and Astronomy, UK |
Prof.. Yi Liu, Institute of Atmospheric Physics, Chinese Academy of Sciences, CHINA |
Atmosphere |
EarthÔÇÖs climate is influenced Prof.oundly by anthropogenic greenhouse gas (GHG) emissions. Climate forecasts are needed so that we can prepare, mitigate and adapt to the changing climate. The forecasts require accurate information about the sources and sinks of natural and anthropogenic GHGs, in particular, carbon dioxide (CO2) and methane (CH4). Presently, GHG concentrations are observed using ground-based and satellite observations. While local sources can be observed using accurate in-situ measurements, remote sensing methods from satellites are needed to obtain global and regional coverage, which are important for climate research. A number of studies have indicated that uncertainties in regional CO2 and CH4 surface fluxes can be significantly reduced with global, unbiased, precise space-borne measurements which can lead to a more complete understanding of the CO2 and CH4 budget. The accuracy requirements of satellite remote sensing of atmospheric composition and, in particular, GHGs are challenging. Validation of measurements and their uncertainties and continuous development of retrieval methods are important for the success of satellite remote sensing systems, especially for GHGs where error requirements are demanding. Furthermore, sophisticated data assimilation methods and atmospheric transport models are needed to link atmospheric concentration to the underlying surface fluxes. The main objectives of this research project 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 intercomparisons, to assess them against model calculations and to ingest them into inverse methods to assess surface flux estimates of CO2 and CH4. The main geographic focus will be China but we will also take advantage of our global view provided by the space-borne data. Furthermore, we will look towards future observing systems from Europe and China. Specifically, we will use TCCON and Chinese ground-based measurements and extend the validation previously applied. AirCore Prof.ile observations of GHGs at Sodankyl├ñ will be used to support the validation at high latitudes. We will apply two independent retrieval algorithms available at University of Leicester and IAP to intercompare and advance retrieval methods. We will use the GEOS-Chem atmospheric transport model combined with Ensemble Kalman Filter to infer flux estimates of Chinese CO2 and CH4. No extra funding for this project is presently available. Work by both teams will be part of the normal scientific research. The Chinese team is funded by MOST and CAS, from which a limited amount of funding could be used to support international cooperation research. University of Leicester and University of Edinburgh will carry out the work using existing resources and by synergies with ongoing research projects funded by the National Centre for Earth Observations NCEO, NERC, ESA and the EU and the Finnish Meteorological Institute will use existing resources from the projects funded by the Finnish Academy, ESA and the EU.
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MONITORING OF GREENHOUSE GASES WITH ADVANCED HYPER-SPECTRAL AND POLARIMETRIC TECHNIQUES
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Greenhouse gas emissions lead to global warming, frequent extreme weather and increasing natural disasters. It has become a global focus to clarify the impact of carbon emissions and reduce carbon emissions. As the dominant technology of carbon [...] |
Dr. Jochen Landgraf, Netherlands Institute for Space Research (SRON), NETHERLANDS |
Dr. Hailiang Shi, Hefei Institutes of Physical Science(HIPS),Chinese Academy of Sciences(CAS), CHINA |
Atmosphere |
Greenhouse gas emissions lead to global warming, frequent extreme weather and increasing natural disasters. It has become a global focus to clarify the impact of carbon emissions and reduce carbon emissions. As the dominant technology of carbon emission and carbon cycle monitoring, satellite remote sensing plays an important role in global climate research, but there are still large errors in the inversion results of high value aerosol, cloud coverage and other areas, which greatly reduces the effective detection data rate. Therefore, it is an inevitable trend to develop new satellite remote sensing monitoring and inversion technology which can provide more precise carbon information. The inversion of greenhouse gases requires not only high-resolution atmospheric absorption spectrum, but also information such as AOD and cloud parameters at the same time. Therefore, GOSAT and TanSat satellites are equipped with hyper-spectral instruments and aerosol instruments. The first greenhouse gas payload GMI based on spatial heterodyne spectroscopy （SHS） was built on the Chinese GaoFen-5 satellite launched in May 2018, which includes two carbon dioxide bands, one methane band and one oxygen band. In addition, The Directional Polarimetric Camera (DPC) is the first Chinese multi-angle polarized earth observation satellite sensor, which is synchronously carried on this satellite for cloud and aerosol product acquisition. DPC employed a charge coupled device detection unit with 512×512 effective pixels from the 554×512 useful pixels, realizing spatial resolution of 3.3 km under a swath width of 1850 km. Meanwhile, DPC has 3 polarized channels (490, 670 and 865 nm) together with 5 non-polarized bands (443, 565, 763, 765 and 910 nm) and can obtain at least 9 viewing angles by continuously capturing series images over the same target on orbit. This proposal is mainly based on the new hyper-spectral payload GMI and polarization payload DPC to carry out the greenhouse gas inversion research. We can use DPC observation to invert high precision aerosol optical and physical properties to calculate the air mass factor (AMF) for the greenhouse retrieval with the hyper-spectral sensor GMI. By adopting an optimal estimation (OE) algorithm combined with the aerosol high-precision microphysical and optical characteristics from the DPC sensor to perform the inversion of greenhouses gases, we can improve the accuracy at low AOD loading and file the current gaps inversion in satellite retrieval in the high-value area of AOD. Finally, the inversion results of TanSat, GOSAT, OCO-2 and other satellite are used as verification data. This proposal can also be used to provide a wealth of real measured observation data for the design of future greenhouse gas sensor incorporating aerosols. This proposal is a joint project of Hefei Institutes of Physical Science, Chinese Academy of Sciences (HIPS-CAS), Space Research Organization Netherlands (SRON). No extra funding for this project is presently available. China is jointly funded by the State Administration of science, technology and industry of national defense (Civil Aerospace pre research project: main greenhouse gas monitor of multimodal atmosphere, with a fund of 8.6 million yuan) and the Chinese Academy of Sciences (key deployment project of the Academy: high spatial-temporal resolution greenhouse gas detection and application technology, with a fund of 7 million yuan), some of which can be used for international cooperative research. The European side is mainly funded by projects that have been approved for research in progress, which are funded by the Netherlands space research center.
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THREE DIMENSIONAL CLOUD EFFECTS ON ATMOSPHERIC COMPOSITION AND AEROSOLS FROM NEW GENERATION SATELLITE OBSERVATIONS
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About 70% of the Earth is covered by clouds, therefore clouds are often present in satellite observations. Cloud properties can be retrieved from satellite observation. Cloudy pixels are often screened before deriving atmospheric and surface [...] |
Dr. Ping Wang, The Royal Netherlands Meteorological Institute (KNMI), NETHERLANDS |
Prof.. Minzheng Duan, Institute of Atmospheric Physics, Chinese Academy of Science, CHINA |
Atmosphere |
About 70% of the Earth is covered by clouds, therefore clouds are often present in satellite observations. Cloud properties can be retrieved from satellite observation. Cloudy pixels are often screened before deriving atmospheric and surface properties. In the satellite products, cloud is typically assumed as a horizontal homogeneous layer. However, in reality cloud is a three dimensional (3D) object: clouds cast shadows on the ground surface or on lower clouds; clouds look brighter on the sun illuminated side and darker on the shadow side. The impacts of 3D cloud features on aerosol retrievals have been studied using high resolution satellite imagery data and lidar measurements. Clouds are also important in the trace gas retrievals. The research on the 3D cloud effects on trace gas retrievals is a new topic because the pixel size of the satellite spectrometers like GOME-2 is too big (40 km x 80 km) to see the 3D cloud effects. Since the launch of Sentinel-5p (S5p) in 2017, the trace gases are retrieved at a pixel size of 3.6 km x 5.6 km. We have seen the cloud shadows on the S5P images, which indicates the present of 3D cloud features in the S5p products. The objectives of the project are to analyze the impacts of the 3D clouds on trace gas retrievals, detect the cloud shadows, and derive aerosol and surface albedo products. Aerosol properties and surface albedo are important input parameters in the trace gas retrievals. Aerosol optical thickness (AOT) and surface albedo will be retrieved for selected scenes using the cloud shadow pixels. This is a complimentary method for the general used method nowadays. The algorithm will be demonstrated using Sentinel-2, Sentinel-5P, GF-1/6. The retrieved AOT will be validated from ground-based measurements and compared with Sentinel-3 aerosol products.We will detect cloud shadows from S5p and compared with collocated VIIRS data. The high resolution imagery of VIIRS will provide more accurate detection of cloud shadows and cloud edges on the S5p data. From selected scenes we will study the variation of trace gas column densities with the distance to the clouds. We will use the 3D radiative transfer components of the Earth Clouds and Aerosol Radiation Explorer (EarthCARE) simulator (ECSIM) together with 3D high resolution cloud fields generated using Large-Eddy Simulation (LES) model to simulate S5p/TROPOMI measurements. The simulations will help us to understand the shadow and the 3D cloud effects on the TROPOMI cloud, Absorbing Aerosol Index (AAI), AOT, and nitrogen dioxide (NO2) products. Ultimately, we plan to correct the impact of 3D clouds (shadows) on the Sentinel-5p/4/5 products. The project will use Sentinel-2/3/5p, GF-1/6 products and can be applied to S4/S5 after they are in orbit.The deliverable are reports, publications, and demonstration products and data analysis results. The KNMI team is partly supported by the User Support Programme Space Research of Dutch Research Council and KNMI internal funding. The IAP/CAS team is supported by IAP internal funding.The topic is Atmosphere. Subtopic is related to air quality but also related to greenhouse gases because the greenhouse gas products from satellite observations will also be impacted by 3D clouds and shadows.
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