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Register a new userA high-resolution gridded inventory of coal mine methane emissions for India and Australia
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Coal mines are globally an important source of methane and also one of the largest point sources of methane. We present a high-resolution 0.1deg x 0.1deg bottom-up gridded emission inventory for methane emissions from coal mines in India and Australia, which are among the top five coal-producing countries in 2018. The aim is to reduce the uncertainty in local coal mine methane emissions and to improve the spatial localization to support monitoring and mitigation of these emissions. For India, we improve the spatial allocation of the emissions by identifying the exact location of surface and underground coal mines and, we use a tier-2 Intergovernmental Panel on Climate Change (IPCC) methodology to estimate the emissions from each coal mine using country-specific measured emission factors. For Australia, we estimate the emission for each coal mine by distributing the state-level reported total emissions using proxies of coal production and the coal basin-specific gas content profile of underground mines. Comparison of our total coal mine methane emission from India with existing global inventories showed our estimates are about a factor 3 lower, but well within the range of the national Indian estimate reported to the United Nations framework convention on climate change (UNFCCC). For both countries, the new spatial distribution of the emissions shows a large difference from the global inventories. Our improved emissions dataset will be useful for air quality or climate modeling and while assessing the satellite methane observations.
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Two years of satellite observations were used to estimate the methane emission from coal mines in Queensland, the largest coal-producing state in Australia. The six analyzed surface and underground coal mines are estimated to emit 570+/-98 Gg a-1 in 2018-2019. Together, they account for 7% of the national coal production, while emitting 55+/-10% of the reported methane emission from coal mining in Australia. Most remarkably, 40% of the quantified emission came from a single surface mine (Hail Creek). While surface coal mining is generally assumed to be a relatively minor source of methane, this suggests we may have to rethink its importance in the global methane budget. Our findings call for increased monitoring and investment in methane recovery technologies for both surface and underground mines. Our results indicate that for two of the three locations our satellite-based estimates are significantly higher than reported to the Australian government.
Precise and high-resolution carbon dioxide (CO$_2$) emission data is of great importance of achieving the carbon neutrality around the world. Here we present for the first time the near-real-time Global Gridded Daily CO$_2$ Emission Datasets (called GRACED) from fossil fuel and cement production with a global spatial-resolution of 0.1$^circ$ by 0.1$^circ$ and a temporal-resolution of 1-day. Gridded fossil emissions are computed for different sectors based on the daily national CO$_2$ emissions from near real time dataset (Carbon Monitor), the spatial patterns of point source emission dataset Global Carbon Grid (GID), Emission Database for Global Atmospheric Research (EDGAR) and spatiotemporal patters of satellite nitrogen dioxide (NO$_2$) retrievals. Our study on the global CO$_2$ emissions responds to the growing and urgent need for high-quality, fine-grained near-real-time CO2 emissions estimates to support global emissions monitoring across various spatial scales. We show the spatial patterns of emission changes for power, industry, residential consumption, ground transportation, domestic and international aviation, and international shipping sectors between 2019 and 2020. This help us to give insights on the relative contributions of various sectors and provides a fast and fine-grained overview of where and when fossil CO$_2$ emissions have decreased and rebounded in response to emergencies (e.g. COVID-19) and other disturbances of human activities than any previously published dataset. As the world recovers from the pandemic and decarbonizes its energy systems, regular updates of this dataset will allow policymakers to more closely monitor the effectiveness of climate and energy policies and quickly adapt.
1) The annual cycle of atmospheric methane in southern high latitudes is extremely highly correlated with Antarctic sea ice extent. 2) The annual cycle of atmospheric methane in the Arctic is highly correlated with Antarctic or Arctic plus Antarctic sea ice extent. 3) We propose the global annual cycle of atmospheric methane is largely driven by Antarctic sea ice dynamics, with relatively stronger influence from other fluxes (probably the biota) in the Northern Hemisphere. 4) We propose degassing during sea ice freeze and temperature dependent solubility in the ocean dominate the annual methane cycle. 5) Results provide evidence that carbon cycle pathways, parameters and predictions must be reassessed.
A high-resolution wave climate projection for the northwestern Atlantic Ocean has been conducted to help assess possible regional impacts due to global climate change. The spectral wave model NOAA WAVEWATCH III is utilized with three coupled (two-way) grids to resolve the northwestern Atlantic and coastal southern and eastern USA at approximately 21 km and 7 km respectively, and covers the periods 1979--2003 (historic) and 2075--2099 (future). Hourly wind field forcings are provided by a high-resolution AGCM (MRI-AGCM 3.2S; 21 km) and allow for better modeling of large storm events (important for extreme event statistics). Climatological (25-year) comparisons between future and historical periods indicate significant wave heights will decrease in the northwestern Atlantic Ocean (-5.7 %) and Gulf of Mexico (-4.7 %) but increase in the Caribbean Sea (2.4 %). Comparisons also indicate that large changes in mean wave direction will occur in the Gulf of Mexico (5.0{deg}), with the largest occurring west of the Florida peninsula (over 15{deg}).
The University of Tokyo and JAMSTEC have conducted state-of-the-art wave and current resource assessments to assist with generator site identification and construction in Japan. These assessments are publicly-available and accessible via a web GIS service designed by WebBrain that utilizes TDS and GeoServer software with Leaflet libraries. The web GIS dataset contains statistical analyses of wave power, ocean and tidal current power, ocean temperature power, and other basic physical variables. The data (2D maps, time charts, depth profiles, etc.) is accessed through interactive browser sessions and downloadable files.
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