Tracing anthropogenic carbon dioxide and methane emissions to fossil fuel and cement producers, 1854–2010

AbstractA gridded social-economic data is essential for geoscience analysis and multidisciplinary application. Spatial allocation of carbon dioxide statistics data is an important issue in the context of global climate change, which involves the carbon emissions accounting and decomposition of responsibility for carbon emission reductions. In this research a new spatial allocation method for non-point source anthropogenic carbon dioxide emissions (ACDE) fusing multi-source data using Bayesian Network (BN) was introduced. In addition to common-used DMSP (Defense Meteorological Satellite Program), PD (population density) and GDP (Gross Domestic Production) data, the land cover and vegetation data was imported into the model as prior knowledge to optimize the model fitting. The prior knowledge here was based on the understanding that ACDE was dominated by human activities and has strong correlations with land cover and vegetation conditions. A 1 km gridded ACDE map integrated emissions form point-source and non-point source was generated and validated. The model predicts ACDE with high accuracies and great improvement can be observed when fusing land cover and vegetation as prior knowledge. The model can achieve successful statistics data downscaling on national scale provided adequate sample data are available, offering a novel method for ACDE accounting in China.

Download Full-text

Quantifying the contribution of regional methane emissions to the global methane budget between 2008 and 2018 using the TOMCAT chemical transport model

10.5194/egusphere-egu21-6104 ◽

2021 ◽

Author(s):

Emily Dowd ◽

Christopher Wilson ◽

Martyn Chipperfield ◽

Manuel Gloor

Keyword(s):

Carbon Dioxide ◽

Land Surface ◽

Fossil Fuels ◽

Fossil Fuel ◽

Transport Model ◽

Chemical Transport ◽

Methane Emissions ◽

Anthropogenic Sources ◽

Chemical Transport Model ◽

Methane Budget

Methane (CH4) is the second most important atmospheric greenhouse gas after carbon dioxide. Global concentrations of CH4 have been rising in the last decade and our understanding of what is driving the increase remains incomplete. Natural sources, such as wetlands, contribute to the uncertainty of the methane budget. However, anthropogenic sources, such as fossil fuels, present an opportunity to mitigate the human contribution to climate change on a relatively short timescale, since CH4 has a much shorter lifetime than carbon dioxide. Therefore, it is important to know the relative contributions of these sources in different regions.We have investigated the inter-annual variation (IAV) and rising trend of CH4 concentrations using a global 3-D chemical transport model, TOMCAT. We independently tagged several regional natural and anthropogenic CH4 tracers in TOMCAT to identify their contribution to the atmospheric CH4 concentrations over the period 2009 &#8211; 2018. The tagged regions were selected based on the land surface types and the predominant flux sector within each region and include subcontinental regions, such as tropical South America, boreal regions and anthropogenic regions such as Europe. We used surface CH4 fluxes derived from a previous TOMCAT-based atmospheric inversion study (Wilson et al., 2020). These atmospheric inversions were constrained by satellite and surface flask observations of CH4, giving optimised monthly estimates for fossil fuel and non-fossil fuel emissions on a 5.6&#176; horizontal grid. During the study period, the total optimised CH4 flux grew from 552 Tg/yr to 593 Tg/yr. This increase in emissions, particularly in the tropics, contributed to the increase in atmospheric CH4 concentrations and added to the imbalance in the CH4 budget. We will use the results of the regional tagged tracers to quantify the contribution of regional methane emissions at surface observation sites, and to quantify the contributions of the natural and anthropogenic emissions from the tagged regions to the IAV and the rising methane concentrations.Wilson, C., Chipperfield, M. P., Gloor, M., Parker, R. J., Boesch, H., McNorton, J., Gatti, L. V., Miller, J. B., Basso, L. S., and Monks, S. A.: Large and increasing methane emissions from Eastern Amazonia derived from satellite data, 2010&#8211;2018, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1136, in review, 2020.

Download Full-text