Comment on Soon et al. (2001) 'Modeling climatic effects of anthropogenic carbon dioxide emissions: unknowns and uncertainties'

2003 ◽  
Vol 24 ◽  
pp. 91-92
Author(s):  
DJ Karoly ◽  
JFB Mitchell ◽  
M Allen ◽  
G Hegerl ◽  
J Marengo ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Climatic Effects ◽  
Anthropogenic Carbon ◽  
Anthropogenic Carbon Dioxide

scholarly journals Modeling climatic effects of anthropogenic carbon dioxide emissions: unknowns and uncertainties

2001 ◽  
Vol 18 ◽  
pp. 259-275 ◽  
Author(s):  
W Soon ◽  
S Baliunas ◽  
SB Idso ◽  
KY Kondratyev ◽  
ES Posmentier
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Climatic Effects ◽  
Anthropogenic Carbon ◽  
Anthropogenic Carbon Dioxide

scholarly journals Vegetation sensitivity to global anthropogenic carbon dioxide emissions in a topographically complex region

2003 ◽  
Vol 17 (2) ◽  
pp. n/a-n/a ◽  
Author(s):  
Noah S. Diffenbaugh ◽  
Lisa C. Sloan ◽  
Mark A. Snyder ◽  
Jason L. Bell ◽  
Jed Kaplan ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Complex Region ◽  
Anthropogenic Carbon ◽  
Anthropogenic Carbon Dioxide

scholarly journals Spatial allocation of anthropogenic carbon dioxide emission statistics data fusing multi-source data based on Bayesian network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jianbin Tao ◽  
XiangBing Kong
Keyword(s):  
Carbon Dioxide ◽  
Land Cover ◽  
Point Source ◽  
Bayesian Network ◽  
Prior Knowledge ◽  
Carbon Dioxide Emissions ◽  
Spatial Allocation ◽  
Source Data ◽  
Anthropogenic Carbon ◽  
Anthropogenic Carbon Dioxide

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.

Copernicus CO2M mission: Status of the instrument suite for monitoring anthropogenic carbon dioxide emissions from space

2021 ◽  
Author(s):  
Yannig Durand ◽  
Grégory Bazalgette Courrèges-Lacoste ◽  
Charlotte Pachot ◽  
Luc Boucher ◽  
Arnaud Pasquet ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Anthropogenic Carbon ◽  
Anthropogenic Carbon Dioxide

scholarly journals Spatial Modeling of Local‐Scale Biogenic and Anthropogenic Carbon Dioxide Emissions in Helsinki

2019 ◽  
Vol 124 (15) ◽  
pp. 8363-8384 ◽  
Author(s):  
Leena Järvi ◽  
Minttu Havu ◽  
Helen C. Ward ◽  
Veronica Bellucco ◽  
Joseph P. McFadden ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Spatial Modeling ◽  
Carbon Dioxide Emissions ◽  
Local Scale ◽  
Anthropogenic Carbon ◽  
Anthropogenic Carbon Dioxide
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