scholarly journals Advancing national greenhouse gas inventories for agriculture in developing countries: improving activity data, emission factors and software technology

2013 ◽  
Vol 8 (1) ◽  
pp. 015030 ◽  
Author(s):  
Stephen M Ogle ◽  
Leandro Buendia ◽  
Klaus Butterbach-Bahl ◽  
F Jay Breidt ◽  
Melannie Hartman ◽  
...  
Keyword(s):  
Developing Countries ◽  
Greenhouse Gas ◽  
Emission Factors ◽  
Activity Data ◽  
Software Technology ◽  
Greenhouse Gas Inventories ◽  
National Greenhouse Gas Inventories

scholarly journals European anthropogenic AFOLU greenhouse gas emissions: a review and benchmark data

2020 ◽  
Vol 12 (2) ◽  
pp. 961-1001 ◽  
Author(s):  
Ana Maria Roxana Petrescu ◽  
Glen P. Peters ◽  
Greet Janssens-Maenhout ◽  
Philippe Ciais ◽  
Francesco N. Tubiello ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Large Scale ◽  
Ghg Emissions ◽  
The European Union ◽  
Activity Data ◽  
Bottom Up ◽  
Greenhouse Gas Inventories ◽  
National Greenhouse Gas Inventories ◽  
Reliable Quantification ◽  
Mitigation Action

Abstract. Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthropogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU281). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990–2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.3662371 (Petrescu et al., 2020).

scholarly journals Remote Sensing Support for the Gain-Loss Approach for Greenhouse Gas Inventories

2020 ◽  
Vol 12 (11) ◽  
pp. 1891 ◽  
Author(s):  
Ronald E. McRoberts ◽  
Erik Næsset ◽  
Christophe Sannier ◽  
Stephen V. Stehman ◽  
Erkki O. Tomppo
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Greenhouse Gas ◽  
Good Practice ◽  
Remotely Sensed ◽  
Current Status ◽  
Remotely Sensed Data ◽  
Activity Data ◽  
Greenhouse Gas Inventories ◽  
Gain Loss

For tropical countries that do not have extensive ground sampling programs such as national forest inventories, the gain-loss approach for greenhouse gas inventories is often used. With the gain-loss approach, emissions and removals are estimated as the product of activity data defined as the areas of human-caused emissions and removals and emissions factors defined as the per unit area responses of carbon stocks for those activities. Remotely sensed imagery and remote sensing-based land use and land use change maps have emerged as crucial information sources for facilitating the statistically rigorous estimation of activity data. Similarly, remote sensing-based biomass maps have been used as sources of auxiliary data for enhancing estimates of emissions and removals factors and as sources of biomass data for remote and inaccessible regions. The current status of statistically rigorous methods for combining ground and remotely sensed data that comply with the good practice guidelines for greenhouse gas inventories of the Intergovernmental Panel on Climate Change is reviewed.

scholarly journals The analysis of carbon footprint of the settlement activity in the village of Pedurungan District, Semarang City, Central Java Province

2021 ◽  
Vol 909 (1) ◽  
pp. 012016
Author(s):  
Y I Rahmila ◽  
I M Kusuma ◽  
Syafrudin
Keyword(s):  
Greenhouse Gases ◽  
Greenhouse Gas ◽  
Carbon Footprint ◽  
Greenhouse Gas Inventories ◽  
Central Java ◽  
Transportation Sector ◽  
Ipcc Guidelines ◽  
National Greenhouse Gas Inventories ◽  
The Village ◽  
Central Java Province

Abstract Some important sectors influenced the increase of greenhouse gases, such as waste, transportation, settlement, and agricultural sectors. This research aimed to analyze the amount of CO2 emissions, map the carbon footprint, and analyze tree capability in reducing CO2 in 12 villages in Pedurungan district, Semarang city, Central Java. The method used was based on IPCC Guidelines for National Greenhouse Gas Inventories 2006 and Ministry of Environment 2012 about the Implementation of National Greenhouse Gas Inventories Guidelines. The carbon footprint was mapped using ArcGIS software. The results showed that the energy sector produced 13.723,35 tons CO2 Eq, the transportation sector emitted 1.624,58 tons CO2 Eq, and the waste sector emitted 7.677,08 CO2 Eq. The carbon footprint map was presented in three classifications of carbon footprint: lower, middle, and upper, represented by green, yellow, and red colors. An effort to reduce the carbon footprint was planting 300 trees of ten species in the Pedurungan district.

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