scholarly journals GHG emissions and other environmental impacts of indirect land use change mitigation

GCB Bioenergy ◽  
2016 ◽  
Vol 9 (4) ◽  
pp. 725-742 ◽  
Author(s):  
Sarah J. Gerssen-Gondelach ◽  
Birka Wicke ◽  
Andre P. C. Faaij
2011 ◽  
pp. 224-228
Author(s):  
Uwe Lahl

The study proposes a regional approach to calculating indirect land use change (iLUC). The goal is to determine the greenhouse gas emissions (GHG) of biofuels brought about by iLUC in a specific region. A regional approach can be based on the conditions specific to the respective region and the data for this region which is contained in country statistics. This makes the results more resilient. It also appears that LUC is mainly caused locally or regionally. Relevant policy scenarios for different regions were calculated with a regional model. The calculations show reliable results. It is possible to introduce such a regional model in regulations for combating iLUC. The analysis of the policy options for combating iLUC shows that a regional approach would have a much more effective steering effect.


2017 ◽  
Vol 7 (1) ◽  
pp. e00125 ◽  
Author(s):  
Andrea Nocentini ◽  
John Field ◽  
Andrea Monti ◽  
Keith Paustian

Author(s):  
Sandrine Petit ◽  
Finn P. Vinther ◽  
Pieter J. Verkerk ◽  
Les G. Firbank ◽  
Niels Halberg ◽  
...  

2021 ◽  
Author(s):  
Wahaj Habib ◽  
John Connolly ◽  
Kevin McGuiness

<p>Peatlands are one of the most space-efficient terrestrial carbon stores. They cover approximately 3 % of the terrestrial land surface and account for about one-third of the total soil organic carbon stock. Peatlands have been under severe strain for centuries all over the world due to management related activities. In Ireland, peatlands span over approximately 14600 km<sup>2</sup>, and 85 % of that has already been degraded to some extent. To achieve temperature goals agreed in the Paris agreement and fulfil the EU’s commitment to quantifying the Carbon/Green House Gases (C/GHG) emissions from land use, land use change forestry, accurate mapping and identification of management related activities (land use) on peatlands is important.</p><p>High-resolution multispectral satellite imagery by European Space Agency (ESA) i.e., Sentinel-2 provides a good prospect for mapping peatland land use in Ireland. However, due to persistent cloud cover over Ireland, and the inability of optical sensors to penetrate the clouds makes the acquisition of clear sky imagery a challenge and hence hampers the analysis of the landscape. Google Earth Engine (a cloud-based planetary-scale satellite image platform) was used to create a cloud-free image mosaic from sentinel-2 data was created for raised bogs in Ireland (images collected for the time period between 2017-2020). A preliminary analysis was conducted to identify peatland land use classes, i.e., grassland/pasture, crop/tillage, built-up, cutover, cutaway and coniferous, broadleaf forests using this mosaicked image. The land-use classification results may be used as a baseline dataset since currently, no high-resolution peatland land use dataset exists for Ireland. It can also be used for quantification of land-use change on peatlands. Moreover, since Ireland will now be voluntarily accounting the GHG emissions from managed wetlands (including bogs), this data could also be useful for such type of assessment.</p>


2019 ◽  
Vol 11 (4) ◽  
pp. 1162 ◽  
Author(s):  
Claudia Parra Paitan ◽  
Peter Verburg

The increasing international trade of agricultural products has contributed to a larger diversity of food at low prices and represents an important economic value. However, such trade can also cause social, environmental and economic impacts beyond the limits of the countries directly involved in the exchange. Agricultural systems are telecoupled because the impacts caused by trade can generate important feedback loops, spillovers, rebound effects, time lags and non-linearities across multiple geographical and temporal scales that make these impacts more difficult to identify and mitigate. We make a comparative review of current impact assessment methods to analyze their suitability to assess the impacts of telecoupled agricultural supply chains. Given the large impacts caused by agricultural production on land systems, we focus on the capacity of methods to account for and spatially allocate direct and indirect land use change. Our analysis identifies trade-offs between methods with respect to the elements of the telecoupled system they address. Hybrid methods are a promising field to navigate these trade-offs. Knowledge gaps in assessing indirect land use change should be overcome in order to improve the accuracy of assessments.


2020 ◽  
Vol 14 (5) ◽  
pp. 924-934 ◽  
Author(s):  
Vassilis Daioglou ◽  
Geert Woltjer ◽  
Bart Strengers ◽  
Berien Elbersen ◽  
Goizeder Barberena Ibañez ◽  
...  

2011 ◽  
Vol 1 (2) ◽  
pp. 224-232 ◽  
Author(s):  
Andre M. Nassar ◽  
Leila Harfuch ◽  
Luciane C. Bachion ◽  
Marcelo R. Moreira

The use of agricultural-based biofuels has expanded. Discussions on how to assess green house gas (GHG) emissions from biofuel policies, specifically on (non-observed) land-use change (LUC) effects involve two main topics: (i) the limitations on the existing methodologies, and (ii) how to isolate the effects of biofuels. This paper discusses the main methodologies currently used by policy-makers to take decisions on how to quantify LUCs owing to biofuel production expansion. It is our opinion that the concerns regarding GHG emissions associated with LUCs should focus on the agricultural sector as a whole rather than concentrating on biofuel production. Actually, there are several limitations of economic models and deterministic methodologies for simulating and explaining LUCs resulting from the expansion of the agricultural sector. However, it is equally true that there are avenues of possibilities to improve models and make them more accurate and precise in order to be used for policy-making. Models available need several improvements to reach perfection. Any top model requires a concentration of interdisciplinary designers in order to replicate empirical evidence and capture correctly the agricultural sector dynamics for different countries and regions. Forgetting those limitations means that models will be used for the wrong purposes.


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