{"type": "FeatureCollection", "features": [{"id": "10.1051/agro/2009039", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:57Z", "type": "Journal Article", "created": "2010-02-10", "title": "Biofuels, Greenhouse Gases And Climate Change. A Review", "description": "Biofuels are fuels produced from biomass, mostly in liquid form, within a time frame sufficiently short to consider that their feedstock (biomass) can be renewed, contrarily to fossil fuels. This paper reviews the current and future biofuel technologies, and their development impacts (including on the climate) within given policy and economic frameworks. Current technologies make it possible to provide first generation biodiesel, ethanol or biogas to the transport sector to be blended with fossil fuels. Still under-development 2nd generation biofuels from lignocellulose should be available on the market by 2020. Research is active on the improvement of their conversion efficiency. A ten-fold increase compared with current cost-effective capacities would make them highly competitive. Within bioenergy policies, emphasis has been put on biofuels for transportation as this sector is fast-growing and represents a major source of anthropogenic greenhouse gas emissions. Compared with fossil fuels, biofuel combustion can emit less greenhouse gases throughout their life cycle, considering that part of the emitted CO2 returns to the atmosphere where it was fixed from by photosynthesis in the first place. Life cycle assessment (LCA) is commonly used to assess the potential environmental impacts of biofuel chains, notably the impact on global warming. This tool, whose holistic nature is fundamental to avoid pollution trade-offs, is a standardised methodology that should make comparisons between biofuel and fossil fuel chains objective and thorough. However, it is a complex and time-consuming process, which requires lots of data, and whose methodology is still lacking harmonisation. Hence the life-cycle performances of biofuel chains vary widely in the literature. Furthermore, LCA is a site- and timeindependent tool that cannot take into account the spatial and temporal dimensions of emissions, and can hardly serve as a decision-making tool either at local or regional levels. Focusing on greenhouse gases, emission factors used in LCAs give a rough estimate of the potential average emissions on a national level. However, they do not take into account the types of crop, soil or management practices, for instance. Modelling the impact of local factors on the determinism of greenhouse gas emissions can provide better estimates for LCA on the local level, which would be the relevant scale and degree of reliability for decision-making purposes. Nevertheless, a deeper understanding of the processes involved, most notably N2O emissions, is still needed to definitely improve the accuracy of LCA. Perennial crops are a promising option for biofuels, due to their rapid and efficient use of nitrogen, and their limited farming operations. However, the main overall limiting factor to biofuel development will ultimately be land availability. Given the available land areas, population growth rate and consumption behaviours, it would be possible to reach by 2030 a global 10% biofuel share in the transport sector, contributing to lower global greenhouse gas emissions by up to 1 GtCO2 eq.year\u22121 (IEA, 2006), provided that harmonised policies ensure that sustainability criteria for the production systems are respected worldwide. Furthermore, policies should also be more integrative across sectors, so that changes in energy efficiency, the automotive sector and global consumption patterns converge towards drastic reduction of the pressure on resources. Indeed, neither biofuels nor other energy source or carriers are likely to mitigate the impacts of anthropogenic pressure on resources in a range that would compensate for this pressure growth. Hence, the first step is to reduce this pressure by starting from the variable that drives it up, i.e. anthropic consumptions.", "keywords": ["[SDV.SA]Life Sciences [q-bio]/Agricultural sciences", "AGRICULTURAL PRATICES", "P05 - Ressources \u00e9nerg\u00e9tiques et leur gestion", "P06 - Sources d'\u00e9nergie renouvelable", "NITROUS OXIDE", "[SDV]Life Sciences [q-bio]", "CLIMATE CHANGE", "BIOFUELS", "710", "02 engineering and technology", "http://aims.fao.org/aos/agrovoc/c_16181", "7. Clean energy", "http://aims.fao.org/aos/agrovoc/c_2570", "land-use change", "CARBON DIOXIDE", "11. Sustainability", "0202 electrical engineering", " electronic engineering", " information engineering", "gaz \u00e0 effet de serre", "http://aims.fao.org/aos/agrovoc/c_34841", "http://aims.fao.org/aos/agrovoc/c_2018", "\u00e9nergie renouvelable", "POLITICAL AND ECONOMIC FRAMEWORKS", "2. Zero hunger", "changement climatique", "[SDV.SA] Life Sciences [q-bio]/Agricultural sciences", "http://aims.fao.org/aos/agrovoc/c_27465", "bioenergy potential", "nitrous oxide", "LCA", "BIOENERGY POTENTIAL", "LAND-USE CHANGE", "[SDV] Life Sciences [q-bio]", "[SDV.EE] Life Sciences [q-bio]/Ecology", " environment", "source d'\u00e9nergie", "http://aims.fao.org/aos/agrovoc/c_926", "climate change", "politique \u00e9nerg\u00e9tique", "perennials", "ENERGY CROPS", "GREENHOUSE GASES", "http://aims.fao.org/aos/agrovoc/c_28744", "oxyde d'azote", "P40 - M\u00e9t\u00e9orologie et climatologie", "PERENNIALS", "agricultural practices", "pollution par l'agriculture", "12. Responsible consumption", "dioxyde de carbone", "greenhouse gases", "http://aims.fao.org/aos/agrovoc/c_25719", "biomasse", "http://aims.fao.org/aos/agrovoc/c_1302", "http://aims.fao.org/aos/agrovoc/c_1666", "AGRONOMIE", "political and economic frameworks", "energy crops", "pratique culturale", "bio\u00e9nergie", "660", "carbon dioxide", "biofuels", "biocarburant", "http://aims.fao.org/aos/agrovoc/c_16002", "13. Climate action", "http://aims.fao.org/aos/agrovoc/c_16526"]}, "links": [{"href": "https://hal.science/cirad-00749753/file/Article_ASD.2010.pdf"}, {"href": "https://doi.org/10.1051/agro/2009039"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy%20for%20Sustainable%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1051/agro/2009039", "name": "item", "description": "10.1051/agro/2009039", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1051/agro/2009039"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-01-01T00:00:00Z"}}, {"id": "10568/135827", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:21:49Z", "type": "Journal Article", "created": "2023-10-15", "title": "Global observation gaps of peatland greenhouse gas balances: needs and obstacles", "description": "Abstract

Greenhouse gas (GHGs) emissions from peatlands contribute significantly to ongoing climate change because of human land use. To develop reliable and comprehensive estimates and predictions of GHG emissions from peatlands, it is necessary to have GHG observations, including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), that cover different peatland types globally. We synthesize published peatland studies with field GHG flux measurements to identify gaps in observations and suggest directions for future research. Although GHG flux measurements have been conducted at numerous sites globally, substantial gaps remain in current observations, encompassing various peatland types, regions and GHGs. Generally, there is a pressing need for additional GHG observations in Africa, Latin America and the Caribbean regions. Despite widespread measurements of CO2 and CH4, studies quantifying N2O emissions from peatlands are scarce, particularly in natural ecosystems. To expand the global coverage of peatland data, it is crucial to conduct more eddy covariance observations for long-term monitoring. Automated chambers are preferable for plot-scale observations to produce high temporal resolution data; however, traditional field campaigns with manual chamber measurements remain necessary, particularly in remote areas. To ensure that the data can be further used for modeling purposes, we suggest that chamber campaigns should be conducted at least monthly for a minimum duration of one year with no fewer than three replicates and measure key environmental variables. In addition, further studies are needed in restored peatlands, focusing on identifying the most effective restoration approaches for different ecosystem types, conditions, climates, and land use histories.