• Energy Research
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Abstract. According to the latest report of the Intergovernmental Panel on Climate Change (IPCC), emissions must be cut by 41–72 % below 2010 levels by 2050 for a likely chance of containing the global mean temperature increase to 2 °C. The AFOLU sector (Agriculture, Forestry and Other Land Use) roughly contributes with a quarter (~ 10–12 PgCO2e.yr−1) of the net anthropogenic GHG emissions mainly from deforestation, fire, wood harvesting, and agricultural emissions including croplands, paddy rice and livestock. In spite of the importance of this sector, it is unclear where are the regions in the planet with AFOLU emissions hotspots, and how uncertain these emissions are. Here we present a novel spatially comparable dataset containing annual mean estimates of gross AFOLU emissions (CO2, CH4, N2O), associated uncertainties, and leading emission sources, in a spatially disaggregated manner (0.5°), for the tropics, for the period 2000–2005. Our data highlight: i) the existence of AFOLU emissions hotspots on all continents, with particular importance of evergreen rainforest deforestation in Central and South America, fire in dry forests in Africa, and both peatland emissions and agriculture in Asia; ii) a predominant contribution of forests and CO2 to the total AFOLU emissions (75 %) and to their uncertainties (98 %), iii) higher gross fluxes from forests coincide with higher uncertainties, making agricultural hotspots more appealing for effective mitigation action, and iv) a lower contribution of non-CO2 agricultural emissions to the total gross budget (ca. 25 %) with livestock (15.5 %) and rice (7 %) leading the emissions. Gross AFOLU tropical emissions 8.2 (5.5–12.2) were in the range of other databases 8.4 and 8.0 PgCO2e.yr−1 (FAOSTAT and EDGAR respectively), but we offer a spatially detailed benchmark for monitoring progress on reducing emissions from the land sector in the tropics. The location of the AFOLU hotspots of emissions and data on their associated uncertainties, will assist national policy makers, investors and other decision-makers who seek to understand the mitigation potential of the AFOLU sector.

Abstract. According to the latest report of the Intergovernmental Panel on Climate Change (IPCC), emissions must be cut by 41–72 % below 2010 levels by 2050 for a likely chance of containing the global mean temperature increase to 2 °C. The AFOLU sector (Agriculture, Forestry and Other Land Use) contributes roughly a quarter ( ∼ 10–12 Pg CO2e yr−1) of the net anthropogenic GHG emissions mainly from deforestation, fire, wood harvesting, and agricultural emissions including croplands, paddy rice, and livestock. In spite of the importance of this sector, it is unclear where the regions with hotspots of AFOLU emissions are and how uncertain these emissions are. Here we present a novel, spatially comparable dataset containing annual mean estimates of gross AFOLU emissions (CO2, CH4, N2O), associated uncertainties, and leading emission sources, in a spatially disaggregated manner (0.5°) for the tropics for the period 2000–2005. Our data highlight the following: (i) the existence of AFOLU emissions hotspots on all continents, with particular importance of evergreen rainforest deforestation in Central and South America, fire in dry forests in Africa, and both peatland emissions and agriculture in Asia; (ii) a predominant contribution of forests and CO2 to the total AFOLU emissions (69 %) and to their uncertainties (98 %); (iii) higher gross fluxes from forests, which coincide with higher uncertainties, making agricultural hotspots appealing for effective mitigation action; and (iv) a lower contribution of non-CO2 agricultural emissions to the total gross emissions (ca. 25 %), with livestock (15.5 %) and rice (7 %) leading the emissions. Gross AFOLU tropical emissions of 8.0 (5.5–12.2) were in the range of other databases (8.4 and 8.0 Pg CO2e yr−1 in FAOSTAT and the Emissions Database for Global Atmospheric Research (EDGAR) respectively), but we offer a spatially detailed benchmark for monitoring progress in reducing emissions from the land sector in the tropics. The location of the AFOLU hotspots of emissions and data on their associated uncertainties will assist national policy makers, investors, and other decision-makers who seek to understand the mitigation potential of the AFOLU sector.

Programs to provide alternative energy sources such as biogas improve indoor air quality and potentially reduce pressure on forests from fuelwood collection. This study tests whether biogas intervention is associated with higher forest biomass and forest regeneration in degraded forests in Chikkaballapur district in Southern India. Using propensity score matching, we find that forest plots in proximity to villages with biogas interventions (treatment) had greater forest biomass than comparable plots around villages without biogas (control). We also found significantly higher sapling abundance and diversity in treatment than control plots despite no significant difference in seedling abundances and diversity in treatment forests, suggesting that plants have a higher probability of reaching sapling stage. These results indicate the potential for alternative energy sources that reduce dependence on fuelwood to promote regeneration of degraded forests. However, forest regrowth is not uniform across treatments and is limited by soil nutrients and biased towards species that are light demanding, fire-resistant and can thrive in poor soil conditions.

The agriculture, forestry and other land use (AFOLU) sectors contribute substantially to the net global anthropogenic greenhouse gas (GHG) emissions. To reduce these emissions under the Paris Agreement, effective mitigation actions are needed that require engagement of multiple stakeholders. Emission reduction also requires that accurate, consistent and comparable datasets are available for transparent reference and progress monitoring. Availability of free and open datasets and portals (referred to as independent data) increases, offering opportunities for improving and reconciling estimates of GHG emissions and mitigation options. Through an online survey, we investigated stakeholders’ data needs for estimating forest area and change, forest biomass and emission factors, and AFOLU GHG emissions. The survey was completed by 359 respondents from governmental, intergovernmental and non-governmental organizations, research institutes and universities, and public and private companies. These can be grouped into data users and data providers. Our results show that current open and freely available datasets and portals are only able to fulfil stakeholder needs to a certain degree. Users require a) detailed documentation regarding the scope and usability of the data, b) comparability between alternative data sources, c) uncertainty estimates for evaluating mitigation options, d) more region-specific and detailed data with higher accuracy for sub-national application, e) regular updates and continuity for establishing consistent time series. These requirements are found to be key elements for increasing overall transparency of data sources, definitions, methodologies and assumptions, which is required under the ParisAgreement. Raising awareness and improving data availability through centralized platforms are important for increasing engagement of data users. In countries with low capacities, independent data can support countries’mitigation planning and implementation, and related GHG reporting. However, there is a strong need for further guidance and capacity development (i.e.‘readiness support’) on how to make proper use of independent datasets. Continued investments will be needed to sustain programmes and keep improving datasets to serve the objectives of the many stakeholders involved in climate change mitigation and should focus on increased accessibility and transparency of data to encourage stakeholder involvement.

Abstract Background The vast majority of households in Sub-Saharan Africa (SSA) depend on wood energy—comprising firewood and charcoal—for their daily energetic needs. Such consumption trends are expected to remain a common feature of SSA’s wood energy production and supply chains, at least in the short- to medium-terms. Notwithstanding its importance, wood energy generally has low priority in SSA national policies. However, the use of wood energy is often considered a key driver of unsustainable management and negative environmental consequences in the humid and dry forests. To date, unsystematic assessments of the socio-economic and environmental consequences of wood energy use have underplayed its significance, thus further hampering policy debates. Therefore, a more balanced approach which considers both demand and supply dynamics is needed. This systematic map aims at providing a comprehensive approach to understanding the role and impacts of wood energy across all regions and aspects in SSA. Methods The objective of this systematic map is to collate evidence from studies of environmental and socio-economic impacts of wood energy value chains, by considering both demand and supply within SSA. The map questions are framed using a Populations, Exposure, Comparators and Outcomes (PECO) approach. We name the supply and demand of wood energy as the “exposure,” composed of wood energy production, harvesting, processing, and consumption. The populations of interest include both the actors involved in these activities and the forest sites where these activities occur. The comparator is defined as those cases where the same wood energy activities occur with i) available/accessible alternative energy sources, ii) regulatory frameworks that govern the sector and iii) alternative technologies for efficient use. The outcomes of interest encompass both socioeconomic and environmental impacts that can affect more than the populations named above. For instance, in addition to the direct socioeconomic impacts felt by participants in the wood energy value chain, forest dwellers may experience livelihood changes due to forest degradation caused by external harvesters. Moreover, intensified deforestation in one area may concurrently lead to forest regeneration in another.

L'objectif d'améliorer la sécurité alimentaire en Afrique subsaharienne (Ass) grâce à une agriculture domestique, économe en ressources et à faible émission de carbone est important.Les interventions visant à produire plus de nourriture pourraient avoir un impact sur la base de ressources et entraîner une augmentation des émissions de gaz à effet de serre (GES) des agroécosystèmes.Malgré cela, les méthodes existantes sont limitées dans l'analyse des systèmes agricoles à petite échelle, et cette situation constitue un obstacle à la prise de décision qui vise une agriculture durable.Dans ce document, nous présentons l'approche Emergy-Data Envelopment Analysis (EM-DEA) récemment développée pour évaluer l'efficacité de l'utilisation des ressources (RUE) et durabilité dans les systèmes de production de maïs au Ghana, SSA.Utilisant le simulateur de systèmes de production agricole (APSIM), cinq scénarios d'utilisation des terres et de gestion des ressources ont été modélisés pour représenter les pratiques en tant qu'unités de prise de décision (DMU) dans les systèmes de maïs à petite échelle.L' empreinte carbone des systèmes a été évaluée à l'aide d'une approche, que nous avons adaptée à partir de l'outil de bilan carbone ex ante de la FAO (EX-ACT).La tendance globale des résultats a montré que le rendement, l'emergie totale, les émissions de GES et l'empreinte carbone augmentaient tous avec l'augmentation de l'intensité de l'application d'urée.Toutefois, la relation entre le rendement et l'apport d'urée n'était pas toujours linéaire.Un système qui utilisait plus de ressources renouvelables ou moins de ressources pour produire un rendement égal à celui de son homologue était considéré comme plus efficace et durable en termes relatifs.En particulier, le scénario de statu quo (12 kg/ha/an d'apport de NPK au système de maïs pluvial, c.-à-d. extensif12) était inefficace par rapport aux quatre scénarios contrastés.Le scénario écologique intensif (20 kg/ha/an d'apport d'urée au système de culture intercalaire maïs pluvial-légumine, c.-à-d. Intercrop20) a atteint le rendement marginal le plus élevé, une meilleure RUE et la durabilité.Le scénario d'intrant élevé (100 kg/ha/an) année d'entrée d'urée plus irrigation supplémentaire pour la monoculture de maïs, c.-à-d. intensive100) a produit le rendement le plus élevé, mais la demande d'intrants achetés ainsi que les émissions de GES et l'empreinte carbone étaient les plus élevées. Le scénario sans intrants externes (0 kg/ha/an d'entrée d'urée pour le système de maïs pluvial, c.-à-d. intensive0) et le scénario d'intrants modérés (50 kg/ha/an d'entrée d'urée plus irrigation supplémentaire pour la monoculture de maïs, c.-à-d. intensive50) ont montré les écarts de rendement les plus importants et les moins importants par rapport à Intensive100, respectivement. Sur la base de ces résultats et de l'analyse des compromis, il était évident que Intercrop20 et Intensive50 étaient les deux meilleurs scénarios. En tant que tel, la politique d'utilisation des terres qui vise à l'agriculture durable pourrait recommander Intercrop20 et Intensive50 pour la mise en œuvre dans les systèmes de production de maïs à faible et à fort apport, respectivement. La comparaison entre nos résultats et d'autres études empiriques existantes a révélé des similitudes qui confirment nos résultats. Nous concluons que les informations dérivées en utilisant les approches EM-DEA et EX-ACT pourraient être utiles lors de la prise de décisions éclairées qui visent à l'agriculture durable. Malgré la limitation causée par la rareté des données, l'utilisation de l'approche EM-DEA a conduit à des informations inclusives sur la RUE et la durabilité des DMUs.Hence, l'approche EM-DEA représente une voie à suivre pour mieux évaluer l'empreinte énergétique dans l'utilisation des terres agricoles dans son ensemble. El objetivo de mejorar la seguridad alimentaria en el África subsahariana (ASA) a través de la agricultura doméstica, eficiente en el uso de los recursos y baja en carbono es importante. Las intervenciones para producir más alimentos podrían afectar la base de recursos y conducir a un aumento de las emisiones de gases de efecto invernadero (GEI) de los agroecosistemas. Lamentablemente, los métodos existentes son limitados para analizar los sistemas agrícolas a pequeña escala, y esta situación es un obstáculo para la toma de decisiones que apunta a la agricultura sostenible. En este documento, mostramos el enfoque recientemente desarrollado del Análisis de Envolvimiento de Datos de Emergencia (EM-DEA) para evaluar la eficiencia del uso de los recursos (RUE) y sostenibilidad en los sistemas de producción de maíz en Ghana, SSA. Utilizando el SIMulador de Sistemas de Producción Agrícola (APSIM), se modelaron cinco escenarios de uso de la tierra y gestión de recursos para representar las prácticas como unidades de toma de decisiones (DMU) en sistemas de maíz a pequeña escala. La huella de carbono de los sistemas se evaluó utilizando un enfoque, que adaptamos de la Herramienta de Balance de Carbono Ex-Ante de la FAO (EX-ACT). La tendencia general de los resultados mostró que el rendimiento, la emergencia total, las emisiones de GEI y la huella de carbono aumentaron con el aumento en la intensidad de la aplicación de urea. Sin embargo, la relación entre el rendimiento y la entrada de urea no siempre fue lineal.Un sistema que utilizó más recursos renovables o menos recursos para producir un rendimiento igual al de sus pares se consideró más eficiente y sostenible en términos relativos. En particular, el escenario habitual (12 kg/ha/año de entrada de NPK al sistema de maíz de secano, es decir, Extensive12) fue ineficiente en comparación con los cuatro escenarios contrastantes. El escenario ecológico intensivo (20 kg/ha/año de entrada de urea al sistema de cultivo intercalado de leguminosas de maíz de secano, es decir, Intercrop20) logró el mayor rendimiento marginal, mejor RUDA y sostenibilidad. El escenario de alto insumo (100 kg/ha/el año de entrada de urea más el riego suplementario al monocultivo de maíz, es decir, Intensive100) produjo el mayor rendimiento, pero la demanda de insumos comprados, así como las emisiones de GEI y la huella de carbono fueron mayores. El escenario sin insumos externos (0 kg/ha/año de entrada de urea al sistema de maíz de secano, es decir, Extensive0), y el escenario de insumos moderados (50 kg/ha/año de entrada de urea más el riego suplementario al monocultivo de maíz, es decir, Intensive50) mostraron las mayores y menores brechas de rendimiento en relación con Intensive100, respectivamente. Con base en estos resultados y análisis de compensación, fue evidente que Intercrop20 y Intensive50 fueron los dos mejores escenarios. Por lo tanto, la política de uso de la tierra que apunta a la agricultura sostenible podría recomendar Intercrop20 e Intensive50 para su implementación en sistemas de producción de maíz de bajo y alto insumo, respectivamente. La comparación entre nuestros resultados y otros estudios empíricos existentes reveló similitudes que confirman nuestros resultados. Concluimos que la información derivada utilizando los enfoques EM-DEA y EX-ACT podría ser útil al tomar decisiones informadas que apunten a la agricultura sostenible. A pesar de la limitación causada por la escasez de datos, el uso del enfoque EM-DEA condujo a información inclusiva sobre RUE y sostenibilidad de las DMU. Por lo tanto, el enfoque EM-DEA representa un camino a seguir para evaluar mejor la huella energética en el uso de la tierra agrícola en su conjunto. The goal to improve food security in sub-Saharan Africa (SSA) through domestic, resource efficient and low carbon agriculture is importance.Interventions to produce more food could impact the resource-base and lead to increase in greenhouse gas (GHG) emissions from agroecosystems.Unfortunately, existing methods are limited in analyzing small-scale agricultural systems, and this situation is an obstacle to decision making which aims at sustainable agriculture.In this paper, we showcase the recently developed Emergy-Data Envelopment Analysis (EM-DEA) approach to assess the resource use efficiency (RUE) and sustainability in maize production systems in Ghana, SSA.Using the Agricultural Production Systems sIMulator (APSIM), five land use and resource management scenarios were modeled to represent practices as decision making units (DMUs) in small-scale maize systems.The carbon footprint of the systems was assessed using an approach, which we adapted from the FAO Ex-Ante Carbon balance Tool (EX-ACT).The overall trend of the results showed that the yield, total emergy, GHG emissions and carbon footprint all increased with increase in urea application intensity.However, the relationship between the yield and urea input was not always linear.A system that used more renewable or fewer resources to produce a yield equal to that of its peer was considered more efficient and sustainable in relative terms.In particular, the business-as-usual scenario (12 kg/ha/yr NPK input to rainfed maize system, i.e.Extensive12) was inefficient when compared to the four contrasting scenarios.The ecological intensive scenario (20 kg/ha/yr urea input to rainfed maize-legume intercropping system, i.e.Intercrop20) achieved the greatest marginal yield, better RUE and sustainability.The high input scenario (100 kg/ha/yr urea input plus supplemental irrigation to maize monoculture, i.e.Intensive100) produced the greatest yield, but the demand for purchased inputs as well as GHG emissions and carbon footprint were greatest.The no external input scenario (0 kg/ha/yr urea input to rainfed maize system, i.e.Extensive0), and the moderate input scenario (50 kg/ha/yr urea input plus supplemental irrigation to maize monoculture, i.e.Intensive50) showed the greatest and least yield gaps relative to Intensive100, respectively.Based on these results and trade-off analysis, it was evident that Intercrop20 and Intensive50 were the two best case scenarios.As such, land use policy that aims at sustainable agriculture could recommend Intercrop20 and Intensive50 for implementation in low and high input maize production systems, respectively.Comparison between our results and other existing empirical studies revealed similarities that confirm our results.We conclude that the information derived using the EM-DEA and EX-ACT approaches could be useful when making informed decisions that aim at sustainable agriculture.Despite the limitation caused by scarcity of data, the use of the EM-DEA approach led to inclusive information on RUE and sustainability of the DMUs.Hence, the EM-DEA approach represents a way forward to better assess energy footprint in agricultural land use as a whole. إن هدف تحسين الأمن الغذائي في أفريقيا جنوب الصحراء الكبرى (SSA) من خلال الزراعة المحلية ذات الكفاءة في استخدام الموارد والمنخفضة الكربون أمر مهم. يمكن أن تؤثر التدخلات لإنتاج المزيد من الغذاء على قاعدة الموارد وتؤدي إلى زيادة انبعاثات غازات الدفيئة من النظم الإيكولوجية الزراعية. لسوء الحظ، فإن الأساليب الحالية محدودة في تحليل النظم الزراعية الصغيرة، وهذا الوضع يمثل عقبة أمام صنع القرار الذي يهدف إلى الزراعة المستدامة. في هذه الورقة، نعرض نهج تحليل البيانات الطارئة (EM - DEA) الذي تم تطويره مؤخرًا لتقييم كفاءة استخدام الموارد (RUE) و الاستدامة في أنظمة إنتاج الذرة في غانا، جنوب الصحراء الكبرى. باستخدام محاكي أنظمة الإنتاج الزراعي (APSIM)، تم تصميم خمسة سيناريوهات لاستخدام الأراضي وإدارة الموارد لتمثيل الممارسات كوحدات صنع القرار (DMUs) في أنظمة الذرة الصغيرة. تم تقييم البصمة الكربونية للأنظمة باستخدام نهج، قمنا بتكييفه من أداة توازن الكربون السابق لمنظمة الأغذية والزراعة (EX - ACT). أظهر الاتجاه العام للنتائج أن العائد، إجمالي الطاقة، انبعاثات غازات الدفيئة وبصمة الكربون زادت جميعها مع زيادة كثافة تطبيق اليوريا. ومع ذلك، فإن العلاقة بين العائد ومدخلات اليوريا لم يكن دائمًا خطيًا. واعتبر النظام الذي يستخدم موارد أكثر متجددة أو أقل لإنتاج عائد مساوٍ لعائد نظيره أكثر كفاءة واستدامة من الناحية النسبية. على وجه الخصوص، فإن سيناريو العمل المعتاد (12 كجم/هكتار/سنة مدخلات NPK إلى نظام الذرة البعلية، أي مكثف 12) كان غير فعال عند مقارنته بالسيناريوهات الأربعة المتناقضة. السيناريو المكثف بيئيًا (20 كجم/هكتار/سنة مدخلات اليوريا إلى نظام زراعة البقول والذرة البعلية، أي Intercrop20) حقق أكبر عائد هامشي، وشق أفضل واستدامة. سيناريو المدخلات العالية (100 كجم/هكتار/سنة أنتجت مدخلات اليوريا السنوية بالإضافة إلى الري التكميلي لذرة الزراعة الأحادية، أي المكثفة 100) أكبر عائد، لكن الطلب على المدخلات المشتراة وكذلك انبعاثات غازات الدفيئة وبصمة الكربون كان أكبر. لم يظهر سيناريو المدخلات الخارجية (0 كجم/هكتار/سنة مدخلات اليوريا في نظام الذرة البعلية، أي المكثفة 0)، وسيناريو المدخلات المعتدلة (50 كجم/هكتار/سنة مدخلات اليوريا بالإضافة إلى الري التكميلي لذرة الزراعة الأحادية، أي المكثفة 50) أكبر وأقل فجوات العائد بالنسبة إلى المكثفة 100، على التوالي. استنادًا إلى هذه النتائج وتحليل المفاضلة، كان من الواضح أن Intercrop20 و كانت المكثفة 50 هي أفضل السيناريوهات. على هذا النحو، يمكن لسياسة استخدام الأراضي التي تهدف إلى الزراعة المستدامة أن توصي بتطبيق Intercrop20 و Intensive50 في أنظمة إنتاج الذرة ذات المدخلات المنخفضة والعالية، على التوالي. كشفت المقارنة بين نتائجنا والدراسات التجريبية الحالية الأخرى عن أوجه تشابه تؤكد نتائجنا. نستنتج أن المعلومات المستمدة باستخدام نهج EM - DEA و EX - ACT يمكن أن تكون مفيدة عند اتخاذ قرارات مستنيرة تهدف إلى الزراعة المستدامة. على الرغم من القيود الناجمة عن ندرة البيانات، أدى استخدام نهج EM - DEA إلى معلومات شاملة عن RUE واستدامة DMUs.Hence، يمثل نهج EM - DEA طريقة للمضي قدمًا لتقييم بصمة الطاقة بشكل أفضل في استخدام الأراضي الزراعية ككل.