• Energy Research
• 2016-2025close
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Carbonaceous emissions from wildfires are a dynamic mixture of gases and particles that have important impacts on air quality and climate. Emissions that feed atmospheric models are estimated using burned area and fire radiative power (FRP) methods that rely on satellite products. These approaches show wide variability and have large uncertainties, and their accuracy is challenging to evaluate due to limited aircraft and ground measurements. Here, we present a novel method to estimate fire plume-integrated total carbon and speciated emission rates using a unique combination of lidar remote sensing aerosol extinction profiles and in situ measured carbon constituents. We show strong agreement between these aircraft-derived emission rates of total carbon and a detailed burned area-based inventory that distributes carbon emissions in time using Geostationary Operational Environmental Satellite FRP observations (Fuel2Fire inventory, slope = 1.33 ± 0.04, r2 = 0.93, and RMSE = 0.27). Other more commonly used inventories strongly correlate with aircraft-derived emissions but have wide-ranging over- and under-predictions. A strong correlation is found between carbon monoxide emissions estimated in situ with those derived from the TROPOspheric Monitoring Instrument (TROPOMI) for five wildfires with coincident sampling windows (slope = 0.99 ± 0.18; bias = 28.5%). Smoke emission coefficients (g MJ-1) enable direct estimations of primary gas and aerosol emissions from satellite FRP observations, and we derive these values for many compounds emitted by temperate forest fuels, including several previously unreported species.

This paper investigates the potential effects of the use of reference class forecasting on the World Bank's financing decisions, and quantifies the net economic impact of such decisions in the long run. A set of 57 World Bank-financed hydropower projects constructed between 1975 and 2015 was selected based on data availability. The findings show that reference class forecasting can help reduce net losses by preventing some hydropower projects with negative economic net present values from being executed. However, it also leads to the forfeiture of even larger amounts of net economic benefits by causing the rejection of some projects that are found, from ex-post analysis, to be economically worthwhile. Furthermore, because of the increased ex-ante rejection of projects, the loss of potentially economically positive projects from the portfolio of hydro dam projects is greatly increased. The errors in the estimation of economic net present values of these hydropower projects are highly positively correlated to the errors in the estimation of the benefits and only weakly negatively correlated to the errors in the estimation of costs.

The deep-sea, defined as the area 200 m below the surface, is facing emerging chemical, physical and biological stressors. Currently, very little is known regarding deep-sea ecosystems both globally and in the Arctic. In this thesis I undertook a literature review on the current understanding of global deep-sea ecosystems through the use of stable isotopes. Specifically, I synthesized the available literature on spatial variation, energy pathways, depth, temporal variation, feeding behaviour, niche, trophic position and body size isotopic trends. This thesis then presents a case study examining the isotopic niche of five teleost and two decapod species within Arctic deep-sea food webs across the localized latitudinal gradient of Baffin Island. Spatial variation in isotopic niche was quantified using 13C and 15N for seven deep-sea species at three locations on Baffin Island, Nunavut to determine whether the “Latitudinal Niche Breadth Hypothesis” which states that niche breadth should increase with latitude holds true in the Arctic. Overall, isotopic patterns in global deep-sea ecosystem are variable; consistent trends are not observed across all taxa and habitats. It was concluded that niche breadth did not consistently increase with latitude in the eastern Canadian Arctic; localized conditions (e.g. sea ice, temperature) and individual condition (e.g. hepatosomatic index) may contribute more to a species’ niche than latitude. Overall, this thesis improves our understanding of deep-sea ecosystems globally, contributes baseline data for future monitoring, and by investigating multiple species and locations it will provide input on how climate change may impact Arctic food web diversity, energy dynamics and ecosystem structure to aid in sustainable fishery development.

Social networks influence decision-making in agricultural landscapes by affecting how farmers access knowledge and resources. However, researchers ignore the disparate structures built to access different kinds of knowledge and resources and the social mechanisms that take place on such farmers advice networks. We explored the role of social networks in decision-making among farmers in Navarre (Spain) to understand how and why some practices spread among farming communities. Social network analysis allows us to understand how farmers in this region share both knowledge and resources, and the potential implications of this sharing for the landscape. We find that large-scale farmers undertaking intensive land management are at the core of the network in this region, controlling the flow of knowledge and resources related to farm management, policy, technology, and finance. The central position of these farmers in the social network, and their reputation, is key to the spread of intensive farming practices in the region, which ultimately may lead to homogenization of local agricultural landscapes. Understanding farmer network structures in a context of agricultural intensification can help tease out the social mechanisms, such as farmers joining each other in cooperatives, behind the spread of agricultural practices. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature. Many thanks to all the participants, especially to the lead author?s host Patxi Sueskun, and the people from the local cooperative: Rogelio Rodriguez, Andrea Ayestaran, and Leire Elorz. Without their help, this work would have not been possible. The lead author would also like to mention Julen Ugalde for his support in Canada during the data analysis and Jesse Rieb, Jesse Sayles, Jacopo Baggio, Karina Benessaiah, Carrie Dai, and Yevgen Nazarenko for their help at different stages of this research. Likewise, we are grateful for the insightful comments of the four reviewers that have made this paper stronger and sharper.

Renewable energy projects, such as wind farms and hydropower dams, can indirectly benefit biodiversity by mitigating climate change. However, we explain why such indirect benefits should not contribute towards the accounting of project-level net biodiversity outcomes and provide guidance on the steps needed to legitimately claim no-net-loss of biodiversity.