New Techniques for Assessing Critical Raw Material Aspects in Energy and Other Technologies.

Transitioning to more sustainable energy technologies is a vital step in the move toward reducing global greenhouse gas emissions. However, several physical constraints could hinder the implementation of these technologies, and many of the raw materials required to produce new infrastructure are scarce, nonrenewable, and nonsubstitutable. Various factors relating to material extraction and processing activities may also affect the security and sociopolitical aspects of future supply lines. Here, we introduce methods for quantifying three key indicators relating to raw material supplies for specific production processes: (1) overall supply risk, (2) environmental impacts from sourcing raw materials, and (3) environmental justice threats at sourcing locations. The use of the proposed methods is demonstrated via an exploratory case study examining projected electricity production scenarios within the European Union. Results suggest that renewable sources of electricity─particularly wind, solar, and geothermal technologies─are more likely to exacerbate supply risks and environmental issues than other technologies. Furthermore, projected expansions of wind and solar technologies mean that all three indicators appear likely to rise significantly systemwide by 2050. Ultimately, the methods represent a much-needed first attempt at providing practitioners with simple and robust approaches for integrating factors relating specifically to raw material supply into energy modeling and other applications.

Mapping direct N2O emissions from peri-urban agriculture: The case of the Metropolitan Area of Barcelona.

Geographically explicit datasets reflecting local management of crops are needed to help improve direct nitrous oxide (N2O) emission inventories. Yet, the lack of geographically explicit datasets of relevant factors influencing the emissions make it difficult to estimate them in such way. Particularly, for local peri-urban agriculture, spatially explicit datasets of crop type, fertilizer use, irrigation, and emission factors (EFs) are hard to find, yet necessary for evaluating and promoting urban self-sufficiency, resilience, and circularity. We spatially distribute these factors for the peri-urban agriculture in the Metropolitan Area of Barcelona (AMB) and create N2O emissions maps using crop-specific EFs as well as Tier 1 IPCC EFs for comparison. Further, the role of the soil types is qualitatively assessed. When compared to Tier 1 IPCC EFs, we find 15% more emissions (i.e. 7718 kg N2O-N year-1) than those estimated with the crop-specific EFs (i.e. 6533 kg N2O-N year-1) for the entire AMB. Emissions for most rainfed crop areas like cereals (e.g. oat and barley) and non-citric fruits (e.g. cherries and peaches), which cover 24% and 13% of AMB's peri-urban agricultural area respectively, are higher with Tier 1 EF. Conversely, crop-specific EFs estimate higher emissions for irrigated horticultural crops (e.g. tomato, artichoke) which cover 33% of AMB's peri-urban agricultural area and make up 70% of the total N2O emissions (4588 kg N2O-N year-1 using crop-specific EFs). Mapping the emissions helps evaluate spatial variability of key factors such as fertilizer use and irrigation of crops but carry uncertainties due to downscaling regional data to represent urban level data gaps. It also highlighted core emitting areas. Further the usefulness of the outputs on mitigation, sustainability and circularity studies are briefly discussed.