Evaluating the suitability of marginal land for a perennial energy crop on the Loess Plateau of China

Abstract With a large marginal land area, the Loess Plateau in China holds great potential for biomass production and environmental improvement. Identifying suitable locations for biomass production on marginal land is important for decision‐makers from the viewpoint of land‐use planning. However, there is limited information on the suitability of marginal land within the Loess Plateau for biomass production. Therefore, this study aims to evaluate the suitability of the promising perennial energy crop switchgrass (Panicum virgatum L.) on marginal land across the Loess Plateau. A fuzzy logical model was developed and validated based on field trials on the Loess Plateau and applied to the marginal land of this region, owing to its ability of dealing with the continuous nature of soil, landscape variations, and uncertainties of the input data. This study identified that approximately 12.8–20.8 Mha of the Loess Plateau as available marginal land, of which 2.8–4.7 Mha is theoretically suitable for switchgrass cultivation. These parts of the total marginal land are mainly distributed in northeast and southwest of the Loess Plateau. The potential yield of switchgrass ranges between 44 and 77 Tg. This study showed that switchgrass can grow on a large proportion of the marginal land of the Loess Plateau and therefore offers great potential for biomass provision. The spatial suitability maps produced in this study provide information to farmers and policymakers to enable a more sustainable development of biomass production on the Loess Plateau. In addition, the fuzzy‐theory‐based model developed in this study provided a good framework for evaluating the suitability of marginal land

The distribution of food security impacts of biofuels, a Ghana case study

The demand for biofuels is expected to increase significantly in the coming years. However, there are major concerns on the impact of increased biofuel production on food security. As biofuel affects food security in various ways, it is important to assess the impacts on the four pillars of food security, availability, access, utilisation and stability. The objective of this study is to ex-ante quantify impacts of biofuel production on the four pillars of food security for urban and rural households in a developing country. We illustrate this for Ghana, which proposed a 10% biodiesel and 15% ethanol mandate for 2030 and which faces food security issues. We used the computable general equilibrium (CGE) model MAGNET in combination with a household and a nutrition module to quantify 13 food security indicators. The results show that the largest food security effects of the biofuel mandate are negative impacts on food prices and import dependency. However, the projected food security impacts of the biofuel mandate in 2030 are relatively small compared to the projected food security effects of economic development in Ghana towards 2030. Our approach enables ex-ante quantification of the effects of biofuel on the four pillars of food security and the differentiation of the effects between urban and rural households. Although improvements can be made, the approach means a big step forward compared to the state-of-the-art knowledge on food security impacts of biofuel production and it could contribute to identify options to minimise negative and optimise positive food security effects

Greenhouse gas emission curves for advanced biofuel supply chains

Most climate change mitigation scenarios that are consistent with the 1.5–2 °C target rely on a large-scale contribution from biomass, including advanced (second-generation) biofuels. However, land-based biofuel production has been associated with substantial land-use change emissions. Previous studies show a wide range of emission factors, often hiding the influence of spatial heterogeneity. Here we introduce a spatially explicit method for assessing the supply of advanced biofuels at different emission factors and present the results as emission curves. Dedicated crops grown on grasslands, savannahs and abandoned agricultural lands could provide 30 EJBiofuel yr−1 with emission factors less than 40 kg of CO2-equivalent (CO2e) emissions per GJBiofuel (for an 85-year time horizon). This increases to 100 EJBiofuel yr−1 for emission factors less than 60 kgCO2e GJBiofuel −1. While these results are uncertain and depend on model assumptions (including time horizon, spatial resolution, technology assumptions and so on), emission curves improve our understanding of the relationship between biofuel supply and its potential contribution to climate change mitigation while accounting for spatial heterogeneity

GHG Balance of Agricultural Intensification & Bioenergy Production in the Orinoquia Region, Colombia

Energy crop expansion can increase land demand and generate displacement of food crops, which impacts greenhouse gas (GHG) emissions mainly through land-use change (LUC). Increased agricultural productivity could compensate for this. Our study aims to evaluate the regional combined GHG emissions of increasing agricultural yields for food crop and beef production and using the generated surplus land for biomass production to replace fossil fuels in the Orinoquia region of Colombia until 2030. The results show that surplus land for biomass production is obtained only when strong measures are applied to increase agricultural productivity. In the medium and high scenario, a land surplus of 0.6 and 2.4 Mha, respectively, could be generated. Such intensification results in up to 83% emission reduction in Orinoquia’s agricultural sector, largely coming from increasing productivity of cattle production and improving degraded pastures. Biofuel potential from the surplus land is projected at 36 to 368 PJ per year, with a low risk of causing indirect LUC, and results in GHG emission reductions of more than 100% compared to its fossil fuel equivalent. An integrated perspective of the agricultural land use enables sustainable production of both food and bioenergy

Integral analysis of environmental and economic performance of combined agricultural intensification & bioenergy production in the Orinoquia region

Agricultural intensification is a key strategy to help meet increasing demand for food and bioenergy. It has the potential to reduce direct and indirect land use change (LUC) and associated environmental impacts while contributing to a favorable economic performance of the agriculture sector. We conduct an integral analysis of environmental and economic impacts of LUC from projected agricultural intensification and bioenergy production in the Orinoquia region in 2030. We compare three agricultural intensification scenarios (low, medium, high) and a reference scenario, which assumes a business-as-usual development of agricultural production. The results show that with current inefficient management or with only very little intensification between 26% and 93% of the existing natural vegetation areas will be converted to agricultural land to meet increasing food demand. This results in the loss of biodiversity by 53% and increased water consumption by 111%. In the medium and high scenarios, the intensification allows meeting increased food demand within current agricultural lands and even generating surplus land which can be used to produce bioenergy crops. This results in the reduction of biodiversity loss by 8-13% with medium and high levels of intensification compared to the situation in 2018. Also, a positive economic performance is observed, stemming primarily from intensification of cattle production and additional energy crop production. Despite increasing irrigation efficiency in more intensive production systems, the water demand for perennial crops and cattle production over the dry season increases significantly, thus sustainable management practices that target efficient water use are needed. Agricultural productivity improvements, particularly for cattle production, are crucial for reducing the pressure on natural areas from increasing demand for both food products and bioenergy. This implies targeted investments in the agricultural sector and integrated planning of land use. Our results showed that production intensification in the Orinoquia region is a mechanism that could reduce the pressure on natural land and its associated environmental and economic impacts

Environmental co-benefits and adverse side-effects of alternative power sector decarbonization strategies

A rapid and deep decarbonization of power supply worldwide is required to limit global warming to well below 2 °C. Beyond greenhouse gas emissions, the power sector is also responsible for numerous other environmental impacts. Here we combine scenarios from integrated assessment models with a forward-looking life-cycle assessment to explore how alternative technology choices in power sector decarbonization pathways compare in terms of non-climate environmental impacts at the system level. While all decarbonization pathways yield major environmental co-benefits, we find that the scale of co-benefits as well as profiles of adverse side-effects depend strongly on technology choice. Mitigation scenarios focusing on wind and solar power are more effective in reducing human health impacts compared to those with low renewable energy, while inducing a more pronounced shift away from fossil and toward mineral resource depletion. Conversely, non-climate ecosystem damages are highly uncertain but tend to increase, chiefly due to land requirements for bioenergy

Emerging technologies in the renewable energy sector: A comparison of expert review with a text mining software

This paper compares the results from quantitative text mining to qualitative expert reviews to identify emerging technologies in the fields of solar photovoltaics (PV), wind power, ocean and tidal energy, hydropower. The text mining analysis is based on the software “Tools for Innovation Monitoring” (TIM). The TIM software extracts a set of relevant keywords from a corpus of pertinent scientific publications. TIM outputs are compared to those extracted by the software VOSviewer, showing agreement. The top 300 ranked keywords are the optimum trade-off between retrieved technologies and analyst efforts. The emerging technologies identified by the experts can be retrieved in the top 300 keywords with a probability of 65%, 25%, depending on the technology sector and the algorithm adopted. The more salient keywords tend to correspond to technologies with an established and univocal jargon such as: "dye sensitised solar cells" or "vertical axis wind turbines". Two methods are here used and compared: the frequency of author keywords and the term frequency-inverse document frequency (TF-IDF) algorithm. The comparison of their performances is not showing a general prevalence of one method against the other, but rather a different suitability to different technology sectors

Life cycle sustainability analysis applied to an innovative configuration of concentrated solar power

Purpose Life cycle sustainability analysis (LCSA) is being developed as a holistic tool to evaluate environmental, economic and social impacts of products or services throughout their life cycle. This study responds to the need expressed by the scientific community to develop and test LCSA methodology, by assessing the sustainability of a concentrated solar power (CSP) plant based on HYSOL technology (an innovative configuration delivering improved efficiency and power dispatchability). Methods The methodology proposed consists of three stages: goal and scope definition, modelling and application of tools, and interpretation of results. The goal of the case study was to investigate to what extent may the HYSOL technology improve the sustainability of power generation in the Spanish electricity sector. To this purpose, several sustainability sub-questions were framed and different analysis tools were applied as follows: attributional and consequential life cycle assessment, life cycle cost (LCC) analysis and multiregional input-output analysis (MRIO), and social life cycle assessment (S-LCA) in combination with social risk assessment (with the Social Hotspots Database). Visual diagrams representing the sustainability of the analysed scenarios were also produced to facilitate the interpretation of results and decision making. Results and discussion The results obtained in the three sustainability dimensions were integrated using a “questions and answers” layout, each answer describing a specific element of sustainability. The HYSOL technology was investigated considering two different operation modes: HYSOL BIO with biomethane as hybridization fuel and HYSOL NG with natural gas. The results indicated that the deployment of HYSOL technology would produce a reduction in the climate change impact of the electricity sector for both operation modes. The LCC analysis indicated economic benefits per MWh for a HYSOL NG power plant, but losses for a HYSOL BIO power plant. The MRIO analysis indicated an increase in goods and services generation, and value added for the HYSOL technology affecting primarily Spain and to a lower extent other foreign economies. The social analysis indicated that both alternatives would provide a slight increase of social welfare Spain. Conclusions The methodological approach described in this investigation provided flexibility in the selection of objectives and analysis tools, which helped to quantify the sustainability effect of the system at a micro and meso level in the three sustainability dimensions. The results indicated that the innovation of HYSOL power plants is well aimed to improve the sustainability of CSP technology and the Spanish electricity sector

Improving the analytical framework for quantifying technological progress in energy technologies

This article reviews experience curve applications in energy technology studies to illustrate best practices in analyzing technological learning. Findings are then applied to evaluate future performance projections of three emerging offshore energy technologies, namely, offshore wind, wave & tidal, and biofuel production from seaweed. Key insights from the review are: First, the experience curve approach provides a strong analytical construct to describe and project technology cost developments. However, disaggregating the influences of individual learning mechanisms on observed cost developments demands extensive data requirements, e.g., R&D expenditures, component level cost information, which are often not publicly available/readily accessible. Second, in an experience curve analysis, the LR estimate of the technology is highly sensitive towards the changes in model specifications and data assumptions. Future studies should evaluate the impact of these variations and inform the uncertainties associated with using the observed learning rates. Third, the review of the literature relevant to offshore energy technology developments revealed that experience curve studies have commonly applied single-factor experience curve model to derive technology cost projections. This has led to an overview of the role of distinct learning mechanisms (e.g., learning-by-doing, scale effects), and factors (site-specific parameters) influencing their developments. To overcome these limitations, we propose a coherent framework based on the findings of this review. The framework disaggregates the technological development process into multiple stages and maps the expected data availability, characteristics, and methodological options to quantify the learning effects. The evaluation of the framework using three offshore energy technologies signals that the data limitations that restrict the process of disaggregating the learning process and identifying cost drivers can be overcome by utilizing detailed bottom-up engineering cost modeling and technology diffusion curves; with experience curve models

Straw utilization for biofuel production: A consequential assessment of greenhouse gas emissions from bioethanol and biomethane provision with a focus on the time dependency of emissions

The shift from straw incorporation to biofuel production entails emissions from production, changes in soil organic carbon (SOC) and through the provision of (co-)products and entailed displacement effects. This paper analyses changes in greenhouse gas (GHG) emissions arising from the shift from straw incorporation to biomethane and bioethanol production. The biomethane concept comprises comminution, anaerobic digestion and amine washing. It additionally provides an organic fertilizer. Bioethanol production comprises energetic use of lignin, steam explosion, enzymatic hydrolysis and co-fermentation. Additionally, feed is provided. A detailed consequential GHG balance with in-depth focus on the time dependency of emissions is conducted: (a) the change in the atmospheric load of emissions arising from the change in the temporal occurrence of emissions comparing two steady states (before the shift and once a new steady state has established); and (b) the annual change in overall emissions over time starting from the shift are assessed. The shift from straw incorporation to biomethane production results in net changes in GHG emissions of (a) −979 (−436 to −1,654) and (b) −955 (−220 to −1,623) kg CO2-eq. per tdry matter straw converted to biomethane (minimum and maximum). The shift to bioethanol production results in net changes of (a) −409 (−107 to −610) and (b) −361 (57 to −603) kg CO2-eq. per tdry matter straw converted to bioethanol. If the atmospheric load of emissions arising from different timing of emissions is neglected in case (a), the change in GHG emissions differs by up to 54%. Case (b) reveals carbon payback times of 0 (0–49) and 19 (1–100) years in case of biomethane and bioethanol production, respectively. These results demonstrate that the detailed inclusion of temporal aspects into GHG balances is required to get a comprehensive understanding of changes in GHG emissions induced by the introduction of advanced biofuels from agricultural residues