Concentrated solar power (CSP) can be a flexible renewable resource on electric grids. Here we assess the direct and upstream socio-economic and environmental impacts of the projected deployment of... Show moreConcentrated solar power (CSP) can be a flexible renewable resource on electric grids. Here we assess the direct and upstream socio-economic and environmental impacts of the projected deployment of CSP in China and Europe, using Input-Output Analysis. We first quantify the CSP experience curve, finding a learning rate of similar to 16%, and combine this with future projections for installed capacity from China's National Development and Reform Commission and the International Energy Agency. We find employment intensities of 4.2 and 2.3 person-year/GWh in China and Europe, respectively (higher than PV and wind). The carbon emission intensity of CSP is currently higher than alternatives but this gap may narrow through learning. Carbon intensities are estimated at 129.7 and 99.8 gCO2eq/kWh in 2020 (in China and Europe, respectively) and could drop to 40.4 and 31.1 gCO2eq/kWh by 2050 given the projected expansion. We discuss the importance of including both environ -mental and socio-economic dimensions when assessing the impact of energy technologies and provide context for the role of CSP in the energy transition. Show less
In 2011 China initiated policies to promote the adoption of solar photovoltaic (PV) using feed-in tariff (FIT) policies. Since then the PV domestic market expanded substantially. In the past six... Show moreIn 2011 China initiated policies to promote the adoption of solar photovoltaic (PV) using feed-in tariff (FIT) policies. Since then the PV domestic market expanded substantially. In the past six years, the FIT policies were updated (adjustment of tariff levels, division of three FIT regions, setting of installation quotas) to address emerging problems such as PV waste, explosive installation, unbalanced spatial distribution. This paper aims to investigate the historical development and implementation of FIT policies in China from 2011 to 2016. The tools of net present value (NPV)/internal rate of return (IRR), learning curve and the system dynamics are employed to show the degree of economic incentives of FIT policies, to understand the learning rate of centralized PV systems, and to study the dynamic mechanism of the FIT system. We conclude that in the near term the tariff levels should be adjusted more frequently to keep IRR values in the range of 8–12%, and a tight quota combined with the deployment of ultra-high voltage (UHV) lines should be continued for the provinces with severe PV waste. Show less
Rodrigues, J.F.D.; Marques, A.; Wood, R.; Tukker, A. 2016
Input–output (IO) models, describing trade between different sectors and regions, are widely used to study the environmental repercussions of human activities. A frequent challenge in assembling an... Show moreInput–output (IO) models, describing trade between different sectors and regions, are widely used to study the environmental repercussions of human activities. A frequent challenge in assembling an IO model or linking several such models is the absence of flow data with the same level of detail for all components. Such problems can be addressed using proportional allocation, which is a form of algebraic transformations. In this paper, we propose a novel approach whereby the IO system is viewed as a network, the topology of which is transformed with the addition of virtual nodes so that available empirical flow data can be mapped directly to existing links, with no additional estimation required, and no impact on results. As IO systems become increasingly disaggregated, and coupled to adjacent databases and models, the adaptability of IO frameworks becomes increasingly important. We show that topological transformations also offer large advantages in terms of transparency, modularity and increasingly importantly for global IO models, efficiency. We illustrate the results in the context of trade linking, multi-scale integration and other applications. Show less
Urban metabolism provides a characterization of anthropogenic material flows in urban systemsand should contribute to identify the economic activities that were involved on their supply... Show moreUrban metabolism provides a characterization of anthropogenic material flows in urban systemsand should contribute to identify the economic activities that were involved on their supply andtransformation. Typically, its quantification requires data that is not easily available in differentgeographies. This paper makes use of a methodology based on monetary input–output tables andinternational trade statistics that might be easily replicable to many metropolitan areas in theworld, and which is intended to provide a first rough estimation of urban material flows.The paper discusses the results obtained for four metropolitan areas (Lisbon, Paris, Seoul–Incheonand Shanghai), assessing the material requirements of these economies. The urban areas arecompared in terms of the quantity and the type of material input, destination of materials withinthe economy and their distribution among economic activities. The results showed that whileLisbon is the most diverse urban area in terms of the consumption of material types, it is also theurban area with the least diversified manufacturing sector.The application of this methodology to several urban areas and across multiple years enables theassessment of the technological and economic evolution of those regions Show less
Empirical estimates of source statistical economic data such as trade flows, greenhouse gas emissions or employment figures are always subject to uncertainty (stemming from measurement errors or... Show moreEmpirical estimates of source statistical economic data such as trade flows, greenhouse gas emissions or employment figures are always subject to uncertainty (stemming from measurement errors or confidentiality) but information concerning that uncertainty is often missing. This paper uses concepts from Bayesian inference and the Maximum Entropy Principle to estimate the prior probability distribution, uncertainty and correlations of source data when such information is not explicitly provided. In the absence of additional information, an isolated datum is described by a truncated Gaussian distribution, and if an uncertainty estimate is missing, its prior equals the best guess. When the sum of a set of disaggregate data is constrained to match an aggregate datum, it is possible to determine the prior correlations among disaggregate data. If aggregate uncertainty is missing, all prior correlations are positive. If aggregate uncertainty is available, prior correlations can be either all positive, all negative, or a mix of both. An empirical example is presented, which reports relative uncertainties and correlation priors for the County Business Patterns database. In this example relative uncertainties range from 1 to 80 percent and twenty percent of data pairs exhibit correlations below −0.9 or above 0.9. Show less
