Carbon capture and storage (CCS) is expected to play a key role to achieve deep emission cuts in the energy intensive industry sector. The implementation of carbon capture comes with a considerable investment cost and a significant effect on the plants operating cost, which both depend on site conditions, mainly due to differences in flue gas flow and composition and depending on the availability of excess heat that can be utilized to power the capture unit. In this study we map the costs required to install and operate amine-based post-combustion CO 2 capture at all manufacturing plants in Sweden with annual emissions of 500 kt CO 2 or more, of both fossil and of biogenic origin, of which there are 28 plants (including a petrochemical site, refineries, iron and steel plants, cement plants and pulp and paper mills). The work considers differences in the investment required as well as differences in potential for using excess heat to cover the steam demand of the capture process. We present the resulting total CO 2 capture costs in the form of a marginal abatement cost curve (MACC) for the emission sources investigated. Cost estimations for a transport and storage system are also indicated. The MACC shows that CO 2 capture applied to 28 industrial units capture CO 2 emissions corresponding to more than 50% of Swedish total CO 2 emissions (from all sectors) at a cost ranging from around 40 €/t CO 2 to 110 €/t CO 2 , depending on emission source. Partial capture from the most suited sites may reduce capture cost and, thus, may serve as a low-cost option for introducing CCS. The cost for transport and storage will add some 25 to 40 €/t CO 2 , depending on location and type of transportation infrastructure.

An optimization methodology for identifying robust process integration investments under uncertainty AbstractUncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a fivestep methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures.

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The cultivation and processing of microalgal biomass is resource-and energy-intensive, negatively affecting the sustainability and profitability of producing bulk commodities, limiting this platform to the manufacture of relatively small quantities of high-value compounds. A biorefinery approach where all fractions of the biomass are valorized might improve the case for producing lower-value products. However, these systems are still likely to operate very close to thresholds of profitability and energy balance, with wide-ranging environmental and societal impacts. It thus remains critically important to reduce the use of costly and impactful inputs and energy-intensive processes involved in these scenarios. Integration with industrial infrastructure can provide a number of residual streams that can be readily used during microalgal cultivation and downstream processing. This review critically considers some of the main inputs required for microalgal biorefineries-such as nutrients, water, carbon dioxide, and heat-and appraises the benefits and possibilities for industrial integration on a more quantitative basis. Recent literature and demonstration studies will also be considered to best illustrate these benefits to both producers and industrial operators. Additionally, this review will highlight some inconsistencies in the data used in assessments of microalgal production scenarios, allowing more accurate evaluation of potential future biorefineries.

This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO 2 emissions charges. The work follows the methodology described in Svensson, E. et al. (2008b) where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the timedependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO 2 emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives.