Search

Bioenergy is often considered an important component, alongside other renewables, to mitigate global warming and to reduce fossil fuel dependency. Determining sustainable strategies for utilizing biomass resources, however, requires a holistic perspective to reflect a wider range of potential environmental consequences. To circumvent the limitations of scenario-based life cycle assessment (LCA), we develop a multiobjective optimization model to systematically identify the environmentally optimal use of biomass for energy under given system constraints. Besides satisfying annual final energy demand, the model constraints comprise availability of biomass and arable land, technology- and system-specific capacities, and relevant policy targets. Efficiencies and environmental performances of bioenergy conversions are derived using biochemical process models combined with LCA data. The application of the optimization model is exemplified by a case aimed at determining the environmentally optimal use of biomass in the Danish energy system in 2025. A multiobjective formulation based on fuzzy intervals for six environmental impact categories resulted in impact reductions of 13-43% compared to the baseline. The robustness of the optimal solution was analyzed with respect to parameter uncertainty and choice of environmental objectives.

Bottom ash, the main solid output from municipal solid waste incineration (MSWI), has significant potential for the recovery of resources such as scrap metals and aggregates. The utilisation of these resources ideally enables natural resources to be saved. However, the quality of the recovered scrap metals may limit recycling potential, and the utilisation of aggregates may cause the release of toxic substances into the natural environment through leaching. A life cycle assessment (LCA) was applied to a full-scale MSWI bottom ash management and recovery system to identify environmental breakeven points beyond which the burdens of the recovery processes outweigh the environmental benefits from valorising metals and mineral aggregates. Experimental data for the quantity and quality of individual material fractions were used as a basis for LCA modelling. For the aggregates, three disposal routes were compared: landfilling, road sub-base and aggregate in concrete, while specific leaching data were used as the basis for evaluating toxic impacts. The recovery and recycling of aluminium, ferrous, stainless steel and copper scrap were considered, and the importance of aluminium scrap quality, choice of marginal energy technologies and substitution rates between primary and secondary aluminium, stainless steel and ferrous products, were assessed and discussed. The modelling resulted in burdens to toxic impacts associated with metal recycling and leaching from aggregates during utilisation, while large savings were obtained in terms of non-toxic impacts. However, by varying the substitution rate for aluminium recycling between 0.35 and 0.05 (on the basis of aluminium scrap and secondary aluminium alloy market value), it was found that the current recovery system might reach a breakeven point between the benefits of recycling and energy expended on sorting and upgrading the scrap., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Resources have received significant attention in recent years resulting in development of a wide range of resource depletion indicators within life cycle assessment (LCA). Understanding the differences in assessment principles used to derive these indicators and the effects on the impact assessment results is critical for indicator selection and interpretation of the results. Eleven resource depletion methods were evaluated quantitatively with respect to resource coverage, characterization factors (CF), impact contributions from individual resources, and total impact scores. We included 2247 individual market inventory data sets covering a wide range of societal activities (ecoinvent database v3.0). Log-linear regression analysis was carried out for all pairwise combinations of the 11 methods for identification of correlations in CFs (resources) and total impacts (inventory data sets) between methods. Significant differences in resource coverage were observed (9-73 resources) revealing a trade-off between resource coverage and model complexity. High correlation in CFs between methods did not necessarily manifest in high correlation in total impacts. This indicates that also resource coverage may be critical for impact assessment results. Although no consistent correlations between methods applying similar assessment models could be observed, all methods showed relatively high correlation regarding the assessment of energy resources. Finally, we classify the existing methods into three groups, according to method focus and modeling approach, to aid method selection within LCA.

This paper presents a regionalized LCA-based multiobjective optimization model of building energy demand and supply for the case of a Swiss municipality for the minimization of greenhouse gas emissions and particulate matter formation. The results show that the environmental improvement potential is very large: in the optimal case, greenhouse gas emissions from energy supply could be reduced by more than 75% and particulate emissions by over 50% in the municipality. This scenario supposes a drastic shift of heat supply systems from a fossil fuel dominated portfolio to a portfolio consisting of mainly heat pump and woodchip incineration systems. In addition to a change in heat supply technologies, roofs, windows and walls would need to be refurbished in more than 65% of the municipality's buildings. The full potential of the environmental impact reductions will hardly be achieved in reality, particularly in the short term, for example, because of financial constraints and social acceptance, which were not taken into account in this study. Nevertheless, the results of the optimization model can help policy makers to identify the most effective measures for improvement at the decision making level, for example, at the building level for refurbishment and selection of heating systems or at the municipal level for designing district heating networks. Therefore, this work represents a starting point for designing effective incentives to reduce the environmental impact of buildings. While the results of the optimization model are specific to the municipality studied, the model could readily be adapted to other regions.

A process model of municipal solid waste incinerators (MSWIs) and new technologies for metal recovery from combustion residues was developed. The environmental impact is modeled as a function of waste composition as well as waste treatment and material recovery technologies. The model includes combustion with a grate incinerator, several flue gas treatment technologies, electricity and steam production from waste heat recovery, metal recovery from slag and fly ash, and landfilling of residues and can be tailored to specific plants and sites (software tools can be downloaded free of charge). Application of the model to Switzerland shows that the treatment of one tonne of municipal solid waste results on average in 425 kg CO2-eq. generated in the incineration process, and 54 kg CO2-eq. accrue in upstream processes such as waste transport and the production of operating materials. Downstream processes, i.e. residue disposal, generates 5 kg CO2-eq. Savings from energy recovery are in the range of 67 to 752 kg CO2-eq. depending on the assumptions regarding the substituted energy production, while the recovery of metals from slag and fly ash currently results in a net saving of approximately 35 kg CO2-eq. A similar impact pattern is observed when assessing the MSWI model for aggregated environmental impacts (ReCiPe) and for non-renewable resource consumption (cumulative exergy demand), except that direct emissions have less and no relevance, respectively, on the total score. The study illustrates that MSWI plants can be an important element of industrial ecology as they provide waste disposal services and can help to close material and energetic cycles., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

India is a major emitter of mercury, a pollutant of global importance. However, quantitative information on mercury flows in the country is lacking. Here, we quantify major transfer pathways for anthropogenic mercury, its emissions to the environment (air, water, soil), and storage in consumer products and anthropogenic sinks (e.g., landfills) in India in the period 2001-2020, and evaluate the potential influence of six pollution control measures. Total mercury emissions in India were approximately 415 tonnes in 2001, 310 tonnes in 2010, and are projected to rise to 540 tonnes in 2020. In 2010, 76% of these emissions went to the atmosphere. The most important emission sources to atmosphere are coal power plants and zinc production. Pesticides were the most important source for emissions to soil in 2005 and dental amalgam in later years. Mercury stocks in products rose from 700 tonnes in 2001 to 1125 tonnes in 2010, and in landfills and ash-made structures (e.g., embankments) from 920 tonnes in 2001 to 1450 tonnes in 2010. These stocks are expected to rise further and may be regarded as stored toxicity, which may become a concern in the future. Total mercury emissions can be reduced by about 50% by combining pollution control measures that target different mercury emission sources.