Angelica Mendoza Beltran

Reduction targets and abatement costs of developing countries resulting from global and developed countries’ reduction targets by 2050

The European Union (EU) has advocated an emission reduction target for developed countries of 80% to 95% below the 1990 level by 2050, and a global reduction target of 50%. Developing countries have resisted the inclusion of these targets in both the UN Framework Convention on Climate Change Copenhagen Accord and Cancún Agreements. This paper analyses what these targets would imply for emission targets, abatement costs and energy consumption of developing countries, taking into account the conditional emission reduction pledges for 2020. An 80% reduction target for developed countries would imply more stringent per capita emission targets for developing countries than developed countries by 2050. Moreover, abatement costs of developing countries would be higher than those of developed countries. An 85% to 90% reduction target for developed countries would result in similar per capita emission targets and abatement costs for developed and developing countries by 2050. Total reduction targets for developing countries would range from 30% to 40% below 2005 levels by 2050 and from 30% to 35% above 2005 levels by 2030. The 2030 target for China would be 40% to 45% above 2005 levels, compared to a target for the EU of 45% to 50% below 1990 and for the United States of America (USA) 30% to 35% below 1990. Emission target trajectories for Brazil, South Africa and China would peak before 2025 and for India by around 2025. From the analysis, we may conclude that from the viewpoint of developing countries either developed countries increase their target above 85%, and/or make substantial side-payments.

The impact of technology availability on the timing and costs of emission reductions for achieving long-term climate targets

While most long-term mitigation scenario studies build on a broad portfolio of mitigation technologies, there is quite some uncertainty about the availability and reduction potential of these technologies. This study explores the impacts of technology limitations on greenhouse gas emission reductions using the integrated model IMAGE. It shows that the required short-term emission reductions to achieve long-term radiative forcing targets strongly depend on assumptions on the availability and potential of mitigation technologies. Limited availability of mitigation technologies which are relatively important in the long run implies that lower short-term emission levels are required. For instance, limited bio-energy availability reduces the optimal 2020 emission level by more than 4 GtCO2eq in order to compensate the reduced availability of negative emissions from bioenergy and carbon capture and storage (BECCS) in the long run. On the other hand, reduced mitigation potential of options that are used in 2020 can also lead to a higher optimal level for 2020 emissions. The results also show the critical role of BECCS for achieving low radiative forcing targets in IMAGE. Without these technologies achieving these targets become much more expensive or even infeasible.

REDD credits in a global carbon market : Options and impacts

How can REDD credits be included in a future global carbon market, and what are the impacts of inclusion? We analyze ten different scenarios through 2020, varying the global emission caps and the REDD rules. An inclusion of REDD credits without any adjustments in the global cap will lower carbon prices significantly and cause crowding out. The cap must move towards the 2 degrees climate target if REDD inclusion is to maintain high carbon prices and strong incentives for emissions reductions in other sectors. At the same time, reaching the 2 degree target without full REDD inclusion will increase global mitigation costs by more than 50%.

Quantified Uncertainties in Comparative Life Cycle Assessment: What Can Be Concluded?

Interpretation of comparative Life Cycle Assessment (LCA) results can be challenging in the presence of uncertainty. To aid in interpreting such results under the goal of any comparative LCA, we aim to provide guidance to practitioners by gaining insights into uncertainty-statistics methods (USMs). We review five USMs—discernibility analysis, impact category relevance, overlap area of probability distributions, null hypothesis significance testing (NHST), and modified NHST–and provide a common notation, terminology, and calculation platform. We further cross-compare all USMs by applying them to a case study on electric cars. USMs belong to a confirmatory or an exploratory statistics’ branch, each serving different purposes to practitioners. Results highlight that common uncertainties and the magnitude of differences per impact are key in offering reliable insights. Common uncertainties are particularly important as disregarding them can lead to incorrect recommendations. On the basis of these considerations, we recommend the modified NHST as a confirmatory USM. We also recommend discernibility analysis as an exploratory USM along with recommendations for its improvement, as it disregards the magnitude of the differences. While further research is necessary to support our conclusions, the results and supporting material provided can help LCA practitioners in delivering a more robust basis for decision-making.

Exploring the bargaining space within international climate negotiations based on political, economic and environmental considerations

This study provides a conceptual framework for exploring the bargaining space within international climate negotiations based on important economic, political and environmental considerations. Based on it, we analyse combinations of the proposed emission reduction ranges for Annex I countries as a group (25–40% below 1990 levels) and non-Annex I as a group (15–30% below baseline) by 2020 to limit global warming to 2°C. We use results of the FAIR model with costs estimates based on two energy system models. We conclude that the range of targets that comply with a set of criteria for economic, political and environmental considerations is smaller than that by environmental considerations alone. More specifically, we find that according to our criteria, a 30% Annex I reduction target below 1990 levels, combined with a 20% non-Annex I reduction target below baseline emission levels (i.e. 20 to 30% above 2005 levels), is the only combination of targets fulfilling all our criteria for both energy system models. Otherwise, reaching the 2°C target becomes less likely, technically infeasible, or non-Annex I abatement costs are likely to exceed those of Annex I, a result, which we consider less plausible from a political viewpoint in our conceptual framework.

Accounting for inventory data and methodological choice uncertainty in a comparative life cycle assessment: the case of integrated multi-trophic aquaculture in an offshore Mediterranean enterprise

PurposeIntegrated multi-trophic aquaculture (IMTA), growing different species in the same space, is a technology that may help manage the environmental impacts of coastal aquaculture. Nutrient discharges to seawater from monoculture aquaculture are conceptually minimized in IMTA, while expanding the farm economic base. In this study, we investigate the environmental trade-offs for a small-to-medium enterprise (SME) considering a shift from monoculture towards IMTA production of marine fish.MethodsA comparative life cycle assessment (LCA), including uncertainty analysis, was implemented for an aquaculture SME in Italy. Quantification and simultaneous propagation of uncertainty of inventory data and uncertainty due to the choice of allocation method were combined with dependent sampling to account for relative uncertainties and statistical testing and interpretation to understand the uncertainty analysis results. Monte Carlo simulations were used as a propagation method. The environmental impacts per kilo of fish produced in monoculture and in IMTA were compared. Twelve impact categories were considered. The comparison is first made excluding uncertainty (deterministic LCA) and then accounting for uncertainties.Results and discussionDeterministic LCA results evidence marginal differences between the impacts of IMTA and monoculture fish production. IMTA performs better on all impacts studied. However, statistical testing and interpretation of the uncertainty analysis results showed that only mean impacts for climate change are significantly different for both productive systems, favoring IMTA. For the case study, technical variables such as scales of production of the species from different trophic levels, their integration (space and time), and the choice of species determine the trade-offs. Also, LCA methodological choices such as that for an allocation method and the treatment of relative uncertainties were determinant in the comparison of environmental trade-offs.ConclusionsThe case study showed that environmental trade-offs between monoculture and IMTA fish production depend on technical variables and methodological choices. The combination of statistical methods to quantify, propagate, and interpret uncertainty was successfully tested. This approach supports more robust environmental trade-off assessments between alternatives in LCAs with uncertainty analysis by adding information on the significance of results. It was difficult to establish whether IMTA does bring benefits given the scales of production in the case study. We recommend that the methodology defined here is applied to fully industrialized IMTA systems or bay-scale environments, to provide more robust conclusions about the environmental benefits of this aquaculture type in Europe.

Uncertain Environmental Footprint of Current and Future Battery Electric Vehicles

The future environmental impacts of battery electric vehicles (EVs) are very important given their expected dominance in future transport systems. Previous studies have shown these impacts to be highly uncertain, though a detailed treatment of this uncertainty is still lacking. We help to fill this gap by using Monte Carlo and global sensitivity analysis to quantify parametric uncertainty and also consider two additional factors that have not yet been addressed in the field. First, we include changes to driving patterns due to the introduction of autonomous and connected vehicles. Second, we deeply integrate scenario results from the IMAGE integrated assessment model into our life cycle database to include the impacts of changes to the electricity sector on the environmental burdens of producing and recharging future EVs. Future EVs are expected to have 45-78% lower climate change impacts than current EVs. Electricity used for charging is the largest source of variability in results, though vehicle size, lifetime, driving patterns, and battery size also strongly contribute to variability. We also show that it is imperative to consider changes to the electricity sector when calculating upstream impacts of EVs, as without this, results could be overestimated by up to 75%.