Alternatives for natural‐gas‐based heating systems: A quantitative GIS‐based analysis of climate impacts and financial feasibility

The heating of buildings currently produces 6% of global greenhouse gas emissions. Sustainable heating technologies can reduce heating‐related CO₂ emissions by up to 90%. We present a Python‐based GIS model to analyze the environmental and financial impact of strategies to reduce heating‐related CO₂ emissions of residential buildings. The city‐wide implementation of three alternatives to natural gas are evaluated: high‐temperature heating networks, low‐temperature heating networks, and heat pumps. We find that both lowering the demand for heat and providing more sustainable sources of heat will be necessary to achieve significant CO₂‐emission reductions. Of the studied alternatives, only low‐temperature heating networks and heat pumps have the potential to reduce CO₂ emissions by 90%. A CO₂ tax and an increase in tax on the use of natural gas are potent policy tools to accelerate the adoption of low‐carbon heating technologies.     

Life Cycle Assessment of Greenhouse Gas Emissions from Marine Fuels: A Case Study of Saudi Crude Oil versus Natural Gas in Different Global Regions

The understanding of the greenhouse gas (GHG) emissions dimension in discussing the future of marine fuels makes it important to advance the current life cycle assessment (LCA) practice in this context. Previous LCA studies of marine fuels rely on general LCA models such as GREET and JEC well‐to‐wheels study. These models do not fully capture the various methane losses in the fuel supply chain. The primary goal of this LCA study is to compare the GHG emissions of heavy fuel oil and marine gas oil produced from Saudi crude oil to liquefied natural gas (LNG) in different global regions. A sensitivity analysis was performed to show how results may vary with non‐Saudi crudes. A secondary goal was to advance LCA of marine fuels by utilizing, for the first time, a set of bottom‐up engineering models that enable detailed analysis of specific oil and gas projects worldwide. The results show particular cases where LNG use in marine applications has a significant countereffect in terms of climate change compared to conventional marine fuels produced from a low‐carbon‐intensity crude oil. When the results are calculated based on a 20‐ versus 100‐year methane global warming potential, LNG appears noncompetitive for climate impact in marine applications.     

Applying the Technology Choice Model in Consequential Life Cycle Assessment: A Case Study in the Peruvian Agricultural Sector

Demand for grapes to produce pisco in southern‐coastal Peru is expected to double by 2030. However, the appellation of this beverage confines the production and limits the space for agricultural expansion, leading to a situation in which potential competition for resources with established constraints is foreseen. Hence, the objective of this study is to understand the environmental impacts, focused on climate change and water consumption, linked to the agricultural dynamism in the valleys of Ica and Pisco due to an increase in the demand of pisco. For this, the viticulture system was analyzed regarding predicted changes in terms of expansion, displacement or intensification using a consequential life cycle assessment (CLCA) approach, identifying the environmental consequences of these shifts. A two‐step CLCA model was used based on the results of a previous attributional study, in which marginal effects were estimated following the stochastic technology‐of‐choice model (STCM) operational framework. Results identified a potential for the increase of pisco production based on crop substitution in the valleys of Ica and Pisco and suggest that greenhouse gas emissions and water consumption will be reduced locally, but the displaced agricultural production would reverse this tendency. Regardless of the policy implications of the results in the analyzed system, the proposed methodology constitutes a robust methodology that can be applied to other highly constrained agricultural systems, namely, those regulated by geographic indications.     

The influence of consumer behavior on energy,greenhouse gas,and water footprints of showering

Understanding variability in consumer behavior can provide further insights into how to effectively reduce environmental footprints related to household activities. Here, we developed a stochastic model to quantify the energy, greenhouse gas (GHG), and water consumption footprints of showering in four different countries (Australia, Switzerland, the United Kingdom, and the United States of America). We assessed the influence of two broadly distinct categories of behavior on the footprints of showering: habitual behaviors and one‐off reasoned actions. We also investigated whether changing showering behavior has a substantial impact on the associated energy, GHG, and water footprints. Our results show that the variation in environmental footprints within the countries due to differences in consumer behavior is a factor of 6–17 (95th percentile/5th percentile) depending on the country and the indicator selected. Both consumers’ reasoned actions (especially the choice of a specific heater and shower type) and habitual behaviors (length of showering in particular, are the dominant sources of footprint variability. Significant savings are achievable by making better one‐off decisions such as buying an efficient water heater and by taking shorter showers.     

International Regulation on Low-Carbon Shipping for Climate Change Mitigation: Development,Challenges, and Prospects

This article outlines the contribution of international shipping to climate change and examines different approaches to regulate international shipping activities to reduce greenhouse gas (GHG) emissions. It considers challenges such as the allocation of GHG emissions to individual states, the selection of the most effective mitigation and regulatory measures, the potential for a disproportionate burden to fall upon developing states, and the debate about whether the United Nations (UN) or the International Maritime Organization (IMO) is the appropriate international authority to regulate emissions from international shipping.     

The role of rice cultivation in changes in atmospheric methane concentration and the Global Methane Pledge

Resumption of the increase in atmospheric methane (CH₄) concentrations since 2007 is of global concern and may partly have resulted from emissions from rice cultivation. Estimates of CH₄ emissions from rice fields and abatement potential are essential to assess the contribution of improved rice management in achieving the targets of the Global Methane Pledge agreed upon by over 100 countries at COP26. However, the contribution of CH₄ emissions from rice fields to the resumed CH₄ growth and the global abatement potential remains unclear. In this study, we estimated the global CH₄ emissions from rice fields to be 27 ± 6 Tg CH₄ year⁻¹ in the recent decade (2008–2017) based on the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. The trend of CH₄ emissions from rice cultivation showed an increase followed by no significant change and then, a stabilization over 1990–2020. Consequently, the contribution of CH₄ emissions from rice fields to the renewed increase in atmospheric CH₄ concentrations since 2007 was minor. We summarized the existing low-cost measures and showed that improved water and straw management could reduce one-third of global CH₄ emissions from rice fields. Straw returned as biochar could reduce CH₄ emissions by 12 Tg CH₄ year⁻¹, equivalent to 10% of the total reduction of all anthropogenic emissions. We conclude that other sectors than rice cultivation must have contributed to the renewed increase in atmospheric CH₄ concentrations, and that optimizing multiple mitigation measures in rice fields could contribute significantly to the abatement goal outlined in the Global Methane Pledge.     

Modeling Corn Ethanol and Climate

New fuel regulations based on life cycle greenhouse gas (GHG) emissions have focused renewed attention on life cycle models of biofuels. The BESS model estimates 25% lower life cycle GHG emissions for corn ethanol than does the well-known GREET model, which raises questions about which model is more accurate. I develop a life cycle metamodel to compare the GREET and BESS models in detail and to explain why the results from these models diverge. I find two main reasons for the divergence: (1) BESS models a more efficient biorefinery than is modeled in the cases to which its results have been compared, and (2) in several instances BESS fails to properly count upstream emissions. Adjustments to BESS to account for these differences raise the estimated global warming intensity (not including land use change) of the corn ethanol pathway considered in that model from 45 to 61 g CO₂e MJ⁻¹. Adjusting GREET to use BESS's biorefinery performance and coproduct credit assumptions reduces the GREET estimate from 64 to 61 g CO₂e MJ⁻¹. Although this analysis explains the gap between the two models, both models would be improved with better data on corn production practices and by better treatment of agricultural inputs.     

A plant‐specific model approach to assess effects of repowering measures on existing biogas plants: The case of Baden‐Wuerttemberg

Up to the latest versions of the German renewable energy act (EEG), there had been a constant growth of new biogas plants (BGPs). After reaching a stagnation in the last years, today the focus has shifted to improving the existing BGPs. Assuming that most plants have not reached the technical end of life, the question arises on how an operation can be realized beyond the initial EEG support period of 20 years. In addition, new legal and economic conditions require the implementation of adjustments, that is, “repowering measures.” Based on a method review, a plant‐specific model approach is presented to assess repowering measures for a wide range of BGPs differing in capacity, substrate mixture and agricultural structures. The techno‐economic model includes different performance indicators like levelized cost of electricity (LCOE) and temporal aspects like technical progress. Using a data set for BGPs in the state of Baden‐Wuerttemberg (Germany), results are illustrated for the different model modules and three repowering scenarios of an extended operation period of ten years. The scenarios regard different options to meet the requirements of the current EEG, namely the flexibilization and restrictions on energy crops, in comparison with a reference case. While in repowering scenarios, the number of plants decreases between 54% and 69% and the overall power capacity changes between ?48% and 13% until 2035. The results further show a reduction potential in the specific area demand and GHG emission up to 12% and 24%, respectively. Technical progress, additional revenues and capacity premiums are shown to be an important factor for efficient substrate utilization, low LCOE and thereby the enabling of an extended operation period. The scenario results indicate that the agricultural areas for energy crop cultivation and the amount of manure used in BGPs will be reduced considerably, inducing new chances and challenges in the future.     

Quantifying GHG emissions enabled by capital and labor: Economic and gender inequalities in France

Many studies have investigated the carbon footprint of households. They rely on consumption-based responsibility and focus on how many emissions are embodied in a product. Here we open a new field by discussing the emissions that individuals enable by providing labor and capital to companies, using the framework of income-based (downstream) responsibility. This perspective focuses on the emissions enabled by providing inputs to production processes, and is relevant for discussion of sustainable work and the carbon impact of investment and financial portfolios. We compute the downstream carbon intensity of primary inputs for 35 industries in France using the multi-regional input–output database EXIOBASE. We provide a detailed picture of enabled emissions, disaggregating those by industry and primary inputs. On average, capital inputs are more carbon intensive than labor inputs. Finally, we couple downstream carbon intensities with an extensive national survey on wages to obtain a distribution of the income-based emissions of employees. Income-based emissions are much more unequally distributed than wages due to the huge variability of carbon intensity across industries: a truck driver enables far more emissions than a social-care worker. Inequalities in emissions do not strongly interact with economic inequality. Yet they are gendered because women work disproportionately in low-carbon-intensive industries such as healthcare. As a result, women contribute less to GHG emissions than their wage share would seem to indicate.