The carbon footprint of desalination: An input-output analysis of seawater reverse osmosis desalination in Australia for 2005–2015

This study examines greenhouse gas emissions for 2005–2015 from seawater desalination in Australia, using conventional energies. We developed a tailor-made multi-regional input-output-model. We complemented macroeconomic top-down data with plant-specific desalination data of the largest 20 desalination plants in Australia. The analysed capacity cumulates to 95% of Australia's overall seawater desalination capacity. We considered the construction and the operation of desalination plants. We measure not only direct effects, but also indirect effects throughout the entire value chain. Our results show the following: We identify the state of Victoria with the highest emissions due to capital and operational expenditures (capex and opex). The contribution of the upstream value chain to total greenhouse gas emissions increases for capex and decreases for opex. For capex, the construction of intake and outfall is the driving factor for carbon emissions. For opex, electricity consumption is the decisive input factor. Both in construction and operation, we identify the critical role of the electricity sector for carbon emissions throughout the supply chain effects. The sector contributes 69% during the zenith of the construction phase and 96% during the operating phase to the entire emissions. We estimate the total emissions for 2015 at 1193 kt CO2e

A note on the use of supply-use tables in impact analyses

Little attention has so far been paid to the problems inherent in interpreting the meaning of results from standard impact analyses using symmetric input-output tables. Impacts as well as drivers of these impacts must be either of the product type or of the industry type. Interestingly, since supply-use tables distinguish products and industries, they can cope with product impacts driven by changes in industries, and vice versa. This paper contributes in two ways. Firstly, the demanddriven Leontief quantity model, both for industry-by-industry as well as for product-by-product tables, is formalised on the basis of supply-use tables, thus leading to impact multipliers, both for industries and products. Secondly, we demonstrate how the supply-use formulation can improve the incorporation of disparate satellite data into input-output models, by offering both industry and product representation. Supply-use blocks can accept any mix of industry and product satellite data, as long as these are not overlapping

The need to decelerate fast fashion in a hot climate - A global sustainability perspective on the garment industry

Controversy exists regarding the scale of the impacts caused by fast fashion. This article aims to provide a robust basis for discussion about the geography, the scale and the temporal trends in the impacts of fast fashion because the globalisation of the fashion industry means original, peer-reviewed, quantitative assessments of the total impacts are relatively rare and difficult to compare. This article presents the first application of Eora, a multiregional environmentally extended input output model, to the assessment of the impacts of clothing and footwear value chain. We focus on the key environmental indicators of energy consumption, climate and water resources impacts, and social indicators of wages and employment. The results of the analysis indicate that the climate impact of clothing and footwear consumption rose from 1.0 to 1.3 Gt carbon dioxide equivalent over the 15 years to 2015. China, India, the USA and Brazil dominate these figures. The trends identified in this and the other indicators represent small increases over the study period compared to the 75% increase in textile production, meaning that the impacts per garment have improved considerably. On the other hand, the climate and water use impacts are larger as a proportion of global figures than the benefits provided via employment and wages. Our analysis of energy consumption suggests most of the per-garment improvement in emissions is the result of increased fashion-industrial efficiency, with a lesser role being played by falling carbon intensity among energy suppliers. While both the social benefits and environmental impacts per mass of garment appear to have decreased in recent times, much greater improvements in the absolute carbon footprint of the fashion industry are attainable by eliminating fossil-fueled electricity supplies, and by eliminating fast fashion as a business model

Consequences of long-term infrastructure decisions—the case of self-healing roads and their CO2 emissions

What could be the reduction in greenhouse gas emissions if the conventional way of maintaining roads is changed? Emissions of greenhouse gases must be reduced if global warming is to be avoided, and urgent political and technological decisions should be taken. However, there is a lock-in in built infrastructures that is limiting the rate at which emissions can be reduced. Self-healing asphalt is a new type of technology that will reduce the need for fossil fuels over the lifetime of a road pavement, at the same time as prolonging the road lifespan. In this study we have assessed the benefits of using self-healing asphalt as an alternative material for road pavements employing a hybrid input–output-assisted Life-Cycle Assessment, as only by determining the plausible scenarios of future emissions will policy makers identify pathways that might achieve climate change mitigation goals. We have concluded that self-healing roads could prevent a considerable amount of emissions and costs over the global road network: 16% lower emissions and 32% lower costs compared to a conventional road over the lifecycle

Hybrid life cycle assessment (LCA) will likely yield more accurate results than process-based LCA

We analyse the comparative investigation into truncation vs. aggregation errors of process-based and hybrid LCA by Yang et al. 2017. We analyse the validity of their findings when the hypothetical five-sector economy is altered to account for realistic technological and sectoral interdependencies. We show that in such cases the truncation error of process-based LCA outweighs the aggregation error of hybrid LCA. To this end, we compare the dominant eigenvalue of our alternative economy with that of real economies, showing good agreement. The same validity check does not hold for the system used by Yang and colleagues. Additionally, we demonstrate that even simple process systems can have higher dominant eigenvalues, provided they are based on realistic data

Renewable-powered desalination as an optimisation pathway for renewable energy systems: the case of Australia's Murray–Darling Basin

The ecology in the Murray–Darling Basin in Australia is threatened by water scarcity due to climate change and the over-extraction and over-use of natural water resources. Ensuring environmental flows and sustainable water resources management is urgently needed. Seawater desalination offers high potential to deliver water in virtually unlimited quantity. However, this technology is energy-intensive. In order to prevent desalination becoming a driver of greenhouse gases, the operation of seawater desalination with renewables is increasingly being considered. Our study examines the optimisation of the operation of a 100% renewable energy grid by integrating seawater desalination plants and pipelines as a variable load. We use a GIS-based renewable energy load-shifting model and show how both technologies create synergy effects. First, we analyse what quantity of water is missing in the basin in the long run. We determine locations for seawater desalination plants and pipelines to distribute the water into existing storages in the Murray–Darling Basin. Second, we design a pipeline system and calculate the electricity needed to pump the water from the plants to the storages. Third, we use the combined renewable energy load-shifting model. We minimise the total cost of the energy system by shifting energy demand for water production to periods of high renewable energy availability. Our calculations show that in such a system, the unused spilt electricity can be reduced by at least 27 TWh. The electricity system's installed capacity and levelised cost of electricity can be reduced by up to 29%, and 43% respectively. This approach can provide an annual net economic benefit of $22.5 bn. The results illustrate that the expansion of seawater desalination capacity for load-shifting is economically beneficial.TU Berlin, Open-Access-Mittel - 201

2012. Input-Output Scenario Analysis - Using constrained optimisation to integrate dynamic model outputs

Abstract Australia faces significant sustainability challenges in the context of climate change, economic growth, population pressures, and increasing resource scarcity. To provide a systematic and integrated analysis of Australia's future development CSIRO is building up and integrating analytical capacity across different science domains. Environmentally extended input-output analysis is one of the techniques to be used for assessing scenarios of future economic and urban development in Australia and to be integrated with other integrated assessment models (IAM) such as a climate/economic systems model, a stocks-and-flows model, a land-use model and an energy sector model. In this paper we describe the process of generating historic and future time series of environmentally extended multi-state input-output tables of the Australia economy (AUS-MRIO). We use the software tool AISHA which was created for the purpose of building series of contingency tables (for example input-output matrices with environmental extensions). The software operates a matrix balancing algorithm and solves a constrained optimisation problem. Creating a time series of input-output tables involves preparing initial estimates, defining and scripting constraints, and setting appropriate boundary conditions. AISHA will not only be used to update an existing AUS-MRIO from 1999 to 2008, but also to implement scenario variables derived from other IAM models as exogenous constraints. Effectively, this creates a dynamically extended version of AUS-MRIO linked to defined scenario pathways. The novelty of our work lies in the cross-model integration of scenario variables by implementing a mechanism to use these variables as data constraints in future time series of IO tables. Application of the dynamically extended IO tool in (urban) sustainability analyses adds the perspective of consumption-based environmental accounting to integrated assessment modelling

Desalination and sustainability: a triple bottom line study of Australia

For many arid countries, desalination is considered as the final possible option to ensure water availability. Although seawater desalination offers the utilisation of almost infinite water resources, the technology is associated with high costs, high energy consumption and thus high carbon emissions when using electricity from fossil sources. In our study, we compare different electricity mixes for seawater desalination in terms of some economic, social and environmental attributes. For this purpose, we developed a comprehensive multi-regional input-output model that we apply in a hybrid life-cycle assessment spanning a period of 29 yr. In our case study, we model desalination plants destined to close the water gap in the Murray-Darling basin, Australia's major agricultural area. We find that under a 100%-renewable electricity system, desalination consumes 20% less water, emits 90% less greenhouse gases, and generates 14% more employment. However, the positive impacts go hand in hand with 17% higher land use, and a 10% decrease in gross value added, excluding external effects.TU Berlin, Open-Access-Mittel – 202

Consumption in the G20 nations causes particulate air pollution resulting in two million premature deaths annually

G20の消費がPM2.5の排出を通じて年200万人の早期死亡者を生むことを推計. 京都大学プレスリリース. 2021-11-05.Worldwide exposure to ambient PM₂.₅ causes over 4 million premature deaths annually. As most of these deaths are in developing countries, without internationally coordinated efforts this polarized situation will continue. As yet, however, no studies have quantified nation-to-nation consumer responsibility for global mortality due to both primary and secondary PM2.5 particles. Here we quantify the global footprint of PM₂.₅-driven premature deaths for the 19 G20 nations in a position to lead such efforts. G20 consumption in 2010 was responsible for 1.983 [95% Confidence Interval: 1.685–2.285] million premature deaths, at an average age of 67, including 78.6 [71.5–84.8] thousand infant deaths, implying that the G20 lifetime consumption of about 28 [24–33] people claims one life. Our results indicate that G20 nations should take responsibility for their footprint rather than focusing solely on transboundary air pollution, as this would expand opportunities for reducing PM2.5-driven premature mortality. Given the infant mortality footprint identified, it would moreover contribute to ensuring infant lives are not unfairly left behind in countries like South Africa, which have a weak relationship with G20 nations