Energy Intensities and Carbon Dioxide Emissions in a Social Accounting Matrix Model of the Andalusian Economy

The aim of this article is to calculate energy intensity and carbon dioxide (CO₂) emissions in Andalusia, the largest and most populated region of Spain. Energy intensities for five energy commodities used in production activities are calculated using a social accounting matrix (SAM) model with three alternative scenarios, each utilizing differing closure rules. More interestingly, by using 2005 data and updating the values of exogenous accounts, the article also provides estimates of CO₂ emissions ten years out from the 1995 base year. Finally, counterfactual experiments are performed to quantify the overall reduction in direct energy coefficients that would have made it possible to maintain constant production‐sector emissions from 1995 to 2005. The results indicate that there is a strong interdependence among energy sectors and the most intensive energy users; they also indicate the importance of induced effects when factor accounts and private consumption are endogenous. The estimates obtained concerning CO₂ emissions are close to official estimates, both from 1995 and 2005. The counterfactual experiments indicate that a 26.5% cut in the size of direct energy requirements would have made it possible to maintain constant emissions. They also indicate that efforts to curtail emissions should be focused on improving efficiency in coal extraction and combustion and oil refining.     

Water Consumption Based on a Disaggregated Social Accounting Matrix of Huesca (Spain)

Making use of the social accounting matrix (SAM) of the Spanish province of Huesca in 2002, updated following Junius and Oosterhaven's GRAS method and work by Lenzen and colleagues, we have estimated the water footprint of the region. The water footprint is defined as the volume of water needed for the production of the goods and services consumed by the inhabitants plus the direct consumption in the households. We built an open Leontief model, which gives us the water embodied in the production of goods. The valuations concern the industrial, service, and domestic sectors’ water consumption, the embodied water imported from and exported to other countries, and the agrarian water use. This agrarian sector, clearly the sector that shows the greatest water consumption, is carefully examined, so it is disaggregated for the calculations into 31 irrigation land products, dry land, and 9 livestock classifications. As a consequence, the framework enables the observation of the relationships and flows of water taking place among all the sectors and activities in the economy. Finally, we also make use of the per capita water footprint estimations to get a clear picture of how the responsibility for water use is distributed once foreign trade is taken into account.     

When Do Allocations and Constructs Respect Material,Energy, Financial,and Production Balances in LCA and EEIO?

Conservation of mass and energy are essential to physical accounting, just as price and market balances are essential to economic accounting. These principles guide data collection and inventory compilation in industrial ecology. The resulting balanced surveys, however, can rarely be used directly for life cycle assessment (LCA) or environmentally extended input‐output (EEIO) analysis; some modeling is necessary to recast coproductions by multifunctional activities as monofunctional unit processes (a.k.a. Leontief production functions or technical “recipes”). This modeling is done with allocations in LCA and constructs in input‐output. In this article, we ask how these models respect or perturb the balances of the original inventory. Which allocations or constructs, applied to what type of data set, have the potential to simultaneously respect its multiple physical, financial, and market balances? Our analysis builds upon the recent harmonization of allocations and constructs and the ongoing development of multilayered supply and use inventory tables. We derive the necessary and sufficient conditions for balanced models, investigate the role of data aggregation, and clarify these models' relation to system expansion. We find that none of the modeling families in LCA and EEIO are balanced in general, but special data characteristics can allow for the respect of multiple balances. An analysis of these special cases allows for clear guidance for data compilation and methods integration.     

Structural Decomposition Analysis of Raw Material Consumption

The aim of this article is to quantify the drivers for the changes in raw material consumption (domestic material consumption expressed in the form of all materials extracted and used in the production phase) in terms of technology, which refers to the concept of sustainable production; the product structure of final demand, which refers to the concept of sustainable consumption; and the volume of final demand, which is related to economic growth. We also aim to determine to what extent the technological development and a shift in product structure of the final demand compensate for the growth in final consumption volume. Therefore, we apply structural decomposition analysis (SDA) to the change in raw material consumption (RMC) of the Czech Republic between 2000 and 2007. To present the study in a broader context, we also show other material flow indicators for the Czech Republic for 2000 and 2007. Our findings of SDA show that final demand structure has a very limited effect on the change in material flows. The rapid change in final demand volume was not compensated for crude oil, metal ores, construction materials, food crops, and timber. For the material category of non‐iron metal ores, even the change in technology contributes to an increase in material flows. The largest relative increases are reported for non‐iron metal ores (38%) and construction materials (30%). The main changes in material flows related to the Czech Republic are driven by exports and enabled by imports, the main source of these increased material flows. This emphasizes the increasing role of international trade.     

Energy Cost of Living and Associated Pollution for Beijing Residents

China's remarkable economic growth in the last 3 decades has brought about big improvements in quality of life while simultaneously contributing to serious environmental problems. The aim of all economic activities is, ultimately, to provide the population with products and services. Analyzing environmental impacts of consumption can be valuable for illuminating underlying drivers for energy use and emissions in society. This study applies an environmentally extended input‐output analysis to estimate household environmental impact (HEI) of urban Beijing households at different levels of development. The analysis covers direct and indirect energy use and emissions of carbon dioxide (CO₂), sulfur dioxide (SO₂), and nitrogen oxide (NO_x). On the basis of observations of how HEI varies across income groups, prospects for near‐future changes in HEI are discussed. Results indicate that in 2007, an urban resident in Beijing used, on average, 52 gigajoules of total primary energy supply. The corresponding annual emissions were 4.2 tonnes CO₂, 27 kilograms SO₂, and 17 kilograms NO_x. Of this, only 18% to 34% was used or emitted by the households directly. While the overall expenditure elasticity of energy use is around 0.9, there is a higher elasticity of energy use associated with transport. The results suggest that significant growth in HEI can be expected in the near future, even with substantial energy efficiency improvements.     

Generalized Make and Use Framework for Allocation in Life Cycle Assessment

Allocation in life cycle inventory (LCI) analysis is one of the long‐standing methodological issues in life cycle assessment (LCA). Discussion on allocation among LCA researchers has taken place almost in complete isolation from the series of closely related discussions from the 1960s in the field of input?output economics, regarding the supply and use framework. This article aims at developing a coherent mathematical framework for allocation in LCA by connecting the parallel developments of the LCA and the input?output communities. In doing so, the article shows that the partitioning method in LCA is equivalent to the industry‐technology model in input?output economics, and system expansion in LCA is equivalent to the by‐product‐technology model in input?output output economics. Furthermore, we argue that the commodity‐technology model and the by‐product‐technology model, which have been considered as two different models in input?output economics for more than 40 years, are essentially equivalent when it comes to practical applications. It is shown that the matrix‐based approach used for system expansion successfully solves the endless regression problem that has been raised in LCA literature. A numerical example is introduced to demonstrate the use of allocation models. The relationship of these approaches with consequential and attributional LCA models is also discussed.