Carbon Footprint Of Consumption Research Articles

The association between the carbon footprint and the socio-economic characteristics of Belgian households

Understanding the demand-side drivers and the distribution of greenhouse gas emissions is key to designing fair and effective environmental policies. In this study, we quantify the relationship between the carbon footprint of consumption and socio-economic characteristics of Belgian households. We use a dataset that combines household-level consumption data with an environmentally extended input-output model which quantifies the greenhouse gas emissions embedded in the supply chain of goods and services that households consume. We find that income and household size are the most important determinants of household consumption-related emissions. We also find the emission intensity of household consumption in the lower part of the income distribution is higher than that of richer households because poorer households spend a higher share on emission intensive products, especially energy.

Negligible impacts of early COVID-19 confinement on household carbon footprints in Japan

The rapid and extensive changes in household consumption patterns during the coronavirus disease 2019 (COVID-19) pandemic can serve as a natural experiment for exploring the environmental outcomes of changing human behavior. Here, we assess the carbon footprint of household consumption in Japan during the early stages of the COVID-19 pandemic (January–May 2020), which were characterized by moderate confinement measures. The associated lifestyle changes did not have a significant effect on the overall household carbon footprint compared with 2015–2019 levels. However, there were significant trade-offs between individual consumption categories such that the carbon footprint increased for some categories (e.g., eating at home) or declined (e.g., eating out, transportation, clothing, and entertainment) or remained relatively unchanged (e.g., housing) for others. Furthermore, carbon footprint patterns between age groups were largely consistent with 2015–2019 levels. However, changes in food-related carbon footprints were visible for all age groups since March and, in some cases, since February.

Quantifying carbon flows in Switzerland: top-down meets bottom-up modelling

Modelling frameworks that aim to support policymakers in deriving effective measures to reduce environmental impacts should provide both: quantitative information on locally occurring consumption patterns and production systems as well as assessment of policy scenario outcomes. Regionalised models that can deliver on these aims are emerging, but are currently limited in resolution or have other restrictions. An advanced model can be achieved by exploiting the advantages and overcoming the limitations of top-down and bottom-up approaches. In this article, we describe a highly detailed, spatially-resolved modelling framework that quantifies local activities and simultaneously analyses system-wide environmental and economic effects of planned interventions. We combined an existing, highly detailed bottom-up model for Switzerland (focusing on individual households) with a macro-economic top-down approach by developing a new Swiss sub-national, multi-region input-output model. We conducted two case studies to demonstrate its abilities and to highlight its usefulness. First, production-based greenhouse gas emissions and consumption-based carbon footprints were computed for all Swiss cantons and regional differences, interdependencies as well as embodied carbon flows among regions were investigated. We find that rural cantons have higher production-based emissions per gross domestic product than more urban cantons because of different economic structures. In contrast, certain ‘city-cantons’ entail highest consumption carbon footprints per inhabitant due to high per-capita gross capital formation. Furthermore, this case study discusses the importance of providing regionalised information on effects of measures along the economic value chains. Second, a detailed scenario assuming a realistic lifestyle change for an actual household and a thorough physical retrofit of its home was set up. Regionalised environmental and economic consequences along the supply chains were evaluated. This case study exemplifies how the modelling framework can be used to inform policymakers about expected benefits and downsides of detailed scenarios and emphasises the importance of considering rebound effects.

The role of allocation of retail trade margins across household segments on their carbon footprint calculation

The homogeneity assumption, inherent to input–output (IO) analysis, implies that every euro spent within one product group is assigned the same environmental burden. We address this assumption applied to price conversion of household expenditures from purchasers’ to basic prices when the carbon footprint of consumption is calculated for specific household segments by linking the IO table and micro-level household consumption data. We perform a sensitivity analysis of the different allocations of the retail trade margin of two consumption groups (Food and Goods) across household expenditure deciles. While a differently allocated retail trade margin influences the carbon footprint of household segments, it does not challenge the general finding that households with higher expenditures are responsible for higher footprints. This finding holds also for different emission intensities of retail trade margins.

Can sustainable restaurant practices enhance customer loyalty? The roles of value theory and environmental concerns

Attracting diner participation in sustainable restaurant practices, such as waste reduction, are highly significant for the environment and in reducing the carbon footprint of food consumption. However, there are concerns as to whether the adoption of sustainable practices in restaurant settings is favored by consumers. To examine such issues we aim to identify, by applying value theory, whether sustainable restaurant practices increase diner loyalty. To do this, this research develops and tests an integrated theoretical model on relationships between sustainable restaurant practices, consumer values (hedonic and utilitarian), environmental concern, and diner behavior. Results reveal that sustainable restaurant practices as a second-order construct of food sustainability and waste reduction influence hedonic/utilitarian values. Sustainable restaurant practices also positively influence diner behavior as a second-order construct of participation in waste reduction practices and loyalty to sustainable restaurants. Diner behavior is affected by hedonic/utilitarian values on waste reduction, which are moderated by environmental concern.

Changing carbon footprint of urban household consumption in Beijing: Insight from a nested input-output analysis

Along with rapid urbanization and economic development, urban household consumption has experienced a remarkable change, leading to a corresponding increase in direct and indirect carbon emissions. A systematic accounting of household carbon footprints (HCFs) in Beijing during 2002, 2007, and 2012 using a nested input-output model is presented in this paper. The results indicate that the per capita carbon footprint from urban household consumption in Beijing increased from 3054.05 kg in 2002–4611.12 kg in 2012, of which the indirect emissions were the majority. In terms of consumption structure, food, housing, transportation and communication, and education and entertainment were the four dominant sources contributing to the indirect urban HCFs in Beijing. With respect to the source, local Beijing was the largest contributor for itself materials and service provisions in 2002 and 2007, while the domestic source became the largest contributor in 2012, accounting for 55.08% of the total indirect household carbon emissions. Moreover, we also discovered that families with high income level had much higher HCFs compared to those with low income level. Given these considerations, transitions towards low-carbon household consumption are needed so as to provide equality and sustainability.

Machine Learning the Carbon Footprint of Bitcoin Mining

Building on an economic model of rational Bitcoin mining, we measure the carbon footprint of Bitcoin mining power consumption using feed-forward neural networks. After reviewing the literature on deep learning methods, we find associated carbon footprints of 3.8038, 23.8313 and 19.83472 MtCOe for 2017, 2018 and 2019, which conform with recent estimates, lie within the economic model bounds while delivering much narrower confidence intervals, and yet raise alarming concerns, given recent evidence from climate-weather integrated models. We demonstrate how machine learning methods can contribute to non-for-profit pressing societal issues, like global warming, where data complexity and availability can be overcome.

A detailed household carbon footprint analysis using expenditure accounts – Case of Flanders (Belgium)

Within national carbon footprints, households are responsible for bulk of the overall direct and indirect carbon emissions. Also, the wide spread in household characteristics (e.g. size, income, age) leads not only to different carbon footprints, but also includes an underlying difference in the contributions of the consumption domains. Therefore, it is essential that policies focussing on climate change mitigation should be customized to take into account these differences. In this study we quantify which socio-economic household characteristics are associated with a higher than average per capita carbon footprint and which consumption domains trigger this higher than average carbon footprint. The results are quantified for the regional case study of Flanders (Belgium). To obtain a better estimate of direct and indirect emissions we draw upon the EXIOBASE2 multi-region input-output dataset combined with the regional input-output data and detailed regional household budget survey data. From our analysis, it is also clear that the decomposition of the carbon footprint into the relevant consumption domains reveals insights that are absent when comparing total carbon footprints. Overall we find that there is a clear link between the income distribution and the carbon footprint of consumption, a finding that returns frequently in literature for both developed and developing countries. However, this income distribution is closely related to several underlying other socio-economic categories (e.g. level of education and household size) which do provide further insights useful for policy as they reveal important socio-economic aspect which needs to be considered.

Agricultural and forestry trade drives large share of tropical deforestation emissions

Deforestation, the second largest source of anthropogenic greenhouse gas emissions, is largely driven by expanding forestry and agriculture. However, despite agricultural expansion being increasingly driven by foreign demand, the links between deforestation and foreign demand for agricultural commodities have only been partially mapped. Here we present a pan-tropical quantification of carbon emissions from deforestation associated with the expansion of agriculture and forest plantations, and trace embodied emissions through global supply chains to consumers. We find that in the period 2010–2014, expansion of agriculture and tree plantations into forests across the tropics was associated with net emissions of approximately 2.6 gigatonnes carbon dioxide per year. Cattle and oilseed products account for over half of these emissions. Europe and China are major importers, and for many developed countries, deforestation emissions embodied in imports rival or exceed emissions from domestic agriculture. Depending on the trade model used, 29–39% of deforestation-related emissions were driven by international trade. This is substantially higher than the share of fossil carbon emissions embodied in trade, indicating that efforts to reduce greenhouse gas emissions from land-use change need to consider the role of international demand in driving deforestation. Additionally, we find that deforestation emissions are similar to, or larger than, other emissions in the carbon footprint of key forest-risk commodities. Similarly, deforestation emissions constitute a substantial share (˜15%) of the total carbon footprint of food consumption in EU countries. This highlights the need for consumption-based accounts to include emissions from deforestation, and for the implementation of policy measures that cross these international supply-chains if deforestation emissions are to be effectively reduced.

The carbon footprint of breastmilk substitutes in comparison with breastfeeding

Breastfeeding is one of the foundations of child health, development and survival. Breastmilk substitutes (BMS) are associated with negative influences on breastfeeding practices and subsequent health concerns and, as with all foods, production and consumption of BMS comes with an environmental cost. The carbon footprint (CFP) of production and consumption of BMS was estimated in this study. To illustrate regional differences among the largest producers and consumers, the CFP of BMS production in New Zealand, United States (USA), Brazil and France and the CFP of BMS consumption in United Kingdom (UK), China, Brazil and Vietnam were assessed. The CFP values were then compared with the CFP of breastfeeding arising from production of the additional food needed for breastfeeding mothers to maintain energy balance (approximately 500 kcal per day). The CFP of production was estimated to be 9.2 ± 1.4, 7.0 ± 1.0, 11 ± 2 and 8.4 ± 1.3 kg CO2e per kg BMS in New Zealand, USA, Brazil and France, respectively, with the largest contribution (68–82% of the total) coming from production of raw milk. The CFP of consumption, which included BMS production, emissions from transport, production and in-home sterilisation of bottles, and preparation of BMS, was estimated to be 11 ± 1, 14 ± 2, 14 ± 2 and 11 ± 1 kg CO2e per kg BMS in UK, China, Brazil and Vietnam, respectively. Comparison of breastfeeding with feeding BMS showed a lower CFP from breastfeeding in all countries studied. However, the results were sensitive to the method used to allocate emissions from raw milk production on different dairy processing co-products (i.e. BMS, cream, cheese and lactose). Using alternative allocation methods still resulted in lower CFP from breastfeeding, but only slightly for UK, Brazil and Vietnam. Care is also needed when interpreting findings about products that are functionally different as regards child health and development.

Research on the changing trend of the carbon footprint of residents' consumption in Beijing.

Emission of greenhouse gas is a global environmental problem. In recent years, China has been facing growing international pressure because of its large energy consumption and elevated greenhouse gas emissions. As the capital of China, Beijing is central to the study of carbon emission reduction since its carbon emissions have ranked at the forefront nationwide. The existing literature mainly revolves around carbon emissions of a few specific years, and there is a lack of trend study of multiple years in Beijing. This paper, based on the input-output method, calculates carbon emissions in Beijing by carbon footprints; the changing trend analysis was carried out by researching available statistical data of three years, 2002, 2007, and 2012, from the perspective of the entire city of Beijing and from that of urban and rural residents' consumption. The reasons for the changing trends of total carbon emission in Beijing have also been analysed using the Structural Decomposition Analysis (SDA) model. Results show that the total direct carbon footprint as well as the urban and rural direct carbon footprints of residents' consumption in Beijing is all increasing gradually. The direct carbon footprint of urban residents' consumption is mainly produced by electricity, gasoline, and heating power, while that of rural residents' consumption is mainly produced by raw coal and electricity. The indirect carbon footprint of residents' consumption in Beijing is increasing gradually, and that of urban areas is higher than that of rural areas. The compositions of indirect carbon footprints of rural and urban residents' consumption are consistent, and both come mainly from the transportation and communication industry, housing, food, culture, education, entertainment, etc. The SDA results show that the per capita consumption level is the main driving factor for the increase of the indirect carbon footprint of Beijing residents' consumption, and the intensity of CO2 emission is the main inhibiting factor. Finally, suggestions for reducing carbon emissions from urban and rural perspectives have been put forward.

Endogenizing Capital in MRIO Models: The Implications for Consumption-Based Accounting.

Nearly 30% of global greenhouse gas emissions are associated with the production of capital goods. Consumption-based emission calculations based on multiregional input-output (MRIO) models allocate emissions occurring in the production of intermediate goods to the final goods produced in an economy. Like intermediate goods, capital goods are used in production processes; yet the emissions associated with their production are not allocated to the industries using them. As a result, the carbon footprint of final consumption as well as emissions embodied in trade are currently underestimated. Here, we address this problem by endogenizing capital transactions in the EXIOBASE global MRIO database, thereby allocating emissions from capital goods to final consumption. We find that endogenizing capital substantially increases the carbon footprint of final consumption (by up to 57% for some countries), and that the gap between production-based and consumption-based emissions increases for most countries. We also find that the global emissions embodied in trade increase by up to 11%, and that current patterns of bilaterally traded emissions are amplified. Furthermore, endogenizing capital leads to a 3-fold increase in the carbon footprint of certain product categories. The results suggest that our approach constitutes an important improvement to current input-output methodology.

Climatic burden of eating at home against away-from-home: A novel Bayesian Belief Network model for the mechanism of eating-out in urban China

Dietary patterns of eating away-from-home (AFH) considerably differ from those of eating at home in urban China, thus generating varied carbon footprints. However, few studies have investigated the effect of eating places on diet-related climatic burden, and few have modelled the mechanism under the condition of eating-out because the decision of consumers on whether to eat AFH or at home is determined by multiple non-linear socioeconomic factors. Here, we compared the carbon footprints of eating at home and AFH using household survey data from 12 Chinese provinces, and developed a Bayesian Belief Network (BBN) model to identify key factors of eating AFH. Our findings show that eating AFH leads to higher climatic burdens though respondents consume less food on average than when eating at home. However, in urban areas, the carbon footprint generated increases more rapidly from eating at-home than when eating AFH. The BBN model was found to have strong capability to predict the possibility of eating out with an accuracy of 89%. Although diet patterns and embedded carbon footprint vary considerably across provinces from northeastern to southwestern China, sufficient evidence could not be found to support the influence of geographic factors on the decision of respondents to eat AFH at large scale. Instead, individual occupation and income were found to be the two key contributors. Thus, merely estimating the carbon footprint of food consumption is currently not sufficient, but social and economic elements need to be quantitatively considered to differentiate the eating-place effect on diet-related climatic burden.

Carbon footprint assessment for the waste management sector: A comparative analysis of China and Japan

Waste management is becoming a crucial issue in modern society owing to rapid urbanization and the increasing generation of municipal solid waste (MSW). This paper evaluates the carbon footprint of the waste management sector to identify direct and indirect carbon emissions, waste recycling carbon emission using a hybrid life cycle assessment and input-output analysis. China and Japan was selected as case study areas to highlight the effects of different industries on waste management. The results show that the life cycle carbon footprints for waste treatment are 59.01 million tons in China and 7.01 million tons in Japan. The gap between these footprints is caused by the different waste management systems and treatment processes used in the two countries. For indirect carbon footprints, China’s material carbon footprint and depreciation carbon footprint are much higher than those of Japan, whereas the purchased electricity and heat carbon footprint in China is half that of Japan. China and Japan have similar direct energy consumption carbon footprints. However, CO2 emissions from MSW treatment processes in China (46.46 million tons) is significantly higher than that in Japan (2.72 million tons). The corresponding effects of waste recycling on CO2 emission reductions are considerable, up to 181.37 million tons for China and 96.76 million tons for Japan. Besides, measures were further proposed for optimizing waste management systems in the two countries. In addition, it is argued that the advanced experience that developed countries have in waste management issues can provide scientific support for waste treatment in developing countries such as China.

Spatial differences in the influence of science popularization resources development on the energy consumption carbon footprint in provincial regions of China

BackgroundScience popularization resources development is an important means to improve public scientific literacy and has a crucial influence on the formation of public consumption habits, patterns and concepts, and ultimately on the energy consumption carbon footprint.MethodsBased on panel data from the provincial regions in China from 2010 to 2014, this paper measures the energy consumption carbon footprint in provincial regions using Intergovernmental Panel on Climate Change (IPCC) methods and builds a geographically weighted regression (GWR) model to evaluate the levels of science popularization resources development in provincial regions by using the global entropy method. Then, the mechanisms of influence on the energy consumption carbon footprint and the levels of science popularization resources development in the provincial regions of China are analyzed and measured.ResultsThe results showed that science popularization resources development could significantly lower the energy consumption carbon footprint; from 2010 to 2014, the lowering effect of science popularization resources development on the energy consumption carbon footprint in the major east, middle, and west provincial regions showed a weakening trend, with a greater lowering amplitude in the east than in the middle and west regions and narrowing spatial differences among them; at present, this influence works best in the west region followed by the middle and east regions.ConclusionsThe results imply that we should give full attention to science popularization resources development to lower the energy consumption carbon footprint in China. In addition, focus should be given to the west region of China and construction mechanisms for science popularization resources that are built with flexible adoptions of means such as a combination of government guidance and market mechanisms, as well as joint construction by government and society.

Analysis of Carbon Footprint in Terms of Electricity Consumption Practices in Primary Schools: A Case Study of Batang Padang District, Perak, Malaysia

Energy resource consumption, and particularly consumption of electrical energy, influences the increase of greenhouse gas – that is, carbon dioxide in the atmosphere – which results in global warming. One of the strategies to overcome this issue is to implement energy saving sustainability practices. Thus, the purpose of this article is to identify the level of carbon foot print from electricity consumption as well as the relationship and effects of sustainability knowledge, green knowledge, and sustainability practices towards electricity consumption (carbon footprint analysis) in primary schools. This study involved 423 students from ten primary schools within the district of Batang Padang, Perak, Malaysia. A cluster sampling method was used during the first stage of selecting the schools and groups of students. Then, the respondents were chosen by a simple random method from among students between the ages of 10 to 12 years old who were able to read. Results show that the carbon footprint emissions in the studied school areas are still at a low level. The relationship analysis shows a weak significant correlation between (i) sustainability practices and sustainability knowledge, (ii) sustainability practices and carbon footprint, and (iii) green environment and carbon footprint analysis. Similarly, the study shows a moderate relationship between 3R practice variables and carbon footprint analysis in schools. Regression analysis shows that sustainability practices contribute to carbon footprint when compared with sustainability knowledge and green environment. Thus, this shows that sustainability knowledge has a direct relationship with sustainability practices and electricity consumption. The results clearly prove that primary school students show positive elements of sustainability practices. These findings can help schools to identify weak variables, such as green practices knowledge, that need to be improved in order to reduce carbon emissions in schools.

The Carbon Footprint of European Households and Income Distribution

This paper calculates the carbon footprint of private consumption in the EU27 by five groups of household income, using a fully fledged macroeconomic input-output model covering 59 industries and five groups of household income for the EU27. Due to macroeconomic feedback mechanisms, this methodology – besides induced intermediate demand – also quantifies: (i) private consumption induced in the other household groups, (ii) impacts on other endogenous final demand components, and (iii) negative feedback effects due to output price effects of household demand. The carbon footprint is calculated separately for the consumption vector of each of the five income groups. The simulation results yield a non-linear income elasticity of direct and indirect emissions at each income level: the value of the direct footprint income elasticity decreases from 1.32 (first quintile) to 0.69 (fourth quintile). The value of the indirect footprint income elasticity is always below unity and decreases from 0.89 to 0.62. The results in general reveal a relative decoupling effect: the share of the top income group in income (45%) is much larger than its share in the carbon footprint (37%) and vice versa for the bottom income group (6% in income and 8% in footprint).

ANALISIS CARBON FOOTPRINT GEDUNG PERPUSTAKAAN PUSAT, REKT

Global warming is the increase in the average temperature of the atmosphere, ocean and land earth. Global warming can occur due to the greenhouse effect. Problems arise when the concentration of greenhouse gases in the atmosphere increases. With increasing concentrations of greenhouse gases, the more heat retained surface of the earth and will cause the earths surface temperature to rise. Increased temperatures also happened in Yogyakarta. The air is cool before now turned into more heat. One cause of greenhouse gas emissions is carbon dioxide which is currently the biggest contributor came from the center of fossil-fueled power plants. In particular the research conducted is to calculate the carbon dioxide emissions (carbon footprint) resulting from a building to measure the adequacy of existing vegetation as reducing greenhouse gas emissions. The carbon footprint is calculated that the energy consumption of the electricity sector in the Central Library building, solids, and Lab. MIPA UII Yogyakarta. The method used in the calculation of the carbon footprint of electricity consumption of data collection, electronic instruments, and absorption of existing vegetation which then calculated the carbon footprint dioxide emissions generated by absorption of existing vegetation. The results of both calculations are then compared to determine the adequacy of the existing vegetation to absorb carbon dioxide emissions. From the results of the calculation are compared, it is known that the absorption of vegetation existing in the building of the central library is able to absorb emissions by 80% of the total carbon dioxide emissions generated at 4548 kg / year, the absorption of vegetation in rectorate building for 50% of carbon dioxide emissions by 1980 kg / year, and the absorption of vegetation in mathematics and natural sciences laboratory building at 3120 kg/year. The comparison showed that the existing vegetation in the objects of research proficiency level sufficient to absorb the carbon dioxide emissions resulting from the energy sector of the electricity consumed.

The Carbon Footprint of Norwegian Household Consumption 1999–2012

SummaryEnvironmentally extended input‐output analysis is the prevailing method for national environmental footprint accounting; however, its practical usefulness for consumers and policy makers suffers from lack of detail. Several extensive global multiregional input‐output (MRIO) databases have recently been released. A standard framework for linking such databases with the highly detailed household expenditure surveys that are conducted regularly by national statistics offices has the potential of providing analysts in countries worldwide with a powerful tool for in‐depth analyses of their national environmental footprints. In this article, we combine the Norwegian consumer expenditure survey with a global MRIO database to assess the carbon footprint (CF) of Norwegian household consumption in 2012, as well as its annual development since 1999. We offer a didactic account of the practical challenges associated with the combination of these types of data sets and the approach taken here to address these, and we discuss what barriers still remain before such analyses can be practically conducted and provide reliable results. We find a CF of 22.3 tonnes of carbon dioxide equivalents per household in 2012, a 26% increase since 1999. Transport, housing, and food were the expenditures contributing the most toward the total footprint. CF per unit of expenditure increased with overall expenditure levels (elasticity: 1.14), notably owing to the correlation between overall household expenditure and transport activities (elasticity: 1.48). Household energy use, which is generally inelastic, is, in Norway, largely based on hydropower and hence contributes comparatively little to the overall expenditure elasticity of household CF.

Tailored advice and services to enhance sustainable household consumption in Finland

Household consumption (for housing, mobility, food, goods and services) accounts for about 70% of Finland's carbon footprint (greenhouse gas emissions caused by the domestic final use of products). Therefore, climate change mitigation calls for changes in human behaviour and consumption patterns. Opinion polls indicate that Finns are concerned about climate issues; at the same time the carbon footprint of household consumption in Finland is high on a global scale. It is clear that environmentally sustainable behaviour and decisions at the household level require knowledge, motivation and services that support actions. To tackle unsustainable consumption patterns, action models promoting households' environmental sustainability were developed and piloted in Finland. The action research approach was applied to study the process of development and piloting of the action models, with key intermediaries and target groups involved in the process. These action models were designed specifically to help households decrease their energy consumption and carbon footprint. The action models provide tailored feedback and advice to address sustainable consumption from two perspectives: (1) everyday sustainable choices and practices and (2) long-term home-renovation decisions. In the action models, the focus is on the most significant consumption choices. Therefore they also supplement Finland's programme for sustainable consumption and production. The pilot work demonstrates the role of the interactive process and feedback from target groups and intermediaries in significantly improving the action models, the importance of personal contact for supporting household interpretation of numerical data and provision of tailored advice, the role of intermediaries in disseminating research-based knowledge and tools, and that sustainability-based perspectives in the renovation and housing-maintenance sector can provide new and supplementary business opportunities.