Household Carbon Dioxide Research Articles

Household carbon dioxide emissions Engel Curve dynamics

AbstractHousehold carbon dioxide emissions depend on the household's attributes and location. Wealthier suburbanites drive more and consume more energy at home. In recent years, affluent individuals have been more likely to purchase electric vehicles and install solar panels. Using several datasets from California, we observe that these shifts in consumer behavior have flattened household Carbon Emissions Engel Curves in the transportation sector and the electricity sector. Based on voting data from a 2018 proposition to repeal a fuel tax in California, we document that communities tend to support higher fuel taxes when their vehicle fleet is more fuel‐efficient.

Development of an extended STIRPAT model to assess the driving factors of household carbon dioxide emissions in China

Although the past twenty years have witnessed China's remarkable economic development, the cost in terms of greenhouse gas emissions and a deteriorating environment has been enormous. Numerous studies have revealed the influence of household factors on household carbon dioxide emissions (HCEs) and called for a reduction of HCEs to mitigate climate change, but few have focused on assessing the most significant household driving factors of HCEs. Using statistical data between 2005 and 2019 in Jiangsu, China, this study developed an extended stochastic impact by regression on population, affluence, and technology (STIRPAT) model to assess the most significant driving factors of HCEs. The results show that the most significant driving factors are household size, total population, unemployment, and urbanisation rate. The study found that HCEs are positively impacted by household size while negatively impacted by the unemployment rate. Based on the study's findings, the following suggestions are proposed to lower HCEs: (i) establish an optimal consumption concept to guide residents towards consuming reasonably; (ii) cultivate a low-carbon concept among residents and promote low-carbon emissions living; and (iii) pay close attention to population structure factors and formulate effective measures accordingly. The study provides insightful information on the key driving factors of HCEs, which can facilitate achieving carbon emissions neutrality.

Effect of Broadband Infrastructure on Rural Household CO2 Emissions in China: A Quasi-Natural Experiment of a “Broadband Village”

This paper explores how broadband infrastructure affects rural household carbon dioxide emissions (HCE). Based on the Environmental Kuznets curve hypothesis, a quasi-natural experiment of a “Broadband Village” (B&V) in China is conducted. Panel data from 9,790 rural households were collected as part of the China Family Finance Survey (CHFS). The consumer lifestyle approach was used to calculate HCE and a Difference-in-Differences (DID) model was used to analyze the impact of a B and V pilot project on rural HCE. The results of DID model showed that B and V significantly increases rural HCE, with an influencing coefficient 1.7. Subsequently, Threshold Model was utilized to examine the nonlinear relationship between household broadband penetration and rural HCE. The results revealed the threshold effect between rural household broadband penetration and rural HCE. Namely, the growth effect of B and V to rural HCE would be much weaker, if rural household broadband penetration goes above a threshold level, 31.32%. Our analysis provides important insights for policymakers to formulate digital village and income redistribution policies to support rural carbon dioxide (CO2) emissions reductions.

Multi-Perspective Analysis of Household Carbon Dioxide Emissions from Direct Energy Consumption by the Methods of Logarithmic Mean Divisia Index and σ Convergence in Central China

Currently, household carbon dioxide (CO2) emissions (HCEs) as one of the leading sources of greenhouse gas (GHG) have drawn notable scholarly concern. Thus, here, taking six provinces in the period of 2000–2017 of Central China as a case, we analyzed the characteristics and the driving factors of HCEs from direct energy consumption and three perspectives: Central China as a whole, urban-rural differences, and inter-provincial comparison. The drivers of direct HCEs were analyzed by the Logarithmic Mean Divisia Index (LMDI). The σ convergence was adopted for analyzing the trend of inter-provincial differences on the HCEs. The key findings are as follows. First, all the direct HCEs from three perspectives had an obvious growth trend. The total direct HCEs grew from 9596.20 × 104 tonnes in 2000 to 30,318.35 × 104 tonnes in 2017, with an increase of 2.16 times. Electricity and coal use were the primary sources. The urban and rural increases of direct HCEs were up 2.57 times and 1.77 times, respectively. The urban-rural gap of direct HCEs narrowed first and then widened. The direct HCEs in the six provinces varied significantly, but the gap was narrowing. Second, as a whole the per capita consumption expenditure and energy demand were the main drivers to the increment of HCEs, with cumulative contribution rates of 118.19% and 59.90%. The energy price effect was mainly responsible for the mitigation of HCEs. Third, the similar drivers’ trend can also be seen from the perspective of inter-provincial comparison. However, from the perspective of urban and rural difference, the population urban-rural structure effect played a reverse influence on both urban and rural areas. Thus, raising the energy prices appropriately, upgrading the residents’ consumption to a sustainable pattern, controlling the growth of population size reasonably, and optimizing the household energy structure might effectively mitigate the growth of HCEs in Central China.

Quantifying the impacts of energy inequality on carbon emissions in China: A household-level analysis

This study empirically investigates the impact of energy inequality on household carbon dioxide (CO2) emissions in China by employing a balanced panel dataset for China's 30 provinces for the period 2000–2017. Fully considering the potential cross-sectional dependence, this study employs a series of empirical approaches allowing for cross-sectional dependence. Moreover, given the significant differences in energy inequality and household CO2 emissions, we further conduct an asymmetric analysis on the nexus between energy inequality and household CO2 emissions. The empirical results indicate energy inequality can positively affect the volume of household CO2 emissions; however, this finding makes no economic sense since it goes against the actual conditions in China (energy inequality and household CO2 emissions have shown reverse change trends in recent years). Simultaneously, we find that narrowing energy inequality can reduce the growth rate of CO2 emissions, a fact we confirm with a series of robustness tests. Notably, the impact of energy inequality on household CO2 growth is asymmetric across various quantiles (i.e., different regions). Accordingly, we highlight several relevant policy implications for the Chinese government to reduce household CO2 emissions and narrow energy inequality.

Development of household carbon dioxide generator from dry ice （J)

Development of household carbon dioxide generator from dry ice （J)

Development of household carbon dioxide generator from dry ice （E)

Development of household carbon dioxide generator from dry ice （E)

A spatial typology of human settlements and their CO2 emissions in England

Case studies demonstrate that urban greenhouse gas emissions are driven by socio-economic, climatic and urban-form specific characteristics. But neither the interdependence between attributes nor their place-specific context has been well understood. In this paper, we develop a nested typology of human settlements in England, containing both urban and rural environments, that is based on local drivers of emissions from direct energy use in nearly 7000 local areas. We reject the standard hypothesis that settlements obey a global linear model explaining emissions. The emissions of human settlement types are characterized by unique, place-specific combinations of emission drivers. We find that density and income are dominant classifiers of local carbon dioxide emissions. However, their specific impacts are particular to human settlement types as characterized by the place-specific combination of income, household size, and local climate, which are themselves spatially contextualized. Our typology strongly correlates with the geographic distribution of lifestyles. Average household carbon dioxide emissions are highest for very high income households (top 3%) living in low-density settlement areas with large houses, mostly concentrated in outer suburbs. Our results provide a first step towards enabling decision makers to go beyond one-size-fits-all approaches but instead to apply appropriate and specific mitigating measures for each type of human settlement. In turn, successful strategies could be transferred between similar types of human settlements.

Does urbanization lead to more direct and indirect household carbon dioxide emissions? Evidence from China during 1996–2012

China is experiencing a stage of rapid urban development. The energy consumption and related carbon dioxide emissions of households continue to increase. This paper calculates direct and indirect carbon dioxide emissions of households based on the input–output method in China from 1996 to 2012. The results reveal that there were more total carbon dioxide emissions from urban households than from rural households, far more indirect emissions from urban households than from rural households, slightly more direct emissions from urban households than from rural households, and differences in direct carbon dioxide emissions from various fuels and in indirect emissions from various sectors between urban and rural households. To examine the causal relationship between urbanization and the carbon dioxide emissions of households, cointegration and Granger causality tests are applied. A unidirectional causal relation was found running from urbanization to both direct and indirect household carbon dioxide emissions, and the direct and indirect carbon dioxide emissions of households would increase 2.9% and 1.1%, respectively, for every increase of one percent in urbanization. We discuss the reasons of why the development of urbanization will lead to more household direct and indirect carbon dioxide emissions, and suggest certain policy implications for urbanization and carbon dioxide emissions based on the results of this study.

Design of Household Carbon Dioxide Heat Pump Controller Man-Machine Interface Based on C8051F500

Carbon dioxide heat pump controller using carbon dioxide phase transition theory, in conjunction with the heat pump main controller and man-machine interface, can realize the user free on the regulation of water temperature. The carbon dioxide heat pump controller design of a human-computer interface. The control core with C8051F500 MCU as the main body of the system, has a unique memory function, including function: display module, key module, clock module, communication module, power module, and the heat pump main control board through the CAN bus. Through the experiment, the system is stable and reliable, has the features of functional diversity, humanization design, can promote household CO2 heat pump.

The Effects of Climate and Socio‐Demographics on Direct Household Carbon Dioxide Emissions in Australia

AbstractHousehold CO2 emissions are a significant contributor to global greenhouse gas emissions and consequently climate warming. Despite this, there has been little consideration of how household CO2 emissions may be affected by changes in climate. The aim of the present study has been to investigate the way climate, as well as socio‐demographic characteristics, may affect household CO2 emissions produced from energy use. A national online survey was conducted to determine current household CO2 emissions in Australia as well as capture the ownership and use of household appliances and installations. Electricity and gas‐based emissions as well as the ownership of a variety of household appliances and installations were found to be strongly associated with temperature. Electricity and gas emissions were found to decrease as annual average temperatures increase. However, as temperatures continue to rise under climate change this pattern may be reversed owing to increased reliance on air conditioners. One option for preventing this from occurring is to encourage houses to adopt more solar‐passive installations. Although this may be expensive, households with higher emissions tend to have higher incomes, indicating that they may have the capacity to pay for such installations.

Household carbon dioxide emissions from peasants and herdsmen in northwestern arid-alpine regions, China

This study assessed household CO2 emissions (related to the consumption of necessary and luxury goods and services) of peasants and herdsmen households in arid-alpine regions in Gansu, Qinghai and Ningxia provinces, China. We also explored whether agriculture types, family income and family size have played any role in household CO2 emissions. In order to address these issues, we: (i) developed assessment indicators for household emissions; (ii) conducted semi-structured questionnaire household surveys; and (iii) employed input-output analysis (IOA). The results showed that, the average household CO2 emission per capita is 1.43 tons (t) CO2; the proportion of subsistence emissions (related to the consumption of necessary goods and services) accounts for 93.24%, whereas luxury emissions (generated due to consumption of specific goods and services that are consumed only when household income improves) only account for 6.76%t. Moreover, household CO2 emissions increase with family income and family size, but per capita emissions are inversely related to family size. The highest average household emissions were found in the alpine agricultural and pastoral region (6.18t CO2), followed by the irrigated agricultural region (6.07t CO2) and the rain-fed agricultural region (5.34t CO2). In consideration of insignificant amount of household emissions from these poor and vulnerable groups of the society, this study suggests to follow the principle of fairness while making energy conservation, emission reduction and adaptation policies.

Design and implementation of an open framework for ubiquitous carbon footprint calculator applications

As climate change is becoming an important global issue, more and more people are beginning to pay attention to reducing greenhouse gas emissions. To measure personal or household carbon dioxide emission, there are already plenty of carbon footprint calculators available on the web. Most of these calculators use quantitative models to estimate carbon emission caused by a user's activities. Although these calculators can promote public awareness regarding carbon emission due to an individual's behavior, there are concerns about the consistency and transparency of these existing CO 2 calculators. Apart from a small group of smart phone based carbon footprint calculator applications, most of the existing CO 2 calculators require users to input data manually. This not only provides a poor user experience but also makes the calculation less accurate. The use of a standard framework for various carbon footprint application developments can increase the accuracy of overall calculations, which in turn may increase energy awareness at the individual human level. We aim for developing a carbon footprint calculation framework that can serve as a platform for various carbon footprint calculator applications. Therefore, in this paper, we propose a platform-agnostic Open Carbon Footprint Framework ( OCFF) that will provide the necessary interfaces for software developers to incorporate the latest scientific knowledge regarding climate change into their applications. OCFF will maintain a clouded knowledge base that will give developers access to a dynamic source of computational information that can be brought to bear on real-time sensor data. Based on the OCFF platform, we developed a Ubiquitous Carbon Footprint Calculator application ( UCFC) that allows the user to be aware of their personal carbon footprint based on their ubiquitous activity and act accordingly. The major contribution of this paper is the presentation of the quantitative model of the platform along with the entire design and implementation of UCFC application. We also present the results, analysis, and findings of an extensive survey that has been conducted to find users’ awareness of increased carbon footprint, feature requirements, and expectations and desires to alleviate CO 2 emissions by using a footprint calculator. The design of UCFC application incorporates the analysis and inferences of the survey results. We are also developing a fuel efficient mobile GPS application for iPhone suggesting the greenest/most fuel efficient route to the user. In this paper, we also point out some important features of such an application.

The greenness of China: household carbon dioxide emissions and urban development

China urbanization is associated with both increases in per capita income and greenhouse gas emissions. This article uses micro data to rank 74 major Chinese cities with respect to their household carbon footprint. We find that the ‘greenest’ cities based on this criterion are Huaian and Suqian while the ‘dirtiest’ cities are Daqing and Mudanjiang. Even in the dirtiest city (Daqing), a standardized household produces only one-fifth of the emissions produced in America’s greenest city (San Diego). We find that the average January temperature is strongly negatively correlated with a city’s household carbon footprint, which suggests that current regional economic development policies that bolster the growth of China’s northeastern cities are likely to increase residential carbon emissions. We use our city-specific income elasticity estimates to predict the growth of carbon emissions in China’s cities.

Carbon Dioxide Emission Savings Potential of Household Water Use Reduction in the UK

The relationship between household water use and energy consumption was examined to establish whether the conservation of water within a domestic environment offers significant potential for saving energy, thereby reducing household carbon dioxide emissions. Average UK water usage is 55,121 L ca-1yr-1. The supply of this volume of water and its subsequent treatment by the water companies is equivalent to just 38.6 kg CO2 ca-1 yr-1, although this is not currently included in the primary footprint. So water consumption per se does not significantly effect CO2 emissions. However, the heating water within the household using electricity requires 5,036 kWh ca-1yr-1, equivalent to a further 2,830 t CO2 ca-1yr-1 with 57% of energy associated with use of heated tap water. Using gas instead of electricity to heat water can reduce emissions by 63%, equivalent to an average reduction of 4.36 t CO2 yr-1 for a standard household (2.4 occupants). Water efficient appliances and the careful use of heated water in the home could reduce average household water use from 151 to 73 L ca-1d-1 as well as the volume of water required to be heated thereby reducing related emissions by 58% or 1,662 kg CO2 ca-1yr-1, where electricity is used. Maximum CO2 emission reduction is achieved by the use of solar collectors using gas as standby heating fuel. This, coupled with simple water conservation measures, emits as little as 130 kg CO2 ca-1yr-1 a potential saving of 2.7 t CO2 ca-1yr-1.

Comparative performance of six carbon footprint models for use in Ireland

Carbon footprint models are increasingly being used to manage personal and household carbon dioxide emissions. Six models were compared for their suitability for use in Ireland using typical data for a household of three people. The annual household energy and transportation emissions ranged from 10,540 to 17,361 kg CO 2 yr − 1 (mean 12,886; sd 2135) rising to a total footprint of 12,053 to 27, 218 kg CO 2 yr − 1 (mean 18,117; sd 5106) when aviation emissions were included. This represents a potential range for individual CO 2 emissions of between 4018 and 9073 kg CO 2/person/annum, a variation of over 5 tonnes/person. The information provided by these models proved to be inconsistent and often contradictory. The high variability between models was due to a number of anomalies. When these were corrected mean household energy and transportation emissions fell to 12,130 kg CO 2 yr − 1 (sd 805), with a total household footprint of 16,552 kg CO 2 yr − 1 (sd 1101). Models vary in their complexity in terms of what is included in the overall estimation of emissions making a full analysis of the primary carbon footprint very difficult. When compared to current Irish conversion factors the corrected models either underestimated or overestimated CO 2 emissions by approximately 10%. Current carbon footprint models excluded emissions from CH 4 and N 2O underestimating CO 2 emissions for the household by 1.8%.

Household Carbon Dioxide Production in Relation to the Greenhouse Effect

A survey of 655 households from eastern suburbs of Melbourne was undertaken to determine householders' attitudes to, and understanding of, the greenhouse effect. Carbon dioxide emissions resulting from car, electricity and gas use were computed and household actions which could reduce CO 2 emissions were addressed. Preliminary analysis of the results indicates that householders in this area are aware of, and concerned about, the greenhouse effect, although their understanding of its causes is often poor. Many appreciate the contribution of cars, but are unclear about the relative importance of other household activities. Carbon dioxide emissions from the three sources examined averaged 21·2 tonnes/year per household and 7·4 tonnes/year per person. Electricity was the largest contributor (8·6 tonnes/year), cars the next largest (7·7 tonnes/year) and gas third (5·0 tonnes/year) per household. Emissions varied considerably from household to household. There was a strong positive correlation between availability of economic resources and household CO 2 output from all sources. Carbon dioxide production, particularly from car use, was greater from households which were more distant from a railway station, and from larger households, and numbers of children in the household had little effect on emissions. There were also some economics of scale for households containing more adults. Understanding the causes of the greenhouse bore little relation to change in CO 2 emissions; being concerned about it was associated with a small reduction; but actual actions to reduce car use and household heating, however motivated, produced significant reductions.