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The pulp and paper industry is a high energy consuming and polluting sector, and carbon emissions emitted from this sector are worthy of attention. This article, based upon an analysis of China’s Pulp and Paper Industry (CPPI), provides estimates of each of the following: carbon emissions from energy consumption, pre-treatment sector, combustion of condensed black liquor, and methane emitted from incomplete aerobic digestion during sewage treatment of CPPI. During the study period (2005–2012), total CO 2 emissions ranged from 126.0 Mt to 155.4 Mt. Energy consumption was estimated to be the largest source of carbon emissions, however, due to the application of the local emission inventory rather than the IPCC inventory, energy consumption decreased by 4.7%, a lower percentage than was calculated in a previous study. According to this study’s estimation, the emissions caused by the recovery of biomass energy contributed 26–29% of the total CO 2 emissions. CH 4 generated from sewage treatment accounted for 9–11% of the total carbon emissions. The CO 2 intensity dropped during the study period, which reflected the improvement of energy efficiency in the pulp and paper industry. The outcome of this study provides not only detailed information about CPPI’s carbon emissions, but also a calculation framework for studying carbon emissions from pulp and paper sector in the other regions. It suggests that the local carbon emissions inventory should be used for estimating carbon emissions and to reduce the fossil fuel energy, increase energy recovery from biomass, and that promoting cleaner production is essential to achieve a low carbon development of the pulp and paper industry. [ABSTRACT FROM AUTHOR]

Market based pricing of CO 2 was designed to control CO 2 emissions by means of the price level, since high CO 2 price levels discourage emissions. In this paper, it will be shown that the level of uncertainty on CO 2 market prices, i.e. the volatility of CO 2 prices itself, has a strong influence not only on generation portfolio risk management but also on CO 2 emissions abatement. A reduction of emissions can be obtained when rational power generation capacity investors decide that the capacity expansion cost risk induced jointly by CO 2 volatility and fossil fuels prices volatility can be efficiently hedged adding to otherwise fossil fuel portfolios some nuclear power as a carbon free asset. This intriguing effect will be discussed using a recently introduced economic analysis tool, called stochastic LCOE theory. The stochastic LCOE theory used here was designed to investigate diversification effects on energy portfolios. In previous papers this theory was used to study diversification effects on portfolios composed of carbon risky fossil technologies and a carbon risk-free nuclear technology in a risk-reward trade-off frame. In this paper the stochastic LCOE theory will be extended to include uncertainty about nuclear power plant construction times, i.e. considering nuclear risky as well, this being the main uncertainty source of financial risk in nuclear technology. Two measures of risk will be used, standard deviation and CVaR deviation, to derive efficient frontiers for generation portfolios. Frontier portfolios will be analyzed in their implications on emissions control. [ABSTRACT FROM AUTHOR]

Despite all improvements in buildings shell, equipment, and design, CO 2 emissions from buildings are increasing. Since occupants spend more than 87% of their time indoors, they are inseparable and significant elements of building system dynamics. Hence, there is a great potential for energy efficiency in buildings using a wide range of programs such as intervention and eco-feedback. Despite the high level of individual differences and intra-class variability of occupants’ behaviors, the current state-of-the-art eco-feedback programs treat all the occupants uniformly and do not target and tailor the feedback. Therefore, it leaves an opportunity to increase the efficacy of eco-feedback systems through the designing of tailored and targeted programs. In this paper, we conducted a comprehensive analysis and tested hypotheses on occupants’ behavioral responses to a normative comparison feedback program, in addition to the impact of notifications on the level of engagement of each group of occupants. We categorized occupants who participated in the normative comparison feedback program into three groups (i.e. low, medium, and high energy consumers) based on their baseline energy consumption, and tested 9 hypotheses. A mixed-effect regression model (MRM) and a paired t -test was implemented to evaluate the proposed hypotheses. The hypotheses examine the variability of occupants’ responses under the same eco-feedback program, and the effectiveness of notifications on reinforcing occupants’ engagement in these programs. The contribution of this paper is two-fold: (1) reporting that the effectiveness of the notifications in eco-feedback programs are initially highly dependent on the type and the nature of the program, and then the interval and the content of the notification, and (2) demonstrating the variability of occupants’ behavioral responses under the same normative comparison eco-feedback program. These findings indicate the need for a shift in focus toward targeted and tailored feedback programs which treat occupants based on their characteristics. Moreover, they highlight the need for eco-feedback design, development, testing and implementation research that acknowledges and addresses differences in occupant responses to feedback. [ABSTRACT FROM AUTHOR]

Trade-related CO 2 emissions are an important component in global emissions. Understanding the role of international trade in emissions is of direct relevance to global and national emission reductions, particularly for major exporters and importers. In the literature, the issue has seldom been studied using index decomposition analysis (IDA), which is a popular tool in assessing growth in national-level CO 2 emissions. In this paper, based on a multi-region I-O analysis, we introduce three inter-linked IDA models to quantify the impacts of trade on the production-based emissions, the consumption-based emissions, and the emission balance of economies, respectively. A salient feature of the models, when applied together, is that they can help to assess the role of trade and the emission performance of economies from multiple perspectives. We discuss the relevant methodological issues as well as the advantages and limitations of the models. We then apply the models to evaluate the impact of international trade on changes in global CO 2 emissions from 1995 to 2009. It is found that while the growing trade volume drove up the total emissions, changes in the emission intensity and goods composition related to trade led to some degree of emission mitigation, particularly after 2005. [ABSTRACT FROM AUTHOR]

To grasp the characteristics of CO 2 emissions across provinces in China and to determine changes in the centre of gravity of CO 2 emissions over the 2000–2014 period, a gravity model is first used to examine the spatial distribution and centre of gravity of energy-related CO 2 emissions. Then, to explore the main factors driving CO 2 emission changes and to uncover feasible ways to reduce CO 2 emissions, this paper decomposes changes in energy-related CO 2 emissions into a population effect ( Δ C P ), an economic output effect ( Δ C Q ), an industrial structure effect ( Δ C S ), an energy intensity effect ( Δ C I ), an energy structure effect ( Δ C M ) and a carbon dioxide emission coefficient effect ( Δ C U ) at both the national and provincial levels based on the Log-Mean Divisia Index (LMDI) method. The results indicate that (1) energy-related CO 2 emissions rose by approximately 5.46 billion tonnes during the 2000–2014 period, with secondary industry accounting for approximately 80% of total CO 2 emissions. (2) Economic output ( Q ) was the dominant positive driving factor, and energy intensity ( I ) was the dominant negative driving factor. The population changes had a weak positive effect on CO 2 emissions, but the industrial structure effect and energy structure effect varied considerably over the years without showing clear trends. (3) Over multiple spatial scales, the contribution ratios of the factors varied significantly across provinces; in general, the positive driving effects outweighed the negative inhibiting effects. Based on these empirical findings, policy recommendations to further reduce CO 2 emissions are provided. The Chinese central and local governments should make full use of the important inhibiting factors, i.e., energy intensity and energy structure, and strive for breakthroughs in secondary sector. [ABSTRACT FROM AUTHOR]

Residential energy consumption is one of the main contributors to CO 2 emissions in the UK. One strategy aimed at reducing emissions is to increase retrofitting rates of buildings. In this paper, an alternative approach is discussed and its potential impact on energy use assessed, that of downsizing (moving to smaller homes). Reviews of previous research show that a wide range of what can be termed psychological barriers exist to downsizing, such as the loss of ownership and independence, concern about what to do with possessions, not having enough space for visitors, and attachment to one’s home. Benefits of downsizing from a personal perspective are economic, with lower bills and/or rent, release of capital, lower maintenance costs, and also potential lifestyle improvements including living in easier-to-maintain and more age-appropriate housing. Wider societal benefits include the potential to significantly reduce energy consumption, and mitigating the housing crisis in cities where not enough properties are available. Empirical analysis on a nationally representative sample in England showed that building size alone accounts for 24% of the variability in energy consumption (compared to 11% of household size). If single-person households with more than two bedrooms downsized by one bedroom, energy-savings of 8% could be achieved, and if single-person households occupied only one bedroom, savings of 27%. Data also showed a significant amount of underoccupation, with almost two-thirds of households having more bedrooms than considered necessary compared to the bedroom-standard. However, analysis also revealed a structural barrier to downsizing, namely the lack of available alternative, smaller houses. The evidence would suggest that downsizing could realize significant energy savings, and address a range of other social benefits. However, against this stand significant personal interests, inadequate alternative housing and other infrastructure issues. Promoting downsizing as a means to achieve energy policy goals is therefore a potentially significant but socially challenging policy option. [ABSTRACT FROM AUTHOR]

China has been the world’s largest cement producer and the cement production has led to increased energy consumption and CO 2 emissions, which greatly affect the country’s social and economic development. In this paper, an integrated assessment framework was developed by combining the Stock-based model and the Integrated MARKAL–EFOM System model of China (China TIMES), and it was used in China’s cement sector to simulate the trends of energy consumption and CO 2 emissions during 2010–2050, under a reference scenario and three carbon tax scenarios. The modeling results show that: (1) the cement production in China will increase from 1.8 billion tons in 2010, to a peak of 2.5 billion tons in around 2017, and then gradually decrease to 1.5 billion tons in 2050; (2) Through the adoption of three alternative abatement measures (i.e., switching the fuel types, implementing the energy-efficient measures and CCS), China’s cement sector could potentially achieve a great reduction in CO 2 emissions; (3) In the near future, the cement sector’s decarbonisation will mainly rely on energy efficiency improvement; while the use of alternative fuel use and CCS will be of great significance from a long-term perspective. Additionally, based on the modeling results, we build the energy-saving and emission-reduction technologies roadmap for China’s cement sector. [ABSTRACT FROM AUTHOR]

Many cities are pursuing the low-carbon practices to reduce CO 2 and other environmental emissions. However, it is still unclear which aspects a low-carbon city (LCC) covers and how to quantify and certify its low carbon level. In this paper, an indicator framework for the evaluation of LCC was established from the perspectives of Economic, Energy pattern, Social and Living, Carbon and Environment, Urban mobility, Solid waste, and Water. A comprehensive evaluation method was employed for LCC ranking by using the entropy weighting factor method. The benchmark values for LCC certification were also identified. The framework was applied to 10 global cities to rank their low-carbon levels. The comparison of cities at different levels of economic, social, and environmental development enhances the holistic of the study. The results showed that Stockholm, Vancouver, and Sydney ranked higher than the benchmark value, indicating these cities achieved a high level of low-carbon development. São Paulo, London, and Mexico City are still in the slow transition towards LCC. Beijing and New York each has much lower LCC level than the benchmark value due to the poor environmental performance and infrastructure supports caused by intensive human activities. The proposed indicator system serves as a guideline for the standardization of LCC and further identifies the key aspects of low-carbon management for different cities. [ABSTRACT FROM AUTHOR]

This paper analyzes global CO 2 emissions growth by fossil fuel type (coal, oil or gas), demand type (consumption or investment), country group (developed or developing country) and industry group. The results indicate that, among the three fossil fuels, CO 2 emissions from coal use grew the most rapidly in developing countries, by 3.76 Gt in the period 1995–2009. By contrast, CO 2 emissions from natural gas use grew the most rapidly in developed countries, by 470 Mt in the period 1995–2009. Further decompositions show that, despite improvements in energy efficiency, the upgrades in infrastructures and changes in electricity requirements in developing countries have led to significant CO 2 emissions growth from coal use. Among these countries, China accounts for a high contribution, causing a coal-use-related CO 2 emissions growth of up to 2.79 Gt in the period 1995–2009. By contrast, consumption by the public and social services as well as chemical products is the dominant force driving CO 2 emission growth from gas in developed countries; the US accounts for a very high contribution, causing a gas-use-related CO 2 emissions growth of up to 100 Mt. [ABSTRACT FROM AUTHOR]

China’s commitment to the UNFCCC to peak its emissions by 2030, or sooner, signaled a long anticipated shift in China’s model of development with far reaching consequences. Cities in China, and particularly the residential sector in cities, will be charged with making significant reductions in emissions growth even as rates of urbanization continue to climb. Focusing on Beijing and Shanghai, this paper carries out a measures-based economic analysis of low carbon investment opportunities in the residential sector. Results find significant opportunity: between 2015 and 2030, BAU levels of CO 2 emissions could be reduced by 10.2% in Beijing and 6.8% in Shanghai with the adoption of economically attractive low carbon measures. While these headline results underline the case for low carbon investment in the residential sectors of these megacities in China, a closer analysis provides insights for understanding the economics of decarbonisation in cities more generally. [ABSTRACT FROM AUTHOR]

The so-called post-China countries (PC-16́s), distinguished by low wages and high economic growth, will replace China as the “world’s factory”. The aim of this paper is to assess the effect of these changes on global CO 2 emissions pathways. To achieve this, a counterfactual is proposed wherein China’s trade with the rest of the world is replaced by the PC-16’s trade in a global multiregional input–output context. The emissions savings realized by trade replacement are significant in those scenarios where the current pattern of trade is maintained (−13% on emissions traded and −3.5% on global emissions) and in scenarios where enterprises relocate their production directly or indirectly to the most environmentally efficient countries (ranging from −15.2% to −18.2% on emissions embodied in trade). Nevertheless, the potential savings drop considerably (ranging from −1.5% to −7.1%) if companies and host countries take advantage of cheaper, but more polluting means of production and do not internalize the externalities. Through changes in international trade, there is a possibility of reducing emissions, which have to be included in international, multilateral and bilateral agreements to mitigate climate change if we do not want to lose the opportunities these changes present. [ABSTRACT FROM AUTHOR]

Abstract: The better to explore the regional characteristics of inter-provincial CO2 emissions and the rational distribution of the reduction of emission intensity reduction in China, this paper proposes an improved PSO-FCM clustering algorithm. This method can obtain the optimal cluster number and membership grade values by utilizing the global capacity of Particle Swarm Optimization (PSO) on Fuzzy C-means (FCM). The clustering results of CO2 emissions indicate that the 30 provinces of China are divided into five clusters and each has its own significant characteristics. Compared with other clustering methods, the results of PSO-FCM are more explanatory. The most important indicators affecting regional emission characteristics are CO2 emission intensity and per capita emissions, whereas CO2 emission per unit of energy is not obvious in clustering. Furthermore, some policy recommendations on setting emission reduction targets according to the emission characteristics of different clusters are made. [Copyright &y& Elsevier]

Abstract: This paper investigates whether the environmental Kuznets curve (EKC) hypothesis for CO2 emissions is satisfied using the panel data of 28 countries by taking nuclear energy into account. Using the pooled mean group (PMG) estimation method, our main results indicate that (1) the impacts of nuclear energy on CO2 emissions are significantly negative, (2) CO2 emissions actually increase monotonically within the sample period in all cases: the full sample, OECD countries, and non-OECD countries, and (3) the growth rate in CO2 emissions with income is decreasing in OECD countries and increasing in non-OECD countries. [Copyright &y& Elsevier]