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Summary Cities, contributing more than 75% of global carbon emissions, are at the heart of climate change mitigation. Given cities' heterogeneity, they need specific low-carbon roadmaps instead of one-size-fits-all approaches. Here, we present the most detailed and up-to-date accounts of CO2 emissions for 294 cities in China and examine the extent to which their economic growth was decoupled from emissions. Results show that from 2005 to 2015, only 11% of cities exhibited strong decoupling, whereas 65.6% showed weak decoupling, and 23.4% showed no decoupling. We attribute the economic-emission decoupling in cities to several socioeconomic factors (i.e., structure and size of the economy, emission intensity, and population size) and find that the decline in emission intensity via improvement in production and carbon efficiency (e.g., decarbonizing the energy mix via building a renewable energy system) is the most important one. The experience and status quo of carbon emissions and emission-GDP (gross domestic product) decoupling in Chinese cities may have implications for other developing economies to design low-carbon development pathways.

Climate change mitigation is one of the biggest problems of the 21st century with anthropogenic carbon dioxide emissions having exceeded the carrying capacity for the planet. The primary contributor to the emissions is increasing nonrenewable energy consumption coupled with economic growth. A major area of social sciences is the study of decoupling energy-related emissions and energy usage from continuous economic growth. The goal of this review paper is to analyze various studies that have focused on decoupling energy and economy, regionally, nationally, and globally. The reviewed 93 investigations show that three kinds of methodologies are employed for decoupling analysis—structural decomposition, index decomposition, and statistical methods. The main factors that inhibit decoupling were found to be economic growth, fossil fuel consumption, and urbanization of population, while the factors that promoted decoupling were found to be energy intensity reduction and emission intensity reduction. A comparative analysis of the two promoting factors for decoupling revealed that emission intensity reduction is easier to implement than energy intensity reduction, because emission intensity does not depend on the fluctuations of economic growth. It is proposed that emission intensity reduction research needs to be accelerated for accurate policy decisions.

Urban household consumption contributes substantially to global greenhouse gases (GHGs) emissions. Urban household emissions encompass both direct and indirect emissions, with the former associated with the direct use of fossil fuels and the latter with the emissions embodied in the consumed goods and services. However, there is a lack of consistent and comprehensive datasets outlining in great detail emissions from urban household consumption. To bridge this data gap, we construct an emission inventory of urban household emissions for 52 major cities in Japan that covers around 500 emission categories. The dataset spans from January 2011 to December 2015 and contains 12,384 data records for direct emissions and 1,543,128 records for indirect emissions. Direct emission intensity is provided in g-CO2/JPY to facilitate both future studies of household emission in Japan, as well as act as a reference for the development of detailed household emission inventories in other countries., Measurement(s)carbon dioxide emissionTechnology Type(s)Consumption of GoodsFactor Type(s)urban carbon footprintSample Characteristic - EnvironmentcitySample Characteristic - LocationJapan Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.15188058

This paper examines the extent to which countries have succeeded in decoupling transport emissions from economic growth, and how changes in emissions intensity, economic growth, and population growth have contributed to changes in transportation-related emissions. The paper employs a modified version of the Tapio decoupling model, and demonstrates that over the 1990–2018 study period only 12 of 145 countries achieved “absolute decoupling,” defined as reducing emissions while growing gross domestic product. The majority of the top emitters remain in a “relative decoupling” state, with emissions growing more slowly than gross domestic product. Many of the middle- and low-income countries have not achieved decoupling; their emissions are growing as fast as or faster than gross domestic product. To understand the driving factors of transport-related carbon emissions, the paper conducts index-decomposition and an econometric analysis. The results reveal that while transportation emission intensity has declined in most countries, economic growth and population growth have offset these declines. If these patterns continue, achieving the goals of the Paris Agreement with improvements in efficiency alone seems unrealistic. The paper also shows evidence that higher energy prices are associated with strong emissions reduction.

Cities are the major contributors to energy consumption and CO2 emissions, as well as being leading innovators and implementers of policy measures in climate change mitigation. Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is an agglomeration of cities put forward by China to strengthen international cooperation among “Belt and Road” countries and promote low-carbon, inclusive, coordinated and sustainable development. Few studies have discussed the emission characteristics of GBA cities. This study, for the first time, compiles emission inventories of 11 GBA cities and their surroundings based on IPCC territorial emission accounting approach, which are consistent and comparable with the national and provincial inventories. Results show that (a) total emissions increased from 426 Mt in 2000 to 610 Mt in 2016, while emissions of GBA cities increased rapidly by 6.9% over 2000–2011 and peaked in 2014 (334 Mt); (b) raw coal and diesel oil are the top two emitters by energy type, while energy production sector and tertiary industry are the top two largest sectors; (c) GBA cities take the lead in low-carbon development, emitted 4% of total national emissions and contributed 13% of national GDP with less than a third of national emission intensities and less than three-quarters of national per capita emissions; (d) Macao, Shenzhen and Hong Kong have the top three lowest emission intensity in the country; (e) most of GBA cities are experiencing the shift from an industrial economy to a service economy, while Hong Kong, Shenzhen, Foshan and Huizhou reached their peak emissions and Guangzhou, Dongguan and Jiangmen remained decreasing emission tendencies; (g) for those coal-dominate or energy-production cities (i.e. Zhuhai, Zhongshan, Zhaoqing, Maoming, Yangjiang, Shanwei, Shaoguan and Zhanjiang) in mid-term industrialization, total emissions experienced soaring increases. The emission inventories provide robust, self-consistent, transparent and comparable data support for identifying spatial–temporal emission characteristics, developing low-carbon policies, monitoring mitigation progress in GBA cities as well as further emissions-related studies at a city-level. The low-carbon roadmaps designed for GBA cities and their surroundings also provide a benchmark for other developing countries/cities to adapting changing climate and achieve sustainable development.

Urban transportation is viewed as the second leading source of carbon dioxide (CO2) emissions. The growing number of vehicles and road infrastructure-based supply in Indian cities is viewed as the essential driver of climate change and relevant consequences affecting the sustainability of cities. Under the 2015 Paris agreement, India had declared its Intended Nationally Determined Contribution (INDC) to curtail the greenhouse gas (GHG) emission intensity of its Gross Domestic Product (GDP) by 33-35 % by 2030 from the 2005 level. In this context, sustainable transport measures were analyzed in this study to understand the emission mitigation potential of the transport sector of the Bengaluru Metropolitan Region (BMR) situated in Karnataka, India. Suitable policies were identified under the planning, regulatory, economic and technological instruments that are grouped under four policy bundles. The mitigation potential of the policy bundles is quantitatively evaluated in terms of Vehicle Kilometers Travelled (VKT), exhaust emissions and greenhouse gas emissions. The study also estimated the carbon emission intensity and consumer surplus for different mode users associated with the policy bundles. The findings from sustainable transport scenarios for the design years 2030 and 2050 are compared with business as usual (BAU) scenarios of the respective design years. The policy bundle 4 - a mixture of policies from all the instruments including technological improvements such as electrification of all buses and cars in the city - demonstrated a critical decrease in VKT and emissions when compared with the other policy bundles and thus, provides good scientific decision support for transport policymakers.

China produces a huge amount of CO2 emissions that need to be reduced to comply with international commitments. Identifying the driving factors is critical for achieving mitigation targets and transiting toward a low-carbon economy in China. This study is one of the first few attempts to apply panel data and spatial econometrics models to analyze the spatial dependence of province-level CO2 emission intensity and the economic drivers of such emissions. First, we conducted a systematical review of the development of spatial econometrics. Second, we generated a panel data set about energy and socioeconomic development of 30 provinces and municipalities in China from 2005 to 2012. Next, we chose the most appropriate model to explain the predominant factors of energy-related CO2 emissions based on a series of tests of the spatial econometrics models. The results suggested that technology improvement, adjustment of industrial and energy structures, and environmentally friendly behaviors and patterns of consumption of habitants play an important role in CO2 emissions mitigation. The results also revealed that CO2 emissions had strong spatial spillover effects, which indicate that policies adopted in one province will affect policy-making in neighboring provinces, implying that provinces need take combined action to balance climate change mitigation and economic policy goals.

The simple action of filling a glass of water at home generates a greenhouse gas emission elsewhere, because it is necessary to spend electricity to treat the water, make it potable and then pump it to the point of consumption. These daily activities, seemingly clean, need electric energy and they carry out a human-induced greenhouse gas emission. Generation of electricity has a significant effect on the inventory of emissions and environmental impacts due to the large differences in the power generation sources used. This paper aims to shed light on the methodological challenge and develop a necessary simplified methodology to illustrate the importance of the power generation mix in urban greenhouse emissions. The electrical mix is a figure that expresses the carbon emissions associated to the electrical power generation, so it is an indicator of the suitability of the sources used for electrical power production. The smaller the mix, the higher is the contribution of low carbon emission sources. The methodology is explained, applying it to Madrid, assessing the greenhouse gas emission per kWh of electricity generated. The proposed estimation covers emissions of CO2 equivalent (KgCO2eq), including the equivalence between each greenhouse gas and carbon dioxide considering a prevalence of 100 years.

Reducing the use of nitrogen fertilizers and returning straw to field are being promoted in northeast China (NEC). In this paper, the agricultural production system model (APSIM) was applied to assess the long-term variations of crop yield and soil GHG emissions in a maize mono-cropping system of NEC, and the simulation results were combined with lifecycle assessment to estimate annual GHG emissions (GHGL) and GHG emission intensity (GHGI, GHG emissions per unit yield) of different agricultural practices. Under current farmers&rsquo, practice, emissions due to machinery input (including production, transportation, repair, and maintenance) and soil organic carbon (SOC) decline accounted for 15% of GHGL, while emissions from nitrogen fertilizer input (production and transportation) and direct N2O emissions from soil accounted for the majority (~60% of GHGL). Current farmers&rsquo, practice in terms of N application and residue management are nearly optimal for crop production but not for climate change mitigation. Reducing N input by 13% and increasing straw retention by 20% can maintain crop yield and SOC, and also reduce GHGL and GHGI by 13% and 11%, respectively. However, it is not feasible to incorporate the straw used as household fuel into soil, which could incur substantial fossil CO2 emissions of 3.98 Mg CO2-eq ha&minus, 1 resulting from the substitution of coal for straw. APSIM was successful in simulating crop yield, N2O emissions, and SOC change in NEC, and our results highlight opportunities to further optimize management strategies (especially for the nitrogen and straw management) to reduce GHG emissions while maintaining crop yield.

Increasing milk yield per cow is considered a promising climate change mitigation strategy for small-scale dairy farms in developing countries. As it can be difficult to increase cow productivity, mitigation options beyond this production strategy need to be identified. The aim of this study was to identify entry points for mitigation of GHG emissions in small-scale dairy farms in Lembang Sub-district, West Java, Indonesia. Data on herd composition, productivity, feeding, and manure management were collected in a survey of 300 randomly selected dairy farms. Characteristics of farms with the 25% lowest (

Cities are a major source of energy use and greenhouse gases emissions, as well as being at the core of climate change mitigation. With the Revitalizing Old Industrial Base of Northeast China strategy, Northeast China has been a typical developing region with rapid industrialization and urbanization accompanied by substantial energy consumption and carbon emissions. Therefore, northeastern Chinese cities should play an important role in regional low-carbon developments. This study presents several improvements to the previous method to improve the accuracy of the results. Using the modified method, for the first time, we compile carbon emission inventories for 30 cities in Northeast China based on fossil fuel combustion and industrial processes. The results indicate that Anshan emitted the most carbon emissions annually, followed by Benxi and the vice-provincial cities (including Changchun, Shenyang, Dalian and Harbin). In 2012, the total carbon emissions of the 30 cities amounted to 973.95 million tonnes, accounting for 9.71% and 2.75% of national and global carbon emissions, respectively. Most of the CO2 emissions of these cities were from the ‘nonmetal and metal industry’ and ‘energy production and supply’. Raw coal was the primary source of carbon emissions in Northeast China, and industrial processes also played a significant role in determining carbon emissions. Additionally, both the average per capita carbon emissions and carbon emission intensity in the 30 cities were higher than the national levels. According to the differences in carbon emissions characteristics, we present several policy recommendations for carbon mitigation for northeastern Chinese cities. This study provides consistent and comparable spatial-temporal city-level emission database for further research on relationships between economic development and environmental protection in Northeast China. Simultaneously, this study provides practical reference values for other developing regions throughout the world to create low-carbon roadmaps.

Climate-smart agriculture targets integrated adaptation and mitigation strategies for delivering food security and greenhouse gas emissions reduction. This study outlines a methodology to identify the trade-offs between food production, emissions, and income under technology and food demand-shift scenario and climate change. The methodology uses Climate Smart Agricultural Prioritization (CSAP) toolkit a multi-objective land-use allocation model, and detailed databases, characterizing the agricultural production processes at the land-unit scale. A case study has also been demonstrated for Bihar, a state in India. The quantification of trade-offs demonstrates that under different technology growth pathways alone the food self-sufficiency for Bihar cannot be achieved whilst the reduction in emission intensity targets are achievable up to 2040. However, both food self-sufficiency and reduction in emission intensity can be achieved if we relax constraints on dietary demand and focus on kilo-calories maximization targets. The district-level analysis shows that food self-sufficiency and reduction in emission intensity targets can be achieved at a local scale through efficient crop-technology portfolios.

With the deepening of the global division of labor, it is significant to analyze the impact of global value chain participation on embodied carbon emission intensity. It provides implications for countries to address climate issues and improve development quality. The present work uses a multi-region input-output table provided by World Input Output Database to calculate the global value chain participation and the embodied carbon emission intensity of 42 different countries, for the period between 2000 and 2014. In addition, we decompose the carbon emission intensity into the carbon emission intensity embodied in domestic demand and foreign exports demand, and the carbon emission intensity of foreign exports demand is further divided into three types of embodied carbon emission intensity. Then, we analyze how global value chain participation affects the embodied carbon emission intensity, and examine different impacts across different development countries and different types of embodied carbon emission intensity. We also explore the different impacts under different embodied carbon emission intensity distributions. The results show that global value chain participation has a significantly negative impact on the embodied carbon emission intensity. Compared with the developed “north” countries, the global value chain participation of developing “south” countries have a larger negative impact of embodied carbon emission intensity. From the perspective of different types of demand, the impact of global value chain participation on carbon emission intensity embodied in foreign exports demand is greater than that embodied in domestic demand. The quantile regression results show that the global value chain participation at the high quantiles has a greater impact on the embodied carbon emission intensity, which indicates countries with higher embodied carbon emission intensity should participate in the global value chain to expand the production scale while reducing carbon emissions. These results provide relevant material and insights to countries about how their participation in the global production fragmentation affects their greenhouse gas emission profile, which can be used to elaborate structured political measures to address, at the same time, global market inclusion and climate change mitigation.

The high energy intensity of the modern industry and the threat of climate change determine the high urgency of increasing the energy efficiency of electric motors. In this paper, energy consumption, energy costs, payback periods, and CO2 emissions of 75 kW, 4 pole induction motors with direct grid supply in a fixed-speed pump unit are evaluated. Motors of the IE2, IE3, and IE4 efficiency classes according to IEC 60034-30-1 standard are compared in terms of life-time energy savings, payback period, and CO2 emissions. To carry out the analysis, polynomial interpolation of the data from the available manufacturer datasheets of the motors is used. It concluded that even though the initial investment cost of the IE4-motor is higher than that of IE3-motor, the IE4-motor is more profitable if more than 3 years of operation are considered and also provides significant reductions of CO2 emissions. The paper presents a calculation method of the aforementioned indicators which can be useful for companies, researchers, and engineers for quick assessment and selection of technical solutions. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. The work was partially supported by the Ministry of Science and Higher Education of the Russian Federation (through the basic part of the government mandate, Project No. FEUZ-2020-0060).

Climate change mitigation issues including China’s carbon emission status, the mitigation potential and cost in different sectors, the target of 40%–45% reduction of emission intensity of GDP in 2020 compared with the 2005 level, and conditions and uncertainties of the carbon emission peak are analyzed and assessed in the Third China National Climate Change Assessment Report and summarized in this paper. Economic structure adjustment has played and is expected to continue to play important role for carbon mitigation. Development of nuclear and renewable power would contribute to around 2 billion tons and 3.7 billion tons carbon reductions by 2020 and 2030 respectively. Key energy saving and low carbon technologies in the end-use sectors such as industry, transportation and building are listed and assessed. The mitigation potential and cost curve for steel is provided as an example to show that a large amount of carbon emissions could be reduced with minus mitigation cost partly resulting to energy saved. For industry process, carbon mitigation potentials would be around 420 million tons and 770 million tons by 2020 and 2030 respectively. Carbon mitigation potentials from LULUCF (Land use, land use change and forestry) are still uncertain and needed further research. For the assessment of 45% carbon intensity reduction target in 2020, it is concluded that economic structure adjustment, energy efficiency improvement, development of non-fossil energy, building and transportation would contribute to 33.4%, 28.5%, 20.4% and 17.3% of the total reductions. Assuming GDP growth rate as 6%–7% during 2010–2030, energy intensity reduction rate as 15% during 2015–2020, 14% during 2020–2025, and 13% during 2025–2030, the total primary energy consumption would be around 6 billion tons. To control coal use to less than 50% of the total primary energy consumption, while increasing the share of nature gas to over 10%, and the share of new and renewable energy to 20% or higher, carbon emissions would peak around 2030 at 11 to 12 billion tons. Finally, Climate change mitigation strategies to facilitate the achievement of China’s carbon emission peak target are proposed. It’s also suggested that measures are needed to accelerate the economy restructuring and development modes shift, to control the growth rate of total energy demand, to maintain a sustainable energy system with the new and renewable energy as its main components, and to achieve the carbon emission peak target by sector and region.

In recent years, the global climate governance is not just for a global environmental problem of climate change, more involved in international politics, economy, investment, technology and other fields, and involves the transformation of production and life style. Accompanied by global energy and technology revolution, the development of low carbon is our inevitable requirement. Recently, China submitted to UNFCCC (United Nations Framework Convention on Climate Change) the Secretariat of the national independent contribution plan and set emission reduction targets: carbon dioxide emissions reach the peak in 2030 and strive to reach the peak as early as possible; carbon emission intensity decreased by 60% - 65% compared with that in 2005. This means that our government will intensify its efforts to reduce carbon emissions. In the past, our target was to reduce carbon emissions intensity, but now our country is to realize the reduction of total carbon emissions, or “absolute reduction”. Carbon finance is an important breakthrough in the development of low carbon economy and the promotion of carbon emission reduction. This paper focuses on the analysis of the development status of China’s carbon financial market, the problems and the opportunities and challenges faced, and finally, the relevant countermeasures and suggestions are given from the perspectives of policy, talent, mechanism, international cooperation and so on, in order to promote the development of carbon financial market innovation, to seize the commanding heights of the era of low-carbon economy.

The Sustainable Development Goals (SDGs) imply country-led implementation. Yet, their achievement depends on sustainability targets compatible across different sectors and scales. Our study examines how the GHG emission intensity of agriculture (EIA) should evolve globally, regionally (Western Europe) and nationally (The Netherlands) under different socioeconomic pathways, so that two major aims of SDGs 2 and 13 (i.e. sufficient food production and climate change mitigation) are achieved simultaneously. Results show that, by 2050, relative to 2010 values, EIA should decrease at all three levels when measured on a product basis (GHG emissions per ton dry matter) and on a land basis (GHG emissions per ha). This indicates that, globally, agriculture should be intensified per unit area, while in Western Europe and even more so in the Netherlands additional emission reductions require increased production efficiency and lower production volumes. Projected reductions in methane and nitrous oxide emissions from enteric fermentation, manure management and fertilizer application in Dutch agriculture are much higher than what would be achieved through the extrapolation of current trends. Given the high costs of increasing production efficiency further, our analysis indicates the need for significantly more ambitious policy targets and systemic changes, including reduced consumption of animal-sourced food. Besides shedding light on the interaction between climate and agricultural strategies, our analysis illustrates the application of cross-scale thinking in the operationalization of the SDG agenda and underscores the need for concerted action amongst countries.

With the Rise of Central China Plan, the central region has had a great opportunity to develop its economy and improve its original industrial structure. However, this region is also under pressure to protect its environment, keep its development sustainable and reduce carbon emissions. Therefore, accurately estimating the temporal and spatial dynamics of CO2 emissions and analysing the factors influencing these emissions are especially important. This paper estimates the CO2 emissions derived from the fossil fuel combustion and industrial processes of 18 central cities in China between 2000 and 2014. The results indicate that these 18 cities, which contain an average of 6.57% of the population and 7.91% of the GDP, contribute 13% of China's total CO2 emissions. The highest cumulative CO2 emissions from 2000 to 2014 were from Taiyuan and Wuhan, with values of 2268.57 and 1847.59 million tons, accounting for 19.21% and 15.64% of the total among these cities, respectively. Therefore, the CO2 emissions in the Taiyuan urban agglomeration and Wuhan urban agglomeration represented 28.53% and 20.14% of the total CO2 emissions from the 18 cities, respectively. The three cities in the Zhongyuan urban agglomeration also accounted for a second highest proportion of emissions at 23.51%. With the proposal and implementation of the Rise of Central China Plan in 2004, the annual average growth rate of total CO2 emissions gradually decreased and was lower in the periods from 2005 to 2010 (5.44%) and 2010 to 2014 (5.61%) compared with the rate prior to 2005 (12.23%). When the 47 socioeconomic sectors were classified into 12 categories, “power generation” contributed the most to the total cumulative CO2 emissions at 36.51%, followed by the “non-metal and metal industry”, “petroleum and chemical industry”, and “mining” sectors, representing emissions proportions of 29.81%, 14.79%, and 9.62%, respectively. Coal remains the primary fuel in central China, accounting for an average of 80.59% of the total CO2 emissions. Industrial processes also played a critical role in determining the CO2 emissions, with an average value of 7.3%. The average CO2 emissions per capita across the 18 cities increased from 6.14 metric tons in 2000 to 15.87 metric tons in 2014, corresponding to a 158.69% expansion. However, the average CO2 emission intensity decreased from 0.8 metric tons/1000 Yuan in 2000 to 0.52 metric tons/1000 Yuan in 2014 with some fluctuations. The changes in and industry contributions of carbon emissions were city specific, and the effects of population and economic development on CO2 emissions varied. Therefore, long-term climate change mitigation strategies should be adjusted for each city.

Many of the climate change mitigation options for dairy systems that aim at optimizing milk production imply a reduced output of meat from these systems. The objective of this study was to evaluate effectiveness of a number of mitigation strategies for dairy systems, taking into account compensation for changes in the amount of beef produced. Four commonly used mitigation strategies for dairy systems were evaluated using an LCA modelling approach: increasing the milk production per cow, extending the productive life span of cows, increasing the calving interval, and changing breed from Holstein Friesian to Jersey. The Dutch dairy system was taken as a case study. For each scenario, analyses were done in two steps. First, effects of the mitigation strategy on production of milk and carcass weight from the dairy system were calculated. Second, GHG emission intensities were calculated for three different functional units (FU): one kg of fat and protein corrected milk (FPCM), one kg of carcass weight (CW), and a fixed amount of milk and beef (i.e. 1 kg FPCM and 40 g CW). In the third FU, in case the amount of CW produced by the dairy system was lower than 40 g per kg FPCM, the remainder was compensated by CW produced in pure beef systems, assuming a GHG emission intensity of 30 kg CO2-eq. per kg CW for pure beef. Results showed a reduction in CW per kg FPCM from the dairy system in all four mitigation strategies. Considering GHG emissions per kg of FPCM only, the strategies reduced emissions by 0.2 to 18.1%. When considering emissions per kg of CW only, emissions were reduced by 12.5 to 48.9%. However, when we used a FU of 1 kg FPCM and 40 g CW, changes in emissions ranged from −0.2 to 3.8%. This was caused by the compensation of the lower CW production from dairy systems by CW from pure beef systems. Differences in emissions per kg FPCM and 40 g CW were smaller when the assumed emission intensity of pure beef was lower. We concluded that the mitigation strategies for dairy systems evaluated in this study were less effective for reduction of GHG emissions from production of milk and beef, when accounting for changes in the amount of beef produced. This study showed that the challenge of reducing GHG emissions of milk and beef production is interrelated. Hence, analyses of GHG emissions related to changes in production of milk and beef requires an integrated approach, beyond the system boundaries of the dairy farm.

Tradeoffs are examined between mitigating black carbon (BC) and carbon dioxide (CO2) for limiting peak global mean warming, using the following set of methods. A two-box climate model is used to simulate temperatures of the atmosphere and ocean for different rates of mitigation. Mitigation rates for BC and CO2 are characterized by respective timescales for e-folding reduction in emissions intensity of gross global product. There are respective emissions models that force the box model. Lastly there is a simple economics model, with cost of mitigation varying inversely with emission intensity. Constant mitigation timescale corresponds to mitigation at a constant annual rate, for example an e-folding timescale of 40 years corresponds to 2.5% reduction each year. Discounted present cost depends only on respective mitigation timescale and respective mitigation cost at present levels of emission intensity. Least-cost mitigation is posed as choosing respective e-folding timescales, to minimize total mitigation cost under a temperature constraint (e.g. within 2 °C above preindustrial). Peak warming is more sensitive to mitigation timescale for CO2 than for BC. Therefore rapid mitigation of CO2 emission intensity is essential to limiting peak warming, but simultaneous mitigation of BC can reduce total mitigation expenditure.

Energy consumption increases with intensity of human activities. People consume energy for movement and other activities and the more fossil-fuel based energy used, the more carbon dioxide (CO2) emission. Since carbon dioxide is the major element of the greenhouse gases (GHG), this phenomenon has a serious implication for global warming and consequent climate change—a scenario that calls for sustainable development. This research considers the emission of CO2 from energy use within the campus of Universiti Teknologi Malaysia. Two major sources of energy consumption were identified, namely: electricity and transport. The emission for electricity was estimated based on electricity meter reading and the conversion rate in accordance with the stand-ardized conversion factors for fuel mix of the purchased electric energy as given by PTM (Pusat Tenaga Malaysia), while the associated CO2 emission for transport was estimated based on the number of miles driven (VMT—Vehicle Miles Travel) within the campus, emissions produced per litre of gasoline, and fuel economy of vehicles plying the campus in line with the Code of Federal Regulations USEPA and consistent with the Inter-governmental Panel on Climate Change (IPCC) guidelines. It was observed that high CO2 emission resulted from electricity energy consumption, and the highest emission in the transport sector was produced by commuting vehicles while emission from service delivery for cooling, lighting and other equipment was similar to national average.

The objective of the study is to investigate the long-run relationship between climatic factors (i.e., greenhouse gas emissions, agricultural methane emissions, and industrial nitrous oxide emission), air pollution (i.e., carbon dioxide emissions), and energy sources (i.e., nuclear energy; oil, gas, and coal energy; and fossil fuel energy) in the panel of 35 developed countries (including EU-15, new EU member states, G-7, and other countries) over a period of 1975-2012. In order to achieve this objective, the present study uses sophisticated panel econometric techniques including panel cointegration, panel fully modified OLS (FMOLS), and dynamic OLS (DOLS). The results show that there is a long-run relationship between the variables. Nuclear energy reduces greenhouse gases and carbon emissions; however, the other emissions, i.e., agricultural methane emissions and industrial nitrous oxide, are still to increase during the study period. Electricity production from oil, gas, and coal sources increases the greenhouse gases and carbon emissions; however, the intensity to increase emissions is far less than the intensity to increase emissions through fossil fuel. Policies that reduce emissions of greenhouse gases can simultaneously alter emissions of conventional pollutants that have deleterious effects on human health and the environment.

Brazil’s economic development has been underpinned by a diverse and – in a global comparison – unusual set of energy carriers, notably hydroelectricity and ethanol from sugar cane. Its energy mix makes Brazil one of the least energy-related carbon-intensive economies worldwide. Given that the country is fast becoming one of the world’s economic powerhouses, decision-makers need to understand the drivers underlying past and current carbon dioxide emissions trends. We therefore investigate a) which key long-term drivers have led to Brazil’s unique emissions profile, and b) the implications of these drivers for Brazil’s national policies. We show that Brazil’s emissions are growing mainly due to increasing individual standards of living, exports and population size, and that this growth is so far unchallenged by technological and structural improvements toward lower emissions intensities and more efficient production structures. As these trends are likely to continue amidst growing international pressure on key economies to reduce their carbon emissions, a decoupling of drivers from emissions is needed to simultaneously meet development and environmental goals.

This article presents an updated overview of recent literature on the role of nuclear power in mitigating greenhouse gas (GHG) and particulate matter (PM) emissions from electricity generation. Emission intensities are strongly dependent on the country of operation and type of technology used in each category of power production options, but robust observations can be made with regards to the average emission intensity of each main alternative. The majority of emissions from nuclear energy is associated with parts of its overall life cycle other than the operation of nuclear power plants. Technological progress in especially uranium enrichment has recently yielded energy intensity reductions that have significantly lowered the GHG footprint of nuclear power, which at present amounts to 5–17 gCO2eq/kWh. As a result, average GHG emissions are today around two orders of magnitude lower for nuclear energy than for conventional coal-based power production. This article also addresses the feasibility of potential deployment scenarios for nuclear power and their implications in terms of global GHG emissions mitigation. Keywords: Power production, Nuclear energy, Life cycle analysis, Greenhouse gases, Carbon dioxide, Climate change mitigation, Particulate matter

In this work, the authors present a mathematical model capable of calculating CO2, NOx and PM emissions, based on statistical data for emission sources at country level. The underlying methodology has been based on both the IPCC guidelines and the EMEP/CORINAIR air pollutant emission inventory guidebook. The case study focuses on Cyprus and investigates the application of specific climate change mitigation scenarios. The key results of the study show that an increased use of biomass and diesel can promote decarbonisation, but fail to reduce air pollution, while hybrid technologies and natural gas offer significant improvements for both goals.

The objective of this transport component of the broader Africa Climate Business Plan (ACBP) is to begin to mainstream climate benefits into the World Bank’s transport program for Sub-Saharan Africa, the better to assist African countries in bringing their climate change efforts to scale. It is a first step towards mainstreaming responses to the climate challenge into transport programs in Africa, and it represents the first time the Transport & ICT GP has produced a work plan for its investment and technical assistance operations that takes into account the content of countries’ Nationally Determined Contributions (NDCs) and attempts to align World Bank support to the goals stated therein. The transport work plan under this Africa Climate Business Plan will consist of up to $3.2 billion in investments and technical assistance over the 2016-2020 period – including $2.8 billion in World Bank funds. Those investments will help to make progress on two strategic objectives: (1) improving the resilience of African transport infrastructure to climate change by defining four pillars of resilient transport; and (2) improving the carbon-efficiency of transport systems in Sub-Saharan Africa.

This paper analyses the factors affecting greenhouse gas (GHG) emissions in Greece, (i.e. the drivers of pressures on climate change), using environmental indicators related to energy, demographics and economic growth. The analysis is based on the data of 2008 and considers types of fuel and sectors. The Kaya identity is used to identify the relationship between drivers and pressures, using annual time series data of National GHG emissions, population, energy consumption and gross domestic product. The analysis shows that over the period 2000–2008, GHG emissions show a slight variation, but they are almost stabilised, with a total increase of 1.6%. Despite the economic growth over that period, this stabilisation may be considered as a combination of reductions in the energy intensity of GDP and the carbon intensity of energy, which are affected by improvements in energy efficiency and introduction of “cleaner” fuels, such as natural gas and renewables in the energy mixture of the country.

This paper explores the relationship between productivity of dairy production and greenhouse gas (GHG) emissions on a global scale. A Life Cycle Assessment (LCA) methodology was used to assess GHG emissions from dairy production and processing chains. Milk yield expressed as kg fat and protein corrected milk (FPCM) per animal was chosen as a proxy for system productivity. On a per cow basis, GHG emissions increase with higher yields. However, GHG emissions per kg FPCM decline substantially as animal productivity increases. The contribution of different gases to total GHG emissions of dairy production systems vary; methane and nitrous oxide emissions decrease with increasing productivity, while carbon dioxide emissions increase, but on a lower scale. Productivity increase therefore offers not only a pathway to satisfying increasing demand for milk but also a viable mitigation approach, especially in areas where milk yields are currently below 2000 kg/cow and year.

Low-carbon economy is becoming a new approach to optimize economic development, ensuring energy security and coping with climate change. As one of the important emission sources of greenhouse gases (GHG), the industrial sector should be prioritized in the development of low-carbon economy. In this study, the carbon emission from industrial energy use of Chongqing is accounted. On basis of industrial carbon emission (ICE) accounting, main factors responsible for industrial CO2 emission are identified and quantitatively analyzed using the Log-Mean Divisia Index method. The factors influenc- ing ICE include energy mix, energy intensity, industrial structure and industrial output. It is found that the industrial output is the main driving force of ICE. The energy structure performs as a negative factor in carbon emission growth. By means of decomposing the influenc- ing factors, several policy proposals were suggested for policy makers to build a low carbon city.

Dynamic targets have been long advocated as a participatory tool for developing countries in climate change mitigation. Copenhagen commitments of India and China resume this trend after the unsuccessful attempt of Argentina a decade ago. However, linear intensity targets are prone to ‘hot air’ problems or non-compliance risks. Intensity targets of India and China are analyzed using their elasticity parameters. The relationship of these parameters to the structural nature of emissions and GDP profiles has been demonstrated and a method of comparing the probability indices of target achievement has been formulated in this paper, showing a lower probability for China compared to India. Similarly, a method of defining stringency factor for linear targets has been suggested and stringency factors evaluated for India (40%) and China (90%), which shows the relative stability of India’s targets. This paper evaluates an energy–GDP–emissions index (EYE index) to indicate the extent of coupling/decoupling of economic growth from emissions. The three indices developed in this paper, namely, elasticity parameter, stringency factor and EYE index can be effectively used to analyze the economy–emissions relationships for policy making and target setting.

This article analyses the greenhouse gas (GHG) impact potential of improved management practices and technologies for smallholder agriculture promoted under a global food security development program. Under 'business-as-usual' development, global studies on the future of agriculture to 2050 project considerable increases in total food production and cultivated area. Conventional cropland intensification and conversion of natural vegetation typically result in increased GHG emissions and loss of carbon stocks. There is a strong need to understand the potential greenhouse gas impacts of agricultural development programs intended to achieve large-scale change, and to identify pathways of smallholder agricultural development that can achieve food security and agricultural production growth without drastic increases in GHG emissions.In an analysis of 134 crop and livestock production systems in 15 countries with reported impacts on 4.8 million ha, improved management practices and technologies by smallholder farmers significantly reduce GHG emission intensity of agricultural production, increase yields and reduce post-harvest losses, while either decreasing or only moderately increasing net GHG emissions per area. Investments in both production and post-harvest stages meaningfully reduced GHG emission intensity, contributing to low emission development. We present average impacts on net GHG emissions per hectare and GHG emission intensity, while not providing detailed statistics of GHG impacts at scale that are associated to additional uncertainties. While reported improvements in smallholder systems effectively reduce future GHG emissions compared to business-as-usual development, these contributions are insufficient to significantly reduce net GHG emission in agriculture beyond current levels, particularly if future agricultural production grows at projected rates.

The United States is moving closer to enacting a policy to reduce domestic emissions of greenhouse gases. A key element in any plan to reduce emissions will be to place a price on greenhouse gas emissions. This paper discusses the different approaches that can be taken to price emissions and assesses their strengths and weaknesses.

In this paper a general equilibrium model of greenhouse gas emissions in Brazil is developed, and some policies for emissions reductions are evaluated. The core model is derived from the MMRF-GREEN model of Australia (Adams, Horridge and Wittwer, 2002). It is a static inter-regional “bottom-up” general equilibrium model, which distinguishes 27 regions inside Brazil, as well as 38 commodities and industries in the economy. The core database is calibrated with Brazilian economic data from 1996, while the emissions module is based on the Brazilian Initial National Communication to the United Nations Convention about Global Climate Change (Ministerio da Ciencia e Tecnologia, 2004) for the 1994 reference year. The gas module in the model comprises all known sources of greenhouse gases emissions except emissions from land use change (deforestation). The recent introduction in Brazil of the flexfuel technology for vehicles (which allows the use of alcohol, gasoline, or any blend of these two fuels) is a particular characteristic of the fuel market in the country. Although gasoline in Brazil has for long been blended with alcohol (the so called gasoalcool fuel), the flexfuel engines allow instant substitution based on relative price changes. The number of cars with flexfuel engines is increasing fast as a share of the national fleet. To deal with this aspect of the Brazilian economy, the model has as a special feature a detailed specification of substitution in fuel use between alcohol and gasoline. Emissions in the model are classified in basically two sources: emissions on fuel use, and emissions on the activity level of the economic sectors. The main characteristics of the emissions patterns in the Brazilian economy are analyzed, and simulations with carbon taxes are performed. The simulations comprise carbon taxes on emissions, either on fuel use or on the activity level of industries. Results show that taxing activities is more relevant for greenhouse gases emissions reductions in Brazil than just taxing fuel use, due to the importance of activity related emissions in the Brazilian emissions matrix. Livestock is found to be one of the most important emission sectors in Brazil. Due to the importance of this particular sector, sensitivity analysis is performed with the value of the coefficient for conversion of CH4 emissions into CO2 equivalents. Sensitivity analysis is also performed on the value the alcohol/gasoline substitution parameter. The impact on aggregated results of increasing this parameter, however, is not very high, due to the relative little importance of gasoline in the Brazilian emissions matrix, although this has important impacts on the alcohol production and related sectors.

The case for climate action has never been stronger. Current weather extremes, including storms, floods and drought, affect millions of people across the world. Climate change is putting water security at risk; threatening agricultural and other supply chains as well as many coastal cities. The likelihood of severe pervasive and irreversible impacts will grow without action to limit and reverse the growth of GHG emissions globally. Last year’s Intergovernmental Panel on Climate Change (IPCC) report makes clear the overwhelming need to take action now on climate change and that the costs of inaction will only rise. The challenge is to decarbonize our economies by 2100 with action in the next decades being critical. The choices made by government, the private sector, and civil society as part of the transition to a decarbonized economy will determine the extent of future climate impacts but also provide an opportunity to unlock investment and build an innovative, dynamic low-carbon economy.

This paper shows the importance of including region-specific circumstances in long-term climate change mitigation strategies, by example of a modeling exercise of the transport sector. Important emission reduction options in the transport sector include biofuels, electric vehicles and efficiency standards. The most effective combination of these options depends, among others, on the availability of biofuels, the effectiveness of efficiency standards, and the (expected) emission intensity of the power sector—all of which differ between regions. Differences in climate policies between regions influence these factors. For instance, fuel efficiency standards slowdown the long-term transition in regions where plugin hybrid electric cars compete with gasoline cars (such as the USA or Europe) by decreasing the costs for driving gasoline costs and therefore in fact increase long-term emissions. Another example is that promoting electric vehicles is less effective in regions which are expected to rely heavily on fossil fuels for power generation, such as South Africa, China and India. Based on these findings from the TIMER energy model, we introduce an indicative region-specific framework for assessing mitigation strategies for the transport sector up to 2050, for different ambition levels of climate policy.

Eco innovations (EI) that address climate change mitigation require pressures and knowledge from outside the firm’s and sector’s boundaries, due to the radicalness and variety of techno-organisational knowledge the economy needs to curb emissions by 90 % in the long run and 40 % in the medium run, at least according to EU targets. The role of policy as a tool that potentially tackles two externalities—innovation and environmental market failures—has been studied over the past decade. Sector integration, which is increasingly relevant for understanding the economic, environmental and innovation performances of countries, might additionally influence innovations, and it is relatively overlooked. We integrate these two perspectives to provide evidence on the adoption of EI in EU sectors over 2006–2008. Using past CO2 emission intensity as a proxy of policy stringency we find that emission intensive sectors are more likely to adopt CO2-related eco-innovations. The aforementioned results are valid for both the economy as a whole and for industrial sectors specifically. We additionally show that inter sector integration and knowledge sources matter: we do observe that sectors with more emission intensive upstream ‘partners’ eco-innovate more to reduce their CO2 footprints. The positive and significant effect of upstream emission intensity (supplier’s emission intensity) on EI is actually stronger than the effect of ‘direct’ CO2 emission intensity (policy effect).

The need to decompose CO2 emission intensity is predicated upon the need for effective climate change mitigation and adaptation policies. Such analysis enables key variables that instigate CO2 emission intensity to be identified while at the same time providing opportunities to verify the mitigation and adaptation capacities of countries. However, most CO2 decomposition analysis has been conducted for the developed economies and little attention has been paid to sub-Saharan Africa. The need for such an analysis for SSA is overwhelming for several reasons. Firstly, the region is amongst the most vulnerable to climate change. Secondly, there are disparities in the amount and composition of energy consumption and the levels of economic growth and development in the region. Thus, a decomposition analysis of CO2 emission intensity for SSA affords the opportunity to identify key influencing variables and to see how they compare among countries in the region. Also, attempts have been made to distinguish between oil and non-oil-producing SSA countries. To this effect a comparative static analysis of CO2 emission intensity for oil-producing and non oil-producing SSA countries for the periods 1971–1998 has been undertaken, using the refined Laspeyres decomposition model. Our analysis confirms the findings for other regions that CO2 emission intensity is attributable to energy consumption intensity, CO2 emission coefficient of energy types and economic structure. Particularly, CO2 emission coefficient of energy use was found to exercise the most influence on CO2 emission intensity for both oil and non-oil-producing sub-Saharan African countries in the first sub-interval period of our investigation from 1971–1981. In the second subinterval of 1981–1991, energy intensity and structural effect were the two major influencing factors on emission intensity for the two groups of countries. However, energy intensity effect had the most pronounced impact on CO2 emission intensity in non-oil-producing sub-Saharan African countries, while the structural effect explained most of the increase in CO2 emission intensity among the oil-producing countries. Finally, for the period 1991–1998, structural effect accounted for much of the decrease in intensity among non-oil-producers, while CO2 emission coefficient of energy use was the major force driving the decrease among oil-producing countries. The dynamic changes in the CO2 emission intensity and energy intensity effects for the two groups of countries suggest that fuel switching had been predominantly towards more carbon-intensive production in oil-producing countries and less carbon-intensive production in non-oil-producing SSA countries. In addition to the decomposition analysis, the article discusses policy implications of the results. We hope that the information and analyses provided here would help inform national energy and climate policy makers in SSA of the relative weaknesses and possible areas of strategic emphasis in their planning processes for mitigating the effects of climate change.

The United Nations Framework Convention on Climate Change (UNFCCC) requires that all parties to the convention periodically report their emissions of greenhouse gases and the Intergovernmental Panel on Climate Change (IPCC) has published guidelines on how to estimate these emissions. Estimating carbon dioxide (CO 2 ) emissions is complicated by the fact that consumption of fossil-fuels and harvesting of forests do not necessarily mean that the contained C has been released to the atmosphere as CO 2 . Some fractions of fossil-fuels and harvested wood are incorporated into products that have lifetimes ranging from months to centuries. The IPCC methodology addresses durable products by assuming that some prescribed fraction goes to permanent storage while the remainder is oxidized instantly. The question posed here is whether the annual increase in stocks of durable products, i.e. the difference between the rates of production and oxidation, can be reasonably estimated as a simple fraction of their current rate of production. Although the annual stock change can be described as a simple fraction of annual production when production is growing exponentially and oxidation is a first order decay process, a description of annual stock changes needs to consider how both production and oxidation are evolving with time, regardless of the functional forms of these changes with time.

The global warming is the most important environmental issue for human society in terms of its scale and impact. The Japanese Government established the Global Worming Headquarters in December 1997 to implement effective measures against global warming-related issues. The Japanese Diet approved the Kyoto Protocol in May 2002, and accordingly, Japan has an obligation of greenhouse gas emissions reduction of 6% below 1990 levels.The greenhouse gas emissions in Japan are mainly generated from energy sources, such as oil, coal and natural gas. They are closely related to the public life and economic activities. Therefore, it is necessary to take various measures for both energy supply and demand sides to achieve the reduction of greenhouse gases stipulated in the Kyoto Protocol.The input-output analysis is a useful tool to examine the economic structural problems concerning the economic growth, the industrial structure and the environment. Various researches have been made to estimate the carbon dioxide emissions from the economic activities and the public life in Japan using input-output tables.This paper aims to identify the relationships between the regional economic structure and the carbon dioxide emission in Japanese regions. The study employs regional input-output tables published by the Ministry of Economy, Trade and Industry and the data for carbon dioxide emission intensity estimated by the National Institute for Environmental Studies for years 1975, 1980, 1985, 1990 and 1995.The empirical study has revealed that the electricity and the transport sectors showed marked increases in carbon dioxide emissions during 1975-95, whereas most of the manufacturing sectors showed reduction during the same period. According to the analysis by region, the carbon dioxide emission showed a growing trend in each region due to an increase in final demand. The trend was the clearest in the capital region, Kanto.

China is now facing great challenges resulting from climate change and air pollution, driven by the processes of industrialization and urbanization. Greenhouse gas and air pollutant emissions produced by the coal-fired power industry represent approximately 70% of the total emissions in China’s industrial sector. In this study, 39 coal-fired power plants built in China between 2014 and 2015 were analyzed in regards to the co-effects oncarbon dioxide and air pollutant emissions generated directly and indirectly by end-of-pipe measures of pollution control. After completing the quantitative analysis with input data from 83units of power plants, we found that co-effects were positive only for air pollutant reductions through the implementation of desulfurization, denitrification, and dedusting measures, but co-effects were negative for carbon dioxide production because of the corresponding electricity use and chemical reactions that led to the increases in carbon dioxide emissions. We also performed an assessment of the synergistic coefficients to better understand the degree of co-effects. It will be important for researchers to take a comprehensive view of China’s coal-fired power plants and look for solutions that can maximize positive co-effects and achieve overall co-benefits of reductions in greenhouse gas emissions and air pollutants.

“Decarbonizing” the world’s energy matrix is the strategy being implemented by most countries to reduce CO 2 emissions and thus contribute to achieve the ultimate objectives of the Climate Convention. The evolution of the carbon intensity ( I c =CO 2 /GDP) in the period 1990–2007 was encouraging but not sufficient to reduce the growth of carbon emission. As a result of COP-15 in Copenhagen these countries (and regions) made pledges that could lead to more reduction: for the United States a 17% reduction in CO 2 emissions by 2020 below the level of 2005; for the European Union a 20% reduction in CO 2 emissions by 2020 below the 1990 level; for China a 40–45% reduction in the carbon intensity and for India a 20–25% reduction in carbon intensity by 2020. We analyzed the consequences of such pledges and concluded that the expected yearly rate of decrease of the carbon intensity follows basically the “business as usual” trend in the period 1990–2007 and will, in all likelihood, be insufficient to reduce carbon emissions up to 2020.

A new set of no-policy global greenhouse gas (GHG) emission scenarios was developed using the atmospheric stabilization framework, the same modeling tool that was used to generate the IS92 emission scenarios for the Intergovernmental Panel on Climate Change. Revised assumptions about population and economic growth, combined with updated information on changes in renewable energy supply, the efficiency of energy generation and other factors resulted in changes in GHG emission profiles over the next century, which led to an increase in the estimated global average temperature change as compared to the IS92 scenarios. Model results indicate that the largest increase in emissions, which led to a temperature increase of about 3.4°C by 2100 (relative to 1990), can be expected when a rapid increase in the GNP per capita levels of the non-OECD countries is combined with a low availability of solar/wind and biomass energy resources and slow energy efficiency improvements. The smallest increase in emissions and temperature by 2100 (about 2.5°C) occurred when a relatively slow increase in the GNP per capita in the non-OECD countries was combined with a high availability of renewable energy resources and rapid energy efficiency improvements.

Emissions of carbon dioxide from the combustion of fossil fuels, which may contribute to long-term climate change, are projected through 2050 using reduced-form models estimated with national-level panel data for the period of 1950-1990. Using the same set of income and population growth assumptions as the Intergovernmental Panel on Climate Change (IPCC), we find that the IPCC's widely used emissions growth projections exhibit significant and substantial departures from the implications of historical experience. Our model employs a flexible form for income effects, along with fixed time and country effects, and we handle forecast uncertainty explicitly. We find clear evidence of an "inverse U" relation with a within-sample peak between carbon dioxide emissions (and energy use) per capita and per-capita income. © 1998 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology