City density and CO2 efficiency

Cities play a vital role in the global climate change mitigation agenda. City population density is one of the key factors that influence urban energy consumption and the subsequent GHG emissions. However, previous research on the relationship between population density and GHG emissions led to contradictory results due to urban/rural definition conundrum and the varying methodologies for estimating GHG emissions. This work addresses these ambiguities by employing the City Clustering Algorithm (CCA) and utilizing the gridded CO₂ emissions data. Our results, derived from the analysis of all inhabited areas in the US, show a sub-linear relationship between population density and the total emissions (i.e. the sum of on-road and building emissions) on a per capita basis. Accordingly, we find that doubling the population density would entail a reduction in the total CO₂ emissions in buildings and on-road sectors typically by at least 42%. Moreover, we find that population density exerts a higher influence on on-road emissions than buildings emissions. From an energy consumption point of view, our results suggest that on-going urban sprawl will lead to an increase in on-road energy consumption in cities and therefore stresses the importance of developing adequate local policy measures to limit urban sprawl.     

The impact of household consumption on energy use and CO2 emissions in China

In this paper, the consumer lifestyle approach is applied to analyze the impact of consumption by urban and rural households on energy use and CO₂ emissions for different regions and income levels in China. Grey Model is used to compare the relationship between energy consumption, consumption expenditure and CO₂ emissions for different lifestyles. The results show that direct energy consumption is diverse for urban households and simple for rural households in China. Direct energy consumption and CO₂ emissions are increasing faster for urban than for rural households. Indirect energy consumption and CO₂ emissions for urban households are much greater than the direct consumption values. The total indirect energy consumption and CO₂ emissions differ by regions and the structures are different, but the latter differences are not obvious. The impact of household income is enormous. Indirect energy consumption and CO₂ emissions are higher for high-income than for low-income households. The structural difference for indirect energy consumption and CO₂ emissions for households with different income levels is significant. The higher the income, the more diverse is the energy consumption and CO₂ emission structure. The structures for indirect energy use and CO₂ emissions are diverse for urban households, but simple for rural households.     

Auditing energy use in cities

`Energy auditing’ as a technique for obtaining a ‘snapshot’ of the energy flows in a city or urban conurbation is discussed in the context of meeting national and international targets for CO₂ emissions abatement. An audit methodology is presented which addresses the key questions: Who needs to be involved in the audit? How should the city or conurbation be divided? What data are required? How might these data be obtained and then analysed? Which are the areas of significant consumption? A basis for setting local targets for reducing future energy consumption and CO₂ emissions is presented. The scope for auditing major cities and conurbations in the United Kingdom is identified with reference to implementing Local Agenda 21 and satisfying CO₂ emissions reduction targets.     

Energy and environmental evaluation of municipal facilities: Case study in the province of Barcelona

The service sector is extraordinarily important for the European economy, as it accounts for 75% of the GDP. Yet it is also a huge consumer of energy, especially in urban environments. Municipalities have the authority to develop and manage municipal services, and as a result the European Commission drew up the Covenant of Mayors in which the signatory municipalities pledge to reduce their CO₂ emissions by 20% of their 1990 rates. Sustainable Energy Action Plans (SEAPs) emerged from this covenant with the goal of analysing the current consumption patterns and compiling the actions that the municipalities should undertake in order to fulfil their pledges.This article focuses on analysing the energy consumption and greenhouse gas emissions of 978 municipal service facilities in the province of Barcelona in the year 2005. The average consumption per facility by surface area is 118.8 kWh/m². Regarding greenhouse gas emissions, the average annual emissions in the facilities studied in the province of Barcelona were 40.0 kg CO₂ eq/m².     

The impact of lifestyle on energy use and CO2 emission: An empirical analysis of China's residents

Based on the application of a Consumer Lifestyle Approach (CLA), this paper quantifies the direct and indirect impact of lifestyle of urban and rural residents on China's energy use and the related CO₂ emissions during the period 1999–2002. The results show that approximately 26 per cent of total energy consumption and 30 per cent of CO₂ emission every year are a consequence of residents’ lifestyles, and the economic activities to support these demands. For urban residents the indirect impact on energy consumption is 2.44 times greater than the direct impact. Residence; home energy use; food; and education, cultural and recreation services are the most energy-intensive and carbon-emission-intensive activities. For rural residents, the direct impact on energy consumption is 1.86 times that of the indirect, and home energy use; food; education, and cultural recreation services; and personal travel are the most energy-intensive and carbon-emission-intensive activities. This paper provides quantitative evidence for energy conservation and environmental protection focused policies. China's security for energy supply is singled out as a serious issue for government policy-makers, and we suggest that government should harmonize the relationships between stakeholders to determine rational strategies.     

A new look at the FDI–income–energy–environment nexus: Dynamic panel data analysis of ASEAN

The main focus of this paper is to estimate the effects of foreign direct investment (FDI) inflows, income and energy consumption on CO₂ emissions using panel data of five ASEAN countries over 1981–2010. The results based on the pooled mean group (PMG) estimator of dynamic panels show that FDI tends to increase CO₂ emissions, supporting evidence of the pollution haven hypothesis. We also find that income and energy consumption have a detrimental impact on reducing CO₂ emissions.     

Non-renewable and renewable energy consumption and CO2 emissions in OECD countries: A comparative analysis

This paper attempts to explore the determinants of CO₂ emissions using the STIRPAT model and data from 1980 to 2011 for OECD countries. The empirical results show that non-renewable energy consumption increases CO₂ emissions, whereas renewable energy consumption decreases CO₂ emissions. Further, the results support the existence of an environmental Kuznets curve between urbanisation and CO₂ emissions, implying that at higher levels of urbanisation, the environmental impact decreases. Therefore, the overall evidence suggests that policy makers should focus on urban planning as well as clean energy development to make substantial contributions to both reducing non-renewable energy use and mitigating climate change.     

Energy-related emissions and mitigation opportunities from the household sector in Delhi

Urban centers are the major consumers of energy, which is a major source of air pollution. Therefore, an insight into energy consumption and quantification of emissions from urban areas are extremely important for identifying impacts and finding solution to air pollution in urban centers. This paper applies the Long-range Energy Alternatives Planning (LEAP) system for modeling the total energy consumption and associated emissions from the household sector of Delhi. Energy consumption under different sets of policy and technology options are analyzed for a time span of 2001–2021 and emissions of carbon dioxide (CO₂), carbon monoxide (CO), methane (CH₄), non-methane volatile organic compounds (NMVOCs), nitrogen oxides (NO_x), nitrous oxide (N₂O), total suspended particulates (TSP) and sulfur dioxide (SO₂) are estimated. Different scenarios are generated to examine the level of pollution reduction achievable by application of various options. The business as usual (BAU) scenario is developed considering the time series trends of energy use in Delhi households. The fuel substitution (FS) scenario analyzes policies having potential to impact fuel switching and their implications towards reducing emissions. The energy conservation (EC) scenario focuses on efficiency improvement technologies and policies for energy-intensity reduction. An integrated (INT) scenario is also generated to assess the cumulative impact of the two alternate scenarios on energy consumption and direct emissions from household sectors of Delhi. Maximum reduction in energy consumption in households of Delhi is observed in the EC scenario, whereas, the FS scenario seems to be a viable option if the emission loadings are to be reduced.     

Analysis of the energy metabolism of urban socioeconomic sectors and the associated carbon footprints: Model development and a case study for Beijing

Cities consume 80% of the world׳s energy; therefore, analyzing urban energy metabolism and the resulting carbon footprint provides basic data for formulating target carbon emission reductions. While energy metabolism includes both direct and indirect consumptions among sectors, few researchers have studied indirect consumption due to a lack of data. In this study, we used input–output analysis to calculate the energy flows among directly linked sectors. Building on this, we used ecological network analysis to develop a model of urban energy flows and also account for energy consumption embodied by the flows among indirectly linked sectors (represented numerically as paths with a length of 2 or more). To illustrate the model, monetary input–output tables for Beijing from 2000 to 2010 were analyzed to determine the embodied energy consumption and associated carbon footprints of these sectors. This analysis reveals the environmental pressure based on the source (energy consumption) and sink (carbon footprint) values. Indirect consumption was Beijing׳s primary form, and the carbon footprint therefore resulted mainly from indirect consumption (both accounting for ca. 60% of the total, though with considerable variation among sectors). To reduce emissions, the utilization efficiency of indirect consumption must improve.     

The dynamic impact of renewable energy consumption and financial development on CO2 emissions: For selected African countries

This empirical study examines the impact of economic growth, renewable energy, energy consumption, financial developments, trade openness, and urbanization growth on CO₂ emissions using the Pooled Mean Group (PMG) approach and Granger Causality in the EKC model a data set of 25 African countries over the period 1985–2015. The results showed that increases in renewable energy consumption and trade openness decrease CO₂ emissions, and the EKC hypothesis is supported for the African countries. Granger’s causality results indicated the presence of bidirectional causality between economic growth and financial development and CO₂ emissions. These results could support policymakers manage financial development and consider clean investments and other ecological aspects for sustainable urban development. The causality tests showed a unidirectional causality running from renewable energy consumption to CO₂ emissions in African countries.     

Driving forces of residential CO2 emissions in urban and rural China: An index decomposition analysis

There exist many differences between urban and rural China among which residential CO₂ emissions arising from energy consumption is a major one. In this paper, we estimate and compare the energy related CO₂ emissions from urban and rural residential energy consumption from 1991 to 2004. The logarithmic mean Divisia index decomposition analysis is then applied to investigate the factors that may affect the changes of the CO₂ emissions. It is found that energy intensity and the income effects, respectively, contributed most to the decline and the increase of residential CO₂ emissions for both urban and rural China. In urban China, the population effect was found to contribute to the increase of residential CO₂ emissions with a rising tendency. However, in rural China, the population effect for residential CO₂ emissions kept decreasing since 1998.     

Urban energy use and carbon emissions from cities in China and policy implications

Urban areas contain 40% of the population and contribute 75% of the Chinese national economy. Thus, a better understanding of urban energy uses is necessary for Chinese decision-makers at various levels to address energy security, climate change mitigation, and local pollution abatement. Therefore, this paper addresses three key questions: What is the urban contribution to China's energy usage and CO₂ emissions? What is the contribution of large cities, and what alternate energy–economy pathways are they following? How have energy uses and CO₂ emissions transformed in the last two decades in key Chinese cities? This three-tier analysis illustrates the changes in urban energy uses and CO₂ emissions in China. The results show that the urban contributions make up 84% of China's commercial energy usage. The 35 largest cities in China, which contain 18% of the population, contribute 40% of China's energy uses and CO₂ emissions. In four provincial cities, the per capita energy usage and CO₂ emissions have increased several-fold. Rapid progress was made in reducing the carbon intensity of economic activities in cities throughout the 1990s, but alarmingly, such progress has either slowed down or been reversed in the last few years. These results have important policy implications.     

Modeling of current and future energyintensity and greenhouse gas emissions ofthe Lebanese industrial sector: assessmentof mitigation options

Greenhouse gas emissions in Lebanon mainly come from energy activities, which are responsible for 85% of all CO₂ emissions. The CO₂ emissions from energy use in manufacturing industries and construction represent 24% of the total emissions of the energy sector. Lebanese manufacturers' accounted for 39.15 million gigajoules of fuel consumption for heat and power generation in 1994, including both fuel used directly and fuel burned remotely to generate electricity used in the sector. In addition to being processed by combustion, CO₂ is generated in calcining of carbonates in the manufacture of cement, iron and glass. Electricity, the most expensive form of energy, represented 25.87% of all fuel used for heat and power. Residual fuel oil and diesel, which are used mainly in direct combustion processes, represent 26.85 and 26.55% of all energy use by industry, respectively. Scenarios for future energy use and CO₂ emissions are developed for the industrial sector in Lebanon. The development of the baseline scenario relied on available data on major plants' outputs, and on reported amounts of fuels used by the industrial sector as a whole. Energy use in industry and the corresponding greenhouse gas (GHG) emissions for Lebanon are projected in baseline scenarios that reflect technologies, activities and practices that are likely to evolve from the base year 1994 to year 2040. Mitigation work targets a 15% of CO₂ emissions from the baseline scenario by year 2005 and a 20–30% reduction of CO₂ emissions by year 2040. The mitigation options selected for analysis are screened on the basis of GHG emissions and expert judgement on the viability of their wide-scale implementation and economic benefits. Using macroeconomic assessment and energy price assumptions, the final estimates of potential GHG emissions and reduction costs of various mitigation scenarios are calculated. The results show that the use of efficient electric motors, efficient boilers and furnaces with fuel switching from fuel oil to natural gas has the largest impact on GHG emissions at a levelized annual cost that ranges from −20 to −5 US$/tonne of CO₂ reduced. The negative costs are indicative of direct savings obtained in energy cost for those mitigation options.     

CO2 emissions structure of Indian economy

This paper analyses carbon dioxide (CO₂) emissions of the Indian economy by producing sectors and due to household final consumption. The analysis is based on an Input–Output (IO) table and Social Accounting Matrix (SAM) for the year 2003–04 that distinguishes 25 sectors and 10 household classes. Total emissions of the Indian economy in 2003–04 are estimated to be 1217 million tons (MT) of CO₂, of which 57% is due to the use of coal and lignite. The per capita emissions turn out to be about 1.14 tons. The highest direct emissions are due to electricity sector followed by manufacturing, steel and road transportation. Final demands for construction and manufacturing sectors account for the highest emissions considering both direct and indirect emissions as the outputs from almost all the energy-intensive sectors go into the production process of these two sectors. In terms of life style differences across income classes, the urban top 10% accounts for emissions of 3416 kg per year while rural bottom 10% class accounts for only 141 kg per year. The CO₂ emission embodied in the consumption basket of top 10% of the population in urban India is one-sixth of the per capita emission generated in the US.     

Environmental metabolism of educational services. Case study of nursery schools in the city of Barcelona

The environmental analysis of public nursery schools is of great interest since they are crucial in the early education of children and are expected to show high environmental standards. This paper aims to analyse the environmental profile (energy, water and transport flows) of this sector. A sample of 12 public nursery schools belonging to the Scholar Agenda 21 (SA21) of the city of Barcelona were selected given their data quality (eight centres applied to all analysis) to determine their energy and water consumption, as well as the greenhouse gas emissions resulting from energy consumption and transport use. For each centre, energy and water consumption were obtained from bills and surveys were conducted to get data regarding the transport associated with the centre. Results show that, on average, a child consumes 966 kWh of energy (electricity and gas) and 12.9 m³ of potable water every year. Nursery schools with more energy-efficient devices hold lower energy consumption, a trend which could not be found in the case of water and water-efficient devices. Regarding transport, car usage was the flow with highest impact, since it accounts for 69 % of CO₂eq emissions, although only 19 % of the children commute by car.     

The contribution of direct energy use for livestock breeding to the greenhouse gases emissions of Cyprus

This paper presents a methodology for the estimation of the contribution of direct energy use to the greenhouse gases emissions of cattle, pig and poultry breeding in Cyprus. The energy consumption was estimated using the factors of 2034 MJ/cow, 2182 MJ/sow and 0.002797 MJ/bird. The greenhouse gases emissions for each animal species and energy source were estimated using emission factor of each greenhouse gas according to fuel type as proposed by the IPCC 2006 guidelines and for electricity according to national verified data from the Electricity Authority of Cyprus. Livestock breeding in Cyprus consumes electricity, diesel oil and LPG. The results obtained, show that the emissions from energy use in livestock breeding contribute 16% to the total agricultural energy emissions. Agricultural energy emissions contribute 0.7% to the total energy greenhouse gases (GHG) emissions. The three species of animal considered contribute 3% to their total livestock breeding emissions when compared with enteric fermentation and manure management, of which 2.6% is CO₂. These results agree with the findings in available literature. The contribution of direct energy use in the greenhouse gases emissions of livestock breeding could be further examined with the influence of anaerobic digestion to the emissions.     

Regional variations in spatial structure of nightlights,population density and fossil-fuel CO2 emissions

We evaluate the joint use of satellite-observed intensity of urban nightlights and census-based population density data as constraints on the spatial structure of CO₂ emissions from fossil fuels. Findings are: (1) the probability that population density exceeds a given value follows a power-law distribution over two orders of magnitude of population density, encompassing the 40% of the global population at the highest densities. (2) The corresponding probability distribution for nightlights intensity also follows a power-law, departing near instrumental saturation. (3) Assuming that the true nightlights intensity distribution follows the power-law above instrumental saturation, we obtain a correction for saturation errors in the nightlights data. The amplification of nightlights intensity required to correct for saturation errors is estimated to be a factor of 1.15–1.23 globally and much greater in regions with high nightlights intensities. (4) Correcting for saturation, we observe clear empirical relationships between nightlights intensity and areal densities of energy consumption, fossil-fuel emissions and economic activity, holding throughout the development spectrum. (5) We indicate how these relationships underpin a fossil-fuel data assimilation system (FFDAS) for estimating fossil-fuel CO₂ emissions.     

CO2 emissions,energy consumption and economic growth in China: A panel data analysis

This paper examines the causal relationships between carbon dioxide emissions, energy consumption and real economic output using panel cointegration and panel vector error correction modeling techniques based on the panel data for 28 provinces in China over the period 1995–2007. Our empirical results show that CO₂ emissions, energy consumption and economic growth have appeared to be cointegrated. Moreover, there exists bidirectional causality between CO₂ emissions and energy consumption, and also between energy consumption and economic growth. It has also been found that energy consumption and economic growth are the long-run causes for CO₂ emissions and CO₂ emissions and economic growth are the long-run causes for energy consumption. The results indicate that China's CO₂ emissions will not decrease in a long period of time and reducing CO₂ emissions may handicap China's economic growth to some degree. Some policy implications of the empirical results have finally been proposed.     

Sustainable cities – modelling urban energy supply and demand

A model of urban energy consumption has been developed using energy supply data and post-code information. The model simulates spatial and diurnal variations in energy demand, and also models the effect of energy-management measures and associated reductions in CO₂ emissions. A linear programming optimisation module is used to identify the most cost-effective measures to achieve specified CO₂ or energy reduction-targets. When combined with data from an associated attitudinal survey, the model can be used to assess the potential for CO₂ reduction in the urban environment.     

Implications of uncertainty on regional CO2 mitigation policies for the U.S. onroad sector based on a high-resolution emissions estimate

In this study we present onroad fossil fuel CO₂ emissions estimated by the Vulcan Project, an effort quantifying fossil fuel CO₂ emissions for the U.S. in high spatial and temporal resolution. This high-resolution data, aggregated at the state-level and classified in broad road and vehicle type categories, is compared to a commonly used national-average approach. We find that the use of national averages incurs state-level biases for road groupings that are almost twice as large as for vehicle groupings. The uncertainty for all groups exceeds the bias, and both quantities are positively correlated with total state emissions. States with the largest emissions totals are typically similar to one another in terms of emissions fraction distribution across road and vehicle groups, while smaller-emitting states have a wider range of variation in all groups. Uncertainties in reduction estimates as large as ±60% corresponding to ±0.2 MtC are found for a national-average emissions mitigation strategy focused on a 10% emissions reduction from a single vehicle class, such as passenger gas vehicles or heavy diesel trucks. Recommendations are made for reducing CO₂ emissions uncertainty by addressing its main drivers: VMT and fuel efficiency uncertainty.