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Population dynamics has been acknowledged as a key concern for projecting future emissions, partly because of the huge uncertainties related to human behaviour. However, the heterogeneous shifts of human behaviour in the process of demographic transition are not well explored when scrutinizing the impacts of population dynamics on carbon emissions. Here, we expand the existing population–economy–environment analytical structure to address the above limitations by representing the trend of demographic transitions to small-family and ageing society. We specifically accommodate for inter- and intra-life-stage variations in time allocation and consumption in the population rather than assuming a representative household, and take a less developed province, Sichuan, in China as the empirical context. Our results show that the demographic shift to small and ageing households will boost energy consumption and carbon emissions, driven by the joint variations in time-use and consumption patterns. Furthermore, biased pictures of changing emissions will emerge if the time effect is disregarded. Future demographic changes will impact on energy use and hence carbon emissions through time-use and consumption pattern shifts. Using representative national time-use data, Yu et al. model scenarios for demographic transitions in China to explore shifts in energy demand as households change in size and age.

The curtailment and storage associated with the fluctuation of electricity supplied by variable renewable energy (VRE) may limit its penetration into electricity systems. Therefore, these factors need to be explicitly treated in the integrated assessment models (IAMs). This study improves the representation of curtailment and storage of VRE in a computable general equilibrium (CGE) model. With the data generated from an hourly power sector model, curtailment and storage of VRE electricity are treated as a function of the shares of solar and wind in the electricity mix. This relationship is incorporated into a CGE model and we also updated the VRE costs and resource potential. The results show that with such improvement, by 2100, in a 450 ppm atmospheric CO 2 equivalent concentration (henceforth ppm) scenario, some electricity generated from VRE is either curtailed (2.1%) or needs to be stored (2.9%). In contrast, if VRE fluctuation is not considered, the long-term global economic cost of carbon mitigation is significantly underestimated (by 52%) in the same scenario. Conversely, updating the VRE costs and resource potential leads to a decrease in mitigation costs. Our simulation implies that the fluctuation of VRE cannot be ignored and needs to be incorporated into CGE models. Moreover, in addition to storage with batteries, many other options are available to reduce curtailment of VRE. The top-down type CGE model has limitations to fully incorporate all aspects due to its limited spatial, temporal, and technological resolution.

The Agriculture, forestry and other land use (AFOLU) sector as a whole accounts for more than 80% of the total greenhouse gas (GHG) emission in Nepal. This study estimates the GHG emissions from the AFOLU sector in the business as usual (BAU) case during 2010–2050 and identifies the economically attractive countermeasures to abate GHG emissions from the sector at different carbon prices. It also estimates the carbon price elasticity of GHG abatement from the sector. The study finds that enteric fermentation processes in the livestock and emissions from agricultural soils are the two major contributors of GHG emission in AFOLU sector. It identifies no-regret abatement options in the AFOLU sector that could mitigate about 41.5% of the total GHG emission during 2016–2050 in the BAU scenario. There would be a net cumulative carbon sequestration of 16 million tonnes of carbon dioxide equivalent (MtCO2e) at $10 per tonne of carbon dioxide equivalent (tCO2e) during the period. Carbon price above $75/tCO2e is not found to be much effective in achieving significant additional reduction in GHG emissions from the AFOLU sector.

The formulation of a policy for a low-carbon development plan is one of the most important steps to help Cambodia achieve sustainable development objectives, promote a greener development path, and contribute to the global effort to reducing CO 2 emissions. This study is designed to propose some low-carbon energy strategies and quantitatively to assess CO 2 emissions and reductions. The Extended Snapshot (ExSS) tool is used to quantify socioeconomic assumptions and to estimate CO 2 emissions and reduction potentials. The results show that CO 2 emissions are projected to increase to about 23,277 (by about 5.5 times) and 91,325 ktCO 2 /year (by about 21.6 times) in 2030BaU and 2050BaU, respectively, from 4,221 ktCO 2 /year in 2010. This study proposes five strategies for low-carbon development plan towards 2050 which are expected to reduce CO 2 emissions by about 12,826 (about 55%) and 52,153 ktCO 2 /year (about 57%) in 2030CM and 2050CM, respectively. The present results should help researchers and experts gain a better understanding of CO 2 emissions and reduction potentials by applying a number of low-carbon measures in Cambodia. While the results should be counted as a preliminary study because of limited available country information, they are expected to provide useful insights for the government in formulating a concrete climate change mitigation policy for the country.

This paper performs energy model hindcasting which compared the historical energy simulation results with the observations. We used one of the Integrated Assessment Models and simulated global historical energy consumption from 1981 to 2010 associated with exogenous socioeconomic assumptions, as is typically performed for future scenario. The simulation period was chosen with consideration of data availability and structural constancy of the model. Based on comparison with observations, there are three main findings. First, the global aggregated primary energy shows high reproducibility. In terms of energy source specific results, the fitness in electricity, coal, and biomass consumption were high. However, that of crude oil and natural gas is lower than others. This could be due to the price elasticity assumption, implying that the model can be improved with regard to this element. Second, the reproducibility increases as the simulation is close to the base year 2005. Third, although the global aggregated information shows high reproducibility, some disaggregated regions have lower reproducibility. Furthermore, high income countries tend to show higher reproducibility than in low income countries. Given the uncertainties in the ability of IAMs to reproduce certain aspects of the energy system, forecasts must be treated with caution.

We propose a new climate change mitigation assessment method focusing on agriculture, forestry, and land-use change sectors by coupling the computable general equilibrium (CGE) model with a bottom-up type technology model. The CGE model covers the entire economic market, but includes a rough description of mitigation measures, whereas the bottom-up type technology model takes into account abatement cost and mitigation effects of individual mitigation measures, but only focuses on a few sectors. The coupled framework enables us to connect relevant conditions and to complement the shortcomings of each model. As a test, we applied our method to Indonesia, which has set a national greenhouse gas emissions reduction target for 2020. A large proportion of Indonesia's greenhouse gas emissions are from the land-use sector. We assessed the differences in modeling behaviors between the CGE models with and without coupling the bottom-up type model. The two primary findings were: 1) consumption loss estimated by the coupled CGE (1.2%) was larger than the loss estimated by the uncoupled model (0.5%), because the emission reduction estimated by the bottom-up model was less than the standalone CGE's estimate; and 2) consumption loss caused by achieving the reduction target by 2020 in Indonesia strongly depends on the assumption of mitigation costs and available land area for the emission reduction measures.

The global waste sector produces, on average, 2–5 % of global anthropogenic greenhouse gas (GHG) emissions. The amount of GHG emissions has grown steadily and is predicted to increase considerable in the forthcoming decades because of the increases in population and gross domestic product (GDP). However, the GHG mitigation opportunities for the sector are still fully not exploited, in particularly in developing countries. A series of initiatives were highly successful and showed that large reductions in emissions are possible. This study aims to propose a holistic quantification model, which can be used for estimation of waste generation and evaluation of the potential reduction of GHG emissions in waste sector for developing countries with a particular application to Vietnam. The two scenarios set for the study were business as usual (BaU) which waste management is assumed to follow past and current trends and CounterMeasure (CM) which alternative waste treatment and management are assessed. Total emissions in the BaU scenario are projected to increase from 29.47 MtCO2eq in 2010 to 85.60 MtCO2eq by 2030 and 176.32 MtCO2eq by 2050. The highest emissions are due to methane (CH4) released by disposal sites, accounting for about 60 % of the GHG emissions from waste in Vietnam in 2030. This emission is projected to increase significantly (67 % in 2050), unless more of the methane is captured and used for energy generation. The CM scenario gives emission reductions from 25.7 % (2020), 40.5 % (2030) to 56.6 % (2050) compared to the BaU scenario. The highest GHG reduction is achieved through recycling, followed by methane recovery to optimize the co-benefit for climate change mitigation.

Energy is a commodity which impacts heavily upon the competitiveness of a country in the global scale. Thus, nations have begun to understand that utilization of energy affects its economic performance. In recent times, there has been a drive for global awareness on Low Carbon Society (LCS) measures, where carbon mitigation is at the forefront. Thus, this paper analyses the LCS measures for the Thai industrial sector. Thai industrial sector is the second highest CO 2 emitting end-use sector and contributes approximately 30% to the national income of Thailand. The total CO 2 emission from end use sectors in 2010 was 119 Mton-CO 2 and approximately 38% constituted industrial sector emissions. The primary objective of this research study is to quantitatively analyse the carbon mitigation possible in the Thai industrial sector and the co-benefits which accrue along with mitigation in various policy pathway scenarios. Thai industrial sector was modeled using Asia-Pacific Integrated Model (AIM)/Enduse. Three groups of scenarios under LCS, emission tax and reduction target principles were modeled along with the BAU case. Results show that LCS scenarios are capable of cumulative mitigation of approximately 35% by 2050 in comparison to the BAU case and the predominant technologies are the 2nd generation biomass and the CCS technology. The emission tax scenarios, where tax rates of 50, 100, 200 and 500 USD/t-CO 2 were enforced show a maximum of 55% cumulative mitigation by 2050. Even though this reduction is higher than the LCS scenarios, there is no shift to long term renewable or sustainable technologies in the emission tax scenarios. The same applies to reduction target scenarios as well. The co-benefits, which were measured along the themes of energy security and local air pollutant mitigation show maximum benefits accruing to the LCS scenarios, where renewable fuel share increases, whilst primary energy intensity and carbon intensity decreases. The LCS scenarios also show a mitigation of local air pollutants such as SO 2 and Particulate Matter.

This study quantified the effectiveness of emission trading by considering multiple technological constraints, burden sharing schemes, and climate stabilization targets. We used a global computable general equilibrium model, and evaluated the effectiveness of emission trading using welfare losses associated with climate mitigation for scenarios with and without emission trading, as measured by the Hicksian Equivalent Variation (HEV). We found that emission trading contributed to a reduction in the economic losses associated with climate mitigation for all technological assumptions, burden sharing schemes, and stabilization targets. The net global welfare losses in scenarios without emission trading ranged between 0.7% and 1.9%, whereas emission trading reduced the losses by 0.1% to 0.5%. The range depended on the assumptions in the burden sharing schemes, technological constraints, and stabilization targets. The percentage change in welfare gain from emission trading varied regionally, and was relatively high in low-income or middle-income countries (0.2% to 1.0% and − 0.1% to 1.2%, respectively) compared to high-income countries (− 0.1% to 0.3%). Some regions displayed negative values with regard to the effectiveness of emission trading, which might be due to the change in goods and service trades associated with emission trading. If the usage of carbon capture and storage was constrained, welfare loss became large and the effectiveness of emission trading ultimately increased. The use of a burden sharing scheme was a significant factor in changing the effectiveness of emission trading, and the per capita emission convergence in 2050 was more effective for emission trading than a per income convergence.

The increasing volumes of industrial solid wastes (ISW) generated have become a serious issue in Shanghai, China. Knowing the volume of ISW that is to be generated in the future is considered a prerequisite for an effective reduction policy and the successful design of treatment facilities. It has been verified that the prediction of ISW generation has an inherent relationship with industrial restructuring caused by economic growth. This study contributes its efforts to develop a systematic approach involving a regional input–output analysis for the forecasting of ISW generation, taking into account the probable industrial restructuring developments. In the process, changes in the consumption patterns, export structure, and technical change are considered to be the important drivers. Further, a sensitivity analysis is carried out as well to investigate the influence of change in consumption on ISW generation. The case study of Shanghai provides for a feasible application of our model on a regional level until the year 2020.

A global computable general equilibrium (CGE) model integrating detailed energy end-use technologies is developed in this paper. The paper (1) presents how energy end-use technologies are treated within the model and (2) analyzes the characteristics of the model’s behavior. Energy service demand and end-use technologies are explicitly considered, and the share of technologies is determined by a discrete probabilistic function, namely a Logit function, to meet the energy service demand. Coupling with detailed technology information enables the CGE model to have more realistic representation in the energy consumption. The proposed model in this paper is compared with the aggregated traditional model under the same assumptions in scenarios with and without mitigation roughly consistent with the two degree climate mitigation target. Although the results of aggregated energy supply and greenhouse gas emissions are similar, there are three main differences between the aggregated and the detailed technologies models. First, GDP losses in mitigation scenarios are lower in the detailed technology model (2.8% in 2050) as compared with the aggregated model (3.2%). Second, price elasticity and autonomous energy efficiency improvement are heterogeneous across regions and sectors in the detailed technology model, whereas the traditional aggregated model generally utilizes a single value for each of these variables. Third, the magnitude of emissions reduction and factors (energy intensity and carbon factor reduction) related to climate mitigation also varies among sectors in the detailed technology model. The household sector in the detailed technology model has a relatively higher reduction for both energy intensity and the carbon factor.

During 1990–2010, the power generation sector has been the highest energy consuming and CO2 emitting sector while the residential and building sectors have been the largest electricity consuming sector, accounted for about 57.1% of overall electricity consumption in Thailand. This study employed AIM/Enduse model to investigate the CO2 reduction measures which are related to the marginal abatement cost (MAC) in the long term planning. Seven mitigation measures by replacing existing energy devices with more efficient ones based on the data currently available on the market are implemented: (1) efficient lighting devices, (2) efficient cooling devices, (3) efficient heating devices, (4) efficient other electrical devices, (5) efficient cooking devices, (6) Insulated houses, and (7) building codes. Results indicate that in the business-as-usual (BAU) scenario between 2010 and 2050, the energy demand and CO2 emissions would increase to 39,140 ktoe and 52,047 kt-CO2, respectively. By adopting these policy strategies, energy demand can be reduced by about 42.7% of total energy demand in 2050 while CO2 emissions can be mitigated by 35.0% of overall CO2 emissions in 2050. The efficient cooling devices will contribute to the largest CO2 reduction in 2050 with low MAC when compared to other measures.

In Bangladesh, 53 % of domestic greenhouse gas (GHG) emissions were generated in the agriculture and other land use sectors in 2005. However, no specified measures for climate change mitigation have thus far been designated nationally in these sectors. In this paper, we quantified future greenhouse gas emissions and mitigation potentials through 2025 by using the Agriculture Forestry and Other Land Use Bottom-up model to clarify cost-effective technological options under different mitigation cost scenarios. We found that (1) GHG emissions of 69.1 MtCO2eq (Million tons of carbon dioxide (CO2) equilivalent)/year will be generated from the agriculture and land use sectors in 2025 in a baseline scenario, (2) a reduction of 32 MtCO2-eq/year (a 47 % reduction from baseline emissions) is possible at a cost of as much as US$10/tCO2-eq in 2025, (3) in agriculture, an emissions reduction of 10 MtCO2-eq/year could be achieved by implementing midseason drainage in rice cultivation, generating bioenergy from livestock manure, and replacing roughage with concentrated feed at mitigation cost of US$10/tCO2-eq in 2025, and (4) in the other land use sector, a mean annual mitigation potential of 6.5 MtCO2-eq/year can be achieved with a total mitigation cost of less than US$10 million (52 % of baseline land use emissions in 2025).

Recently, Low Carbon Society (LCS) principle has emerged as a practicable campaign for both developing and developed countries to deal with the dramatic increment of greenhouse gas concentration in the atmosphere. Various key features of LCS entail reducing energy demand and consumption while avoiding the fossil fuel utilization which is a major contributor to substantial CO 2 emissions. In this study, Thailand's power sector is modeled using Asia-Pacific Integrated Model (AIM/Enduse). The objective of this study is to model the Thai power sector such that the viability of clean generating technologies for Thailand is considered and their mitigating effects are analyzed. The results demonstrate that the fossil fuel based technology would be replaced by clean technologies including, coal-fired power plant with CCS technology and renewable energies in the LCS scenario. The LCS scenario can mitigate CO 2 emissions by 58,098 ktCO 2 in 2050 when compared to BAU scenario.

GHG emission reduction targets for 230 countries/regions in the world are estimated under the overall target of a 50% global reduction by 2050 compared with 1990. Three burden-sharing schemes, Emission per capita (pCAP), Emission per GDP (pGDP), and Cumulative emission per capita (pCUM), are taken into account. Future GDP in the 230 countries/regions is projected under two future scenarios, the advanced society scenario (ADV) and conventional society scenario (CNV). Differences in reduction targets between GHG total and GHG excluding LU, different target years, and the required speed of improvement of GHG/GDP are also investigated. The global GDP growth rate for 2010–2050 is 3.39% under the ADV scenario and 2.23% under the CNV scenario. Under the ADV scenario, the ratio of GDP per capita of Annex I countries to that of non-Annex I countries converges to 3.4 in 2050 from 13.0 in 2005. The reduction targets for pCAP, pGDP, and pCUM in 2050 are respectively 83%, 58%, and 95% for Annex I, and 42%, 57%, and 34% for non-Annex I. In the case of pGDP, Annex I has a high reduction target under the ADV scenario, while non-Annex I has a high reduction target under the CNV scenario.

Long-term analysis of tropospheric nitrogen dioxide (NO2) columns retrieved from GOME, SCIAMACHY, OMI and GOME-2 satellites, carbon monoxide (CO) columns from MOPITT satellite, and aerosol optical depths (AODs) from MODIS satellite was performed for Southeast Asian countries including Japan and China during 1996–2012. The results show that significant increasing levels of tropospheric NO2 columns can be clearly observed during the study period, especially above the eastern regions of China. The cities located in different latitude zones present the seasonal cycle of NO2 columns, CO columns, and AODs differently. For the cities located around mid-latitude zone, the maximum levels of NO2 and CO columns can be observed in the winter (November–March) and the minimum in the summer (June–September). On the contrary, the maximum levels for the cities near Equator zone are revealed in dry season (June–October). In the case of AODs, the maximum peaks normally occur during biomass burning season. Ground monitoring concentrations of NO2, CO, and PM10 were also comparably analyzed with satellite NO2 columns, CO columns, and AODs, respectively. Anthropogenic and biomass burning emissions were derived to investigate the consistency with satellite retrievals. The results show that satellite observations are able to capture the trend and seasonal variability of the emissions and ground concentrations. The model simulations were conducted using CMAQ model. Generally, simulated model results agree well with those retrieved from satellite measurements for spatial distribution and seasonal pattern. However, the modeled results underestimate satellite data probably due to the inaccuracy in emission inventories, the inaccuracy of spatial and temporal allocations, and the uncertainties in the satellite retrievals.

We quantitatively evaluated mitigation potentials of greenhouse gas emissions from agriculture and land use sectors in Indonesia. We also determined for the land use sector 1) how much time is needed to plan the mitigation strategy, and 2) how much time is needed to evaluate the effectiveness of mitigation measures? We used a bottom-up type model on emission mitigation named Agriculture Forestry and Other Land Use Bottom-up model (AFOLU-B model) to consider a characteristics time sequence of actions, effects and costs of mitigation countermeasures. To input to the model, we developed future scenarios on human activities in these sectors based on data from Indonesian government. We found that i) evaluation on effects and costs of mitigation measures from a long-term viewpoint and their continuing implementation are required to increase future mitigation potentials under a limited budget. ii) a long-term reduction target will also play an important role for cost-effective countermeasure selection. iii) reforestation of slow glowing species and enhanced natural regeneration will cause great increase in mitigation potential in the country.

Sustainability policies that have quantitative emission or carbon footprint measurements are important in view of climate change and current rapid urbanization in developing countries like Malaysia. Although sustainability policies are mentioned in national development plan as early as in the 1990s, many of these policies are piecemeal and expressed qualitatively. In achieving environmental sustainability, planning of city or a region can be more functional and implementable by using low carbon city concept. Planning a low carbon city uses sustainable development principles; this demonstrates a high level of energy efficiency using low carbon energy sources and production technologies. It also adopts patterns of consumption and behavior that are consistent with low levels of greenhouse gas emissions in the urban areas. The planning of the fast developing region of Iskandar Malaysia, which is located in southern part of Peninsular Malaysia, provides a good opportunity for urban managers to incorporate the ideas of low carbon cities in this proposed high growth urban conurbation. This paper aims to explore implementation of the concept and vision of low carbon scenarios and examine the strategies toward the reduction of CO2 emission. This study also prepares a quantitative scenario study on the establishment of low carbon urban development in Iskandar Malaysia.

This study aims to estimate greenhouse gas (GHG) emissions and mitigation potentials in Agriculture, Forestry and Other Land Use (AFOLU) in the Southeast Asian countries: Indonesia, Malaysia and Vietnam, up to 2030. We developed a bottom-up type model named the AFOLUB Model, which calculates GHG mitigations based on the detailed information of specific technologies. The model illustrates producer's behaviour of agricultural production and mitigation technology selection as a result of profit maximization. Using this model, we evaluated mitigations and effective technologies with high mitigation potentials in the sectors. As a result, GHG emissions in agriculture and Land Use, Land-Use Change and Forestry (LULUCF) in the three countries were 149 MtCO2eq/year and 1.0 GtCO2eq/year in 2005 and will increase 1.7 and 1.8 times up to 2030 in the BaU case. Indonesia is the largest emission country among them. We also found that no-regret mitigation technologies are expected to reduce 33MtCO2eq/year in 2030, which...

Agriculture, Forestry and Other Land Use (AFOLU) sectors account for 53 % of the domestic greenhouse gas emissions (GHG) in Vietnam in 2000. However, due to political focus on adaptation, Vietnamese government has not formulated particular policy on mitigation in the sectors. This study aims to identify and assess mitigation potential in AFOLU sectors in Vietnam up to 2030 using AFOLU Bottom-up model. Therefore, the results can help government towards building mitigation strategies in the country. The methodology involves: (1) development of future assumptions of crops harvested areas, livestock population and area of land use and land use change and (2) identification of mitigation countermeasures with high potential and assessment of their cost-effectiveness. In 2030, 11 MtCO2eq/year of emission can be reduced by no-regret countermeasures which take zero or negative cost. In the case of full application of countermeasures, 48 MtCO2eq/year can be reduced compared to the baseline emission level. Mitigation countermeasures, which have great contribution for GHG reduction in Vietnam, are midseason drainage in rice paddy (7 MtCO2eq/year), off-season incorporation of rice straw (3 MtCO2eq/year) and conservation of existing protection forests (17 MtCO2eq/year). Based on our findings, a package of mitigation countermeasures at 10 USD/tCO2eq is expected to have the most economic efficiency and high mitigation for GHG mitigation in AFOLU sectors in Vietnam.

This paper presents the possibility for Thailand to become a low-carbon society (LCS). The methodology involves development of current CO 2 emission inventory, and quantification of socio-economic activity level in 2030. In this study, the increase of CO 2 emissions is estimated based on i) 2030 BAU (business-as-usual) without mitigation measures, and ii) 2030 CM (climate change mitigation measures) assumptions of employed demand-side technologies as well as the potential to reduce the CO 2 emissions by low-carbon measures available during 2005–2030. In this study, only selected climate change mitigation options, which have been found to be cost effective, are included in the 2030 CM scenario. Several comprehensive demand-side measures such as diffusion of low-carbon technologies in the residential sector, energy efficient buildings, energy efficient industry and fuel switching, and fuel substitution in the transport sector are proposed. Results show that i) the annual CO 2 emissions in the base year of 2005 are 185,983 kilo-ton (kt) of CO 2 , ii) under the scenario without climate change mitigation measures (the BAU scenario), year 2030 CO 2 emissions would increase to 563,730 kt-CO 2 or 3.03 times that of the base year 2005, and iii) by adopting the selected climate change mitigation measures, CO 2 emissions can be decreased approximately 28.4% compared to the 2030 BAU scenario, i.e. to 403,642 kt-CO 2 . The research findings hope to contribute to sustainable energy and environmental transition of Thailand, one of the fastest growing economies in Southeast Asia, towards a Thai low carbon society.

Most household fuels used in Asian countries are solid fuels such as coal and biomass (firewood, crop residue and animal dung). The particulate matter (PM), CO, NOx and SOx produced through the combustion of these fuels inside the residence for cooking and heating has an adverse impact on people's health. PM 2.5 in particular, consisting of particles with an aerodynamic diameter of 2.5 μm or less, penetrates deep into the lungs and causes respiratory system and circulatory system diseases and so on. As a result, the World Health Organization (WHO) established guideline values for this type of particulate matter in 2005. In this study, the authors focused on PM 2.5 and estimated indoor exposure concentrations for PM 2.5 in 15 Asian countries. For each environment used for cooking, eating, heating and illumination in which people are present temporarily (microenvironment), exposure concentrations were estimated for individual cohorts categorized according to sex, age and occupation status. To establish the residence time in each microenvironment for each of the cohorts, data from time use surveys conducted in individual countries were used. China had the highest estimate for average exposure concentration in microenvironment used for cooking at 427.5 μg/m3, followed by Nepal, Laos and India at 285.2 μg/m3, 266.3 μg/m3 and 205.7 μg/m3, respectively. The study found that, in each country, the PM2.5 exposure concentration was highest for children and unemployed women between the ages of 35 and 64. The study also found that the exposure concentration for individual cohorts in each country was greatly affected by people's use of time indoors. Because differences in individual daily life activities were reflected in the use of time and linked to an assessment of exposure to indoor air-polluting substances, the study enabled detailed assessment of the impact of exposure.

In order to realize a low-carbon society (LCS), it is necessary to formulate a comprehensive policy consisting of a large number of “options” (i.e., policies as well as technical and behavioral measures). Based on the concept of backcasting, this paper proposes a methodology and a model, called the backcasting model (BCM), that organizes a system of various LCS options and projects their detailed schedule toward a given target year. The methodology and model mainly focus on describing a complex system of LCS options and the consistency of their schedule. Other aspects such as the costs of LCS measures, stock dynamics of technologies, and effects of economic instruments are not explicitly considered. To permit quantitative treatment of various types of options, they are classified into several categories. The BCM calculates the schedule of the options under given quantitative information on the options and relationships between them. The methodology and model were applied to Kyoto City as an example. First, a quantitative snapshot of socioeconomic status and greenhouse gas (GHG) emissions was described. In the snapshot, a 45% reduction of GHG emissions compared with 1990 was achieved with moderate economic growth. The BCM was applied to about 130 options shown in an action plan of the Kyoto Municipal Government, and a schedule of the options was calculated. This methodology treats wide-ranging and complex low-carbon options in a quantitative and consistent manner and supports the policymaking process toward the realization of a low-carbon society.

China made a commitment in Copenhagen to reduce its carbon dioxide emissions per unit of GDP from 40% to 45% compared with the 2005 level by 2020, and is determined to vigorously develop non-fossil fuels. This study analyzes the effects and impacts of policies that could help to achieve China's Copenhagen commitments with a hybrid static CGE model in which the electricity sector is disaggregated into 12 generation technologies. Four scenarios are developed, including the reference scenario A, the reference scenario B and two carbon constraint scenarios. The results show that carbon intensity in terms of GDP will fall by 30.97% between 2005 and 2020 in the reference scenario A, and will be reduced further by 7.97% if China's targeted non-fossil energy development plans can be achieved in the reference scenario B. However, the rest of the 40–45% target must be realized by other measures such as carbon constraint. It is also observed that due to carbon intensity constraints, GDP loss would be from 0.032% to 0.24% compared to the reference scenario B, and CO2 emission reductions are due mainly to decreases in coal consumption in the electricity sector and manufacturing sector.

The energy balances published by the International Energy Agency (IEA) are one of the most valuable sources of energy statistics covering world energy supply and demand. However, some issues arise when these data are analyzed or used directly. Even when industrial energy consumption alone is examined, at least three types of issues are encountered: missing data, large amounts of misallocated data in some countries, and numerous unrealistic outliers in the time-series variations. When we deal with only a few regions, we can look at data one by one and modify them. In this case, we are going to overcome these issues with a systematic method because the data covers world including more than a hundred regions. This paper proposes a data reconciliation method to treat these issues, and describes its application to world industrial energy consumption. As a result of its application, we found that the three issues mentioned above seemed to be overcome. The degree of the reconciliation by region showed that OECD countries' degree tends to be smaller than those of non-OECD countries. However, not all of the OECD countries have low values and some countries, such as the United States, have high values.

In this study, we simulate global CO2 emissions and their reduction potentials in the industrial sector up to the year 2030. Future industrial CO2 emissions depend on changes in both technology and industrial activity. However, earlier bottom-up analyses mainly focused on technology change. In this study, we estimate changes in both technology and industrial activity. We developed a three-part simulation system. The first part is a macro economic model that simulates macro economic indicators, such as GDP and value added by sector. The second part consists of industrial production models that simulate future steel and cement production. The third part is a bottom-up type technology model that estimates future CO2 emissions. Assuming no changes in technology since 2005, we estimate that global CO2 emissions in 2030 increase by 15 GtCO2 from 2005 level. This increase is due to growth in industrial production. Introducing technological reduction options within 100 US$/tCO2 provides a reduction potential of 5.3 GtCO2 compared to the case of no technology changes. As a result, even with large technological reduction potential, global industrial CO2 emissions in 2030 are estimated to be higher as compared to 2005 level because of growth of industrial production.

This survey proposed a new methodology - iGAEZ (improved GAEZ), developed based on the GAEZ (Global Agro-Ecological Zones) model, capable of simulating crop yields on a global scale for wheat, potato, cassava, soybean, rice, sweet potato, maize, green beans. iGAEZ determines the optimum criteria of crop parameter of growth cycles to ensure best realistic crop yield combinations under comprehensive consideration of climate and crop condition. Global-scale crop yields were calculated using iGAEZ model for the period of 1990-1999. Through comparing simulated yields and FAO statistics, iGAEZ has demonstrated a very good ability to reproduce realistic crop yields on a global scale. We also predicted the impact of global warming on crop yields from the 1990s to 2090s by projecting five GCM outputs for AR4 under SRES A1B scenarios. According to the result, temperature rise will make many cultivated areas (eastern part of USA, India, eastern China, Africa) less productive. On the other hand, the regions with cold weather under current climate condition (Canada, northern Europe, northeastern China) become suitable for crop productivity under future climate scenario. Copyright © 2011 John Wiley & Sons, Ltd.

The unsustainable consumption pattern is argued as a driving factor of the environmental loads; however, hardly any relevant quantitative results are available. Quantifying the consumer behavior is particularly required for facilitating the contemporary unsustainable consumption pattern. This paper aims at developing two types of the consumer behavior model, comprising of the linear expenditure system (LES) model and the multinomial logit (MNL) model, to analyze the individual’s consumption expenditure hierarchically in light of the changes in lifestyle. The models are validated for the case of Taiwan where the economy is growing rapidly and making dents on every phase of life. Analysis results present the structure of an individual’s consumption preferences during the study period. Mainly, the individual’s consumption expenditures on “food” and “housing” occupy the most portions in his/her subsistence level while the individual spends more on “housing,” “medicines & medical care” and “amusement & education” in his/her non-subsistence level. In addition, the consumer behavior model is coupled with the municipal solid waste (MSW) discard model, which was established in the authors’ earlier study, to consecutively estimate an individual’s consumption expenditure and the amount of his/her MSW discards by waste fraction. By using the coupled model, a more sustainable consumption pattern and lifestyle can be proposed, and the corresponding MSW management system can be planned so as to develop the sustainable lifestyle and a low-waste-discard society.

On May 2008, Kyoto city government set up a low-carbon target of a 50% GHG reduction by 2030 compared to the 1990 level. To contribute to these discussions, we developed a local (city-scale) low-carbon scenario creation method. An estimation model was developed to show a quantitative and consistent future snapshot. The model can explicitly treat the uncertainty of future socio-economic situations, which originate from the openness of local economy. The method was applied to Kyoto city, and countermeasures to achieve the low-carbon target were identified. Without countermeasures, emissions would increase 12% from 2000. Among the measures, the reduction potential of energy efficiency improvements to residential and commercial sectors was found to be relatively large (15% and 18% of total reductions, respectively). The reduction potential of the passenger transport sector, in which the city government's policy is especially important, was 17% of the total amount. A sensitivity analysis showed that a 10% increase in exports leads to an 8.5% increase in CO 2 emissions, and a 20% increase in the share of the commuters from outside the city leads to a 3.5% decrease of CO 2 emissions because of the smaller number of residents in the city.

Agricultural activities account for almost 50 and 60% of the total anthropogenic CH4 and N2O emissions, respectively in 2005 (IPCC. 2007. Climate change 2007. Mitigation of climate change, Working Group III contribution to the fourth assessment report of the intergovermental panel on climate change summary for policymakers and technical summary). Thus, we developed an integrated model to estimate global CH4 and N2O emissions and reduction potentials related to agricultural production from 2000 to 2030. In this model, the amounts of implemented countermeasures for greenhouse gas mitigation are calculated as an optimal problem to minimize the total reduction costs under several marginal abatement costs. As a result, we determined the most cost-effective countermeasures, regions and emission sources with high reduction potentials in 2030. Global CH4 and N2O emission in agricultural activities was 4.0 GtCO2 eq/year in 2000 and will increase to approximately 40% (up to 5.6 GtCO2 eq/year) by 2030. Moreover, in ...

This paper presents a quantitative methodology and an empirical case study in Taiwan on modelling municipal solid waste (MSW) discards based on the consumption and MSW policy effects through a simultaneous equation system (SES) model. The results indicate that per capita consumption expenditures on ‘food’, ‘household appliances’ and ‘amusement & education’ are associated with the changes of the discards of most of the waste streams in Taiwan from 1992 to 2004. The developed model, meanwhile, identifies the effects of several important MSW policy measures. With regard to the model implication, consumers could try to reduce their unnecessary consumption, producers may rethink their responsibility on reducing MSW discards, and municipalities could evaluate the effectiveness of the existing policy measures to improve it upon based on the quantitative analysis. The backcasts and estimates of the discards of MSW streams could enable the planning, designing and executing of MSW system. The findings of this study would facilitate the consumer behaviour and support the policy design towards a low-waste-discard society.

We assessed the impact of climate change on rice production in Asia in comprehensive consideration of the process/parameter uncertainty in general circulation models (GCMs). After inputting future climate scenarios based on the projections of GCMs for three Special Report on Emissions Scenarios (SRES) (18 GCMs for A1B, 14 GCMs for A2, and 17 GCMs for B1) into a crop model, we calculated the average change in production (ACP), the standard deviation of the change in production (SDCP), and the probability of a production decrease (PPD) for each SRES scenario, taking into account the effect of CO2 fertilization. In the 2020s, PPD values were high for all SRES scenarios because the negative impacts of climate change were larger than the positive effects of CO2 fertilization in almost all climate scenarios in the near future. This suggests that it will be necessary to take immediate adaptive actions, regardless of the emission scenario, in the near future. In the 2080s, there were large differences in ACP, SDCP, and PPD among the SRES scenarios. The scenario with the highest atmospheric CO2 concentration, A2, showed a notable decrease in production and a high PPD in the 2080s compared with the other scenarios, despite having the largest CO2 fertilization effect. In addition, A2 had the largest SDCP among the SRES scenarios. On the other hand, the scenario with the lowest atmospheric CO2 concentration, B1, showed a small decrease in production, and a much smaller SDCP and a much lower PPD, than in the case of A2. These results for the 2080s suggest that a reduction in CO2 emissions in the long term has great potential not only to mitigate decreases in rice production, but also to reduce the uncertainty in these changes.

Industrialization and urbanization result in significant changes in lifestyle. These lifestyle changes seem to lead to unsustainable consumption patterns and increase the generation of various kinds of environmental loads, especially the amount of municipal solid waste (MSW). Taiwan is a small island with scarce natural resources. The economic development in Taiwan has resulted in the generation of large amounts of MSW. As a result, the Taiwan Environmental Pollution Administration (TEPA) has produced regulations for waste minimization and has imposed several important policy measures that have successfully reduced the MSW discard rate in recent years and have established a public recycling network as a part of the MSW collection. Nowadays, the objective of the MSW policies in Taiwan is to develop a “zero-waste society.” This article aims to review the MSW management progress in Taiwan and to project future MSW discards up to 2011 based on the national plan and assumed scenarios for socioeconomic variables. According to the analysis results, a more sustainable consumption pattern can be proposed and the corresponding MSW management system can be planned so as to develop a low-waste-discard society.

This study analyzes the role of energy intensity improvement in the short term (to the year 2020) and midterm (to the year 2050) in the context of long-term greenhouse gases (GHG) stabilization scenarios. The data come from the latest Emissions Scenarios Database and were reviewed in the Fourth Assessment Report (AR4) by the Intergovernmental Panel on Climate Change. In this study, quantitative decomposition analyses using the extended Kaya identity are applied to the stabilization scenarios in Categories I to IV of Table SPM.5 in the AR4. Furthermore, quantitative decomposition analyses of Category IV scenarios are conducted for major GHG-emitting countries, such as the USA, Western Europe, China, and India, by utilizing the large number of reports in the database. This study provides in-depth analyses of the relationship between energy intensity improvement and other major indicators. One finding is that energy intensity improvement plays an important role in the short term, and the rate of energy intensity improvement is assumed to be around 2% per year as a median value across Categories I–III in the midterm on the global scale. However, achieving stringent stabilization levels requires various other measures regarding the use of less-carbon intensive fossil fuels, the shift to non-fossil fuel energies, and advanced technologies such as carbon capture and storage.

Highly accurate global polygonal drainage basin data (PDBD) was developed in this research. The PDBD was derived from digital elevation models (DEMs) at high-resolution (about 100 m–1 km) by automatic and non-automatic methods to suppress DEM errors which derive wrong PDBD. The automatic methods are ‘stream burning’ and ‘ridge fencing’, while the non-automatic method is one which manually corrects DEM errors (‘manual correction’). For the derivation of the PDBD, we collected and used geographic basin and river data published from governments, institutes, publishers, and water-related programs. The PDBD derived from the DEMs at high-resolution can represent the boundaries of the basins in detail, and precise geographic and topographic information can be thus derived. These features are helpful for regional and global analysis, assessment, and management with hydrological models in water-related studies. To assess the accuracy of the derived PDBD, we conducted two types of comparisons. Firstly, we geographically compared the derived PDBD with the collected basin data. The derived PDBD showed good geographic agreement with the collected basin data, and the geographic agreement of the derived PDBD was better than that of HYDRO1k. Secondly, we compared upstream areas and discharges based on the derived PDBD with the observed upstream areas and discharges. The upstream areas and discharges based on the derived PDBD showed good agreement with the observed upstream areas and discharges, and the agreement of the derived PDBD was better than that of HYDRO1k. These comparisons reveal that the derived PDBD are highly accurate and reliable. The derived PDBD are thus thought to offer the best information on the surface drainage of the earth. Copyright © 2008 John Wiley & Sons, Ltd.

This paper considers three questions concerning a low-carbon society. The first is the implication of a 50% reduction in greenhouse gases (GHGs) by 2050. In the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report, released in 2007 (IPCC 2007b; http://www.gtp89.dial.pipex.com/chpt.htm), the suggested limit of increase in average worldwide temperatures is 2–3°C above the current level, but is this consistent with a 50% reduction by 2050? Second, when a 50% reduction in global emissions is envisioned, what is the level of reduction needed in Japan? Should the 50% reduction be uniform for advanced industrial countries and developing countries, or differentiated based on a country’s emissions? Third, how feasible are emission reduction targets in Japan? Even if the emission reduction target set for each country takes into account climate change impact and equity, whether the target is technically, or socially and economically, acceptable is another matter.

本研究は各種統計値に合致する貨幣・物質勘定表を推計, 調整する構築手法を提案し, それを適用し化石燃料由来のエネルギー消費量, CO2排出量を推計する. 推計には様々な経済統計, エネルギー統計を統合的に用いた. 本研究の推計値と既存の統計値を比較すると, 世界全体の化石燃料エネルギー消費量, あるいはエネルギー消費量の大きな国の国内エネルギー消費量は近い値を示した. 一方, 一部の特定の国では既存の統計値と本研究の値は大きく異なる値を示した. 既存の統計値からエネルギー消費量が修正された主たる要因は, 本研究において複数のエネルギー統計を用いたこと, 経済情報によるエネルギーフローの補完・修正を行ったことであった. また, エネルギー財の価格を既存の統計と比較すると世界の平均から異常に離れているような価格が修正された.

We simulate CO2 emissions from global iron and steel sector until 2050 in the case of no political intervention. In this study, we project future economic activity level of each country/region by macro economic model. And we estimate production of all country/region simultaneously by international trade model which considers domestic and international market equilibrium. And we simulate CO2 emissions by technology bottom-up type model. As a result, global steel production is projected to be 2324 Mt in 2050. And CO2 emissions are projected to be 3717 MtCO2 in 2050 which is an increase by 2044MtCO2 from year 2000. In that case, CO2 reduction from technology fixed case, which means reduction by technologies change, is estimated to be 1360MtCO2. It is also shown emission growth in China and India during 2000-2050 accounts for 75% of world emission growth in the same period.

気候変動の緩和のために, 地方自治体が低炭素社会を実現するための長期シナリオが必要とされ策定され始めている. しかし地方自治体の社会・経済構造は国と比べて開放的であり, より大きな不確実性・不安定性を伴う. 本研究では地域経済の開放性を考慮した低炭素社会シナリオの構築手法を開発した. またその中で将来像を定量的に描写, 温室効果ガス排出量・削減量を評価する定量推計ツールを開発した. この手法を2030年の京都市へ適用し, 1.3%/年程度の経済成長のもとで化石燃料起源の二酸化炭素排出量を1990年比50%削減するための対策を同定した. 削減量の中では家庭部門と業務部門のエネルギー効率改善が大きな割合を占める (それぞれ約15%, 18%) ことが示された. 感度分析を行い, 移輸出額の想定の±0%の増減が二酸化炭素排出量に±8.5%の影響を与えることを示した.

全世界のCH4・N2O排出量のうち農畜産業が占める割合はそれぞれ50%, 60%に達する (2005年時点). 本研究では農畜産生産量に関する将計モデル及びそれに伴う温室効果ガス削減ポテンシャル推計モデルを開発し, 世界23地域を対象に2000-2030年において食料生産が今後どのように変化するかを推計し, 食料生産に由来するGHG排出量および削減ポテンシャルの定量的な評価を行った. 2000年の排出量は3959MtCO2eqで, 家畜反芻が高い寄与率を示した. 地域別では, 中国, インド, アメリカで高い排出量となった. 2030年の最大削減ポテンシャルは1403MtCO2eqとなり, 2000年比で約35%削減でき, 最も経済効果が大きい対策は, 「家畜糞尿の散布」であることが示された.

In this study, we developed an integrated model to provide a long-term perspective and a quantitative basis for analyzing the GHG emissions in agriculture for 23 world regions. The main objective is to quantify the relative importance of major emissions resources. In the result, world total meat production will increase by 1.9 times from 2000 to 2030 with population growth and a gradual shift from the main staples to meat products, particularly in the developing counties. The factor analysis showed GHG emissions increases mainly depending on growth of population, food production per capita and fertilizer consumption.

To tackle global climate stabilization concretely, we have developed a method formulating long-term scenarios towards a low-carbon economy at local level. As a result of the pioneering application of this method to Shiga Prefecture, we have found the following: (i) it is possible to design scenarios for moving towards a low-carbon economy in which CO 2 emission is lowered by 30–50% from the 1990 level by 2030, while the prefecture's gross production continues to grow by 1.6% annually; (ii) in order to halve the emission by 2030, socio-economic structural changes as well as technological measures are essential; and (iii) innovative measures at the prefectural level, such as land planning, renewable energy promotion and lifestyle change, play an increasingly important role as the target reduction rate gets higher.

Japan should undertake drastic greenhouse gas (GHG) emission reductions by the middle of this century in order to mitigate climate change problems. Municipalities should design and execute scenarios toward a low-carbon society suited to their respective regions. This study describes long-term future visions developed for Shiga Prefecture targeting CO2 emission reductions of 30–50% by 2030, and presents scenarios to attain these targets, which are achievable with mild economic growth. For targets over a 30% reduction, region-specific measures including land-use reform and citizen behavioral changes are necessary. Compared with other regions in Japan, Shiga should give priority to a modal shift in transport, efficiency improvements in industry, and photovoltaic energy generation.

本研究の目的は, 都市旅客交通からのCO, NOx, PM, CO2排出を対象に, 環境負荷量と都市構造との関連に関する都市横断的知見を得ることである. まず, 世界の都市において環境負荷量が異なる要因を解析した. 結果, すべての物質について, 交通量が環境負荷量の都市間差異を最も説明することが示された. 続いて, 交通需要量を人口密度, 都市面積等の変数を用いて説明する交通需要モデルを構築した. 交通需要モデルおよび排出係数モデルを用いた感度分析の結果, 人口密度を20%増加させた場合, 面積あたりNOx排出量は6.2%～25.8%増加し, 一人あたりCO2排出量は3.1%～11.3%減少することが示された. 一人あたりCO2排出量減少率は, 乗用車トリップ分担率が60%程度の都市で大きいことが示された.

地球温暖化による気温と降水の変化に対して, 世界各国の水資源量がどのように応答するかを表す全球水資源影響関数を作成した. まず詳細な全球水文モデルを利用し, 現在気候から気温を-5℃から15℃ まで, 降水量を-75%から+200%まで変化させた252通りのシミュレーションを行い, 各国の水資源量の応答をデータベース化した. 利用時にはこのデータベースを参照するだけなので計算機負荷が小さく, 操作の度に気候条件が変化する温暖化政策支援モデルへの搭載に向いている1このモデルから得られる国別の水資源量は元の詳細モデルから得られるものと約±20%の誤差範囲で一致し, 十分な代替性を示した.