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Between 60% and 80% of global energy is consumed in urban areas and given the projected increase in world׳s urban population, this share is expected to further increase in the future. Continuity of energy supply in cities is affected by climate change and a growing array of other threats such as cyber attacks, terrorism, technical deficiencies, and market volatility. Determined efforts, acknowledging the interactions and interlinkages between energy and other sectors, are needed to avoid adverse consequences of disruption in energy supply. Resilience thinking is an approach to management of socio-ecological systems that aims to develop an integrated framework for bringing together the (often) fragmented, diverse research on disaster risk management. The literature on urban resilience is immense and still growing. This paper reviews literature related to energy resilience to develop a conceptual framework for assessing urban energy resilience, identify planning and design criteria that can be used for assessing urban energy resilience, and examine the relationship of these criteria with the underlying components of the conceptual framework. In the conceptual framework, it is proposed that in order to be resilient, urban energy system needs to be capable of “planning and preparing for”, “absorbing”, “recovering from”, and “adapting” to any adverse events that may happen in the future. Integrating these four abilities into the system would enable it to continuously address “availability”, “accessibility”, “affordability”, and “acceptability” as the four sustainability-related dimensions of energy. The paper explains different resilience principles associated with these abilities and sustainability dimensions. Also, different planning and design criteria were extracted from the literature and categorized into five themes: infrastructure; resources; land use, urban geometry and morphology; governance; and socio-demographic aspects and human behavior. Examination of the relationship of these criteria with the underlying components of the conceptual framework highlighted the complexity and multi-faceted nature of energy resilience. Exploration of the relevance of the identified criteria to climate change mitigation and adaptation revealed that most of the identified criteria can provide both mitigation and adaptation benefits. [ABSTRACT FROM AUTHOR]

An assessment of residential CO 2 emissions is typically performed through the intensity method, in which total energy consumption is estimated by multiplying floor space by intensity value. Although spatially detailed intensity data is required for an accurate estimation, the finer spatial resolution will result in a less stable estimated value due to the small sample size; hence, existing studies in Japan created intensity data at a regional or prefectural level. The objective of this study is to create municipality level intensity data via a statistical approach, using the household level micro data from the National Survey of Family Income and Expenditure, of the Ministry of Internal Affairs and Communications, Japan, by focusing on electricity. First, this study builds several (spatial) statistical models, where per household electricity expenditure is regressed on housing types (two categories), household types (seven categories), and other household specific variables. Second, by substituting averaged municipality level explanatory variables from official statistics into the model, it estimates municipality level intensity data. The obtained results suggest that conventional intensity data in Japan, created by the simple average of samples in each unit (prefecture), may suffer from an upward bias, suggesting a danger of overestimation of residential CO 2 emissions. [ABSTRACT FROM AUTHOR]

This paper systematically reviews literature on passive heating and cooling of buildings using roof ponds. The main aims were to gain a detailed understanding of different roof pond configurations and their performance, compare effectiveness of different roof pond variants, evaluate performance of different roof pond variants relative to other passive design techniques, explore effects of climatic conditions and various design configurations on the performance of roof ponds, and identify gaps in knowledge and data. Overall, 19 roof pond cooling and 4 roof pond heating systems were identified. This review suggests that, in some cases, roof ponds can provide year-round thermal comfort while reducing demand for active heating and cooling systems. Therefore, they can be utilized in efforts towards the goal of carbon–neutral design. Roof ponds with wet gunny bags, shaded roof ponds, ventilated roof ponds, and roof ponds with movable insulation proved to be more effective relative to other variants of roof pond cooling systems. Comparing performance relative to other passive strategies showed that, in many cases, roof pond cooling systems are about equally effective in maintaining indoor thermal comfort. Meteorological conditions, water depth, roof deck material, and thickness of the insulating panel are the main factors affecting performance of roof ponds. Several areas of weakness in the literature are identified. Future research should, among other things, provide more detailed knowledge on performance of all roof pond variants, further explore suitability of roof ponds relative to other passive design measures, examine effectiveness of roof ponds when combined with other passive design measures, analyze life-cycle costs of roof ponds, and provide more knowledge on their real-world application. [ABSTRACT FROM AUTHOR]

Scenarios of future population at the grid level (e.g., 1 km 2 ) is very important for various types of regional planning, including energy planning. Though the most often used method for population projection is the so-called cohort-component method, if our focus is world level, not country or finer level, we must rely on much simpler methods. In this study, we compare the performance of several typical simple population projection methods using the residential electricity demand derived from each population scenario, especially focusing on spatial patterns. We show that different projection methods may produce different spatial patterns such as “compact” or “dispersed” urban form, which is quantified using the Gini coefficient. Also, we show that the projection method for gravity-based residential electricity demand is very flexible in that it can create the most compact and the most dispersed urban form among the focused methods. Furthermore, we point out the usefulness of model ensemble in projection. [ABSTRACT FROM AUTHOR]

Abstract: Designing a future smart city (FSC) that copes with the reduction of CO2 has become one of the urgent tasks of the next 20years. One promising approach to achieve FSC is to combine appropriate land use (compact city with energy efficient buildings and photovoltaic panels (PVs)), transportation (electric vehicles (EVs) and public transportation system) and energy systems (smart grid systems), because of the interaction between these elements. However, there are few models which simulate these elements in an integrated manner. This paper presents the concept of the integrated model, and shows the land use-energy part of the model created for the Tokyo metropolitan area, which is the largest Mega city in the world. Firstly, a spatially explicit land use model (urban economic model) is constructed for the study area, and the model is calibrated using existing statistical data. Secondly, possible future compact/dispersion city scenarios for the year 2050 are created using the model. Thirdly, intra-day dynamics (hourly) of electricity demand and supply from PVs, which is assumed to be installed to the roofs of all detached houses in the study area, under two urban scenarios is simulated. The obtained results suggest that [1] “compact” urban form may contribute to the reduction of electricity demand from the residential sector, but [2] PV-supply under the scenario may also be reduced because of the decreased share of detached houses. Hence in the compact city scenario, it is important to discuss the effective use of vacant areas in suburbs, which may be used for large PV installations, or be re-vegetated to mitigate urban heat island effects. [Copyright &y& Elsevier]

Abstract: The estimates of above-ground forest biomass (AGB) in Northern Eurasia are highly uncertain, despite the global importance of AGB for ecosystem services and its role as carbon stores. In this paper, we demonstrate the potential of ALOS/PALSAR (Advanced Land Observing Satellite/Phased Array L-band Synthetic Aperture Radar), for the estimation of AGB in the range of 10–190tons (dry matter)/ha in mixed and deciduous forests at the southern edge of the boreal region in Western Siberia. Various regression models were tested to determine the relationship between forest biomass derived from field measurements and radar backscatter. The best results were obtained using HV-polarized backscatter with the Water Cloud model, giving estimation errors in terms of root mean square errors (RMSE) between 25% and 32% of the mean biomass, and coefficient of determination (R 2) between 0.35 and 0.49 for the whole range of SAR backscatter used in the analysis. The method displayed a higher prediction accuracy with RMSE of 15%, and the R 2 between 0.55 and 0.72 when restricted to SAR backscatter (σ 0)<−12.6dB where the model was clearly defined. The SAR-based estimates offer a potential of rapid, high resolution and low cost mapping of the lower biomass woody vegetation (sparse or young forests on shallow peat) in Siberia, the area where more accurate national or large scale forest inventories hardly exist. [Copyright &y& Elsevier]

Abstract: Combining remote sensing data and socio-economic data to quantitatively analyze urban growth is a topic growing in importance. We used square grid cells to investigate the spatial and temporal dynamics of urban growth in the Tokyo, Japan, metropolitan area by using remote sensing imagery from 1972 to 2011 and census population data from 1970 to 2010. First, we used the subspace classification method to produce land-cover maps by using Landsat images from 1972, 1987, 2001, and 2011. Next, we integrated the land-cover maps with basic grid cell maps (using the standard 1km2 grid cell system of Japan) to represent the proportion of each land-cover category within each 1km2 grid cell area. Finally, we combined the proportional land-cover maps and population census data to investigate the relationship between land-cover changes and population density change based on grid cells. By using grid cells it is straightforward to (i) integrate remote sensing, geographic information system (GIS), and statistical data within the cells; (ii) quantify land-cover changes in terms of the percentage of area affected and rates of change and compare them with population census data; and (iii) analyze the spatial-temporal dynamics of urban growth patterns. Between 1972 and 2011 the rapid expansion of the urban area was accompanied by extensive shrinking of the agricultural area around the new settlements. As a result, the urban growth rate exceeded the population growth rate by more than a factor of 2.6. We used the grid cells to investigate the spatial relationship between the changes of land-cover classes and population density change, and then calculated the correlation coefficients of land-cover categories and population density changes for 3 intervals between 1972 and 2011 (1972–1987, 1987–2001, and 2001–2011). The results showed that the urban/built-up density decreased in the metropolitan inner core as the city center experienced depopulation. Spatial correlation analysis showed a strong positive correlation between urban expansion and population density change (r =0.59), and that urban expansion was strongly negatively correlated with cropland change (r =−0.77). The results also demonstrated that grid cells allow remote sensing and statistics data to be combined, improving the knowledge, understanding, and analysis of urban dynamics. [Copyright &y& Elsevier]

Abstract: To develop a scenario, easily traceable even for ordinary citizens, toward the national challenge target of 80% CO2 reduction by 2050, we have proposed a new model that calculates the total CO2 emission based on the final consumption. Using the model, we have tested appropriate (locally available) technology based sub-scenarios: (1) energy saving through electrification of all transportation; (2) promotion of wood utilization for housing; (3) introduction of renewable energies; and (4) efficient energy recovery from wastes. Applying the scenarios to the Kyoto-city as a case study, we have found that local 80% CO2 emission reduction could be possible using appropriate technologies including emission reduction from construction of private and public infrastructures, and shifting our final consumption mode into low CO2 emission has a significant impact. We have also argued that it is of interest to examine the future socio-economic change that would influence on people’s consumption behavior. [Copyright &y& Elsevier]

Abstract: We suggests that temperature response of plant productivity can be modeled by the Arrhenius function modified to describe the effect of temperature on enzyme activity: G A(T)=2f(T)/(1+ f 2(T)), where f(T)=exp(E a/RT opt − E a/RT), R the universal gas constant, E a the activation energy and T opt is the optimal temperature. In common with other functions used for modeling the temperature response of plant productivity, the curve of function G is almost symmetrical and bell-shaped. The special convenience of G A is that it relates the width of the “bell” to thermodynamic concepts, such as activation energy of chemical reactions converting carbon dioxide and water to carbohydrates. [Copyright &y& Elsevier]

Land use has changed dramatically in the Inner Mongolia Autonomous Region because of rapid economic growth and human disturbances. However, little information is available about the medium- and long-term land use changes in this region. The effects of ecological recovery policies have also been evaluated rarely. In this study, we employed the self-organizing map neural network method to identify the land cover changes in Inner Mongolia between 2000 and 2014. MOD13Q1, Landsat, and DMSP/OLS night-time light data were used as the data resources. The dynamic change map was characterized using the grid cell method. The results showed that urban area of Inner Mongolia increased by more than five times during the 15-year study period, while the mining area also increased. In addition, 35.3% of the farmland was changed into grassland, which may have been caused by the “Grain to Green” policy. The most significant environmental issue in Inner Mongolia is the loss of wetland. >40% of the wetland was converted into other land use types between 2000 and 2014. Grassland increased by 6.05%, but areas of open water and woodland remained about the same. In terms of the geographical distribution, cropland increased in the eastern and middle parts of the region. The transformation from wetland to grassland mainly occurred in the north. Grassland degradation occurred in the west. Thus, environmental policy has resulted in some ecological improvements in Inner Mongolia. However, new environmental problems associated with rapid economic development should be addressed in a timely manner. [ABSTRACT FROM AUTHOR]

By using household-level micro data captured through the National Survey of Family Income and Expenditure for 2004, this study evaluates the residential parking rent price elasticity of car ownership in Japan. It analyzes the number of cars owned by a household, using various attributes including expenditure for renting a parking space on a monthly basis. The estimation results derived from the IV-ordered probit model show that the absolute value of parking rent price elasticity of car ownership is, at most, 0.48, which is fairly small (i.e., inelastic). The elasticity value varies depending on city size; for megacities, elasticity is always negative for car ownership, whereas for middle-sized or small cities, towns, and villages, elasticity is positive for one-car ownership and negative for the ownership of more than one car. Hence, when the price of parking increases, some people may switch from more than one car to one car and some people in megacities may switch from one to zero cars. Indeed, the net effect of a price increase may be that non-car ownership increases in megacities and one-car ownership increases in other cities. [ABSTRACT FROM AUTHOR]

Highlights: [•] This paper purposed to reduce total electricity consumption of households in a cold area, Japan. [•] We implemented an information provision system to install four households for one year. [•] The system provided the information of electricity consumption 15min interval via websites. [•] We considered temperature effects to electricity demand and made a benchmark for evaluation. [•] Consequently, a tendency of reduction of electricity consumption could be seen in two households. [Copyright &y& Elsevier]

Global land cover maps are widely used for assessment and in research of various kinds, and in recent years have also come to be used for socio-economic forecasting. However, existing maps are not very accurate, and differences between maps also contribute to their unreliability. Improving the accuracy of global land cover maps would benefit a number of research fields. In this paper, we propose a methodology for using ground truth data to integrate existing global land cover maps. We checked the accuracy of a map created using this methodology and found that the accuracy of the new map is 74.6%, which is 3% higher than for existing maps. We then created a 0.5-min latitude by 0.5-min longitude probability map. This map indicates the probability of agreement between the category class of the new map and truth data. Using the map, we found that the probabilities of cropland and grassland are relatively low compared with other land cover types. This appears to be because the definitions of cropland differ between maps, so the accuracy may be improved by including pasture and idle plot categories. [ABSTRACT FROM AUTHOR]

Abstract: Biomass energy is one of mitigation method of CO2 reduction. In Japan, it aimed to reduce fossil fuels supply 670,000kL of crude oil equivalent in thermal power plants and 340,000kL of crude oil equivalent in the utilization of heat by biomass. It was decided to use 25% or more of the forestry products such as logging residues. Japanese government aim to supply 634PJ of woody biomass for power generation in 2010. This amount of energy accounts for 2.8% of total primary energy. More than 68% of Japan is covered by forests, and more than 40% of these forests are plantations. But the use of woody biomass is limited because it is still not seen as economically viable. In this article, we developed a large scale forestry economic model which can estimate the wood chips supply for coal thermal power plants across all around Japan. By using this model, wood chips supply potential is currently 32,000m3/year and supply will increase drastically when wood chips price increase or carbon credit is installed and we found that biomass production of 15PJ that is the numeric target of Japanese government is possible. Especially, the lengthening of rotation period of forestry and the decrease of wood chips transportation cost is important for wood chips use in coal thermal plant. [Copyright &y& Elsevier]

The purpose of this study was to contribute to filling the knowledge gap in public opinion and knowledge about forest and its certification in Japan, as well as to identify key elements and the possible role of public opinion within integrated bottom-up policies, bridging the sectors of forest, environment and energy. For the study 1930 questionnaires were disseminated in a small town in early 2007. Results from the statistical analysis indicated that forest was perceived as an ecosystem with a protective function against e.g. soil erosion or flooding, rather than a place that might serve for wood production and providing jobs. Forest certification and bioenergy from forest were identified as key elements for future integrated bottom-up policies that need to concentrate on facilitating the linkage between forestry and renewable energy as well as on promoting environmentally sound management and forest certification. [Copyright &y& Elsevier]

• Combining PV and EV in a city scale can reduce CO 2 emission by 60–74%. • The PV + EV systems can save energy costs by 22–37% in Kyoto City in 2030. • EV penetration policy should be reinforced integrating with PV systems. • Roof-top PV + EV system in a city-scale is defined as Solar-EV City. • Citizen's decision-making process is key to build PV + EV systems. To minimize the impacts of climate change, it is increasingly clear that global CO 2 emissions should be eliminated by 2050 and that leading low-carbon cities should reach net zero emissions by 2040. However, the precise pathways by which they can reach such ambitious goals have yet to be identified. As costs of photovoltaics (PV), batteries, and electric vehicles (EVs) are likely to keep falling, they can jointly play a key role for deep decarbonization. Here, we conduct a techno-economic analysis of a city-scale energy system with roof-top PV, batteries, and EVs for Kyoto City, Japan. We find that aggressive EV adoption and the use of EVs for electricity storage could help roof-top PV penetration in the city with substantially lower costs than just deploying PV and batteries alone or allowing EV to charge only. CO 2 emissions from vehicle and electricity usage in the city could be reduced by 60–74% if the entire current car fleet is replaced by EVs while also reducing energy costs by 22–37% by 2030. The largest challenge of a city-wide "PV + EV" system (named as "Solar-EV city") is its implementation. We explore how it could be realized in Kyoto through peer-to-peer (P2P) power trading/blockchain technology initially on a community scale as smart microgrids, then gradually expanding/converging into a city-wide. For the transition to decentralized power systems, citizen's decision-making process is one of the keys to overcome social, institutional, and regulatory barriers. [ABSTRACT FROM AUTHOR]

Spaceborne light detection and ranging (LiDAR) sensors can accurately observe forest parameters, such as canopy height and forest biomass. In this study, we investigated the potential of spaceborne LiDAR to quantify the effects of forest disturbances caused by typhoons on Hokkaido Island, Japan, after typhoon Songda in 2004. We developed a model to estimate canopy height from the Geoscience Laser Altimeter System (GLAS) of the Ice Cloud and land Elevation Satellite. GLAS waveforms are broadened by slopes (“pulse broadening”), so we used the lead10 and trail10 values (edge extents referring to 10% and 90% of the cumulative energy returned) to correct for this effect, because they were the parameters most strongly correlated with pulse broadening. We developed the estimation model by dividing GLAS data between gentle and steep slopes, using an empirically determined threshold, and obtained a root-mean-square error of 3.5 m for canopy height. We then applied the model to GLAS data in the area damaged by typhoon Songda to estimate changes in canopy height caused by the typhoon. We used a wind damage map produced in a previous study to identify the damage severity. The model showed that canopy height decreased by an average of 2.7 ± 1.8 m (95% confidence interval) in heavily damaged areas. The canopy height decreased most in coniferous forests, and especially in Japanese larch forests, that they have very shallow roots. We also assessed the geographic factors that most strongly influenced wind damage risk by means of multivariate analysis. We found serious damage in areas with a gentle slope that sustained strong winds. Understory plants and topography type also affected the risk. Our results show that spaceborne LiDAR can be used to quantify the severity of wind damage caused by forest disturbances, thereby providing guidance for forest management. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this study is to analyze the in situ BECCS capacity for green-field bioenergy plants in South Korea. The technical assessment is used to support a policy discussion on the suitability of BECCS as a mitigation tool. We examined the technical potential of bioenergy production from domestic forest biomass. In a first step, the biophysical global forestry model (G4M) was applied to estimate biomass availability. In a second step, the results from G4M were used as input data to the engineering model BeWhere, which optimizes scaling and location of combined heat and power plants (CHP). The geographically explicit locations and capacities obtained for forest-based bioenergy plants were then overlaid with a geological suitability map for carbon storage. From this, a theoretical potential for in situ BECCS was derived. Results indicate that, given the abundant forest cover in South Korea, there is substantial potential for bioenergy production, which could contribute not only to substituting emissions from fossil fuels but also to meeting the targets of the country's commitments under any climate change mitigation agreement. However, there seems to be only limited potential for direct in situ carbon storage in South Korea. [Copyright &y& Elsevier]

• "PV only" system in 2020 is already cost competitive relative to existing systems. • Electricity sharing between houses enhances decarbonization potential of "PV + EV". • Decarbonization potentials of "PV + EV" rapidly increase in residential district. • Decarbonization potentials of "PV + EV" become highly cost-competitive after 2025. • Residential "PV + EV" system cuts CO 2 emission by up to 94 %. Rooftop photovoltaics (PVs) integrated with electric vehicles (EVs) has the potential to deeply decarbonize urban energy systems in a cost-effective way. The SolarEV City Concept suggested that the rooftop PV plus EV systems can supply up to 95% of electricity demand within cities in Japan. However, it was not clear which district in city could consume, generate, and store the PV electricity, as each district has different load patterns, building structures, and number of parked cars. In this study, we performed techno-economic analyses on rooftop PV systems integrated with stand-alone batteries or EVs in residential and commercial districts in Japan from 2020 to 2040. We found that rooftop PV systems in 2020 are already cost competitive relative to existing energy systems. However, "PV + EV" systems in residential houses rapidly increases its economic advantage over commercial districts due to greater rooftop space and higher number of available vehicles. Moreover, energy sharing significantly improved the decarbonization potential. By 2025, energy cost savings, payback periods, and internal rate of return (IRR) of residential "PV + EV" systems respectively reached 23%, 9 years, and 11%, and continued improving in subsequent years. CO 2 emissions from electricity and gasoline consumption was reduced by 88%, and the system was capable to supplying 89% of electricity demand. The results indicate that residential "PV + EV" systems are a potential source for significant renewable energy generation and storage that can also produce increasingly dispatchable electricity. Policy makers, industries, and communities should prepare to establish these systems through regulatory reform and demonstration projects to scale-up after 2025. [ABSTRACT FROM AUTHOR]

Abstract: Spaceborne light detection and ranging (LiDAR) enables us to obtain information about vertical forest structure directly, and it has often been used to measure forest canopy height or above-ground biomass. However, little attention has been given to comparisons of the accuracy of the different estimation methods of canopy height or to the evaluation of the error factors in canopy height estimation. In this study, we tested three methods of estimating canopy height using the Geoscience Laser Altimeter System (GLAS) onboard NASA’s Ice, Cloud, and land Elevation Satellite (ICESat), and evaluated several factors that affected accuracy. Our study areas were Tomakomai and Kushiro, two forested areas on Hokkaido in Japan. The accuracy of the canopy height estimates was verified by ground-based measurements. We also conducted a multivariate analysis using quantification theory type I (multiple-regression analysis of qualitative data) and identified the observation conditions that had a large influence on estimation accuracy. The method using the digital elevation model was the most accurate, with a root-mean-square error (RMSE) of 3.2m. However, GLAS data with a low signal-to-noise ratio (⩽10.0) and that taken from September to October 2009 had to be excluded from the analysis because the estimation accuracy of canopy height was remarkably low. After these data were excluded, the multivariate analysis showed that surface slope had the greatest effect on estimation accuracy, and the accuracy dropped the most in steeply sloped areas. We developed a second model with two equations to estimate canopy height depending on the surface slope, which improved estimation accuracy (RMSE=2.8m). These results should prove useful and provide practical suggestions for estimating forest canopy height using spaceborne LiDAR. [Copyright &y& Elsevier]

Abstract: We conducted a spatial evaluation of forest biomass usage using a geographic information system (GIS) for the Japanese town of Yusuhara. In Japan, over 60% of the land is covered with forest, of which at least 40% is artificial forest. However, because of high labor costs, the profitability of forestry is decreasing, so timber cultivation is not done to the extent that it could be, and thinning has to be subsidized. Under these circumstances, much of the forest is deteriorating. Most of the thinning is accounted for by throwaway thinning, in which the resulting wood is not used. However, with the steep rise in oil prices and the intensification of global warming concerns, expectations are rising for the use of biomass energy from thinned timber that has previously been discarded. If thinned timber, logging residues, and offcuts are utilized for biomass energy and their economic value becomes apparent, profitability will improve for both final cutting and thinning. And in addition to forestry activities being invigorated, it will be possible for some of the deteriorating forests (which have associated dangers such as landslides) to recover. However, using thinned timber and logging residues is problematic in that profitability is affected by harvesting costs. Harvesting costs are largely determined by geographic factors and are higher for more distant stands. Accordingly, in this article, operational costs for different stands are calculated using GIS and matched with total demand in the subject region. In addition, stands with lower operational costs are identified and an investigation of a highly feasible use of forest biomass is carried out. [Copyright &y& Elsevier]

Cities produce over 70% of global carbon emissions and are thus crucial in driving climate change. Urban carbon emissions may continue to increase especially in those less-developed countries and regions which are still under rapid urban development. Policymakers need to find ways to effectively control and reduce carbon emissions. Thus, spatial modeling methods to map and predict urban carbon emissions have been developed to meet these needs. This paper examines the progress of the spatial modeling of carbon emissions and the relationship between urban form and carbon emissions in China by reviewing more than 100 peer-reviewed journal articles in the Scopus database. The latest prediction methods and techniques are described in the paper. Their advantages and limitations are then discussed. Urban forms have a significant influence on carbon emissions and have been applied in spatial modeling studies in other countries. However, this review has identified the lack of urban form data and high-resolution inventories from existing studies in China. Future developments in the spatial modeling in China should therefore have a fine spatial resolution and incorporate open and high-quality urban form data, including urban morphology and land use/land cover. • The spatial modeling studies of urban carbon emission in China are reviewed. • The available data and methods are summarized. • The strengths and weaknesses of the methods are compared. • Urban forms can affect urban carbon emissions. • Future developments will require a finer spatial resolution and urban form data. [ABSTRACT FROM AUTHOR]

Abstract: We have provided a framework for identifying least-cost sites for afforestation and reforestation and deriving carbon sequestration cost curves at a global level in a scenario of limited information. Special attention is given to country risk in developing countries and the sensitivity to spatial datasets. Our model results suggest that within 20 years and considering a carbon price of US$50/tC, tree-planting activities could offset 1 year of global carbon emissions in the energy sector. However, if we account for country risk considerations–associated with political, economic and financial risks–carbon sequestration is reduced by approximately 60%. With respect to the geography of supply, illustrated by grid-scale maps, we find that most least-cost sites are located in regions of developing countries such as the Sub-Sahara, Southeast Brazil and Southeast Asia. [Copyright &y& Elsevier]

Finding economical and sustainable pathways for the deployment of renewables is critical for the success of decarbonizing energy systems. Because of the variable nature of renewable energy, however, the integration of renewables becomes increasingly costly and difficult as the renewable penetration becomes higher. The recent rise of electric vehicles (EVs) provides us with an opportunity to increase self-consumption of solar photovoltaic (PV) at households with substantially lower additional costs. In this paper, an environmental techno-economic assessment of residential PV systems is conducted with battery or EVs allowing charging and discharging (Vehicle to Home: V2H) in Kyoto, Japan, and Shenzhen, China, incorporating the cost projections of these technologies towards 2030. It is found that "PV + EV" (V2H) becomes highly cost-effective towards 2030 in Kyoto in comparison with "PV only", "PV + battery", and "EV charge". In the region of lower electricity costs such as Shenzhen, switching to EVs from gasoline vehicles is the most cost-effective option during 2020s. Finally, it is found that "PV + EV" has the highest CO 2 emission reduction potential across all the technology combinations considered, owing to EV charging of carbon-free electricity from PV. To facilitate a rapid household decarbonization, policy makers should reinforce policies to enhance the penetration of combined technologies of "PV + EV" (V2H) towards 2030. • PV + EV becomes highly cost-effective towards 2030 in Kyoto. • Switching to EV is the most cost-effective option in Shenzhen during 2020s. • PV + EV has the highest decarbonization potentials. [ABSTRACT FROM AUTHOR]