Towards Studying Collective Dynamics of Electricity Sharing Systems

AbstractIn this paper, we propose an agent-based model for investigating collective dynamics in community-based electricity sharing systems. In our simulations, we assume the absence of electricity grids and telecommunication infrastructure–a situation which might be induced by a big natural disaster or a large-scale black-out. Under such circumstances, electricity sharing systems based on decentralized, small-scale renewables could help meeting basic electricity demand. Since real-world tests are hardly possible for such a scenario, we analyze possible collective reactions via means of social simulation

Principles and criteria for assessing urban energy resilience: A literature review

AbstractBetween 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

土地利用-交通-エネルギーモデルによるスマートシティーシミュレーション：リアルタイム計測情報の動的データ同化手法に関する予備的な検討

Open House, ISM in Tachikawa, 2012.6.15統計数理研究所オープンハウス（立川）、H24.6.15ポスター発

ビックデータを用いた都市レジリエンス分析のための新たな空間統計手法の開発：Eigenvector spatial filteringの連続空間への拡張

Open House, ISM in Tachikawa, 2014.6.13統計数理研究所オープンハウス（立川）、H26.6.13ポスター発

Systematizing and upscaling urban climate change mitigation

The question of what cities can contribute to mitigation and adapting to climate change is gaining traction among researchers and policy makers alike. However, while the field is rich with case studies, methods that provide rich data across municipalities and potentially at global scale remain underdeveloped, and comparative insights remain scarce. Here we summarize contributions to the focus issue on 'Systematizing and Upscaling Urban Climate Solutions', also drawing from presentations given at an accompanying conference in 2018. We highlight four core areas for systematizing and upscaling urban climate mitigation solutions. First, with more and better (big) data and associated machine learning methods, there is increasing potential to compare types of cities and leverage collective understanding. Second, while urban climate assessments have mostly emphasized urban planning, demand-side action as related to both behavioral change and modified social practices relevant to urban space deserve more academic attention and integration across a diverse set of social sciences. Third, climate mitigation would be intangible as a single objective at the urban scale, and measures and solutions that coordinate mitigation coherently with adaptation and broader sustainable development goals require explicit conceptualization and systematization. Forth, all insights should come together to develop governance frameworks that translate scientific exercises into concrete, realistic and organized action plans on the ground, for all cities

Involvement of Spinal Angiotensin II System in Streptozotocin-Induced Diabetic Neuropathic Pain in Mice

ABSTRACT Renin-angiotensin system (RAS) activity increases under hyperglycemic states, and is thought to be involved in diabetic complications. We previously demonstrated that angiotensin (Ang) II, a main bioactive component of the RAS, might act as a neurotransmitter and/or neuromodulator in the transmission of nociceptive information in the spinal cord. Here, we examined whether the spinal Ang II system is responsible for diabetic neuropathic pain induced by streptozotocin (STZ). Tactile allodynia was observed concurrently with an increase in blood glucose levels the day after mice received STZ (200 mg/kg, i.v.) injections. Tactile allodynia on day 14 was dose-dependently inhibited by intrathecal administration of losartan, an Ang II type 1 (AT1) receptor antagonist, but not by PD123319, an AT2 receptor antagonist. In the lumbar dorsal spinal cord, the expression of Ang II, Ang converting enzyme (ACE), and phosphop38 mitogen-activated protein kinase (MAPK) were all significantly increased on day 14 after STZ injection compared with vehicletreated controls, whereas no differences were observed among AT1 receptors or angiotensinogen levels. Moreover, the increase in phospho-p38 MAPK was significantly inhibited by intrathecal administration of losartan. These results indicate that the expression of spinal ACE increased in STZ-induced diabetic mice, which in turn led to an increase in Ang II levels and tactile allodynia. This increase in spinal Ang II was accompanied by the phosphorylation of p38 MAPK, which was shown to be mediated by AT1 receptors

Extended Averaged Learning Subspace Method for Hyperspectral Data Classification

Averaged learning subspace methods (ALSM) have the advantage of being easily implemented and appear to outperform in classification problems of hyperspectral images. However, there remain some open and challenging problems, which if addressed, could further improve their performance in terms of classification accuracy. We carried out experiments mainly by using two kinds of improved subspace methods (namely, dynamic and fixed subspace methods), in conjunction with the [0,1] and [-1,+1] normalization methods. We used different performance indicators to support our experimental studies: classification accuracy, computation time, and the stability of the parameter settings. Results are presented for the AVIRIS Indian Pines data set. Experimental analysis showed that the fixed subspace method combined with the [0,1] normalization method yielded higher classification accuracy than other subspace methods. Moreover, ALSMs are easily applied: only two parameters need to be set, and they can be applied directly to hyperspectral data. In addition, they can completely identify training samples in a finite number of iterations

Pathway using WUDAPT's Digital Synthetic City tool towards generating urban canopy parameters for multi-scale urban atmospheric modeling

The WUDAPT (World Urban Database and Access Portal Tools project goal is to capture consistent information on urban form and function for cities worldwide that can support urban weather, climate, hydrology and air quality modeling. These data are provided as urban canopy parameters (UCPs) as used by weather, climate and air quality models to simulate the effects of urban surfaces on the overlying atmosphere. Information is stored with different levels of detail (LOD). With higher LOD greater spatial precision is provided. At the lowest LOD, Local Climate Zones(LCZ) with nominal UCP ranges is provided (order 100 m or more). To describe the spatial heterogeneity present in cities with great specificity at different urban scales we introduce the Digital Synthetic City (DSC) tool to generate UCPs at any desired scale meeting the fit-for-purpose goal of WUDAPT. 3D building and road elements of entire city landscapes are simulated based on readily available data. Comparisons with real-world urban data are very encouraging. It is customized (C-DSC) to incorporate each city's unique building morphologies based on unique types, variations and spatial distribution of building typologies, architecture features, construction materials and distribution of green and pervious surfaces. The C-DSC uses crowdsourcing methods and sampling within city Testbeds from around the world. UCP data can be computed from synthetic images at selected grid sizes and stored such that the coded string provides UCP values for individual grid cells

Assessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b)

In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a "special report in 2018 on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways". In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5°C, including a potential overshoot and long-term impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the low-emissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global and regional hydrology, lakes, global crops, global vegetation, regional forests, global and regional marine ecosystems and fisheries, global and regional coastal infrastructure, energy supply and demand, temperature-related mortality, and global terrestrial biodiversity)