Climate change poses significant challenges and impacts to coastal communities. In order to limit future coastal flood risk, adaptation is necessary. This study presents an integrated model to ...simulate storm surge inundation risk in Osaka Bay under climate change and provide a cost–benefit analysis of structure adaptation strategies to reduce risk. The results show that storm surge inundation risk will increase dramatically as combined impacts of sea level rise and intensified storm surges due to global warming. Without adaptation measures, the expected annual damage cost increases from 9.85 billion JPY to 69.17 billion JPY in Osaka Bay under the projected RCP8.5 scenario to 2100. We then explore the effectiveness of structural adaptation strategies. The results indicate that raising the height of existing dikes can reduce inundation risk effectively. The benefits and costs depend on the elevated height and the discount rate. Using cost–benefit analysis, we find that upgrading by 1 m the height of existing dikes is the most cost-effective strategy for Osaka Bay. The methodology developed in this paper provides a reference for Osaka Bay and other coastal regions when they make coastal flood risk management and adaptation strategies to respond to climate change.
•Focused on the short-term, firm-level business scale, indirect economic impact of lifeline service disruptions.•Markov process model is applied in the field of post-disaster business recovery from a ...microeconomic perspective that can capture the uncertainty and randomness of the stochastic recovery process.•Integrated the recovery of multiple lifeline services and how their recovery impact on firm's production capacity.•The proposed model was applied to a real post-disaster business recovery case study.
Lifeline disruptions can represent a serious economic threat at various scales. However, firm-level empirical evidence regarding the consequences and reliability of lifeline services, and how lifeline service disruptions impact on economic losses after disasters, is still lacking. This study applies a temporal, non-homogeneous, Markov process approach that explicitly considers multiple lifeline service disruptions. This approach is used to quantitatively estimate the impacts of multiple lifeline disruptions on business production capacity losses. The model is illustrated based on the 2011 Great East Japan Earthquake case study with detailed information obtained from individual business recovery data. The result indicates that the restoration of lifeline systems during disruptions should consider each business service given that it significantly affects business production capacity recovery. For example, the case study results indicate that if electrical power, water and gas are disrupted, restoration of electrical power supply yields the highest influence on production capacity improvement, amounting to 15% per day on average, compared with 10% per day for gas restorations, and 8% per day for water restoration. The proposed model can provide information to business managers and policymakers on the optimum recovery strategy and on how to mitigate economic losses in disruption event cases.
This paper provides an overview of economic impacts in the first year after the 2011 Tohoku-oki earthquake, tsunami, and nuclear accident - at an estimated (Yen)16.9 trillion (US$211 billion) in ...direct damage, the costliest natural disaster on record. Documented costs to date include (Yen)2.9 trillion in insurance payouts and (Yen)17.7 trillion in response and recovery budgets by the national government that will be financed largely by tax increases and bonds. In the regions with physical damage, fisheries and agriculture, among other sectors, were very hard hit. The disaster also caused measurable economic impacts well beyond the damage regions, including losses in gross domestic product (GDP), in manufacturing from supply-chain disruptions, and in retail trade and tourism due to restrained consumption and radiation fears. Reduced capacity for generating electricity has led to substantial energy conservation nationwide. Results from applying a loss estimation model demonstrated good agreement with observed post-disaster economic activity.
Numerous scholars and researchers have long advocated for citizen engagement in post-disaster recovery and reconstruction initiatives, although unique opportunities and challenges in effectively ...implementing citizen engagement still exist. It has been 12 years since the Great East Japan Earthquake, where the government called for a citizen-centered recovery and reconstruction process, and reconstruction in most areas in the Tohoku region has almost been concluded. Using qualitative data acquired through interviews with the residents, field observations during the World Bosai Walk, and questionnaire and archival research, this study aimed to discuss the overall reconstruction of Unosumai in Iwate Prefecture, giving the residents’ perspective on the benefits and challenges they faced in participating in recovery planning and reconstruction and how the community has been able to strengthen their participation in disaster reduction initiatives since the earthquake and tsunami. This discussion is crucial as it would effectively offer lessons on engaging residents in post-disaster recovery and reconstruction after mega-disasters.
This study proposes a probabilistic methodology for estimating the business interruption loss of industrial sectors as an extension of current methodology. The functional forms and parameters are ...selected and calibrated based on survey data obtained from businesses located in the inundated area at the time of the 2000 Tokai Heavy Rain in Japan. The Tokai Heavy Rain was a rare event that hit a densely populated and industrialized area. In the estimation of business interruption losses, functional fragility curves and accelerated failure time models are selected to estimate the extent of damage to production capacity and production recovery time. Significant explanatory variables, such as inundation depth, distinct vulnerability, and the resilience characteristics of each sector, as well as the accuracy of fit of the model, are analyzed in the study. The function obtained and the estimated parameters can be utilized as benchmarks in estimating the probabilistic distribution of business interruption losses, especially in the case of urban flood disasters.
Relocation is not typically considered the best planning option for post-disaster reconstruction and rehabilitation, but it may be necessary if the site has suffered severe damage or is at imminent ...risk. There is a growing recognition that strong community participation is necessary in the post-disaster relocation decision-making process since relocation can have detrimental effects on a community’s livelihood, cultural system, and way of life, among others. However, the realization of this still needs to be improved. As of yet, few studies have examined a comprehensive account of meaningful community engagement in post-disaster relocation and reconstruction, particularly in developing countries. This study investigated what factors influenced local communities’ participation in post-disaster relocation and reconstruction works after the 2017 Cyclone Dineo flood disaster in the Tsholotsho District of Zimbabwe. Qualitative research methods such as face-to-face interviews, observations, and focus groups were used to collect qualitative data from a purposive sample of 25 community members and 6 stakeholders. This empirical investigation showed that despite the fact that the relocation project was conceived as a community-centered project, there was no meaningful community engagement, due to the absence of a participatory framework or planning guidelines for stakeholder engagement, as well as the lack of political willingness among government officials. The study concluded that the lack of community involvement led to local communities abandoning the reconstruction sites because relocation projects failed to accommodate the cultural beliefs, place attachments, and livelihood concerns of local communities. This study suggested that it is imperative to enhance the awareness of government officials and other stakeholders about the importance of community participation for the effective implementation of post-disaster relocation works. Meaningful community participation can also provide avenues for incorporating local needs and concerns, cultural beliefs, and alternative and sustainable livelihood restoration, which are essential for effective reconstruction after disasters. This research aimed to enrich the academic discourse by providing valuable insights into the intricacies of post-disaster recovery initiatives in the country.
Although for decades, public participation in disaster risk management has been strongly advocated for, in reality, it remains elusive. Planners and practitioners are still struggling to find ways to ...meaningfully involve the local community in disaster management programs; so far, apparently successful projects and initiatives have seldom been scaled up or replicated. The reason for this is that no comprehensive framework for participatory disaster risk management exists, and no systematic evaluation has been made to assess the necessary elements and appropriate paths for meaningful public participation in disaster management. This study attempts to examine the process and identify outcome-based factors that account for successful participatory disaster risk management. To accomplish this, we have evaluated reconstruction projects in earthquake-affected rural Gujarat, India, where the government envisioned a people-centric reconstruction project, but provided no public participation framework or guidelines. As a result, several reconstruction models pursuing different levels and types of public participation ultimately emerged. We selected three dominant reconstruction approaches and examined the extent to which various processes and outcome-based factors were successful in promoting ideal levels of public participation during these reconstruction projects. This study is considered an example of pioneering research in defining factors that account for successful participatory disaster risk management.
► A bottom-up framework is developed to exam the residential carbon intensity in China. ► Energy intensity of activities has a significant and both-side effect. ► End-use mode is the biggest ...contributor on the increase of aggregate carbon intensity. ► Guiding residents’ life styles is summarized as a wise and first policy choice.
The residential sector is the second largest consumer in China with great room for energy consumption growth, as well as the related carbon emissions. Thus, how to reduce the growth rate of carbon emissions is crucial for realizing the target of energy conservation and emission mitigation in the residential sector. Based on a bottom-up framework with survey data and official statistics, this paper examines the changes of aggregate residential carbon intensity, and analyzes its driving factors from an end-use perspective over the period of 1996–2008. The Adaptive Weighting Divisia with rolling base year index specification is applied to identify the quantitative effects of driving components and their further decomposing results of end-use activities. Results show that, the residential aggregate carbon intensity has grown rapidly since 2002 in both urban and rural China. The changes in primary fuel mix for electricity and heat generation have an overall negative but insignificant effect on the residential aggregate carbon intensity, while the effect of final energy structure is positive with a rising tendency. The significant impact of changes in energy intensity shift from negative to positive over time, and contribute more to a decline than to an increase. The driving force arising from the residential end-use mode has the highest contribution to the increase of aggregate carbon intensity. Finally, some policy implications are proposed to effectively slow down the accelerated rate of the residential aggregate carbon intensity. Guiding households towards energy-saving behaviors is recommended as a wise and first policy choice.
Scientific uncertainties in climate change projections are generally addressed using an ensemble method, in which multiple models are used to generate climate projections. In the interest of ...transparent and honesty, such uncertainty should be communicated to the general public. Thus, it is important to investigate how such uncertainty should be communicated to the general public. This study explored three uncertainty representation formats—average, range, and multi-value—to investigate how each format affected the general public’s trust, perceived accuracy, perceived likelihood, and concern after acknowledging the presence of uncertainty in climate projections (i.e., the use of multi-model climate projections). We conducted a web survey of 2400 participants in Japan, in which we randomly assigned each participant to one of three formats by which climate projection uncertainty was presented. We then asked participants to rate trust, perceived accuracy, perceived likelihood, and concern regarding the climate projections. The multi-value format enhanced trust and perceived accuracy and partially increased perceived likelihood and concern regarding the climate projections compared to the average and range formats, regardless of participants’ numeracy and education level. This study suggests that the multi-value format might be effective for communicating multi-model projections and promoting public trust and support for climate polices.
With growing regional economic integration, transportation systems have become critical to regional development and economic vitality but vulnerable to disasters. However, the regional economic ...ripple effect of a disaster is difficult to quantify accurately, especially considering the cumulated influence of traffic disruptions. This study explored integrating transportation system analysis with economic modeling to capture the regional economic ripple effect. A state-of-the-art spatial computable general equilibrium model is leveraged to simulate the operation of the economic system, and the marginal rate of transport cost is introduced to reflect traffic network damage post-disaster. The model is applied to the 50-year return period flood in 2020 in Hubei Province, China. The results show the following. First, when traffic disruption costs are considered, the total output loss of non-affected areas is 1.81 times than before, and non-negligible losses reach relatively remote zones of the country, such as the Northwest Comprehensive Economic Zone (36% of total ripple effects). Second, traffic disruptions have a significant hindering effect on regional trade activities, especially in the regional intermediate input—about three times more than before. The industries most sensitive to traffic disruptions were transportation, storage, and postal service (5 times), and processing and assembly manufacturing (4.4 times). Third, the longer the distance, the stronger traffic disruptions’ impact on interregional intermediate inputs. Thus, increasing investment in transportation infrastructure significantly contributes to mitigating disaster ripple effects and accelerating the process of industrial recovery in affected areas.
