NEO Smart Contract for Drought-Based Insurance

The increasing intensity and frequency of extreme weather events resulting from climate change have led to grid outages and other negative consequences. To ensure the resilience of buildings which serve as primary shelters for occupants, resilient strategies are being developed to improve their ability to withstand these extreme events (e.g., building upgrades and renewable energy generators and storage). However, a crucial step towards creating a resilient built environment is accurately estimating building performance during such conditions using historical extreme climate change-induced weather events. To conduct Building Performance Simulation (BPS) in extreme conditions, such as weather events induced by climate change, it is essential to utilize Actual Meteorological Year (AMY) weather files instead of Typical Meteorological Year (TMY) files. AMY files capture the precise climatic conditions during extreme weather events, enabling accurate simulation of such scenarios. These weather files provide valuable data that can be used to assess the vulnerabilities and resilience of buildings to extreme weather events. By analyzing past events and their impacts using BPS tools, we can gain insights into the specific weaknesses and areas that require improvement. This approach applies to both existing buildings needing climate change-resilient retrofits and new building designs that must be compatible with future climatic conditions. Moreover, the intensification and frequency increase of these extreme weather events makes developing adaptation and resilient-building measures imperative. This involves understanding the potential losses that households may experience due to the intensification of extreme events and developing farsighted coping strategies and climate-proof resilient-building initiatives. However, addressing the knowledge gap caused by the absence of an AMY weather file dataset of extreme events is essential. This will allow for accurate BPS during past extreme climate change-induced weather events. To fill this gap, this article introduces a comprehensive .epw format weather file dataset focusing on historical extreme weather events in Canada. This collection encompasses a diverse array of past extreme climate change occurrences in various locations, with potential for future expansion to include additional locations and countries. This dataset enables energy simulations for different types of buildings and considers a diverse range of historical weather conditions, allowing for better estimation of thermal performance.

Extreme weather events and their resulting impacts threaten all levels of society. Climate change can amplify the frequency and intensity of associated hazards. One of the key-challenges for decision-makers in civil protection is adapting to the changing landscape of weather-induced impacts driven by climate change. It is therefore essential to assess and estimate the changing conditions for extreme weather events under climate change.This study investigates the changing landscape of regional extreme weather events in the Alpine region by utilizing weather circulation type classification through its relationship with weather-induced potential extreme events. Therein, large-scale weather types take the role of relevant precursors for regional extreme events. The local-scale potential impact events that are associated with prevailing weather types are derived by using percentile-based methods on high-resolution, gridded precipitation data. ERA5 mean sea level pressure and the classification scheme GWT ('Gross-Wetter-Typen') are used to derive 18 classes of cyclonic and anti-cyclonic weather types, representing a prevailing circulation on a daily basis for the whole Alpine region. Subsequently, unsupervised hierarchical clustering (Agglomerative clustering) is used to evaluate overlaps between cluster families in order to derive a subset of 'high-impact' weather types. The relationship between those weather types and local-scale extreme events is further characterized by analyzing percentile-based indicators from station data and high-resolution observational data. Finally, we extend our analysis by applying found relationships to state-of-the-art climate models from the Coupled Model Intercomparison Project 6 (CMIP6) to investigate the changing landscape for extreme weather events under different climate change scenarios.Our findings indicate that a subset of weather types, related to specific cyclonic circulation patterns, is mostly responsible as precursor for extreme precipitation events. Those patterns furthermore show increases in frequency under the scenario SSP3-7.0, that are consistent across the climate model ensemble. Associated changes of precipitation totals suggest increases in intensity, however these intensity changes are not as conclusive due to large inter-model spread.

Extreme Weather, agricultural insurance and farmer's climate adaptation technologies adoption in China

PurposeAgriculture insurance is the panacea for the farming community. Many policy interventions were implemented for stimulating agriculture insurance access to farmers in India. However, access to agriculture insurance constantly remained one of the major challenges to Indian policy planners. The goal of the present paper is to explore current policy interventions in the area of agriculture insurance in India.Design/methodology/approachThe present paper reviews and analyzes the evidence literature through a content analysis method on development and performance analysis perspective of existing agriculture insurance schemes in India.FindingsAgriculture insurance is a significant risk management policy, but this is not easily reachable to the majority of farmers in India. The government of India introduces a novel agriculture scheme every decade, but every crop insurance scheme was inconsistent and ineffective owing to operational defects. Agriculture insurance in India is still developing in terms of coverage, scope, and exposure, but farmers' dissatisfaction about agriculture insurance turned out to be a negative word of mouth. Insurance illiteracy and farmers' preference for agriculture relief payments are the main reasons for limited access to agriculture insurance. The current crop insurance schemes are improperly operated because of implementation issues at the state level.Research limitations/implicationsThis paper will be useful for researchers and academicians to analyze the past and present status of crop insurance in India.Originality/valueThe paper is the unique work of the authors as it has attempted to present India's journey with agriculture insurance. An effort is made in the present study to provide a comprehensive and holistic developmental and performance analysis perspective of agriculture insurance in India.

BackgroundTransitional economies in Southeast Asia—a distinct group of developing countries—have experienced rapid urbanization in the past several decades due to the economic transition that fundamentally changed the function of their economies, societies and the environment. Myanmar, one of the least developed transitional economies in Southeast Asia, increased urbanization substantially from 25% in 1990 to 31% in 2019. However, major knowledge gaps exist in understanding the changes in urban land use and land cover and environment and their drivers in its cities.MethodsWe studied Yangon, the largest city in Myanmar, for the urbanization, environmental changes, and the underlying driving forces in a radically transitioned economy in the developing world. Based on satellite imagery and historic land use maps, we quantified the expansion of urban built-up land and constructed the land conversion matrix from 1990 through 2020. We also used three air pollutants to illustrate the changes in environmental conditions. We analyzed the coupled dynamics among urbanization, economic development, and environmental changes. Through conducting a workshop with 20 local experts, we further analyzed the influence of human systems and natural systems on Yangon’s urbanization and sustainability.ResultsThe city of Yangon expanded urban built-up land rapidly from 1990 to 2000, slowed down from 2000 to 2010, but gained momentum again from 2010 to 2020, with most newly added urban built-up land appearing to be converted from farmland and green land in both 1990–2000 and 2010–2020. Furthermore, the air pollutant concentration of CO decreased, but that of NO2 and PM2.5 increased in recent years. A positive correlation exists between population and economic development and the concentration of PM2.5 is highly associated with population, the economy, and the number of vehicles. Finally, the expert panel also identified other potential drivers for urbanization, including the extreme climate event of Cyclone Nargis, capital relocation, and globalization.ConclusionsOur research highlights the dramatic expansion of urban land and degradation of urban environment measured by air pollutants and interdependent changes between urbanization, economic development, and environmental changes.

PurposeCross border trade, involving different business environments between the sellers’ and buyers’ countries, may result in conflicts because of asymmetry in the information structure across the borders. The International Chambers of Commerce (ICC) has laid down ground rules on terms of shipment and payment, enabling harmonization and standardization of business process, and fixing of responsibilities for international trade. The international commercial (INCO) terms by ICC define the duties, obligations and cost borne by the exporter and the importer. An exporter’s uncertainty looms once the goods cross his/her border. Therefore, there is a need for a smart contract that is secured, transparent, legitimate and trustworthy. The authors propose a blockchain technology-based smart global contract (BTGC) framework for international trade.Design/methodology/approachIn this paper, the authors develop the framework based on value chain analysis (VCA) of international trade and an ontology-driven-blockchain-design approach. The paper analyzes the sequence of activities in the value chain of global trade, the terms of the contract, the data structure templates, the validation rules and the points-of-failure, and proposes the smart contract blockchain structure.FindingsThis paper proposes the BTGC framework considering the INCO terms 2020; it provides the validation rules and the probability of failures; and identifies the elements that cause the halting of contracts and conditions of creation of side blockchains. The framework also includes the governance of the BTGC system.Research limitations/implicationsThe proposed framework not only has implications at the firm level as it automates and secures a global sale contract but also is expected to harmonize the global-trade process as well. The developers may use the attributes, data structure templates and the rules identified in this paper for developing the GC software. Future research may consider using case analysis, class diagrams and the related steps for developing the blockchain software.Originality/valueThis paper proposes a complete value chain of global contract (GC) concerning exports, an ontology of GC and a blockchain-based smart-contract framework based on global standards. Besides, it specifies the elements of fraud (such as the non-integration of side chains) and uncertainty, i.e. the probability of failures. Such a framework will harmonize the global-trade process and build an international standards for smart GC based on blockchain technology (ISSGCBT), which is not yet done.

Since the beginning of the industrial era, the climate of our planet and the human environment have been changing rapidly. Therefore, known and new types of extreme events have been and will continue to be a challenge. An example of a climate challenge is climatological extremes. In recent decades, extreme weather events such as wildfires, floods, droughts, and heat waves have increased across the globe. These extreme events can disturb and alter ecosystems over timescales ranging from minutes to months. However, the recovery and adaptation processes often take far longer than the extreme events. While the intensity of adaptation efforts may vary, they inevitably follow disturbances.Here, we focus on the recovery dynamics of vegetation in different types of ecosystems after droughts and heat waves, which are the most damaging types of weather extremes. The study covers the last decades period and is based on satellite data.Disturbance-induced changes in terrestrial ecosystems affect photosynthetic activity, reducing carbon dioxide (CO2) fixation. We hypothesise that, in return, the temporal dynamics of atmospheric CO2 fixation by vegetation may indicate different stages of ecosystem recovery - normal ecosystem state (before extreme), imbalance phase, post-extreme phase, recovery phase, or collapse. We find such an approach helpful for understanding the time frames of the phases and capturing phase transitions and general ecosystem states in near real-time.The identification of vegetation recovery stages is influenced by several factors, including environmental conditions and seasonal cyclicity. To ensure the effectiveness of an automated approach, a unified phase-stage representation for comparability and analysis of CO2 uptake is required.To achieve this, we divide daily CO2 uptake values by their maximum values observed during a year without significant droughts and heatwaves. We have chosen the observation period from 1993 to 2005, which includes a European drought in 2003 and the periods before and after it. As a result of normalisation, stronger ecosystem recovery will correspond to values around “1” and weaker recovery - to a range around “0”. Negative values could indicate the dominance of CO2 emissions or ecosystem degradation processes.Vegetation indices, such as NDVI, can be employed as markers of transformation scope to identify the beginning and end of the vegetation growth period activity. This allows us to represent the time scale in a normalised relative interval – [0;1].The results are a first step towards a normalised representation of the response of terrestrial vegetation to further study the dynamics of its recovery from extreme weather events.

Abstract. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was used to study the effect of extreme weather events on ozone in the US for historical (2001–2010) and future (2046–2055) periods under the RCP8.5 scenario. During extreme weather events, including heat waves, atmospheric stagnation, and their compound events, ozone concentration is much higher compared to the non-extreme events period. A striking enhancement of effect during compound events is revealed when heat wave and stagnation occur simultaneously as both high temperature and low wind speed promote the production of high ozone concentrations. In regions with high emissions, compound extreme events can shift the high-end tails of the probability density functions (PDFs) of ozone to even higher values to generate extreme ozone episodes. In regions with low emissions, extreme events can still increase high-ozone frequency but the high-end tails of the PDFs are constrained by the low emissions. Despite the large anthropogenic emission reduction projected for the future, compound events increase ozone more than the single events by 10 to 13 %, comparable to the present, and high-ozone episodes with a maximum daily 8 h average (MDA8) ozone concentration over 70 ppbv are not eliminated. Using the CMIP5 multi-model ensemble, the frequency of compound events is found to increase more dominantly compared to the increased frequency of single events in the future over the US, Europe, and China. High-ozone episodes will likely continue in the future due to increases in both frequency and intensity of extreme events, despite reductions in anthropogenic emissions of its precursors. However, the latter could reduce or eliminate extreme ozone episodes; thus improving projections of compound events and their impacts on extreme ozone may better constrain future projections of extreme ozone episodes that have detrimental effects on human health.

Extreme weather events and disruptions to HIV services: a systematic review.

Smart contracts are computer codes that represent contract terms and are designed to run on a blockchain platform, automatically enforced upon receiving predetermined inputs. This technological innovation, a key component of the Fourth Industrial Revolution, provides an advanced and innovative approach to executing contract terms. Incorporating this technology into Shariah-compliant contracts within Islamic Banks (IBs) holds the potential to reduce Shariah non-compliance risk (SNC) and enhance operational transparency, ensuring compatibility with contemporary technological applications. In particular, blockchain-based smart contracts have the potential to be integrated into the operations of IBs’ products that are based on tawarruq contracts. This study aims to investigate the potential application of blockchain-based smart contract technology in tawarruq contract operations within IBs and to suggest directions for future research. This study adopted a qualitative approach, drawing on relevant literature. The findings indicated that blockchain-based smart contracts can address Shariah Non-Compliance (SNC) issues in IB’s tawarruq operations while enhancing transaction transparency. This paper discussed the Shariah and operational challenges associated with blockchain technology and posits that blockchain-based smart contracts can improve the practices of tawarruq contracts within Islamic Banks. This paper offers insights for IB entities and regulatory authorities to evaluate the potential and impact of blockchain-based smart contracts within their operations and the broader financial system.

Bangladesh is one of the most vulnerable countries in the world to extreme climate events. With over 60% of its population living in rural areas, over a third of which lives under the poverty line and depends on agriculture, these climate stresses constitute a major challenge. The traditional financial instruments, e.g., microcredit and relief programs, continue today. However, how climate risk can be tackled through innovative financial instruments focusing on agriculture farms and farmers is crucial. Considering this issue, the Sadharan Bima Corporation and the Bangladesh Meteorological Department joined forces in 2014 to launch a $2.5 million three-year pilot project on weather-index-based crop insurance (WIBCI) executed by the Financial Institutions Division of the Bangladesh government’s Ministry of Finance. This study examined the basic strategy of this pilot project, the major challenges confronted, and possible solutions for creating a successful weather-index-based crop insurance scheme in Bangladesh. We relied on key informant interviews, informal discussions, focus group discussions, and in-depth interviews with the major stakeholders of the WIBCI pilot. These showed the WIBCI pilot to be a promising initiative that still faces problems from limited weather data, a costly business operations system, farmer insurance illiteracy, and fatalism, as well as problems with designing insurance products and recruiting qualified personnel. We compared this WIBCI pilot against the challenges of other projects, recommending best practices for a viable weather-index-based crop insurance system. The insurance mechanism of this study may apply to other vegetation sectors of Bangladesh, e.g., forest plantation or agroforestry for protecting natural resources from natural disasters.

A study has been conducted on Extreme Weather Events (EWEs) induced mortalities in Jammu and Kashmir, India during 2010-2022. In the present study, we used the frequency of heavy rain, heavy snow, lightning/thunderstorm, Hailstorm and squall during the period 2010 to 2022 of 10 stations of J&K from India Meteorological Department. The mortalities occurred due to these extreme weather events for each district were collected from the Meteorological Centre Srinagar. The mean monthly precipitation and number of rainy days for each month was calculated for each station based on 40 years data (1982 to 2022). During the past 12 years, (2010-2022) a total of 2863 EWEs occurred over J&K in which 552 deaths occurred till 31st December 2022. Among the various EWEs, lightning (1942) and heavy rainfall (409) events were more frequent. When we compare the mortality per event, the heavy snow was more destructive compared to any other EWEs. The mortality per event due to heavy snow was highest (4.33) as compared to other extreme events, although the number of events of heavy snow is less (42) as compared to heavy rain (409), flash floods (168) and lightning (1942). District wise results of EWEs results revealed the highest deaths due to heavy snow were observed over Kupwara, Bandipora, Baramulla and Ganderbal. Similarly for flash floods, the highest deaths were observed over Kishtwar, Anantnag, Ganderbaland Doda. The Pearson correlation results revealed highest correlation of total deaths for heavy rain (0.77) and heavy snow (0.69) (significant at p value p<0.01) followed by flash floods (0.492) (significant at p value p<0.05). Negative correlation result was observed between heavy snow and windstorm (0.584) (significant at p value p<0.05). The present study has shown that, for the union territory as a whole, the heavy rain and heavy snow have been two major disasters causing mortality, though flashfloods, thunderstorms and windstorms are gaining importance. The trend analysis results also revealed that there is a significant increase in mortality over the years particularly due to flash floods (R2 value 0.434) and windstorm (R2 value 0.371).

Changes in comparative advantage should reflect changes in factor endowment, but increasingly, changes in trade policies also affect a region's trade performance. Based on the arguments in Balassa's stages of comparative advantage thesis, this paper looks at the performance of manufacture exports in a number of Asian and Latin American economies over the period 1981-1997 and examines the revealed comparative advantage indices between economies in East Asia, Southeast Asia and Latin America. Although the RCA measurement may not distinguish between the factor endowment effects from the trade policy effect, we argue that RCA measures provide indication on the movement in a region's comparative advantage. The evidence strongly suggests that despite the strong export performance experienced by East Asian economies, they are losing their comparative advantage to the lower-tier economies in Southeast Asia and Latin America.

This study aims to analyze consumer recognition of the impact of extreme weather events on the Korean agricultural sector,BRand the social demand for government countermeasures addressing extreme weather events. For this study, food buyers who buy food mainly in their household were asked about their recognition of and how to cope with extreme weather events through a mail questionnaire survey, and the contingent valuation method was used to analyze their marginal willingness to pay for a policy to respond to extreme weather events. In the analysis, 80.2% of respondents said lower productivity and quality of agri-livestock products has a negative impact on consumption, and that they would reduce consumption (62.9%) or purchase substitutes (30.7%) when the prices of agri-livestock products rise while the quality worsens. This implies that lower productivity and quality of agri-livestock products has a negative impact on consumer welfare. While the analysis of marginal willingness to pay showed annual taxes have a negative impact on marginal willingness to pay, the positive impact of the prospect of incomes and extreme weather events on the marginal willingness to pay was statistically significant. The total willingness to pay to respond to extreme weather events in the agricultural sector measured about 860 billion won, which is greater than the current budget used for this purpose. This analysis suggests that greater awareness of the effects of extreme weather events on the agricultural sector is needed among consumers, so that they will view policies and costs related to addressing these issues more positively. The social demand for addressing extreme weather events related to climate change in the agricultural sector can be increased by educating the public about the frequency and intensity of extreme weather events.

Extreme weather events lead to many adverse societal, economic, and environmental consequences. Anthropogenic climate change has been identified as a factor that, in many cases, increases the frequency and intensity of these weather extremes. In the last two decades, the methods of Extreme Event Attribution (EEA) have been used to quantify the extent to which climate change affected the nature of specific recent extreme weather events. More recently, these methods are being combined with socioeconomic impact data to quantify extreme weather’s impacts attributable to climate change in what we term Extreme Event Impacts Attribution (EEIA). EEIA is a quickly developing field that considers which kinds of questions about the impacts of climate change on extreme weather events we should ask, what methods are best suited to answer them, how to interpret the results these methods provide, and what purpose these results can serve. In this survey, we discuss the basic structure and methods of EEIA, review the results of the existing EEIA studies, and discuss the implications and outlook for this strand of research including its relevance for quantification of climate change costs, the Loss and Damage Fund, climate litigation, or adaptation planning.