Paesaggi marginali nel paesaggio culturale UNESCO delle Colline del Prosecco di Conegliano e Valdobbiadene Per una topografia della resilienza al cambiamento climatico

This paper begins with a discussion on the potential of the cultural landscape of the Colline del Prosecco to play an experimentative role in climate-resilience, and presents a research project that looks at the marginal areas in this UNESCO Buffer Zone as spaces that could play a decisive role in climate change adaptation strategies. By means of field explorations and meetings with the residents, it has been possible to identify a set of sample areas that model a potential operative topography for local groups and communities to elaborate shared resilient adaptation scenarios.

Climate change adaptation networks for small and medium-sized cities

Cities are particularly vulnerable to the impacts of climate change. Many larger cities have identified the potential impacts of different climate change adaptation scenarios. However, their smaller and medium-sized counterparts are often not able to address climate risks effectively due to a lack of necessary resources. Since a large number of cities worldwide are indeed small and medium-sized, this lack of preparedness represents a crucial weakness in global response systems. A promising approach to tackling this issue is to establish regional municipal networks. Yet, how might a regional network for small and medium-sized cities be systematically designed and further developed? Focussing on the German federal state of Baden-Wuerttemberg, we have explored this question by applying a participatory action research approach. As part of our research, we established a regional network framework for small and medium-sized cities. The framework supports small and medium-sized cities in identifying key regional actors, while taking local and regional contextual factors into account. Based on our findings, we suggest that other small and medium sized cities follow these steps: develop the knowledge base; build the network; and transfer and consolidate knowledge.

Climate effects on US infrastructure: the economics of adaptation for rail, roads, and coastal development

Changes in temperature, precipitation, sea level, and coastal storms will likely increase the vulnerability of infrastructure across the USA. Using models that analyze vulnerability, impacts, and adaptation, this paper estimates impacts to railroad, roads, and coastal properties under three infrastructure management response scenarios: No Adaptation; Reactive Adaptation, and Proactive Adaptation. Comparing damages under each of these potential responses provides strong support for facilitating effective adaptation in these three sectors. Under a high greenhouse gas emissions scenario and without adaptation, overall costs are projected to range in the $100s of billions annually by the end of this century. The first (reactive) tier of adaptation action, however, reduces costs by a factor of 10, and the second (proactive) tier reduces total costs across all three sectors to the low $10s of billions annually. For the rail and road sectors, estimated costs for Reactive and Proactive Adaptation scenarios capture a broader share of potential impacts, including selected indirect costs to rail and road users, and so are consistently about a factor of 2 higher than prior estimates. The results highlight the importance of considering climate risks in infrastructure planning and management.

Building Climate Change Adaptation Scenarios with Stakeholders for Water Management: A Hybrid Approach Adapted to the South Indian Water Crisis

Climate change threatens the sustainability of agriculture and natural resources. Adaptive solutions must be designed locally with stakeholders. We developed the Approach for Building Adaptation Scenarios with Stakeholders (ABASS), which aims to identify adaptation policies and corresponding scenarios of natural resource management in the context of climate change. Its originality is the combination of different existing participatory methods, organized in three phases. In step 1, experts identify local environmental problems on a map and build the assumption tree of local climate change effects. In step 2, experts identify stakeholders. Step 3 leads to the construction of adaptation scenarios with stakeholders in two phases. First, in a participatory workshop gathering numerous stakeholders, the assumption tree is presented to help stakeholders identify potential policies that address the effects of climate change. Then, using the map produced in step 1, each group of stakeholders separately translates each potential policy into a detailed scenario. We applied ABASS to the context of groundwater overexploitation in South India. Two policies at the farm level emerged as consensual: (i) ponds to harvest runoff water and (ii) drip irrigation to conserve water; but their implementation highlights the differences of opinion among stakeholders.

Numerical simulation of thermal effects of urban green enhancements in different urban environments in the city of Augsburg (Bavaria, SE Germany)

<p><span><span>The interdisciplinary research project Abc (Augsburg bleibt cool – Augsburg stays cool) – funded by the German Federal Ministry for Environment, Nature Conservation and Nuclear Safety – deals with different aspects of heat-stress exposure and adaptation to heat-stress in </span></span><span><span>indoor and outdoor </span></span><span><span>urban environments </span></span><span><span>in the urban area of Augsburg (Bavaria, SE Germany)</span></span><span><span>.</span></span></p><p><span><span>As one essential research approach this includes the estimation of the thermal effects of vegetation enhancements in different urban environments via numerical simulations performed with the ENVI-met V4 numerical model.</span></span></p><p><span><span>For several model domains – </span></span><span><span>each of them </span></span><span><span>covering 300 m x 300 m with a 2 m x 2 m horizontal resolution - model runs have been performed utilizing observational data for a heat wave end of Ju</span></span><span><span>ly</span></span><span><span> 2019 as meteorological forcing, </span></span><span><span>thus serving as a climate analogue for thermal conditions expected to appear more frequently under future climate change conditions. For each domain model runs for the current-state and several adaptation scenarios have been performed. Adaptation scenarios thereby comprise varying measures for enhancing urban green (street and facade greening) and blue infrastructure.</span></span></p><p><span><span>I</span></span><span><span>n this contribution we present and discuss selected model settings and scenarios.</span></span></p><p><span><span>Model results indicate the general capability of vegetation enhancements to counteract heat-stress exposure in urban environments. </span></span><span><span>However, </span></span><span><span>partly also contrary effects emerge pointing to </span></span><span><span>the </span></span><span><span>complex interdependencies within the urban climate system </span></span><span><span>which have to be taken into account when projecting urban heat island adaptation strategies.</span></span></p>

Research on the Application of Blockchain Technology in the Management of Financial Transfer Payment

Blockchain technology is considered to be a subversive innovation of computing mode after mainframe, personal computer and Internet. In the financial, medical, supply chain and other industries show great development potential. As an important part of financial management, financial transfer payment system is an important part of modern financial system. This paper combines blockchain technology with the management of financial transfer payment, analyzes the adaptation scenarios of blockchain technology, summarizes the status and development bottleneck of financial transfer payment informatization, tries to establish a financial transfer payment system based on blockchain technology, describes the advantages of blockchain technology in supporting the management of financial transfer payment, and puts forward suggestions on the possible problems.

A cost–benefit analysis of implementing urban heat island adaptation measures in small- and medium-sized cities in Austria

Urban heat islands are an increasing concern even in small- to medium-sized cities, although these areas are still understudied especially in terms of the economic feasibility of adaptation options. This paper uses adaptation scenarios produced by an urban climate model as inputs to a social cost–benefit analysis in three small- to medium-sized cities in Austria: Mödling, Klagenfurt, and Salzburg. The adaptation scenarios, which consider measures such as increasing the reflectivity of different sealed surfaces (referred to as the White City scenario) as well as greening measures (i.e. the Green City scenario), show decreases in the number of hot days (Tmax ≥30°C) when implemented. Benefits include reductions in heat-related mortality, which are modeled based on trends of daily mortality and climate data, reduced morbidity, productivity loss, and numerous urban ecosystem services. The results demonstrate favorable benefit–cost ratios of a combination of measures (White and Green City) of 1.27, 1.36, and 2.68 for Mödling, Klagenfurt, and Salzburg, respectively, indicating positive economic grounds for supporting policies in line with the adaptation scenarios. Furthermore, results of the Green City vs. White City showed higher benefits for the combined and Green City scenarios despite higher costs for each of the cities.

A Generalized Framework for Assessing Flood Risk and Suitable Strategies under Various Vulnerability and Adaptation Scenarios: A Case Study for Residents of Kyoto City in Japan

This study proposes a generalized framework for the assessment of flood risk and potential strategies to mitigate flood under various vulnerability and adaptation scenarios. The possible causes of hazard, exposure and vulnerability in flood disaster were clearly identified by using a climate risk template. Then, levels of exposure and vulnerability with adaptive capacity and sensitivity were further defined by a quantification approach, and the climate risk maps were consequently provided. The potential possible climate adaptation strategies were investigated through the comparison of climate risk maps with diverse adaptation options. The framework was demonstrated in the Kyoto City in Japan with residents as a target population to reduce the flood risk. The results indicate that the government should pay attention to reducing the population in flood-prone areas and adopt diverse adaptation strategies to reduce the flood risk to the residents. Rainwater storage and green roofs as adaptation strategies as short-term planning options are recommended. The construction of detention ponds has been suggested to prevent flood risks in future as a part of the long-term planning process. In conclusion, the proposed framework is expected to be a suitable tool for supporting climate risk analysis in the context of flood disasters.

C2DAN: An Improved Deep Adaptation Network with Domain Confusion and Classifier Adaptation

Deep neural networks have been successfully applied in domain adaptation which uses the labeled data of source domain to supplement useful information for target domain. Deep Adaptation Network (DAN) is one of these efficient frameworks, it utilizes Multi-Kernel Maximum Mean Discrepancy (MK-MMD) to align the feature distribution in a reproducing kernel Hilbert space. However, DAN does not perform very well in feature level transfer, and the assumption that source and target domain share classifiers is too strict in different adaptation scenarios. In this paper, we further improve the adaptability of DAN by incorporating Domain Confusion (DC) and Classifier Adaptation (CA). To achieve this, we propose a novel domain adaptation method named C2DAN. Our approach first enables Domain Confusion (DC) by using a domain discriminator for adversarial training. For Classifier Adaptation (CA), a residual block is added to the source domain classifier in order to learn the difference between source classifier and target classifier. Beyond validating our framework on the standard domain adaptation dataset office-31, we also introduce and evaluate on the Comprehensive Cars (CompCars) dataset, and the experiment results demonstrate the effectiveness of the proposed framework C2DAN.