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This paper introduces a comprehensive approach to studying the impact of climate-related factors on commodity and financial markets using network analysis. We utilize a Bayesian network Vector Autoregressive model to investigate whether climate risk significantly influ-ences commodity prices and financial market returns. Our findings provide evidence of a climate effect on major commodities and global financial markets. Specifically, we identify Crude oil, Cotton, and Sugar as the commodities most affected by climate risk, with Gold demonstrating the least susceptibility. Additionally, we observe that climate-related risk on commodities is likely propagated by patterns such as PNA, NN1, and AO. In terms of financial markets, we find that stock markets in Hong Kong, India, and Spain are the most susceptible to climate risk, while Switzerland's market appears to be the least affected. Furthermore, we document evidence that climate-related risk capable of altering financial markets is likely propagated by factors like ENP, NN1, and WH. Overall, our study underscores the intricate relationship between climate factors and market dynamics, highlighting the importance of considering climate risk in assessing market behavior and performance.

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Lenders are likely to face significant financial risks from the shift to a low-carbon economy, but it remains unclear whether such risks are incorporated into their lending practices. The extent of this risk depends on whether banks incorporate such risks into their lending activity and whether financial instruments' tenors are long enough to cover the period when such risks materialize. Using a case study of shipping loans, we combine quantitative data and semi-structured interviews with key shipping debt providers. Our results show that banks, in particular signatories of the Poseidon Principles, a voluntary disclosure initiative in shipping, have started to price in the climate score of shipowners they lend to after the Paris Agreement but on a corporate rather than an asset basis. However, signatories do not differentiate their margins based on a ship's carbon intensity, despite a relatively long loan maturity, reinforcing the limitations of disclosure initiatives to influence investment outlays.

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In light of the escalating global warming and the escalating frequency of extreme weather events, the agricultural sector, being a fundamental and pivotal industry worldwide, is encountering substantial challenges due to climate change. Using Chinese provincial panel data for 2000-2021, this paper utilizes a two-way fixed-effect model to investigate the impact of Climate Risk (CR) on green total factor productivity in agriculture (AGTFP), with China's climate policy uncertainty (CPU) being introduced as a moderating variable within the research framework to scrutinize its influence in this context. The findings reveal a noteworthy adverse effect of CR on AGTFP, further exacerbated by CPU. Heterogeneity analysis results show that there is a clear regional variation in the effect of CR on AGTFP across different Chinese regions, with CR significantly inhibiting AGTFP development in the northern regions and provinces in major grain producing regions. Consequently, there is a pressing necessity to bolster the establishment of climate change monitoring infrastructures, devise tailored climate adaptation strategies at a regional level, and enhance the clarity and predictability of climate policies to fortify the resilience and sustainability of agricultural production systems.

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BACKGROUND: Coffee (Coffea arabica L.) is one of the most important commodities today, with a high economic value worldwide. Coffee leaf rust (Hemileia vastatrix Berk. et Br.) has been showing a high impact on Brazilian coffee trees among the various diseases that attack coffee. The climate has a great influence on the development of diseases, especially when fungi are the causal agents. This study aimed to carry out the zoning of climate favorability for coffee leaf rust in the traditional and main coffee-producing regions of Brazil. The study was conducted in 13 locations in the states of Paraná, São Paulo, Rio de Janeiro, Espírito Santo, Minas Gerais, Goiás and Bahia. Air temperature and daily precipitation data for the current scenario were collected using the WorldClim version 2.1 platform for the last climatological normal and future climate change data. The ideal climate conditions for coffee leaf rust consist of a mean air temperature ranging from 21 to 25 °C and precipitation >30 mm per month. The Coupled Model Intercomparison Projects scenarios associated with the Intergovernmental Panel on Climate Change reports consisted of the Shared Socio-Economic Pathways SSP-1 2.6, SSP-2 4.5, SSP-3 7.0 and SSP-5 8.5, the latter being considered one of the most catastrophic. All steps to carry out the suitability zoning were performed in a tool using the QGIS geographic information system software. RESULTS: Zoning for coffee leaf rust had three classes: favorable, relatively favorable and unfavorable. Currently, the largest coffee-producing region in Brazil has 49.1% of its analyzed area classified as favorable, 39.2% as relatively favorable and 11.7% as unfavorable. In the current scenario, Patrocínio and Três Pontas are locations with high coffee production in which the favorable class is predominant. The state of Minas Gerais has an annual mean of 55.3% of its entire territory apt for the disease, with the highest occurrence between September and March. CONCLUSIONS: Climate change has a negative impact on the development of coffee leaf rust, mainly in the long term, as in the period of 2081-2100, in which the SSP-5 8.5 scenario led to a decrease in the favorable and unfavorable areas and an increase in the relatively favorable areas of 9.8%, 18.6% and 71.5% for the Brazilian territory, respectively. © 2024 Society of Chemical Industry.

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We summarize historic New York City (NYC) climate change trends and provide the latest scientific analyses on projected future changes based on a range of global greenhouse gas emissions scenarios. Building on previous NPCC assessment reports, we describe new methods used to develop the projections of record for sea level rise, temperature, and precipitation for NYC, across multiple emissions pathways and analyze the issue of the "hot models" associated with the 6th phase of the Coupled Model Intercomparison Project (CMIP6) and their potential impact on NYC's climate projections. We describe the state of the science on temperature variability within NYC and explain both the large-scale and regional dynamics that lead to extreme heat events, as well as the local physical drivers that lead to inequitable distributions of exposure to extreme heat. We identify three areas of tail risk and potential for its mischaracterization, including the physical processes of extreme events and the effects of a changing climate. Finally, we review opportunities for future research, with a focus on the hot model problem and the intersection of spatial resolution of projections with gaps in knowledge in the impacts of the climate signal on intraurban heat and heat exposure.

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Climate change leading to Climate extremes in the twenty-first century is more evident in megacities across the world, especially in West Africa. The Greater Accra region is one of the most populated regions in West Africa. As a result, the region has become more susceptible to climate extremes such as floods, heatwaves, and droughts. The study employed the Coupled Model Intercomparison Project 6 models in simulating climate extreme indices under the Shared Socioeconomic Pathway scenarios (SSPs) over West Africa between 1979 and 2059 as exemplified by the Greater Accra region. The study observed a generally weak drought in the historical period and expected to intensify especially under SSP585 in Greater Accra. For instance, continuous dry days (CDD) reveal an increasing trend under the SSPs. Similarly, the overall projected trend of CDD over West Africa reveals an increase signifying a more frequent and longer drought in the future. The flood indices revealed a surge in the intensity and duration of extreme precipitation events under the SSPs in the region. For instance, R99pTOT and Rx5days are expected to significantly increase under the SSPs with intensification under the SSP245, SSP370, and SSP585. A similar trend has been projected across West Africa, especially along the Guinean coast. The study foresees a gradual and intensifying rise in heatwave indices over the Greater Accra region. The warming and cooling indices reveal an increasing and decreasing trend respectively in the historical period as well as under the SSPs particularly within urban centers like Accra and Tema. Most West African countries are projected to observe more frequent warm days and nights with cold nights and days becoming less frequent. Expected effects of future climate extreme indices pose potential threats to the water, food, and energy systems as well as trigger recurrent floods and droughts over Greater Accra. The findings of the study are expected to inform climate policies and the nationally determined contribution of the Paris Agreement as well as address the sustainable development goal 11 (Sustainable cities) and 13 (Climate action) in West Africa.

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How to address climate risks and achieve green transformation has become a critical issue that businesses urgently need to consider. We apply growth option theory and prospect theory to examine the impact of corporate climate risk perceptions on green outward foreign direct investment (GFDI) using a research sample of heavily polluting listed companies in China from 2009 to 2022. Our findings reveal that companies with higher perceived climate risks tend to increase their inclination towards GFDI, and the informal hierarchy of boards reinforces the positive effect of both. Supplementary analyses indicate that through GFDI, corporations can exert positive effects on their own environmental performance and future green innovations. The positive impact is notably more visible in nonstate-owned companies and sample units from provinces along the Belt and Road. These findings extend the economic consequences of climate risk at the firm level from the perspective of international business research and provide empirical references for firms to promote their own green transformation from a practical perspective.

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We examine the impact of climate risk on discouraged borrowers among small and medium-sized enterprises (SMEs) in the eurozone, using a unique European Central Bank dataset focusing on the demand side of credit markets. We argue that two opposing channels may exist in this relationship: Either climate risk has a negative effect stemming from increased demand for sustainable or climate-resilient projects that enhance creditworthiness, or climate risk has a positive effect arising from heightened climate uncertainty and risk aversion, leading to credit self-rationing among SMEs. Our findings reveal that heightened climate risk prompts SMEs to self-ration credit, leading to higher probabilities of discouraged borrowers. Our research deepens the understanding of the impact of climate risk on credit-related decisions, stressing the need for proactive measures to integrate climate risk assessments into regulatory frameworks and lending practices. The findings underscore the vulnerability of SMEs to climate risk, emphasizing emphasizing the importance of tailored support mechanisms for economic resilience.

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This Introduction to NPCC4 provides an overview of the first three NPCC Reports and contextualizes NPCC4's deliberate decision to address justice, equity, diversity, and inclusion in its collective work and in its own practices, procedures, and methods of assessment. Next, it summarizes the assessment process, including greater emphasis on sustained assessment. Finally, it introduces the NPCC4 chapters and their scope.

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Building on prior research on managerial ownership and firm performance, this study is the first to link CEO ownership to carbon commitment. We examine if firms led by CEOs with substantial ownership are more or less inclined to prioritise reducing carbon emissions than those without such ownership. We find that higher CEO ownership is associated with a lower carbon commitment, indicating that CEOs with more significant ownership do not prioritise carbon emissions reduction. However, we notice an inverted U-shaped relationship. Particularly, moderate CEO ownership (between 5% and 10% of total shares) has the stronger impact. The results are robust to alternative measures and approaches. The study provides empirical evidence on how CEO ownership can influence corporate carbon commitment and contribute to the global fight against climate change.

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New York City (NYC) faces many challenges in the coming decades due to climate change and its interactions with social vulnerabilities and uneven urban development patterns and processes. This New York City Panel on Climate Change (NPCC) report contributes to the Panel's mandate to advise the city on climate change and provide timely climate risk information that can inform flexible and equitable adaptation pathways that enhance resilience to climate change. This report presents up-to-date scientific information as well as updated sea level rise projections of record. We also present a new methodology related to climate extremes and describe new methods for developing the next generation of climate projections for the New York metropolitan region. Future work by the Panel should compare the temperature and precipitation projections presented in this report with a subset of models to determine the potential impact and relevance of the "hot model" problem. NPCC4 expects to establish new projections-of-record for precipitation and temperature in 2024 based on this comparison and additional analysis. Nevertheless, the temperature and precipitation projections presented in this report may be useful for NYC stakeholders in the interim as they rely on the newest generation of global climate models.

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The planned relocation of communities away from areas of climate-related risk has emerged as a critical strategy to adapt to the impacts of climate change. Empirical examples from around the world show, however, that such relocations often lead to poor outcomes for affected communities. To address this challenge, and contribute to developing guidelines for just and sustainable relocation processes, this paper calls attention to three fundamental tensions in planned relocation processes: (1) conceptualizations of risk and habitability; (2) community consultation and ownership; and (3) siloed policy frameworks and funding mechanisms. Drawing on the collective experience of 29 researchers, policymakers and practitioners from around the world working on planned relocations in the context of a changing climate, we provide strategies for collectively and collaboratively acknowledging and navigating these tensions among actors at all levels, to foster more equitable and sustainable relocation processes and outcomes.

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Extreme climate events have become more frequent and have had serious impacts on the global community. Consequently, the risk associated with climate change has gained increasing attention and has been considered as a new source of risk factors. To understand the socio-economic impacts of this new risk, systematically measuring risk around the world is critical for researchers and policymakers. Building on daily observations from meteorological stations, a Climate Physical Risk Index (CPRI) dataset is constructed for 170 countries, paying special attention to four extreme climate events: extreme low temperature (LTD), extreme high temperature (HTD), extreme rainfall (ERD), and extreme drought (EDD). A comprehensive index of climate physical risk for each country has also been constructed, covering the period from 1993 to 2023. The dataset will be updated regularly. Subnational indices or more detailed regional indices are available upon request.

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Based on empirical analysis of 113 climate disasters affecting 3563 listed firms across 31 provinces in China from 2010 to 2022, as documented in the Emergency Events Database (EM-DAT), this study employs event study and multiple regression to explore the impact of proactive green innovation on firm climate resilience. By categorizing proactive green innovation into process and product innovation and climate resilience into short-term and long-term resilience, a proactive green innovation-firm climate resilience 2 × 2 matrix is constructed to provide innovative insights. This study reveals that proactive green innovation enhances firm climate resilience. Specifically, proactive green process innovation both enhances short-term and long-term climate resilience, while proactive green product innovation only enhances long-term rather than short-term climate resilience. Furthermore, climate disaster has inverted U-shaped interaction effect on the relationship between proactive green innovation and short-term climate resilience and U-shaped interaction effect on the relationship between proactive green innovation and long-term climate resilience. Additionally, this study also investigates the heterogeneous mechanisms of proactive green innovation enhancing short-term and long-term climate resilience based on network embeddedness theory and legitimacy theory.

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Prospective risks from climate change impacts in ocean and coastal systems are urging the implementation of nature-based solutions (NBS). These are climate-resilient strategies to maintain biodiversity and the delivery of ecosystem services, contributing to the adaptation of social-ecological systems and the mitigation of climate-related impacts. However, the effectiveness of measures like marine restoration or conservation is not exempt from the impacts of climate change, and the degree to which they can sustain biodiversity and ecosystem services remains unknown. Such uncertainty, together with the slow pace of implementation, causes decision-makers and societies to demand a better understanding of NBS effects. To address this gap, in this study, we use the risk mitigation capacity of marine NBS as a proxy for their effectiveness while providing a toolset for the implementation of the method. The method considers environmental data and relies on expert elicitation, allowing us to go beyond current practice to evaluate the effectiveness of NBS in reducing habitat or species risks under different future socio-political and climate-change scenarios. As a result, we present a ready-to-use tool, and supporting materials, for the implementation of the Climate Risk Assessment method and an illustrative example considering the application of the NBS "nature-inclusive harvesting" in two shellfisheries. The method works as a rapid assessment that guarantees comparability across sites and species due to its low data or resource demand, so it can be widely incorporated to adaptation policies across the marine realm.

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The enforcement of a global hydrofluorocarbon (HFC) refrigerant phase down led to the introduction of hydrofluoroolefins (HFOs) as a low Global Warming Potential (GWP) substitute, given their low atmospheric lifetime. However, to this date it is not fully clear the long-term atmospheric fate of HFOs primary degradation products: trifluoro acetaldehyde (TFE), trifluoro acetyl fluoride (TFF), and trifluoroacetic acid (TFA). It particularly concerns the possibility of forming HFC-23, a potent global warming agent. Although the atmospheric reaction networks of TFE, TFF, and TFA have a fair level of complexity, the relevant atmospheric chemical pathways are well characterized in the literature, enabling a comprehensive hazard assessment of HFC-23 formation as a secondary HFO breakdown product in diverse scenarios. A lower bound of the HFOs effective GWP in a baseline scenario is found above regulatory thresholds. While further research is crucial to refine climate risk assessments, the existing evidence suggests a non-negligible climate hazard associated with HFOs.

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Greenhouse gas emissions are considered the culprit of extreme high temperatures, and low-carbon transformation has become a global consensus. The low-carbon action by enterprises is an inevitable choice if they are to adapt to economic and social needs. Green innovation is an important measure for enterprises to respond to the challenges of low-carbon transformation. This study mainly discusses the causal relationship between extreme high temperatures and green innovation of enterprises. Using China's industrial enterprise database, we construct county-annual panel data from 2000 to 2013. Results show that extreme high temperatures improve the level of green innovation of enterprises. After a series of robustness tests, the results remain. Mechanism analysis shows that extreme high temperatures increase the environmental concerns of the government, the public, and society, thus strengthening government regulation, public participation, and social supervision as well as encouraging enterprises to carry out green innovation. Our heterogeneous analysis shows that in the eastern region with a high level of legal system and economic development, it is easier to promote green innovation for enterprises. In addition, large-scale enterprises are more willing to carry out green innovation after experiencing a heat wave.

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The frequent occurrence of extreme weather events has imparted significant pressure on urban ecosystem management. Evaluating the relationship between extreme climate risk (ECR) and urban ecological resilience (UER) is a key issue in achieving the green and sustainable development objectives of cities. This study measures UER in China from 2005 to 2020 using the entropy weight method-TOPSIS method, investigates the relationship between ECR and UER using the dynamic GMM model, and further explores the influencing mechanism. The results suggest that ECR has an inhibiting influence on UER. Additionally, the moderating mechanism investigation demonstrates that environmental regulation can mitigate the threat of ECR to UER to a certain extent, and with the regulation effect based on the government's environmental concern being better than that of the market pollution fee payment. The group test outcomes demonstrate that the discrepancies in regions and marketization lead to certain differences in the relationship between ECR and UER. Additional investigation indicates that ECR has an asymmetric relationship with UER at distinct quantiles. Our findings reflect the subtle associations between ECR and UER as a whole, and will help relevant organizations in formulating more precise and scientific policies to enhance urban ecological resilience.

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With global warming, cities are vulnerable to extreme weather, increasing the climate risk to cities worldwide. Although existing literature has examined the ex-post impacts of extreme weather, it is less clear how climate risk affects cites before extreme weather occur. To lower the risk of urban waterlogging, which is caused by extreme weather, and improve the ability of cities to adapt to extreme weather, China launched the Sponge City Project (SCP) in 2013 to manage the urban stormwater and waterlogging. Adopting the SCP pilot in China as a quasi-natural experiment, we examine the impact of the climate risk caused by urban stormwater and waterlogging on the house price with the difference-in-differences (DID) method. We find that after implementing the SCP pilot program, the house price in pilot cities increased significantly because of the improvement in cities' resilience to climate risk. Additionally, this effect was only demonstrated in cities with a high waterlogging risk. For SCP pilot cities with lower waterlogging risk, the house price is not significantly affected by SCP implementation. This indicates that the house price in China is sensitive to the climate risk caused by the urban stormwater and waterlogging. Our findings also contribute to the understanding of the significance of the climate risk management, and provided theoretical evidence for urban governance.

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Currently, more than half of the world's human population lives in urban areas, which are increasingly affected by climate hazards. Little is known about how multi-hazard environments affect people, especially those living in urban areas in northern latitudes. This study surveyed homeowners in Anchorage and Fairbanks, USA, Alaska's largest urban centers, to measure individual risk perceptions, mitigation response, and damages related to wildfire, surface ice hazards, and permafrost thaw. Up to one third of residents reported being affected by all three hazards, with surface ice hazards being the most widely distributed, related to an estimated $25 million in annual damages. Behavioral risk response, policy recommendations for rapidly changing urban environments, and the challenges to local governments in mitigation efforts are discussed.

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