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Studies on autonomous driving have started to focus on snowy environments, and studies to acquire data and remove noise and pixels caused by snowfall in such environments are in progress. However, research to determine the necessary weather information for the control of unmanned platforms by sensing the degree of snowfall in real time has not yet been conducted. Therefore, in this study, we attempted to determine snowfall information for autonomous driving control in snowy weather conditions. To this end, snowfall data were acquired by LiDAR sensors in various snowy areas in South Korea, Sweden, and Denmark. Snow, which was extracted using a snow removal filter (the LIOR filter that we previously developed), was newly classified and defined based on the extracted number of snow particles, the actual snowfall total, and the weather forecast at the time. Finally, we developed an algorithm that extracts only snow in real time and then provides snowfall information to an autonomous driving system. This algorithm is expected to have a similar effect to that of actual controllers in promoting driving safety in real-time weather conditions.

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OBJECTIVE: Severe weather events exacerbate existing health disparities due to poorly managed non-communicable diseases (NCDs). Our objective is to understand the experiences of staff, providers, and administrators (employees) of Federally Qualified Health Centers (FQHCs) in Puerto Rico and the US Virgin Islands (USVI) in providing care to patients living with NCDs in the setting of recent climate-related extreme events. METHODS: We used a convergent mixed-methods study design. A quantitative survey was distributed to employees at 2 FQHCs in Puerto Rico and the USVI, assessing experience with disasters, knowledge of disaster preparedness, the relevance of NCDs, and perceived gaps. Qualitative in-depth interviews explored their experience providing care for NCDs during recent disasters. Quantitative and qualitative data were merged using a narrative approach. RESULTS: Through the integration of quantitative and qualitative data, we recognize: (1) significant gaps in confidence and preparedness of employees with a need for more training; (2) challenges faced by persons with multiple NCDs, especially cardiovascular and mental health disorders; and (3) most clinicians do not discuss disaster preparedness with patients but recognize their important role in community resilience. CONCLUSION: With these results, we recommend strengthening the capacity of FQHCs to address the needs of their patients with NCDs in disasters.

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Climate change, a pressing global concern, poses significant challenges to agricultural systems worldwide. Among the myriad impacts of climate change, the cultivation of kiwifruit trees (Actinidia spp.) faces multifaceted challenges. In this review, we delve into the intricate effects of climate change on kiwifruit production, which span phenological shifts, distributional changes, physiological responses, and ecological interactions. Understanding these complexities is crucial for devising effective adaptation and mitigation strategies to safeguard kiwifruit production amidst climate variability. This review scrutinizes the influence of rising global temperatures, altered precipitation patterns, and a heightened frequency of extreme weather events on the regions where kiwifruits are cultivated. Additionally, it delves into the ramifications of changing climatic conditions on kiwifruit tree physiology, phenology, and susceptibility to pests and diseases. The economic and social repercussions of climate change on kiwifruit production, including yield losses, livelihood impacts, and market dynamics, are thoroughly examined. In response to these challenges, this review proposes tailored adaptation and mitigation strategies for kiwifruit cultivation. This includes breeding climate-resilient kiwifruit cultivars of the Actinidia species that could withstand drought and high temperatures. Additional measures would involve implementing sustainable farming practices like irrigation, mulching, rain shelters, and shade management, as well as conserving soil and water resources. Through an examination of the literature, this review showcases the existing innovative approaches for climate change adaptation in kiwifruit farming. It concludes with recommendations for future research directions aimed at promoting the sustainability and resilience of fruit production, particularly in the context of kiwifruit cultivation, amid a changing climate.

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Low-pressure systems (LPSs) are among the most critical weather systems, producing excessive precipitation that causes air temperatures to drop and rise considerably. Acute temperature changes directly affect poultry feed intake (FI) and laying performance. To explore the effects of LPSs on hens, the parameters of air temperature, relative humidity, egg production, and feed utilization efficiency were evaluated during different LPSs in three houses. Results indicated that about 2.8 ± 0.7 d, 2.4 ± 0.5 d, and 2.4 ± 0.5 d before the LPS landfall in houses 1, 2, and 3, respectively, the indoor air temperature started to decrease, with the average decreases being 1.7 °C ± 0.4 °C, 2.4 °C ± 0.6 °C, and 1.8 °C ± 0.4 °C, respectively. Significant differences were observed between different LPSs for reducing indoor air temperature (p < 0.05) in the three houses. In house 1, the egg production rates (EPRs) were decreased by 6.6% and 1.1% when LPSs 1 and 2 landed. The average egg weight (AEW) and FI during the LPS landfall were significantly higher than those before the LPS landfall (p < 0.01). Under successive LPSs landfall in the three houses, the EPRs initially reduced by 3.9%, 4.0%, and 0.5%, respectively, but the second LPS event increased the EPRs by 1.8%, 5.3%, and 1.0%, respectively. Furthermore, the LPS landfall increased the feed conversion ratio (FCRe) in the three houses, all above 2.00. In conclusion, LPSs can reduce heat stress, lower the EPRs, and lead to higher FI, FCRe, and AEW.

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Marine heatwaves (MHWs) are increasing in frequency and intensity, threatening marine organisms and ecosystems they support. Yet, little is known about impacts of intensifying MHWs on ecologically and economically important bivalves cultured in the South China Sea. Here, we compared survival and physiological responses of five bivalve species, Pinctada fucata, Crassostrea angulata, Perna viridis, Argopecten irradians and Paphia undulata, to two consecutive MHWs events (3 days of thermal exposure to + 4 °C or + 8 °C, following 3 days of recovery under ambient conditions). While P. fucata, P. viridis, and P. undulata are native to the South China Sea region, C. angulata and A. irradians are not. Individuals of P. fucata, C. angulata and P. viridis had higher stress tolerance to MHWs than A. irradians and P. undulata, the latter already experiencing 100% mortality under +8 °C conditions during the first event. With increasing intensity of MHWs, standard metabolic rates of all five species increased significantly, in line with significant depressions of function-related energy-metabolizing enzymes (CMA, NKA, and T-ATP). Likewise, activities of antioxidant enzymes (SOD, CAT, and MDA) and shell mineralization-related enzymes (AKP and ACP) responded significantly to MHWs, despite species-specific performances observed. These findings demonstrate that some bivalve species can likely fail to accommodate intensifying MHWs events in the South China Sea, but some may persist. If this is the case, then one would expect substantial loss of fitness in bivalve aquaculture in the South China Sea under intensifying MHWs conditions.

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Extreme precipitation can significantly influence the water quality of surface waters. However, the total amount of bacteria carried by rainfall runoff is poorly understood. Here, thirty rainfall scenarios were simulated by artificial rainfall simulators, with designed rainfall intensity ranging from 19.3 to 250 mm/h. The instantaneous concentration ranges of R2A, nutrient agar (NA) culturable bacteria, and viable bacteria in runoff depended on the types of underlying surfaces. The instantaneous bacterial concentrations in runoff generated by forest lands, grasslands and bare soil were: R2A culturable bacteria = 104.5-6.3, 104.5-6.1, 104.0-5.3 colony-forming units (CFU)/mL, NA culturable bacteria = 104.0-6.0, 103.9-5.8, 103.2-4.9 CFU/mL, and viable bacteria = 106.4-8.0, 107.0-8.9, 106.4-7.6 cells/mL. Based on the measured bacterial instantaneous concentration in runoff, cumulative dynamic models were established, and the maximum amount of culturable bacteria and viable bacteria entering water sources were estimated to be 109.38-11.31 CFU/m2 and 1011.84-13.25 cells/m2, respectively. The model fitting and the bacterial accumulation dynamics were influenced by the rainfall types (p < 0.01). Surface runoff from the underlying surface of forest lands and grasslands had a high microbial risk that persisted even during the "Drought-to-Deluge Transition". Bacterial accumulation models provide valuable insight for predicting microbial risks in catchments during precipitation and can serve as theoretical support for further ensuring the safety of drinking water under the challenge of climate change.

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The U.S. Gulf of Mexico contains a complex network of existing, decommissioned, and abandoned oil and gas pipelines, which are susceptible to a number of stressors in the natural-engineered offshore system including corrosion, environmental hazards, and human error. The age of these structures, coupled with extreme weather events increasing in intensity and occurrence from climate change, have resulted in detrimental environmental and operational impacts such as hydrocarbon release events and pipeline damage. To support the evaluation of pipeline infrastructure integrity for reusability, remediation, and risk prevention, the U.S. Gulf of Mexico Pipeline and Reported Incident Datasets were developed and published. These datasets, in addition to supporting advanced analytics, were constructed to inform regulatory, industry, and research stakeholders. They encompass more than 490 attributes relating to structural information, incident reports, environmental loading statistics, seafloor factors, and potential geohazards, all of which have been spatially, and in some cases temporally matched to more than 89,000 oil and gas pipeline locations. Attributes were acquired or derived from publicly available, credible resources, and were processed using a combination of manual efforts and customized scripts, including big data processing using supercomputing resources. The resulting datasets comprise a spatial geodatabase, tabular files, and metadata. These datasets are publicly available through the Energy Data eXchange®, a curated online data and research library and laboratory developed by the U.S. Department of Energy's National Energy Technology Laboratory. This article describes the contents of the datasets, details the methods involved in processing and curation, and suggests application of the data to inform and mitigate risk associated with offshore pipeline infrastructure in the Gulf of Mexico.

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With climate extremes hitting nations across the globe, disproportionately burdening vulnerable developing countries, the prompt operation of the Loss and Damage fund is of paramount importance. As decisions on resource disbursement at the international level, and investment strategies at the national level, loom, the climate science community's role in providing fair and effective evidence is crucial. Attribution science can provide useful information for decision makers, but both ethical implications and deep uncertainty cannot be ignored. Considering these aspects, we articulate a vision that integrates established attribution methods and multiple lines of evidence within a coherent logical framework.

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BACKGROUND: The impact of weather on human health has been proven, but the impact of extreme weather events on cardiometabolic multimorbidity (CMM) needs to be urgently explored. OBJECTIVES: Investigating the impact of extreme temperature, relative humidity (RH), and laboratory testing parameters at admission on adverse events in CMM hospitalizations. DESIGNS: Time-stratified case-crossover design. METHODS: A distributional lag nonlinear model with a time-stratified case-crossover design was used to explore the nonlinear lagged association between environmental factors and CMM. Subsequently, unbalanced data were processed by 1:2 propensity score matching (PSM) and conditional logistic regression was employed to analyze the association between laboratory indicators and unplanned readmissions for CMM. Finally, the previously identified environmental factors and relevant laboratory indicators were incorporated into different machine learning models to predict the risk of unplanned readmission for CMM. RESULTS: There are nonlinear associations and hysteresis effects between temperature, RH and hospital admissions for a variety of CMM. In addition, the risk of admission is higher under low temperature and high RH conditions with the addition of particulate matter (PM, PM2.5 and PM10) and O3_8h. The risk is greater for females and adults aged 65 and older. Compared with first quartile (Q1), the fourth quartile (Q4) had a higher association between serum calcium (HR = 1.3632, 95% CI: 1.0732 ~ 1.7334), serum creatinine (HR = 1.7987, 95% CI: 1.3528 ~ 2.3958), fasting plasma glucose (HR = 1.2579, 95% CI: 1.0839 ~ 1.4770), aspartate aminotransferase/ alanine aminotransferase ratio (HR = 2.3131, 95% CI: 1.9844 ~ 2.6418), alanine aminotransferase (HR = 1.7687, 95% CI: 1.2388 ~ 2.2986), and gamma-glutamyltransferase (HR = 1.4951, 95% CI: 1.2551 ~ 1.7351) were independently and positively associated with unplanned readmission for CMM. However, serum total bilirubin and High-Density Lipoprotein (HDL) showed negative correlations. After incorporating environmental factors and their lagged terms, eXtreme Gradient Boosting (XGBoost) demonstrated a more prominent predictive performance for unplanned readmission of CMM patients, with an average area under the receiver operating characteristic curve (AUC) of 0.767 (95% CI:0.7486 ~ 0.7854). CONCLUSIONS: Extreme cold or wet weather is linked to worsened adverse health effects in female patients with CMM and in individuals aged 65 years and older. Moreover, meteorologic factors and environmental pollutants may elevate the likelihood of unplanned readmissions for CMM.

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Weather is an important short-term, local driver of population size and dispersal, which in turn contribute to patterns of genetic diversity and differentiation within species. Climate change is leading to greater weather variability and more frequent extreme weather events. While the effects of long-term and broad-scale mean climate conditions on genetic variation are well studied, our understanding of the effects of weather variability and extreme conditions on genetic variation is less developed. We assessed the influence of temperature and snow depth on genetic diversity and differentiation of populations of the alpine butterfly, Parnassius smintheus. We examined the relationships between a suite of variables, including those representing extreme conditions, and population-level genetic diversity and differentiation across 1453 single nucleotide polymorphisms, using both linear and gravity models. We additionally examined effects of land cover variables known to influence dispersal and gene flow in this species. We found that extreme low temperature events and the lowest recorded mean snow depth were significant predictors of genetic diversity. Extreme low temperature events, mean snow depth and land cover resistance were significant predictors of genetic differentiation. These results are congruent with known effects of early winter weather on population size and habitat connectivity on dispersal in P. smintheus. Our results demonstrate the potential for changes in the frequency or magnitude of extreme weather events to alter patterns of genetic diversity and differentiation.

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The importance of climate in water resources management is well recognized, but less is known about how climate affects water access at the household level. Understanding this is crucial for identifying vulnerable households, reducing health and well-being risks, and finding equitable solutions. Using difference-in-differences regression analyses and relying on temporal variation in interview timing from multiple, cross-sectional surveys, we examine the effects of monsoon riverine flooding on household water access among 34 000 households in Bangladesh in 2011 and 2014. We compare water access, a combined measure of both water source and time for collection, among households living in flood-affected and non-flood-affected districts before and after monsoon flooding events. We find that households in monsoon flood-affected districts surveyed after the flooding had between 2.27 and 4.42 times higher odds of experiencing low water access. Separating geographically, we find that while households in coastal districts have lower water access than those in non-coastal districts, monsoon flood exposure is a stronger predictor of low water access in non-coastal districts. Non-coastal districts were particularly burdened in 2014, when households affected by monsoon flooding had 4.71 times higher odds of low water access. We also find that household wealth is a consistent predictor of household water access. Overall, our results show that monsoon flooding is associated with a higher prevalence of low water access; socioeconomically vulnerable households are especially burdened.

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Extreme weather events such as floods, bushfires, cyclones, and drought, are projected to increase in eastern Australia. Understanding how these events influence the combined, sustainable well-being of humans, animals, and ecosystems - that is One Health - will enable development of transdisciplinary and ultimately more effective interventions. A scoping review was conducted to explore the research associated with the effects of extreme weather events in eastern Australia using a One Health lens, specifically identifying the type of extreme weather events studied, the research conducted in the context of One Health, and gaps to inform improved One Health implementation. The review followed JBI guidelines (based on PRISMA). Eligible research was peer-reviewed, in English, and published since 2007, in which primary research studies investigated the impact of extreme weather events in eastern Australia on at least two of ecosystems, human health, and animal health. Using structured search terms, six databases were searched. Following removal of duplicates, 870 records were screened by two reviewers. Eleven records were eligible for data extraction and charting. The scope of extreme weather events studied was relatively limited, with studies in flood and bushfire settings predominating, but relatively little research on cyclones. Major health themes included more than the impact of extreme weather events on physical health (zoonotic and vector-borne diseases) through investigation of social well-being and mental health in the context of the human-animal bond in evacuation behaviors and drought. Research gaps include studies across a broader range of extreme weather events and health topics, as well as a more comprehensive approach to including the impacts of extreme weather events on all three domains of One Health. The limited research focus inevitably translates to limited recommendations for policy, planning and response to manage extreme weather event emergencies. Given the expected increase in frequency of these events, there is a critical need for more comprehensive primary research to better identify strategies and facilitate implementation of One Health promotion for improved outcomes in extreme weather event emergencies.

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BACKGROUND: Asthma is a prevalent chronic respiratory disease among children, influenced by various climate and environmental factors. Despite its prevalence, the specific effects of these factors on asthma remain unclear. This study aims to systematically assess the epidemiological evidence using spatial and temporal methods on the impact of climate and environmental factors on childhood asthma. METHODS: A systematic review was conducted to analyse the impact of climate and environmental factors on childhood asthma and wheezing, focusing on spatial and temporal trends. Searches were carried out in PubMed, Embase, and CINAHL databases for studies published from January 2000 to April 2024, using key search terms 'asthma/wheezing', 'extreme weather, 'green space', 'air pollution' and 'spatial or temporal analyses". RESULTS: The systematic review analysed 28 studies, with six employing spatial and 22 using temporal analysis methods; however, none incorporated spatio-temporal analysis in their models. The findings reveal that extreme weather events, including heatwaves and heavy rainfall, elevate childhood asthma risks across various climates, with significant effects observed during summer and winter months. Dust storms in arid and subtropical regions are linked to immediate spikes in hospital admissions due to asthma exacerbations. The effects of green spaces on childhood asthma are mixed, with some studies indicating protective effects while others suggest increased risks, influenced by local environmental factors. Air pollutants such as PM2.5, NO2, and ozone can exacerbate asthma symptoms and along with other environmental factors, contribute to seasonal effects. High temperatures generally correlate with increased asthma risks, though the effects vary by age, sex, and climate. CONCLUSION: Future research should integrate spatial and temporal methods to better understand the effects of environmental and climate changes on childhood asthma.

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Mosquito-borne diseases are a known tropical phenomenon. This review was conducted to assess the mecha-nisms through which climate change impacts mosquito-borne diseases in temperate regions. Articles were searched from PubMed, Scopus, Web of Science, and Embase databases. Identification criteria were scope (climate change and mosquito-borne diseases), region (temperate), article type (peer-reviewed), publication language (English), and publication years (since 2015). The WWH (who, what, how) framework was applied to develop the research question and thematic analyses identified the mechanisms through which climate change affects mosquito-borne diseases. While temperature ranges for disease transmission vary per mosquito species, all are viable for temperate regions, particularly given projected temperature increases. Zika, chikungunya, and dengue transmission occurs between 18-34 °C (peak at 26-29 °C). West Nile virus establishment occurs at monthly average temperatures between 14-34.3 °C (peak at 23.7-25 °C). Malaria establishment occurs when the consecutive average daily temperatures are above 16 °C until the sum is above 210 °C. The identified mechanisms through which climate change affects the transmission of mosquito-borne diseases in temperate regions include: changes in the development of vectors and pathogens; changes in mosquito habitats; extended transmission seasons; changes in geographic spread; changes in abundance and behaviors of hosts; reduced abundance of mosquito predators; interruptions to control operations; and influence on other non-climate factors. Process and stochastic approaches as well as dynamic and spatial models exist to predict mosquito population dynamics, disease transmission, and climate favorability. Future projections based on the observed relations between climate factors and mosquito-borne diseases suggest that mosquito-borne disease expansion is likely to occur in temperate regions due to climate change. While West Nile virus is already established in some temperate regions, Zika, dengue, chikungunya, and malaria are also likely to become established over time. Moving forward, more research is required to model future risks by incorporating climate, environmental, sociodemographic, and mosquito-related factors under changing climates.

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Grain filling is a critical process for improving crop production under adverse conditions caused by climate change. Here, using a quantitative method, we quantified post-anthesis source-sink relationships of a large data set to assess the contribution of remobilized pre-anthesis assimilates to grain growth for both biomass and nitrogen. The data set came from 13 years' semi-controlled field experimentation, in which six bread wheat genotypes were grown at plot scale under contrasting temperature, water, and nitrogen regimes. On average, grain biomass was ~10% higher than post-anthesis aboveground biomass accumulation across regimes and genotypes. Overall, the estimated relative contribution (%) of remobilized assimilates to grain biomass became increasingly significant with increasing stress intensity, ranging from virtually nil to 100%. This percentage was altered more by water and nitrogen regimes than by temperature, indicating the greater impact of water or nitrogen regimes relative to high temperatures under our experimental conditions. Relationships between grain nitrogen demand and post-anthesis nitrogen uptake were generally insensitive to environmental conditions, as there was always significant remobilization of nitrogen from vegetative organs, which helped to stabilize the amount of grain nitrogen. Moreover, variations in the relative contribution of remobilized assimilates with environmental variables were genotype-dependent. Our analysis provides an overall picture of post-anthesis source-sink relationships and pre-anthesis assimilate contributions to grain filling across (non-)environmental factors, and highlights that designing wheat adaption to climate change should account for complex multi-factor interactions.

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In late summer and autumn, the passage of intense tropical cyclones can profoundly perturb oceanic and coastal ecosystems. Direct negative effects on individuals and marine communities can be dramatic, especially in the coastal zone,1,2,3,4 but cyclones can also enhance pelagic primary and secondary production.5,6,7,8,9 However, cyclone impacts on open ocean marine life remain poorly understood. Here, we investigate their effects on the foraging movements of a wide-ranging higher predator, the Desertas petrel (Pterodroma deserta), in the mid-latitude North Atlantic during hurricane season. Contrary to previously studied pelagic seabirds in tropical and mid-latitude regions,10,11 Desertas petrels did not avoid cyclones by altering course, nor did they seek calmer conditions within the cyclone eye. Approximately one-third of petrels tracked from their breeding colony interacted with approaching cyclones. Upon encountering strong winds, the birds reduced ground speed, likely by spending less time in flight. A quarter of birds followed cyclone wakes for days and over thousands of kilometers, a behavior documented here for the first time. Within these wakes, tailwind support was higher than along alternative routes. Furthermore, at the mesoscale (hours-weeks and hundreds of kilometers), sea surface temperature dropped and surface chlorophyll sharply increased, suggesting direct effects on ocean stratification, primary production, and therefore presumably prey abundance and accessibility for surface-feeding petrels. We therefore hypothesize that cyclone wakes provide both predictably favorable wind conditions and foraging opportunities. As such, cyclones may have positive net effects on the demography of many mid-latitude pelagic seabirds and, likely, other marine top-predators.

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Subseasonal rainfall forecast skill is critical to support preparedness for hydrometeorological extremes. We assess how a process-informed evaluation, which subsamples forecasting model members based on their ability to represent potential predictors of rainfall, can improve monthly rainfall forecasts within Central America in the following month, using Costa Rica and Guatemala as test cases. We generate a constrained ensemble mean by subsampling 130 members from five dynamic forecasting models in the C3S multimodel ensemble based on their representation of both (a) zonal wind direction and (b) Pacific and Atlantic sea surface temperatures (SSTs), at the time of initialization. Our results show in multiple months and locations increased mean squared error skill by 0.4 and improved detection rates of rainfall extremes. This method is transferrable to other regions driven by slowly-changing processes. Process-informed subsampling is successful because it identifies members that fail to represent the entire rainfall distribution when wind/SST error increases.

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BACKGROUND: Climate Change is causing frequent and sever extreme weather events globally, impacting human health and well-being. Primary healthcare (PHC) nurses' are at the forefront of addressing these challenges and must be prepared. PURPOSE: This scoping revieww explored literature on the preparedness of the PHC nursing workforce for extreme weather events and identify gaps in knowledge and practice. METHODS: Using Arksey and O'Malley's framework, a comprehensive search was conducted across PubMed, Scopus, CINHAL, Web of Sciences, and ProQuest, on studies from 2014-2024, addressing PHC nurses' preparedness. DISCUSSION: Nine studies were identified and highlighted a need for preparedness training and facility-based preparedness plans. Key themes included prioritizing regional networks, clinical leadership, service delivery, health information, health workforce, medical products and technologies, and financing. CONCLUSION: Strengthening PHC nurses' resilience against extreme weather requires targeted professional development, mental health support, comprehensive planning, and collaborative efforts. Future strategies should enhance PHC nurses' capacity through training, support, and policy development.

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Pollution and climate change constitute a combined, grave and pervasive threat to humans and to the life-support systems on which they depend. Evidence shows a strong association between pollution and climate change on cardiovascular and respiratory diseases, and pulmonary vascular disease (PVD) is no exception. An increasing number of studies has documented the impact of environmental pollution and extreme temperatures on pulmonary circulation and the right heart, on the severity and outcomes of patients with pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension (PH), on the incidence of pulmonary embolism, and the prevalence and severity of diseases associated with PH. Furthermore, the downstream consequences of climate change impair health care systems' accessibility, which could pose unique obstacles in the case of PVD patients, who require a complex and sophisticated network of health interventions. Patients, caretakers and health care professionals should thus be included in the design of policies aimed at adaptation to and mitigation of current challenges, and prevention of further climate change. The purpose of this review is to summarize the available evidence concerning the impact of environmental pollution and climate change on the pulmonary circulation, and to propose measures at the individual, healthcare and community levels directed at protecting patients with PVD.