International Journal of Biometeorology最新文献

{"title":"Cooling effect of evaporative misters in outdoor restaurant areas: case study of Novi Sad, Serbia","authors":"J. Dunjić,&nbsp;V. Květoňová,&nbsp;S. Manavvi,&nbsp;D. Milošević,&nbsp;S. Savić,&nbsp;V. Stojanović,&nbsp;M. Lehnert","doi":"10.1007/s00484-026-03203-7","DOIUrl":"10.1007/s00484-026-03203-7","url":null,"abstract":"<div><p>Continuing urbanization, together with climate change manifestations, including the increasing frequency and intensity of heat waves, prompts the adoption of various cooling interventions in urban outdoor spaces. Evaporative misting systems have gained popularity as a cost-effective heat mitigation measure, particularly in hospitality venues. However, their effectiveness in moderate climates remains understudied. This study evaluated the effectiveness of these systems in restaurant outdoor seating areas in Novi Sad, Serbia, during hot summer days in 2022 and 2023. Simultaneous micrometeorological measurements were conducted at multiple locations in restaurant outdoor seating areas (sun-exposed, shaded, misted, and non-misted sites), with mean radiant temperature (MRT), Physiological Equivalent Temperature (PET), and Universal Thermal Climate Index (UTCI) being calculated. Additionally, to capture subjective perceptions of microclimatic conditions, questionnaire surveys were conducted with restaurant guests. Results revealed significant location-specific variability in cooling effectiveness. The most favorable thermal conditions occurred in shade; however, in sun-exposed locations, misting systems showed inconsistent performance, sometimes even worsening thermal conditions. Despite these inconsistencies, questionnaire results showed that guests consistently perceived improved thermal comfort under misting systems. Further research should include measurements across different times of day and seasons in moderate climates and across different misting types and intervals to better understand misting systems’ cooling benefits.</p></div>","PeriodicalId":588,"journal":{"name":"International Journal of Biometeorology","volume":"70 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00484-026-03203-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147738882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the carbon reduction benefits of urban blue spaces for mitigating the heat island effect","authors":"Kunneng Jiang,&nbsp;Yumeng Wang,&nbsp;Huiting Zhang,&nbsp;Kaijie Gao,&nbsp;Fang Xu,&nbsp;Yaling Gao,&nbsp;Yuanping Shen,&nbsp;Baojian Ye,&nbsp;Hongxin Wang,&nbsp;Qunyue Liu","doi":"10.1007/s00484-026-03202-8","DOIUrl":"10.1007/s00484-026-03202-8","url":null,"abstract":"<div>\u0000 \u0000 <p>Amid the intensifying urban heat island effect, urban blue spaces have been shown to effectively mitigate daytime high temperatures in surrounding areas. However, limited research has explored the carbon reduction potential resulting from these cooling effects. This study introduces a straightforward method to estimate such potential and analyzes 43 water bodies in Guangzhou. The results indicate that the average temperature of each water body decreased by 2.86 °C, with the cooling effect extending up to 160 m from the shoreline. These cooling effects significantly contribute to the reduction of carbon emissions, leading to a daily decrease of 4875.4 tons of CO₂ during the summer, equivalent to 0.27% of the city’s total daily carbon emissions. To elucidate the relationship between water body characteristics and carbon reduction, a logarithmic function was employed to simulate carbon benefits in relation to water body area and perimeter. This analysis identified a TVoE at 115.09 hectares for area and 163.06 km perimeter. Further analysis, using Pearson correlation and a random forest model, identified key factors influencing these effects, including perimeter, area, and shape complexity of the water bodies. The findings suggest that increasing water body area or maximizing their shape complexity can enhance both cooling and carbon reduction capacities. These insights offer theoretical guidance for the sustainable and low-carbon development of urban environments.</p>\u0000 </div>","PeriodicalId":588,"journal":{"name":"International Journal of Biometeorology","volume":"70 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147738548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban heat stress during heat waves in a mid-sized Central European city (Lublin, Poland): observations and PMPGP-based reconstruction","authors":"Agnieszka Krzyżewska,&nbsp;Sachindra Dhanapala Arachchige,&nbsp;Mateusz Dobek,&nbsp;Sylwester Wereski","doi":"10.1007/s00484-026-03204-6","DOIUrl":"10.1007/s00484-026-03204-6","url":null,"abstract":"<div>\u0000 \u0000 <p>Heat waves are becoming more frequent and intense, increasing biometeorological and public-health risks in urban areas where dense built-up surfaces, limited vegetation, and local humidity patterns modify human heat exposure. This study examines urban heat stress in Lublin (SE Poland), a mid-sized Central European city with a heterogeneous urban structure typical of many cities in the region, and evaluates whether local thermal conditions during heat waves can be reconstructed in data-limited periods using a Parallel Multi-Population Genetic Programming (PMPGP) approach. The analysis combines long-term observations from urban and rural meteorological stations (1975–2024) with detailed intra-urban case studies of the August 2010 and August 2015 heat waves. Air temperature and relative humidity were measured by HOBO® sensors at five sites representing contrasting urban environments (including the Old Town, a central square, high-rise residential estates, and a low-density residential area). For the August 2015 mega-heat wave temperature and relative humidity at four urban sites were reconstructed using PMPGP models calibrated and validated with earlier observations and driven by data from Litewski Square (city centre). Heat stress was assessed using Apparent Temperature (AT). Results showed an urban-rural contrast, especially at night, with more tropical nights and higher minimum temperatures in central Lublin. During heat waves, heat stress was strongest in densely built-up areas, especially the Old Town “urban well” and high-rise districts, while greener sites were cooler. Higher humidity in the outskirts could still increase AT despite cooler air, underscoring humidity’s importance. PMPGP-based reconstruction supports heat-risk assessment and climate adaptation planning in cities. </p>\u0000 </div>","PeriodicalId":588,"journal":{"name":"International Journal of Biometeorology","volume":"70 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147738547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High altitude adaptation: role of nuclear receptor’s exosomes","authors":"Rohit Singh Huirem,&nbsp;M. Kumar Prasanna Reddy","doi":"10.1007/s00484-026-03188-3","DOIUrl":"10.1007/s00484-026-03188-3","url":null,"abstract":"<div><p>High altitude exposes humans to hypobaric hypoxia and poses a significant challenge for human performance and survival. Humans have adapted to the chronic hypoixa of high altitude in several geographical locations and nevertheless, the fundamental questions regarding the functional links between those adoptive unique phenotypic attributes and the associated cellular and molecular signaling mechanisms remains unanswered. The high-altitude acclimatization and adaptation responses are primarily orchestrated by hypoxia inducible factor (HIF). However, some HIF-independent response pathways exists and act either in coordination and/or in parallel to HIF to mediate the physiological response of hypoxia. Recently, several multi-omic analysis studies demonstrated crucial oxygen homeostatic and metabolic signaling pathways in hypoxia including members of nuclear receptor (NR’s) superfamily like LXR’s, RXR’s, ER’s and PPARA’s. Since acclimatization and adaptation to high altitude confers several benefits for the prevention of various high altitude illnesses, the cellular and molecular signaling mechanisms underlying oxygen homeostasis during acute and prolonged high altitude exposure becomes an attractive avenue for understanding the physiology of adaptation and pathophysiology of mal-adaptation. Members of NR’s are of particular interest owing to their involvement in multiple physiological functions and their possible role in epigenetic regulation due to the presence of well defined DNA and ligand binding domains. In this review, we summarize the current understanding of the involvement of NR’s in regulation of physiological responses hypoxia and how they may contribute for high altitude adaptation. Additionally, we have made an effort to draw attention to the connection between NRs and EVs.</p><h3>Graphical Abstract</h3><div><figure><div><div><picture><source><img></source></picture><span>The alternative text for this image may have been generated using AI.</span></div></div></figure></div></div>","PeriodicalId":588,"journal":{"name":"International Journal of Biometeorology","volume":"70 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147737987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A climate region classification for California’s warm season: apparent temperature clustering to support heat-health epidemiology","authors":"Marinelle Villanueva,&nbsp;Sydney Monte-Sano,&nbsp;Scott Sheridan,&nbsp;Michael Allen,&nbsp;Laurence Kalkstein,&nbsp;Michael Jerrett,&nbsp;David P. Eisenman","doi":"10.1007/s00484-026-03200-w","DOIUrl":"10.1007/s00484-026-03200-w","url":null,"abstract":"<div>\u0000 \u0000 <p>Climate classification enhances our understanding of regional climate patterns and enables a science-based framework for assessing environmental and public health relationships. Prior climate classification systems are limited in their ability to capture variation across dynamic subclimates, particularly in the context of complex topographical, elevation, and meteorological characteristics such as California, United States. In this study, we spatially classified climate regions in California during the warm season (May through September) in 2021 and 2022. We applied principal component analysis with k-means clustering algorithms to gridded data consisting of apparent temperature during the study period as a monthly time series. We then performed statistical and spatial analysis to delineate the geographical extent of climate regions with shared apparent temperature distributions. The results of this study include a statewide map of 30 warm season climate regions based on meteorological data characterized by homogenous temperature patterns that are distinct from one another. The climate regions demonstrate highly variable spatial patterns of heat exposures and often span across and within multiple county boundaries. The methods we present within a complex geography can be readily adapted to other regional settings and updated to other temporal periods. This study informs our understanding of regional climate patterns during the warm season and is applicable to the development of early warning systems and quantifying extreme heat impacts across statewide populations.</p>\u0000 </div>","PeriodicalId":588,"journal":{"name":"International Journal of Biometeorology","volume":"70 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00484-026-03200-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147727992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of future climate change on the distribution of cotton bollworms, Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae)","authors":"Jian Huang,&nbsp;Xinyu Lu,&nbsp;Xiaojun Wang","doi":"10.1007/s00484-026-03181-w","DOIUrl":"10.1007/s00484-026-03181-w","url":null,"abstract":"<div>\u0000 \u0000 <p>Climate change is a key factor affecting the distribution of pests. <i>H. armigera</i> is a worldwide pest, and its outbreaks and distribution are closely related to meteorological factors. The Xinjiang, located in the northwest of China, is the country’s most important cotton production base, accounting for 92.2% of the national cotton output. It is also a major area where <i>H. armigera</i> outbreaks occur. Understanding the potential distribution of <i>H. armigera</i> is of great significance for integrated pest management. However, against the backdrop of climate change, the potential distribution of the <i>H. armigera</i> in Xinjiang remains unclear. Based on the occurrence data of <i>H. armigera</i> in Xinjiang, as well as current and future climate data, this study utilized the Maximum Entropy model (MaxEnt), ENMTools, and ArcGIS to simulate the dynamic distribution of <i>H. armigera</i> in Xinjiang under current and future climate conditions (2021–2040, 2041–2060, 2061–2080, 2081–2100) under the three shared socio-economic pathways (SSP126, SSP245, SSP585) of the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6). The results indicated that: (1) Under both current and future climate conditions, the AUC value of the model stood at 0.907, which suggested that the model’s prediction outcomes were extremely good; (2) The areas suitable for the survival of <i>H. armigera</i> were expanding. The highly suitable areas might even double in size, and the suitable areas generally increased by 50% ~ 60%, while the relatively suitable areas showed a decrease of 10% ~ 20%. Therefore, Xinjiang would face greater pest pressure in the next few decades. (3) The current centroid of the cotton bollworm was located in Xinhe County, Xinjiang, and under different future climate scenarios, it would migrate eastward, but by no more than 4 degrees of longitude, and in terms of latitude, it would migrate either southward or northward within a range of 1 degree of latitude. The boundary of the relatively suitable areas expanded northward and eastward. The expansion range varied across different regions. Therefore, management departments should formulate corresponding prevention and control policies according to local characteristics.</p>\u0000 </div>","PeriodicalId":588,"journal":{"name":"International Journal of Biometeorology","volume":"70 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147728056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Random forest-based medical geography: geographical distribution of reference values for LP-PLA2 in healthy adults in China","authors":"Xianzheng Li,&nbsp;Xinrui Pang","doi":"10.1007/s00484-025-03097-x","DOIUrl":"10.1007/s00484-025-03097-x","url":null,"abstract":"<div><p>Lipoprotein-associated phospholipase A2 (LP-PLA2), a vascular-specific inflammatory marker, is associated with coronary heart disease (CHD), a highly prevalent condition among middle-aged and older adults. It explores the relationship between environmental factors in environmentscience, geography, statistics and medicine and the reference value of LP-PLA2 in China. A geographic distribution prediction model for Lp-PLA2 medical reference values was developed using optimized machine learning approaches. The support vector machine (SVM) model employed a polynomial kernel function, with hyperparameters tuned via grid search and cross-validation to determine the optimal classifier configuration. Concurrently, the random forest algorithm was applied to mitigate overfitting and perform regression analysis on the dataset. Further considering the influence of geographical factors on the 100 LP-PLA2 medical reference values in city and county units from 2000 to 2024, using 24 geographical factors as independent variables, to fit 2317 LP-PLA2 medical reference values, and then explore the spatial variation characteristics of LP-PLA2 medical reference values. Further spatial interpolation was visualized on the national map. The medical reference value of LP-PLA2 was significantly correlated with longitude, altitude, annual average wind speed, topsoil clay percentage, topsoil reference capacity, topsoil organic matter content, and total convertible amount of topsoil, respectively. The geospatial distribution map shows that the whole value was high in the east and low in the west, with significant differences in longitude. The geographical characteristics of any given region, when analyzed through either the SVM prediction model or the derived geographical distribution map, enable precise determination of region-specific Lp-PLA2 reference values. This establishes an evidence-based foundation for clinical decision-making and research design in healthcare institutions and medical research organizations.</p></div>","PeriodicalId":588,"journal":{"name":"International Journal of Biometeorology","volume":"70 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147686661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: Climate change and infertility: global evidence on temperature-related reproductive risks and demographic vulnerability","authors":"Yang Tao,&nbsp;Jinjie Wu,&nbsp;Rubing Pan","doi":"10.1007/s00484-026-03193-6","DOIUrl":"10.1007/s00484-026-03193-6","url":null,"abstract":"","PeriodicalId":588,"journal":{"name":"International Journal of Biometeorology","volume":"70 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147686660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing energy fluxes of lowland rice fields using four-year eddy covariance data","authors":"Dibyendu Chatterjee,&nbsp;Abhijit Pradhan,&nbsp;Chinmaya Kumar Swain,&nbsp;Rounak Alam,&nbsp;Rahul Tripathi,&nbsp;Pratap Bhattacharyya","doi":"10.1007/s00484-026-03176-7","DOIUrl":"10.1007/s00484-026-03176-7","url":null,"abstract":"<div>\u0000 \u0000 <p>This study investigates the annual variation of energy balance components in a tropical rice paddy ecosystem located in eastern India from 2017 to 2020. The primary components analyzed include sensible heat flux (H), latent heat flux (LE), net radiation (Rn) and soil heat flux, using an eddy covariance system. The results revealed significant diurnal and seasonal fluctuations, with maximum sensible heat observed at 56.33 W m⁻² and maximum latent heat reaching 238.03 W m⁻² during peak growth periods. Ordinary least squares (OLS), energy balance ratio (EBR) and residual heat flux (RHF) methods were used to assess energy balance closure. The OLS analysis indicated a higher coefficient of determination (R²) in dry seasons compared to wet seasons, reflecting more efficient energy closure. The EBR demonstrated consistently higher values during dry seasons, with the highest mean value of 0.77. Conversely, the RHF analysis indicated greater heat flux partitioning into sensible heat during dry conditions. These findings highlight the impact of climatic variability on energy exchange processes in rice paddies, emphasizing the importance of understanding energy partitioning for sustainable agricultural practices. The study provides valuable insights into the energy dynamics of tropical rice-rice agroecosystems and contributes to improved energy closure models of surface-atmosphere interactions.</p>\u0000 </div>","PeriodicalId":588,"journal":{"name":"International Journal of Biometeorology","volume":"70 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing spring frost-induced production losses across China’s apple planting regions","authors":"Renwei Chen,&nbsp;Jing Wang,&nbsp;Yang Li,&nbsp;Rui Bai,&nbsp;Zhihong Gong,&nbsp;Zhenjiang Qu,&nbsp;Zhangyan Le,&nbsp;Jianshuo Zhou","doi":"10.1007/s00484-026-03205-5","DOIUrl":"10.1007/s00484-026-03205-5","url":null,"abstract":"<div><p>Spring frost poses a major threat to apple production in temperate regions, with severe implications for yield and fruit quality. China’s apple production is particularly vulnerable to spring low temperature, yet comprehensive assessments of apple spring frost-induced production losses remain limited. In this study, we quantified frost-induced apple yield and production losses across China during 1991–2020 by integrating spring frost characteristics and simulated production losses. Frost hazard was characterized using the frequency (accumulated frost days, AFD) and intensity (accumulated frost degree-days, AFDD) of frost events occurring during frost-sensitive phenological stages of apple. Yield losses caused by frost were simulated using the process-based STICS model while spatial exposure was represented by the distribution of apple harvested regions derived from the Spatial Production Allocation Model (SPAM). Total apple production loss was estimated based on simulated yield, yield loss rate, and harvested region. The results show that the average annual AFD ranged from 0.04 to 1.20 d, while AFDD varied between 0.03 and 0.80 °C·d across major apple-planting regions. Frost events resulted in measurable yield reductions, with an average yield loss of 1.3%, and a maximum loss of 9.5% occurring in Region III. During the past three decades, spring frost-induced yield loss rates generally showed an increasing trend, particularly in the Loess Plateau.When combined with the spatial distribution of apple planting regions (averaging 760.7 ha), the estimated national average production loss reached 245.4 t. This study provides a quantitative assessment of frost impacts on apple production at the national scale and offers valuable insights for improving frost risk management, optimizing orchard distribution, and enhancing the resilience of apple production under increasing climate variability.</p></div>","PeriodicalId":588,"journal":{"name":"International Journal of Biometeorology","volume":"70 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}