International Journal of Biometeorology最新文献

Changes in clouds and aerosols may alter the quantity of solar radiance and its diffuse components, as well as air temperature (T_a) and vapor pressure deficit (VPD), thereby affecting canopy photosynthesis. Our aim was to determine how ecosystem gross primary productivity (GPP) responds to the cloudiness and aerosol depth changes, as indicated by diffuse light fraction (fDIF). The environmental factors that caused these responses were examined using 2 years of eddy covariance data from a winter-wheat cropland in northern China. The GPP decreased significantly along with the fDIF in a nonlinear pattern, with a determination coefficient of 0.91. Changes in fDIF altered total photosynthetic active radiation (PAR), diffuse PAR, T_a and VPD. The variations in GPP with fDIF in both fDIF change Phase I (fDIF < 0.65) and Phase II (fDIF > 0.65) resulted from the combined effects of multiple environmental factors. Because the driving factors were closely correlated, a path analysis was used to distinguish their respective contribution to the GPP response to fDIF by integrating path coefficients. In Phases I and II, the decreased responses of GPP to fDIF were mainly caused by total PAR and diffuse PAR, respectively, which contributed approximately 49% and 37% to GPP variations, respectively. Our research has certain implications for the necessity to consider fDIF and to incorporate diffuse light into photosynthetic models.

Exposure to heat stress can cause a significant increase in the death rate and disease susceptibility of poultry birds, ultimately impacting the profitability of the poultry industry. Despite being a more economical choice, Japanese quails (Coturnix japonica) are not immune to the harmful effects of heat stress. Quails may experience negative effects on their reproductive performance due to excessive reactive molecules caused by heat stress. However, they have developed various mechanisms to maintain their reproductive abilities in such conditions. The neuroendocrine system in birds plays a vital role in regulating their reproductive responses to thermal stress, and it is also connected to other environmental factors such as photoperiod that can impact their reproductive performance. Hormones are crucial in the complex interactions necessary for sexual maturation and reproductive responses to heat stress in Japanese quails living in stressful thermal conditions.

Short-term exposure to air pollution has previously been studied in relation to certain neurological disorders, but there is still a lack of convincing data linking air pollution to epileptic seizures. The study's goal was to investigate how exposure to ambient nitrogen dioxide (NO₂) affected the number of patients seeking assistance at the Wuhan Emergency Medical Center due to epileptic seizures. We gathered data on medical emergency calls (MECs), daily ambient air pollution concentrations (SO₂, NO₂, PM_2.5, PM₁₀, CO, and O₃), and meteorological variables in Wuhan, China, spanning from January 1, 2017, to November 30, 2019. To investigate the potential influence of ambient nitrogen dioxide on MECs for epileptic seizures, we carried out a time-series investigation using the general additive model (GAM). Additionally, analyses stratified by season, age, and gender were performed. A total of 8989 records of MECs for epileptic seizures were enrolled in our study during the period. Statistical analysis indicates that a rise of 10 μg/m3 in NO₂ concentration is linked to a 0.17% increase in daily MECs for epileptic seizures (95% confidence interval [CI]: 0.02%, 0.32%). Furthermore, people aged 14-59 years were more susceptible(2.25%, P < 0.05). The short-term effects of NO₂ exposure on daily MECs for epileptic seizures were stronger in warm seasons than in cool seasons (0.55% vs. -0.10%, P < 0.0001). Our findings suggests that short-term exposure to ambient NO₂ was positively correlated with daily MECs for epileptic seizures in Wuhan, China. Additionally, we observed that these associations were stronger in patients aged above 14 but under 60 years and the warmer seasons (from April to September).

Poaceae pollen is one of the most widespread sources of aeroallergens in the world. The aim of this study is to build predictive models for the pollen season start day (PSsd) and peak dates of the Poaceae pollen season and thus give an overview of the climatic parameters that have the greatest influence. In Tétouan, sampling was carried out using a volumetric spore trap of the Burkard Hirst type. The relationships between the PSsd, peak dates and meteorological parameters were determined using correlation analysis. The models were constructed using multiple regression analysis with data from 2008 to 2019 and tested on data from 2022. The PSsd was especially significantly influenced by minimum temperature during winter and precipitation in the autumn of the previous year. The peak dates were significantly correlated with precipitation in January, March and April, but not with temperature. Three models were obtained for each of the season's parameters; the most accurate model for the PSsd explained a variability of 61% and includes as main predictors rainfall from the autumn of the previous year and the mean daily average temperature from 23 February to 8 March. The two most efficient peak dates models included precipitation in January and April as the main predictor variables, and explained greater variability (87 and 88%). Precipitation in autumn and the mean daily and the sum of minimum temperature in winter, showed significant decreasing tendencies. However, the PSsd trend delay was not statistically significant. This study draws the importance of the weather during preseason for grass pollen production and emphasises the usefulness of the models for allergic patients to take preventive measures and for healthcare professionals in allergy therapy.

Increasing heat stress in urban environments due to climate change has a significant adverse impact on human work and daily life. Street canyons as the main component of the underlying surface of the city and the main place of residents' activities, a comprehensive understanding of street morphology and tree planting practices can help to improve thermal comfort. Based on survey data and field experiments, this study designed 30 scenarios and employed ENVI-met model (version 5.0.3) to quantify the effect of street aspect ratio (H/W: H is building height and W is street width) and tree spacing (TS) on pedestrian thermal comfort in two differently oriented streets (north-south and east-west) in Taiyuan, China. Results showed that H/W ratio and TS significantly influenced the street thermal comfort mainly owing to shading. H/W ratio played a pivotal role in reducing mean radiant temperature (Tmrt) and physiological equivalent temperature (PET), and was negatively correlated with Tmrt and PET. Compared to no-tree scenarios, street trees significantly improved thermal comfort (mean reductions of Tmrt and PET were 12.74℃ and 5.66℃, respectively), and PET and Tmrt were significantly negatively correlated with TS. The improvement effect of street trees on Tmrt and PET in east-west oriented street was better than north-south oriented street. H/W = 1.0 and TS = 6 m appeared as the proposed combination to mitigate the summer thermal comfort in the temperate monsoon climate zone. These quantitative results provide new insights into renewal and design strategies for future urban planning.

Smart urban planning needs to have a multicriteria-based approach to prevent the deteriorating local thermal climate. Maximizing the cooling potential using the available grey infrastructure would be the utmost priority of future smart cities. Remote sensing and GIS can be the appropriate tools to develop a climate-resilient urban planning framework. Studies are needed to include different features of vertical and horizontal landscaping to mitigate heat stress and enhance liveability at the city level. With this goal, the current work outlined a holistic approach to efficiently using green spaces with minimal reconstruction. The problem of regional climate threat was evaluated with urban heat island characterization. Moran's I clustering identified nearly 12% of the study area to be under considerable heat stress during summer days. Multiple techniques, such as mapping local climate zones, segment mean shift-based roof extraction, vegetation index computation, solar azimuth-based green wall site selection, etc., were applied to formulate solutions and provide an integrated method for city-level environment enhancement. A considerable area was identified as most suitable for green roof cover, and it was also computed that the transition towards green roof at only these locations may bring down the maximum heat island intensity by 0.74 °C. Additionally, solar zenith, illumination effect, and building height information were combined to create a distinct method where vertical plantation would flourish exceptionally. A rigorous assessment of more than 130 urban green spaces further quantified the relation between landscape geometry and cooling effect to provide optimum green space designs for future urban planning.

Changes caused by air-cleaning devices in the amounts of volatile organic compounds in an intensive care unit were monitored in the study. The cancer risk and hazard index were calculated. The measurements were made for one month at isolated room and two different points and times in the intensive care unit. According to the sampling program, the air-cleaning devices were turned off in weeks 1 and 4 and turned on in weeks 2 and 3. Volatile organic compounds were collected by active sampling. Samples were analyzed by a thermal desorber coupled to a gas chromatography-mass spectrometry instrument with selective ion monitoring. The results showed that the concentrations of benzene, toluene, and o-xylene decreased by about 70% after the air-cleaning devices were installed. The cancer risk assessment for naphthalene was recorded at the highest level of cancer risk (Class A). The hazard index value of naphthalene was recorded at the harmful level when air-cleaning devices were not installed. The concentrations of benzene (p = 0.01), toluene (p = 0.02), ethylbenzene (p = 0.02), styrene (p = 0.01), and m, p-xylene (p = 0.04) before the air-cleaning devices were installed were significantly different from those recorded when the air-cleaning devices were turned on.

Balneotherapy, using heated natural mineral waters at 36-38 °C, presents a comprehensive treatment approach for Fibromyalgia Syndrome (FMS). This study aims to assess the effect of balneotherapy in reducing pain intensity, disability, and depression in patients with FMS. We want to assess this effect at just four time-points: immediately at the end of the therapy, and at 1, 3, and 6 months of follow-up. Following PRISMA guidelines, we conducted an aggregate data meta-analysis, registered in PROSPERO CRD42023478206, searching PubMed Medline, Science Direct, CINAHL Complete, Scopus, and Web of Science until August 2023 for relevant randomized controlled trials (RCTs) that assess the effect of balneotherapy on pain intensity, disability, and depression in FMS patients. Methodological quality was assessed using the Cochrane methodology, and the pooled effect was calculated using Cohen's standardized mean difference (SMD) and its 95% confidence interval (95% CI) in a random-effects model. Sixteen RCTs were included in the meta-analysis. Balneotherapy is effective in reducing pain intensity (SMD - 1.67; 95% CI -2.18 to -1.16), disability (SMD - 1.1; 95% CI -1.46 to -0.7), and depression (SMD - 0.51; 95% CI -0.93 to -0.9) at the end of the intervention. This effect was maintained at 1, 3, and 6 months for pain intensity and disability. Balneotherapy improves both pain intensity and disability in patients with FMS, providing evidence that its positive effects are sustained for up to 6 months of follow-up. Nevertheless, it is important to note that the improvement in depression varies across different temporal phases.

Several remote sensing indices have been used to monitor droughts, mainly in semi-arid regions with limited coverage by meteorological stations. The objective of this study was to estimate and monitor agricultural drought conditions in the Jequitinhonha Valley region, located in the Brazilian biomes of the Cerrado and Atlantic Forest, from 2001 to 2021, using vegetation indices and the meteorological drought index from remote sensing data. Linear regression was applied to analyze drought trends and Pearson's correlation coefficient was applied to evaluate the relationship between vegetation indices and climatic conditions in agricultural areas using the Standardized Precipitation Index. The results revealed divergences in the occurrences of regional droughts, predominantly covering mild to moderate drought conditions. Analysis spatial of drought trends revealed a decreasing pattern, indicating an increase in drought in the Middle and Low Jequitinhonha sub-regions. On the other hand, a reduction in drought was observed in the High Jequitinhonha region. Notably, the Vegetation Condition Index demonstrated the most robust correlation with the Standardized Precipitation Index, with R values ​​greater than 0.5 in all subregions of the study area. This index showed a strong association with precipitation, proving its suitability for monitoring agricultural drought in heterogeneous areas and with different climatic attributes. The use of remote sensing technology made it possible to detect regional variations in the spatio-temporal patterns of drought in the Jequitinhonha Valley. This vision helps in the implementation of personalized strategies and public policies, taking into account the particularities of each area, in order to mitigate the negative impacts of drought on agricultural activities in the region.

Understanding the impact of climate warming on crop yield and its associated mechanisms is paramount for ensuring food security. Here, we conduct a thorough analysis of the impact of vapor pressure deficit (VPD) on maize yield, leveraging a rich dataset comprising temporal and spatial observations spanning 40 years across 31 maize-growing locations in Northeast and North China. Our investigation extends to the influencing meteorological factors that drive changes in VPD during the maize growing phase. Regression analysis reveals a linear negative relationship between VPD and maize yield, demonstrating diverse spatiotemporal characteristics. Spatially, maize yield exhibits higher sensitivity to VPD in Northeast China (NEC), despite the higher VPD levels in North China Plain (NCP). The opposite patterns reveal that high VPD not invariably lead to detrimental yield impacts. Temporal analysis sheds light on an upward trend in VPD, with values of 0.05 and 0.02 kPa/10yr, accompanied by significant abrupt changes around 1996 in NEC and 2006 in NCP, respectively. These temporal shifts contribute to the heightened sensitivity of maize yield in both regions. Importantly, we emphasize the need to pay closer attention to the substantial the impact of actual vapor pressure on abrupt VPD changes during the maize growing phase, particularly in the context of ongoing climate warming.