Oxidative stress across multiple tissues in house sparrows (Passer domesticus) acclimated to warm, stable cold, and unpredictable cold thermal treatments.

With climate change increasing not just mean temperatures but the frequency of cold snaps and heat waves, animals occupying thermally variable areas may be faced with thermal conditions for which they are not prepared. Studies of physiological adaptations of temperate resident birds to such thermal variability are largely lacking in the literature. To address this gap, we acclimated winter-phenotype house sparrows (Passer domesticus) to stable warm, stable cold, and fluctuating cold temperatures. We then measured several metrics of the oxidative stress (OS) system, including enzymatic and non-enzymatic antioxidants and lipid oxidative damage, in brain (post-mitotic), kidney (mitotic), liver (mitotic) and pectoralis muscle (post-mitotic). We predicted that high metabolic flexibility could be linked to increases in reactive oxygen damage. Alternatively, if variation in ROS production is not associated with metabolic flexibility, then we predict no antioxidant compensation with thermal variation. Our data suggest that ROS production is not associated with metabolic flexibility, as we found no differences across thermal treatment groups. However, we did find differences across tissues. Brain catalase activity demonstrated the lowest values compared with kidney, liver and muscle. In contrast, brain glutathione peroxidase (GPx) activities were higher than those in kidney and liver. Muscle GPx activities were intermediate to brain and kidney/liver. Lipid peroxidation damage was lowest in the kidney and highest in muscle tissue.

Uncovering sources, distribution, and seasonal patterns of trace element deposition: the elemental puzzle of the western Himalayas.

The transport and deposition of atmospheric pollutants in the Himalayas have a adverse impact on the climate, cryosphere, ecosystem, and monsoon patterns. Unfortunately, there is a insufficiency of data on trace element concentrations and behaviors in the high-altitude Himalayan region, leading to limited research in this area. This study presents a comprehensive and detailed comprehension of trace element deposition, its spatial distribution, seasonal variations, and anthropogenic signals in the high-altitude Kashmir region of the Western Himalayas. Our investigation involved the analysis of 10 trace elements (Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd, and Pb) in glacier ice, snow pits, surface snow, and rainwater collected at various sites including Kolahoi, Thajwas, Pahalgam (Greater Himalayan ranges), and Kongdori and Shopian (Pir Panjal Ranges) during 2021. The study reveals distinct ranges of concentrations for the trace elements at different sampling sites. Our analysis of trace element concentration depth profiles in snow pits reveals seasonal fluctuations during the deposition year. The highest concentrations were found in the autumn (below 20 cm) and summer (top layer), compared to the winter concentration (10-20 cm). The high enrichment factors (EFs) suggest the severity of human-induced trace metal deposition in the western Himalayan region, relative to surrounding regions. Surprisingly, the concentrations and EFs of trace elements showed seasonal contradictions, with lower concentration values and higher EFs during the non-monsoon season and vice versa. A source apportionment analysis using the positive matrix factorization (PMF) technique identified five sources of trace element deposition in the region, including crustal sources (32.33%), coal combustion (15.62%), biomass burning (17.63%), traffic emission (18.8%), and industrial sources (15.6%). Additionally, the study incorporated backward trajectories coupled with δ18O using the NOAA HYSPLIT model to estimate moisture sources in the region, which suggests atmospheric pollutants predominately deposited from the large-scale atmospheric circulation from westerlies (75%) during non-monsoon season. These findings underscore the urgent need for enhanced monitoring and research efforts in the future.

Calibration Methods for Low-Cost Particulate Matter Sensors Considering Seasonal Variability.

Many countries use low-cost sensors for high-resolution monitoring of particulate matter (PM2.5 and PM10) to manage public health. To enhance the accuracy of low-cost sensors, studies have been conducted to calibrate them considering environmental variables. Previous studies have considered various variables to calibrate seasonal variations in the PM concentration but have limitations in properly accounting for seasonal variability. This study considered the meridian altitude to account for seasonal variations in the PM concentration. In the PM10 calibration, we considered the calibrated PM2.5 as a subset of PM10. To validate the proposed methodology, we used the feedforward neural network, support vector machine, generalized additive model, and stepwise linear regression algorithms to analyze the results for different combinations of input variables. The inclusion of the meridian altitude enhanced the accuracy and explanatory power of the calibration model. For PM2.5, the combination of relative humidity, temperature, and meridian altitude yielded the best performance, with an average R2 of 0.93 and root mean square error of 5.6 µg/m3. For PM10, the average mean absolute percentage error decreased from 27.41% to 18.55% when considering the meridian altitude and further decreased to 15.35% when calibrated PM2.5 was added.

Seasonal variability of lesions distribution in acute ischemic stroke: A retrospective study.

Seasonal variability could have an impact on the incidence and outcome of stroke. However, little is known about the correlation between seasonal variability and location of acute cerebral infarction. This study aimed to explore the relationship between onset season and the lesions distribution of acute ischemic stroke (AIS). We retrospectively analysis data from 1488 AIS patients admitted to the Second Hospital of Tianjin Medical University from 2018 to 2022. All subjects completed head magnetic resonance imaging examination (MRI) and were divided into four groups according to the onset seasons. The lesions distribution of AIS was evaluated for anterior/posterior/double circulation infarction (DCI), unilateral/bilateral infarctions, and single/multiple cerebral infarctions based on MRI. Logistic regression models were employed to assess the association of season with lesions distribution of AIS. Subgroup analysis was performed in different stroke subtypes. Of 1488 patients, 387 (26.0%) AIS occurred in spring, 425 (28.6%) in summer, 331 (22.2%) in autumn and 345 (23.2%) in winter. Multivariate logistic regression demonstrated that the winter group had 2.15 times (95% CI:1.44-3.21) risk of multiple infarctions, 2.69 times (95% CI:1.80-4.02) of bilateral infarctions and 1.54 times (95% CI:1.05-2.26) of DCI compared with summer group, respectively. Subgroup analysis showed an increased risk of multiple (p < 0.01) or bilateral infarctions (p < 0.01) in small-artery occlusion (SAO) subtype, and higher risk of bilateral infarctions (p < 0.01) or DCI (p < 0.05) in large artery atherosclerosis (LAA) subtype during winter. No significant associations of season with lesions distribution in cardioembolism subtype. Our study highlighted a prominent seasonal variability in the lesions distribution of AIS, particularly in LAA and SAO subtypes. The findings could help to formulating meteorological risk warning strategies for different subtypes.

Frequency of office blood pressure measurements and the seasonal variability of blood pressure: results of the Hungarian Hypertension Registry.

PURPOSE: Hypertension is a major public health problem, thus, its timely and appropriate diagnosis and management are crucial for reducing cardiovascular morbidity and mortality. The aim of the new Hungarian Hypertension Registry is to evaluate the blood pressure measurement practices of general practitioners (GPs), internists and cardiologists in outpatient clinics, as well as to assess the seasonal variability of blood pressure. MATERIALS AND METHODS: Omron M3 IT devices were used during four-month periods between October 2018 and April 2023 in GP practices and in hypertension clinics. The blood pressure data were then transmitted online from the monitors' cuffs to a central database using the Medistance system of Omron. RESULTS: Family physicians (n = 2491), and internists/cardiologists (n = 477) participated in the study. A total of 4804 821 blood pressure measurements were taken during 10 four-month evaluation periods. In the ten periods, the daily average number of measurements was between 3.0 and 5.6. Following ESH diagnostic criteria, the proportion of subjects in optimal, normal and high-normal blood pressure categories were 14, 13.4 and 16.7%, respectively. Altogether 56% of the measurements belonged to stage 1, stage 2 or stage 3 hypertension categories (31.6, 17.1 and 7.4%, respectively). On average, a difference of 5/2 mmHg was observed between winter and summer data in systolic and diastolic blood pressures, respectively. The average systolic blood pressure values were higher in GP practices with more than 2000 patients than in the ones with less than 1500 patients (141.86 mmHg versus 140.02 mmHg, p < 0.05). CONCLUSION: In conclusion, the low daily average number of blood pressure measurements indicates a limited blood pressure screening awareness/capacity in the case of Hungarian family physicians. In GP practices with more patients, blood pressure is usually less well-controlled. These results suggest that the further promotion of home blood pressure monitoring is necessary.

What is the background?The standard method for the diagnosis of hypertension and for the control of treatment efficacy in hypertensive patients is office blood pressure measurement.Until now we had no real-life data on the blood pressure measurement practices of general practitioners (GPs), internists and cardiologists.Although seasonal differences in blood pressure values are well known, we had no data on the extent of these changes.What is new?In this real-world, nationwide observational study we were able to measure the frequency of blood pressure measurements in the daily practice of GPs, internists and cardiologists in Hungary, which was found to be very low compared to the number of patients they treat. In practices with more patients, blood pressure is generally less well-controlled.We could also detect a significant seasonal variation in systolic and diastolic blood pressure values over the observed time periods.What is the impact?The low daily average number of blood pressure measurements indicates a limited blood pressure screening awareness/capacity in the case of Hungarian family physicians, supporting the further promotion of home blood pressure measurement.The marked seasonal blood pressure changes demonstrated by our study require attention and the individual adjustment of treatment in different seasons.

Secondary formation of oxygenated and nitrated polycyclic aromatic compounds under stagnant weather conditions: Drivers and seasonal variation.

Severe air pollution tends to occur under stagnant weather conditions. This study focused on the occurrence and formation of PM2.5-bound polycyclic aromatic compounds (PACs) under stagnant weather conditions, in consideration of their adverse human health effect and ecological toxicity. The concentrations of PACs were higher under stagnant weather conditions than in other situations with averaged values of 46.0 ng/m3 versus 12.3-39.9 ng/m3 for total PACs. Secondary formation contributed to over half of the oxygenated and nitrated polycyclic aromatic compounds (OPAHs and NPAHs). Further analyses revealed different formation mechanisms for secondary OPAHs and NPAHs. Secondary production of OPAHs was sensitive to the variations of both temperature (T) and O3 concentration at T < 22 °C but sustained at a high level despite the fluctuation of temperature and O3 concentration at T > 22 °C. Elevated NO2 concentrations favored the formation of inorganic nitrogen-containing products over NPAHs under lower temperature and higher humidity. Stagnant weather events, accompanied by raised PAC levels occurred in all seasons, but their effects on secondary processes differed among seasons. The elevated temperature, lowered humidity, and increased NO2 level facilitated the secondary formation of OPAHs and/or NPAHs during the stagnant weather events in spring and summer. While under the temperature and humidity conditions in autumn and winter, increased NO2 levels during stagnant weather events promoted the production of secondary inorganic nitrogen-containing compounds over organic products. This study raised concern about the toxic organic pollutants in the atmosphere under stagnant weather conditions and revealed different formation mechanisms between secondary oxygenated and nitrated pollutants as well as among different seasons.

Seasonal Variations in Household Water Use, Microbiological Water Quality, and Challenges to the Provision of Adequate Drinking Water: A Case of Peri-urban and Informal Settlements of Hosanna Town, Southern Ethiopia.

Several studies have been conducted on household water use and microbial water quality globally. However, studies that considered seasonal variability of household water use and microbial water quality were limited. Therefore, this study investigated the seasonal variability of household water use, microbiological water quality, and challenges to the provision of adequate water in the peri-urban and informal settlements of Hosanna town, Southern Ethiopia. A longitudinal study was conducted on 288 households. The data was gathered using a pretested structured questionnaire, laboratory-analysis, interviews, storage-container inventories, focus group discussions, key-informant interviews, and an observational checklist. The data was analyzed using stepwise-multiple linear regression, bivariate and multivariable logistic regression, thematic-analysis, t-tests, and non-parametric-tests. Households were visited for 7 consecutive days during the dry and rainy seasons to account for changes in daily and seasonal variation of water use. 440 stored water and 12 source samples were analyzed for E. coli presence during dry and rainy seasons. The prevalence of stored water contamination with E. coli was 43.2% and 34.5% during the dry and rainy seasons, respectively. The per capita water consumption was 19.4 and 20.3 l during the dry and rainy seasons, respectively. Piped water on-premises, small family size, volume, and number of water storage containers were significant predictors of per capita water consumption in both seasons. Piped water off-premises, storing water for more than 3 days, uncovered, and wide-mouthed water storage containers were significantly associated with the presence of E. coli in water in both seasons. Seasonal variability of household water use and microbiological water quality was statistically significant, which is a significant public health concern and needs intervention to enhance water quantity and quality to mitigate the risk of waterborne diseases. Findings also suggest seasonal monitoring of the safety of drinking water to ensure that the water is safe and healthy.

Decoding seasonal variability of air pollutants with climate factors: A geostatistical approach using multimodal regression models for informed climate change mitigation.

In response to changes in climatic patterns, a profound comprehension of air pollutants (AP) variability is vital for enhancing climate models and facilitating informed decision-making in nations susceptible to climate change. Earlier research primarily depended on limited models, potentially neglecting intricate relationships and not fully encapsulating associations. This study, in contrast, probed the spatiotemporal variability of airborne particles (CO, CH4, SO2, and NO2) under varying climatic conditions within a climate-sensitive nation, utilizing multiple regression models. Spatial and seasonal AP data were acquired via the Google Earth Engine platform, which indicated elevated AP concentrations in primarily urban areas. Remarkably, the average airborne particle levels were lower in 2020 than in 2019, though they escalated during winter. The study employed linear regression, Pearson's correlation (PC), Spearman rank correlation models, and Geographically Weighted Regression (GWR) models to probe the relationship between pollutant variability and climatic elements such as rainfall, temperature, and humidity. Across all seasons, APs showed a negative correlation with rainfall while displaying positive correlations with temperature and humidity. The GWR and PC models produced the most reliable results from all the models employed, with the GWR model superseding the rest. Moreover, heightened aerosol levels were detected within a rainfall range of 600 mm/season, a temperature range of 25-30 °C, and humidity levels of 75 %-85 %. Overall, this study emphasizes the growing levels of APs in correlation with meteorological changes. By adopting a comprehensive approach and considering multiple factors, this research provides a more sophisticated understanding of the relationship between AP variability and climatic shifts.

Seasonal impact of acid mine drainage on water quality and potential ecological risk in an old sulfide exploitation.

Sulfides are usually associated with deposits of metals and coal. The reactive wastes from their exploitation, typically stored in piles and tailings dams, are often the mining sector's primary source of environmental problems. The surrounding river waters can present signs of acid mine drainage, responsible for aquatic ecosystem degradation. So, the main target of the present study is to investigate the impact of this process on the water's environmental quality and potential ecological risk. The study area is located at the Iberian Pyrite Belt, in an old sulfide exploitation, closed without environmental rehabilitation measures. The results exhibit high sulfate concentrations (410,601 mg/L) and potentially toxic elements, with prominence of Fe (134,000 mg/L), overcoming many other extreme cases of AMD pollution. The Ficklin diagram exposes that most samples are classified as "high-acid, high-metal." Two of them have extreme classifications (high-acid, extreme-metal). The pH value is well below the acceptable range for the environmental quality of superficial waters (5-7), measuring at a minimum of 0.84. Regarding seasonal variability, the study showed a higher degree of contamination in dry conditions (e.g., 4,420 mg/L of Cu), while the rainy month had lower concentrations of PTE (186.8 mg/L of Cu for the same sampling point). In addition, the water does not accomplish the environmental objectives established by the EU Water Framework Directive. According to the new approach developed based on a scale adjustment, the potential ecological risk index studied indicates that most sampled sites present strong, very strong, and even extremely potential ecological risk. With a typical Mediterranean climate, the region suffers from water scarcity, predicting increasingly in the future more degrading scenarios for water environmental quality. Consequently, urgent mitigation and remediation measures are necessary to improve and preserve water quality and fulfill the objectives of the United Nations Sustainability Development Goals.

The Modern Environment: The New Secondary Cause of Hypertension?

The most important risk factor for cardiovascular disease, the leading cause of death worldwide, is hypertension. Although most cases of hypertension are thought to be essential, the multifactorial associations of the environmental influence on blood pressure seem to play an important role and should be more closely investigated. This review attempts to focus on the recent literature that examines the environmental effects on arterial blood pressure and its management. Seasonal variability and the role of ambient temperature, either occupational or recreational noise pollution, as well as obesity due to environment-caused dietary habits, are recognized as important risk factors, affecting the onset as well as the regulation of hypertension. Furthermore, the effects of seasonal fluctuations in blood pressure, noise pollution, and obesity seem to share a similar pathogenesis, and as such to all further react together, leading to increased blood pressure. The activation of the autonomous nervous system plays a key role and causes an increase in stress hormones that generates oxidative stress on the vascular system and, thus, vasoconstriction. In this review, by focusing on the association of the environmental impact with arterial blood pressure, we come to the question of whether most cases of hypertension-if not all-should, indeed, be considered primary or secondary.

Seasonal distribution patterns of Scomberomorus commerson in the Taiwan Strait in relation to oceanographic conditions: An ensemble modeling approach.

The decline in the stock of the narrow-barred Spanish mackerel in the Taiwan Strait has sparked interest in conservation efforts. To optimize conservation and restoration efforts, it is crucial to understand their habitat preference in response to changing environments. In this study, ensemble modeling was used to investigate the seasonal distribution patterns of Spanish mackerel. Winter was identified as the most productive season, followed by fall; productivity was the lowest in summer. Five single-algorithm models were developed, and on the basis of their performance, four were selected for inclusion in an ensemble species distribution model. The spatial distribution of Spanish mackerel was primarily along the latitudinal range 23°-25°N in spring and summer. However, in fall and winter, the geographical range increased toward the southern region. The findings of this study will contribute to the understanding of this specific species and the approach used in this study may be applicable to other fisheries stocks also.

Statistical study on shallow water soundscape variability of Eastern Arabian Sea using noise level metrics.

Underwater soundscape that spans a broad frequency band shows variability consistent with contributing noise sources and ocean environment. However, increased anthropogenic activities result in noise proliferation which can harm natural marine habitat. Continuous monitoring of background sound is useful to assess such spatio-temporal variability of soundscape. Standard noise level metrics, for instance, mean (µ), 90th percentiles (90P), standard deviation (σ), and kurtosis (ß), are constructed from noise field measured from three coastal stations in Eastern Arabian Sea. These metrics are found to be suitable to describe the soundscape variability with respect to season, frequency, and depth. Mean and 90P are used to compare the seasonal variations while kurtosis metrics are exercised to check the impulsive nature of composite signal. Histogram representation and probability density function (PDF) were utilized to analyze the spectral variation in soundscape with respect to season. Analysis was carried out at 500-ms temporal window in two spectral bands corresponding to traffic and wind noise fields. Seasonal analysis shows that in summer, mean noise level decreases as hydrophone depth increases, while in winter, deeper depths have higher mean value with the presence of seasonal surface duct. This implication of sound speed profile on noise field has also been confirmed using appropriate noise model.

Temperature variability during the growing season affects the quality attributes of table grapes in Pothwar-insight from a new emerging viticulture region in South Asia.

Rising air temperature due to climate change has posed a mammoth challenge to global viticulture and key berry quality traits are compromised. Exploring the effects of seasonal temperature variability on berry ripening and quality attributes in different viticulture regions may help in sustainable viticulture industry. The present research was designed to explore the effect of temperature variables on key quality attributes of table grape cultivars in Pothwar region of Pakistan. Key berry quality traits such as total soluble solids (TSS), titratable acidity (TA), maturity indices (MI), ascorbic acid, sugars, total polyphenol contents (TPC) and total anthocyanin contents (TAC) were unlocked for four important table grape cultivars under varying environmental conditions at Chakwal and Islamabad districts for two consecutive vintages of 2019 and 2020. The district Chakwal has up to 0.92 °C, 1.35 °C, 1.12°C and 0.81°C higher Tmin, Tmax, Tmean and diurnal temperature variation (DTV) respectively, compared to Islamabad particularly for the 2019 vintage. The results of the present study revealed that the warmer site (Chakwal) has significantly (P ≤0.05) higher juice pH, TSS (°brix) and maturity indices (MI) particularly for the relatively hotter vintage of 2019. Interestingly, MI was 33% higher for the relatively warmer vintage of 2019 compared to 2020 with relatively lower acidity (up to 38%). Moreover, higher titratable acidity (11.2%), ascorbic acid (28.5%), polyphenols (20.3%) and anthocyanins (10.6%) were noticed for the colder Islamabad compared to Chakwal. Although elevated temperature for warmer location and vintage favoured berry ripening, however key biochemical attributes such as titratable acidity, ascorbic acid, polyphenols and anthocyanins were negatively affected. The findings of the present research provide useful insight into the impact of growing season temperature on key berry attributes and may help devise adaptation strategies to improve berry quality.

Spatial-temporal variability of methane fluxes in lakes varying in latitude, area, and depth.

Many previous studies have found spatial and seasonal variabilities in CH4 fluxes, which could significantly affect lake-wide CH4 budgets. However, the ways in which the spatial and seasonal patterns of CH4 fluxes vary among lakes on a global scale is largely unknown. We compiled literature on CH4 flux data from global lakes and analyzed the spatial and seasonal variabilities for lakes varying in latitude, maximum depth, and area. Spatially, we found a significant linear relationship between the ratio of littoral to profundal fluxes and lake morphology (more related to area than depth), while globally, half of the lakes would have within 5% error of CH4 emission estimation under single-zone sampling. Seasonally, mid-latitude lakes showed higher CH4 fluxes in the summer and autumn, indicating the influence of temperature and autumn overturn, and the latter being largely related to maximum depth. Globally, due to abundant shallow lakes in the mid-latitude zone, approximately 99% of lakes had higher fluxes in the summer, while 75% of lakes showed errors in CH4 emission estimation within 20% when only the summer flux was investigated. In the high-latitude lakes, CH4 evasion during the spring ice-off period was significantly correlated with lake maximum depth, while lake area was also important when analyzing the CH4 diffusive flux. Our study yields preliminary conclusions about spatial and seasonal patterns of CH4 flux in different lake types, which are fundamental to building an effective sampling strategy and to determining an accurate CH4 budget from global lakes.

Spatio-temporal patterns of zooplankton community in the Yellow River estuary: Effects of seasonal variability and water-sediment regulation.

Zooplankton community is ecological important because of its high sensitivity to environmental changes especially in estuarine areas. The Yellow River estuary (YRE) in China is the fifth biggest estuary in the world with significant seasonal characteristics and anthropogenic influence of Water-Sediment Regulation (WSR). This study investigated the spatio-temporal patterns of zooplankton in the YRE to explore the response of zooplankton to seasonal variation and WSR. Results suggested that the temporal patterns of zooplankton were mainly characterized by seasonal shift of dominant species. Hierarchical cluster analysis and non-metric multidimensional scaling determined summer, summer-autumn and winter-spring three zooplankton assemblages. Zooplankton spatial distributions represented seasonal consistency, in which the abundance generally showed a decreasing gradient from the river mouth to sea. WSR caused a high species replacement rate in July-August (80.36%) and a dramatic abundance decline from 4224.60 ind./m3 to 1541.10 ind./m3 with persistency and hysteresis effect. The high zooplankton abundance moved seaward in spatial distribution after WSR. Summer spatial pattern was determined with two and three zooplankton station assemblages, which was more clear after WSR. Redundancy analysis identified SSS, SST and transparency as important factors structuring zooplankton spatio-temporal patterns, in which SSS was the key one. The results provide a necessary reference for understanding the response of zooplankton community in estuarine areas to spontaneous changes and anthropogenic factors, and can help the protection of estuarine ecosystems and the formulation of hydrological regulatory policies.

Improvement of transpiration estimation based on a two-leaf conductance-photosynthesis model with seasonal parameters for temperate deciduous forests.

Introduction: Conductance-photosynthesis (Gs-A) models, accompanying with light use efficiency (LUE) models for calculating carbon assimilation, are widely used for estimating canopy stomatal conductance (Gs) and transpiration (Tc) under the two-leaf (TL) scheme. However, the key parameters of photosynthetic rate sensitivity (gsu and gsh) and maximum LUE (ϵmsu and ϵmsh) are typically set to temporally constant values for sunlit and shaded leaves, respectively. This may result in Tc estimation errors, as it contradicts field observations. Methods: In this study, the measured flux data from three temperate deciduous broadleaved forests (DBF) FLUXNET sites were adopted, and the key parameters of LUE and Ball-Berry models for sunlit and shaded leaves were calibrated within the entire growing season and each season, respectively. Then, the estimations of gross primary production (GPP) and Tc were compared between the two schemes of parameterization: (1) entire growing season-based fixed parameters (EGS) and (2) season-specific dynamic parameters (SEA). Results: Our results show a cyclical variability of ϵmsu across the sites, with the highest value during the summer and the lowest during the spring. A similar pattern was found for gsu and gsh, which showed a decrease in summer and a slight increase in both spring and autumn. Furthermore, the SEA model (i.e., the dynamic parameterization) better simulated GPP, with a reduction in root mean square error (RMSE) of about 8.0 ± 1.1% and an improvement in correlation coefficient (r) of 3.7 ± 1.5%, relative to the EGS model. Meanwhile, the SEA scheme reduced Tc simulation errors in terms of RMSE by 3.7 ± 4.4%. Discussion: These findings provide a greater understanding of the seasonality of plant functional traits, and help to improve simulations of seasonal carbon and water fluxes in temperate forests.

Aerosols' variability and their relationship with climatic parameters over West Africa.

Aerosols' influences on Earth's climate have been documented by several authors. This ranges from scattering and reflecting of shortwave radiation (direct effect) which is also regarded as the "Whitehouse Effect," to the ability to act as condensation nuclei (indirect effect) which results in cloud droplet formation. This broad summary of aerosol's effect on earth's climate has in turn affected some other weather variables either positively or negatively depending on people's perspectives. This work was done in a view to ascertaining some of these claims by determining the statistical significance of some certain aerosol's relationships with some selected weather variables. This was done over six (6) stations across the West African region to represent the climatic zones from the rainforest around the coasts to the desert of the Sahel. Data used consist of aerosol types (biomass burning, carbonaceous, dust, and PM2.5) and climatic types (convective precipitation, wind speed, and water vapor) over a period of 30 years, with the python and ferret programs explicitly used for the graphical analyses. Climatologically, locations close to the point source seem to record more of the presence of the pollutants than the farthest ones. Results indicated that aerosols were more pronounced in the dry months of NDJF over the rainforest region depending on the latitudinal position of the location. The relationship result showed a negative correlation between convective precipitation and aerosols, except carbonaceous. But the strongest relationship can be found between water vapor and the selected aerosol types.

Variations in the composition and structure of the lignins of oat (Avena sativa L.) straws according to variety and planting season.

The differences in the composition and structure of the lignins from straws of different oat (Avena sativa L.) varieties, planted in two seasons (winter and spring), were studied in detail by different analytical techniques such as pyrolysis coupled to gas chromatography-mass spectrometry (Py-GC/MS), two-dimensional nuclear magnetic resonance (2D-NMR), derivatization followed by reductive cleavage (DFRC), and gel permeation chromatography (GPC). Overall, the analyses revealed that oat straw lignins were enriched in guaiacyl (G; 50-56 %) and syringyl (S; 39-44 %) units, with relatively lower amounts of p-hydroxyphenyl (H; 4-6 %) units. The lignins also incorporated significant quantities of p-coumarates (8-14 % of total lignin units), which are acylating the γ-OH of the lignin side chains, and predominantly over the S units. Furthermore, oat straw lignins also incorporated considerable amounts of the flavone tricin (5-12 % of total lignin units). Interestingly, this study revealed that the lignin content and composition of the oat straws vary with genotype and planting season. Since p-coumarates and tricin are high-value aromatic compounds especially attractive from a biorefinery point of view, the information disclosed here is highly relevant to plant breeding programs aimed at developing functional foods and lignin modifications for improved biorefinery applications.

Distinct seasonal variability of source-dependent health risks from PM2.5-bound PAHs and related derivatives in a megacity, southwest China: Implications for the significance of secondary formation.

In contrast to polycyclic aromatic hydrocarbons (PAHs) which have been regularly monitored, the source-dependent health risk of their derivatives in ambient environment has not been well understood, especially regarding seasonal variability. In this study, oxygenated and nitrated PAHs (OPAHs and NPAHs) in PM2.5 samples from different seasons in urban Chongqing were analyzed and compared with PAHs from a human health perspective. Benzo[a]pyrene equivalent concentrations (BaPeq) were annually averaged at 6.13 ± 8.97 ng/m3 (n = 118) in the present study, with highest levels in winter followed by spring, autumn, and summer. The BaPeq values of OPAHs were higher than PAHs in spring and summer with seasonal averaged value up to 3.7 times of that for PAHs, manifesting significant underestimation of the health impact if only PAHs were considered. Incremental lifetime cancer risk (ILCR) model results suggested that the potential cancer risks were accumulated mostly from inhalation exposure during infancy and adulthood. Furthermore, in comparison with PAHs, OPAHs, mainly 6H-Benzo[c,d]pyren-6-one, had significant contribution to cancer risks (annually averaged at 58.3 %). Source-dependent cancer risks based on positive matrix factorization model denoted secondary formed PAH derivatives as a critical contributor to cancer risk, particularly in spring and summer (attributed to about 61 % of ILCR). The enhanced secondary formation of PAH derivatives during spring and summer was partially justified by diagnostic ratios and further analysis revealed that higher temperature, higher O3 level, and lower relative humidity besides stronger solar intensity during these two seasons as the most likely causes of this seasonal variation. Results in this study emphasizes that more knowledge on the formation and toxicity of OPAHs is imperative, especially in the context of complex PM2.5-ozone pollution in China.

Spatiotemporal trends of NDVI and its response to climate variability in the Abbay River Basin, Ethiopia.

Woody vegetation plays a vital role in regulating the water budget and energy exchange in the Earth's system. This study aimed at analyzing the spatiotemporal variability of Normalized Difference Vegetation Index (NDVI) and its response to Potential Evapotranspiration (PET), rainfall (RF), soil moisture (SM), and temperature (TEM) in the study area. The trends, correlations, and relationships between NDVI and climate variables were executed using Mann-Kendall monotonic trend (MKMT), partial correlation coefficients (PCC), and multiple linear regression (MLR) methods, respectively. Over the last 26 years, the interannual NDVI increased by 0.0065 yr-1 (R2 = 0.159, p = 0.157). The spatiotemporal MKMT and Theil-Sen slope analysis showed that interannual NDVI increased significantly in 78% of the basin's total area. Of the 78% of the basin, 31%, and 47%, of the total area showed extremely significant increasing (Zmk = 4.706, p ≤ 0.01), and significant increasing trends (Zmk = 2.378, p ≤ 0.05) respectively. The interannual variation of NDVI was well explained (R2 = 0.88, Adjusted R2 = 0.84) by the climate variables in the eastern, southeastern, and central sub-basins where agriculture, grass, sparse vegetation and barelands are the predominant land use land cover (LULC) classes. The main climatic factors that control vegetation growth and greenness during the rainy season were found to be PET, SM, and RF with 0.91, 0.99, and 0.86 PCC with NDVI respectively. The current study broadens the scientific community's understanding of the relationship between climate variables and vegetation growth in highland ecosystems. Understanding the seasonal and long-term relationship between climate and NDVI contributes to the scientific knowledge of highland ecosystems, which are extremely vulnerable to climate change.