Search

Abstract In the realm of fruit processing, karonda juice stands out for its elevated moisture levels, posing challenges in storage and transportation. This study presents a pioneer effort for concentration of karonda juice through optimizing the process parameters viz., temperature and time using central composite design (CCD) of response surface methodology (RSM) within rotary evaporator setup. Through ten experimental runs, variations were introduced, adjusting temperatures from 45 to 55 °C and duration from 90 to 210 min. The results showcased the efficacy of vacuum concentration, reducing moisture content to 16.43% and significantly elevating total soluble solids (TSS) from 9.02 to 89˚B. Moreover, key nutrients experienced substantial increase: ascorbic acid surged from 3.79 to 14.66 mg per 100 g, total phenolic content (TPC) soared from 100.74 to 386.97 mg GAE per 100 g, total antioxidant activity (mg AAE/100 g) escalated from 76.74 to 328.10 mg AAE per 100 g, anthocyanin content (mg/100 g) increased from 10.9 to 129.34 mg per 100 g, and iron content rose from 39 to 150.54 mg per 100 g. GC–MS profile elucidated compounds like Tetrahydrofuran, 3-Hydroxy-3-methylvaleric acid, 3-Hexen-2-one, Hydroperoxide and Octane. The optimization process, guided by RSM revealed the ideal parameters: 55 °C for 150 min, marking a significant advancement in karonda concentration techniques.

Wind erosion is one of the most critical problems in arid and semi-arid regions. The wind transports only dry soil, and no soil with a wet surface can be moved. The study aimed to investigate the changes in wind erosion potential in the coastal plains of Hormozgan province, Iran. Data from four synoptic stations from 1988 to 2017, as well as outputs from four climate models, namely HadGEM-2-CC, CSIRO-MK3- 6-0, ACCESS1-3 and CNRM-CM5, based on two Representative Concentration Pathways, RCP 4.5 and RCP 8.5, were used for the analysis. The outputs of climate models were ensembled and downscaled using the Change Factor statistical downscaling method. The downscaled data showed good accuracy in representing the large-scale GCM data. Furthermore, the "Potential of Wind Erosion Occurrence" was calculated for monthly and annual time scales using the Mann-Kendall nonparametric trend test. The results indicated that there were no significant trends in wind erosion occurrence during the base period (i.e., 1988 to 2017). However, it was projected that the "potential for wind erosion occurrence" and the "percentage of windy days associated with drought" would increase in the near future (i.e., 2031 to 2060) under both Representative Concentration Pathways (RCP 4.5 and RCP 8.5). Interestingly, both scenarios showed a decreasing trend in wind erosion occurrence in the far future (i.e., 2071 to 2100). This suggests that changes in wind patterns play a significant role in shaping wind erosion potential, while daily precipitation does not have a significant impact on this trend., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Global warming has amplified the frequency of temperature extremes, especially in hot dry countries, which could have serious consequences for the natural and built environments. Egypt is one of the hot desert climate regions that are more susceptible to climate change and associated hazards. This study attempted to project the changes in temperature extremes for three Shared Socioeconomic Pathways (SSPs), namely, SSP1-2.6, SSP2-4.5, and SSP5-8.5 and two future periods (early future: 2020-2059 and late future: 2060-2099) by using daily maximum (T max ) and minimum temperature (T min ) of general circulation model (GCMs) of Coupled Model Inter-comparison Project phase 6 (CMIP6). The findings showed that most temperature extreme indices would increase especially by the end of the century. In the late future, the change in the mean T min (4.3 °C) was projected to be higher than the mean T max (3.7 °C). Annual maximum T max , temperature above 95th percentile of T max , and the number of hot days above 40 °C and 45 °C were projected to increase in the range 3.0‒5.4 °C, 1.5‒4.8 °C, 20‒95 days, and 10‒52 days, respectively. In contrast, the annual minimum of T min , temperature below the 5th percentile, and the annual percentage of cold nights were projected to change in the range of 2.95‒5.0 °C, 1.4‒3.6 °C, and - 0.1‒0.1%, respectively. In all the cases, the lowest changes would be for SSP1-2.6 in the early period and the greatest changes for SSP5-8.5 in the late period. The study indicates that the country is likely to experience a rise in hot extremes and a decline in cold extremes. Therefore, Egypt should take long-term adaptation plans to build social resiliency to rising hot extremes., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Climate change impact on the habitat distribution of umbrella species presents a critical threat to the entire regional ecosystem. This is further perilous if the species is economically important. Sal (Shorea robusta C.F. Gaertn.), a climax forest forming Central Himalayan tree species, is one of the most valuable timber species and provides several ecological services. Sal forests are under threat due to over-exploitation, habitat destruction, and climate change. Sal's poor natural regeneration and its unimodal density-diameter distribution in the region illustrate the peril to its habitat. We, modelled the current as well as future distribution of suitable sal habitats under different climate scenarios using 179 sal occurrence points and 8 bioclimatic environmental variables (non-collinear). The CMIP5-based RCP4.5 and CMIP6-based SSP245 climate models under 2041-2060 and 2061-2080 periods were used to predict the impact of climate change on sal's future potential distribution area. The niche model results predict the mean annual temperature and precipitation seasonality as the most influential sal habitat governing variables in the region. The current high suitability region for sal was 4.36% of the total geographic area, which shows a drastic decline to 1.31% and 0.07% under SSP245 for 2041-60 and 2061-80, respectively. The RCP-based models predicted more severe impact than SSP; however, both RCP and SSP models showed complete loss of high suitability regions and overall shift of species northwards in the Uttarakhand state. We could identify the current and future suitable habitats for conserving sal population through assisted regeneration and management of other regional issues., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Byline: Stefan Fronzek (1), Timothy R. Carter (1) Abstract: An analysis is presented of the estimated impacts of climate change on resource potential in Europe under a wide range of model-based climate scenarios. Simple models and indices were used to assess impacts on the growing season, potential biomass, thermal suitability for the cultivation of crops, and potential energy demand for indoor cooling. Impacts were estimated for climate during the 1961--1990 baseline period (both observed and modelled) and projected during 2071--2100 based on outputs from a range of regional climate models (RCMs) driven by general circulation models (GCMs) assuming forcing by SRES emission scenarios A2 and B2, and from six atmosphere--ocean GCMs forced by a wider range of emission scenarios. Uncertainties in the projected impacts of climate change are assessed with respect to: (1) the direct climate model output vs. delta change approach, (2) differences in the driving GCMs and the RCM runs, (3) differences across a range of emission scenarios, (4) changes in long-term mean climate, and (5) changes in inter-annual climate variability. Future simulations show substantial changes in all analysed impact sectors, but with a relatively large spread of results attributable to uncertainties in future climate expressed by the different scenarios. Results included shifts of the northern limits of areas thermally suitable for the cultivation of soya bean and grain maize by several hundred kilometres, lengthening of the thermal growing season by 3--12 weeks, strong increases of potential biomass in northern Europe and slight decreases in southern Europe, and increased energy demand for cooling throughout Europe. Our results hint at systematic differences between RCM and GCM projections of temperature, though not precipitation, over Europe. The results also highlight the importance of accounting for inter-annual variability in estimating future impacts, through its affect on levels of risk. However, the results caution against the use of direct RCM outputs in impact models, due to biases in the representation of present-day climate. The delta change approach still appears to be the preferred option for most applications. Author Affiliation: (1) Finnish Environment Institute, Box 140, FIN-00251, Helsinki, Finland Article History: Registration Date: 20/11/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 17/03/2007

Abstract Climate change has placed considerable pressure on the residential environment, agricultural, and water supplies in different areas of the world, especially arid places such as Iraq. Iraq is one of the five most vulnerable countries in the world to climate change, where it has been encountering extremes heat waves during the most recent decades resulted in drought, desertification, and rivers dried up, which led to thousands of hectares to turn dry and yellow. This study aims to investigate the trends of climate change in the middle and western regions of Iraq and future expectations. The daily maximum temperature, minimum temperature, and precipitation are downscaled using the Long Ashton Research Station Weather Generator (LARS-WG) model. Five General Circulation Models (GCMs) from Coupled Model Intercomparison Project Phase 5 (CMIP5) are employed for three future periods: the near future (2021–2040), medium future (2051–2070), and far future (2081–2100), based on two scenarios of the Representative Concentration Pathways (RCP4.5 and RCP8.5) for four selected meteorological stations representing the study area. The outcomes of the calibration and validation of the model supported its skill and reliability to downscale precipitation and temperature time series for statistical indices (R2, RMSE and MBE) ranging between (0.894–0.998), (0.1270–1.9274) and (− 0.6158 to 0.0008), respectively. The results showed that the average minimum and maximum annual temperatures will increase at all selected stations across the three future periods by between 0.94 and 4.98 °C by the end of the twenty-first century. Annual changes in precipitation tend generally towards increase for the study area by average (6.09–14.31%) for RCP4.5 and (11.25–20.97%) for RCP8.5 Compared to the historical data (1990–2020). These findings can contribute to become more acquainted with the effects of climate change on the environment and encourage managers and planners to come up with plans for mitigating and adapting to these effects. They can also serve as a guide for future management of water and agricultural resources in the study region.

In this paper we explore the dominant position of a particular style of scientific modelling in the provision of policy-relevant scientific knowledge on future climate change. We describe how the apical position of General Circulation Models (GCMs) appears to follow 'logically' both from conventional understandings of scientific representation and the use of knowledge, so acquired, in decision-making. We argue, however, that both of these particular understandings are contestable. In addition to questioning their current policy-usefulness, we draw upon existing analyses of GCMs which discuss model trade-offs, errors, and the effects of parameterisations, to raise questions about the validity of the conception of complexity in conventional accounts. An alternative approach to modelling, incorporating concepts of uncertainty, is discussed, and an illustrative example given for the case of the global carbon cycle. In then addressing the question of how GCMs have come to occupy their dominant position, we argue that the development of global climate change science and global environmental 'management' frameworks occurs concurrently and in a mutually supportive fashion, so uniting GCMs and environmental policy developments in certain industrialised nations and international organisations. The more basic questions about what kinds of commitments to theories of knowledge underpin different models of 'complexity' as a normative principle of 'good science' are concealed in this mutual reinforcement. Additionally, a rather technocratic policy orientation to climate change may be supported by such science, even though it involves political choices which deserve to be more widely debated.

The dechlorination of chlorinated organic pollutants by zero valent iron (ZVI) is an important water treatment process with a complex dependence on many variables. This complexity means that there are reported inconsistencies in terms of dechlorination with ZVI and the effect of ZVI acid treatment, which are significant and are as yet unexplained. This study aims to decipher some of this complexity by combining Raman spectroscopy with gas chromatography-mass spectrometry (GC-MS) to investigate the influence of the mineralogy of the iron oxide phases on the surface of ZVI on the reductive dechlorination of pentachlorophenol (PCP). Two electrolytic iron samples (ZVI-T and ZVI-H) were found to have quite different PCP dechlorination reactivity in batch reactors under anoxic conditions. Raman analysis of the "as-received" ZVI-T indicated the iron was mainly covered with the ferrous oxide (FeO) wustite, which is non-conducting and led to a low rate of PCP dechlorination. In contrast, the dominant oxide on the "as-received" ZVI-H was magnetite which is conducting and, compared to ZVI-T, the ZVI-H rate of PCP dechlorination was four times faster. Treating the ZVI-H sample with 1 N H 2 SO 4 made small change to the composition of the oxide layers and also minute change to the rate of PCP dechlorination. However, treating the ZVI-T sample with H 2 SO 4 led to the loss of wustite so that magnetite became the dominant oxide and the rate of PCP dechlorination increased to that of the ZVI-H material. In conclusion, this study clearly shows that iron oxide mineralogy can be a contributing factor to apparent inconsistencies in the literature related to ZVI performance towards dechlorination and the effect of acid treatment on ZVI reactivity.

This study evaluates variability of East Asian Monsoon simulated by 24 coupled general circulation models (GCMs) participating in Coupled Model Inter-comparison Project 3 (CMIP3). Fifty years (1950 - 1999) of each model¡¦s twentieth-century climate simulation are analyzed and compared with observed data. Both East Asian Summer Monsoon (EASM) and East Asian Winter Monsoon (EAWM) are considered. Suitable indices are selected to analyze EASM and EAWM. The Wang-Fan index, associated with 850 hPa circulation pattern and tripole rainfall pattern are considered to analyze EASM. ICHENW, associated with 850 hPa circulation pattern, IGONGDY, associated with Siberian High, and ISUNBM, associated with 500 hPa East Asian trough are considered for analysis of EAWM. Inter-decadal and inter-annual variability of the EASM and EAWM are major focus of this study.

The olive fruit fly, Bactrocera oleae (Diptera: Tephritidae), uses 1,7-dioxaspiro[5.5]undecane ("olean"), produced primarily by females, as a sex pheromone. We used sequential solid phase microextraction-gas chromatography mass spectrometry (SPME-GCMS) analysis to show that female olive flies release about 1000 ng of pheromone at the onset of scotophase for several weeks, while males release about 1/100 as much during the first week after eclosion. The present research demonstrates details of employing SPME-GCMS with the partially known pheromone system of the olive fruit fly as a model for pheromone identification and diurnal release patterns in insects, especially fruit flies. The sequential SPME-GCMS method will readily allow detection and semi-quantification of semiochemicals released by insects in minute amounts throughout the diurnal cycle.

Background, Aim and Scope: Soil organic matter (SOM) is known to increase with time as landscapes recover after a major disturbance; however, little is known about the evolution of the chemistry of SOM in reconstructed ecosystems. In this study, we assessed the development of SOM chemistry in a chronosequence (space for time substitution) of restored Jarrah forest sites in Western Australia., Materials and Methods: Replicated samples were taken at the surface of the mineral soil as well as deeper in the profile at sites of 1, 3, 6, 9, 12, and 17 years of age. A molecular approach was developed to distinguish and quantify numerous individual compounds in SOM. This used accelerated solvent extraction in conjunction with gas chromatography mass spectrometry. A novel multivariate statistical approach was used to assess changes in accelerated solvent extraction (ASE)-gas chromatography-mass spectrometry (GCMS) spectra. This enabled us to track SOM developmental trajectories with restoration time., Results: Results showed total carbon concentrations approached that of native forests soils by 17 years of restoration. Using the relate protocol in PRIMER, we demonstrated an overall linear relationship with site age at both depths, indicating that changes in SOM chemistry were occurring., Conclusions: The surface soils were seen to approach native molecular compositions while the deeper soil retained a more stable chemical signature, suggesting litter from the developing diverse plant community has altered SOM near the surface. Our new approach for assessing SOM development, combining ASE-GCMS with illuminating multivariate statistical analysis, holds great promise to more fully develop ASE for the characterisation of SOM.

NMR spectroscopy and gas chromatography-mass spectrometry (GCMS) have both been used to study cardiac metabolism using substrates labeled with the stable isotope carbon-13. 13C-NMR studies of substrate oxidation are based on the assumption that the 13C-enrichment of glutamate reflects that of 2-ketoglutarate (2-KG). This assumption appears reasonable; however, it has not been thoroughly validated. The higher sensitivity of GCMS enables the direct determination of 13C-enrichment of 2-KG and other tricarboxylic acid (TCA) cycle intermediates. Therefore, using extracts from normal and diabetic hearts perfused with physiological concentrations of unlabeled glucose and 13C-labeled substrates, [3-(13)C](lactate + pyruvate) and [U-13C]palmitate, we compared the mass isotopomer distribution (MID) of citrate, 2-KG succinate and malate measured directly by GCMS with that extrapolated from 13C-NMR glutamate isotopomer analysis. A significant correlation between the absolute molar percent enrichments (MPE) of the various mass isotopomers of glutamate determined by 13C-NMR and 2-KG determined by GCMS was observed for all sixteen-heart samples. This correlation was improved if the contribution from unlabeled 2-KG was removed (i.e. relative MPE) indicating that 13C-NMR under estimated the unlabeled fraction. We attribute this discrepancy in the measurement of unlabeled 2-KG to the fact that GCMS measures M0 directly, while the NMR analysis calculates it by difference, since unlabeled glutamate is not detected by 13C-NMR spectroscopy. Despite the differences between the two methods, 13C-MID of glutamate determined by NMR provides a simple and reliable indicator of fluxes of 13C-enriched substrates through the TCA cycle. It is also clear that MID analysis of TCA cycle intermediates by GCMS is a sensitive and direct approach to assess substrate selection for citrate synthesis as well as a potential indicator of sites and extent of anaplerosis and/or compartmentation. This study demonstrates that the alliance of NMR and GCMS represents a powerful approach for investigating the control and regulation of cardiac carbon metabolism.

Global warming upsets the environmental balance and leads to more frequent and severe climatic events. These extreme events include floods, droughts, and heatwaves. These widespread extreme events disrupt various sectors of ecosystems directly. However, among all these events, drought is one of the most prolonged climatic events that significantly destroys the ecosystem. Therefore, accurate and efficient assessment of droughts is necessary to mitigate their detrimental impacts. In recent years, several drought indices based on global climate models (GCMs) of Coupled Model Intercomparison Project Phase 6 (CMIP6) have been proposed to quantify and monitor droughts. However, each index has its advantages and limitations. As each index ensembles different models by using different statistical approaches, it is well known that the margin of error is always a part of statistics. Therefore, this study proposed a new drought index to reduce the uncertainty involved in the assessment of droughts. The proposed index named the Ridge Ensemble Standardized Drought Index (RESDI) is based on the innovative ensemble approach termed ridge parameters and distance-based weighting (RDW) scheme. And the development of this RDW scheme is based on two types of methods i.e., ridge regression and divergence-based method. In this research, we ensemble 18 different GCMs of CMIP6 using the RDW scheme. A comparative analysis of the RDW scheme is performed against the simple model average (SMA) and Bayesian model averaging (BMA) schemes at 32 locations on the Tibetan plateau. The comparison revealed that RDW has less mean absolute error (MAE) and root-mean-square error (RMSE). Therefore, the developed RESDI based on RDW is used to project drought properties under three distinct shared socioeconomic pathway (SSP) scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5, across seven different time scales (1, 3, 7, 9, 12, 24, and 48). The projected data is then standardized by using the K-components Gaussian mixture model (K-CGMM). In addition, the study employs steady-state probabilities (SSPs) to determine the long-term behavior of drought. The outcome of this research shows that "normal drought (ND)" has the highest probability of occurrence under all scenarios and time scales., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Convective-cloud clusters with strong precipitation occur frequently in most of the Asian-Pacific summer monsoon (APSM) regions such as the Bay of Bengal (BOB), South China Sea (SCS), and Tropical Western North Pacific (TWNP). Cloud radiative forcing (CRF) is important in these regions. The net CRF at the top of the atmosphere (TOA) has shown large cooling over these APSM regions. This is on account of the presence of large amounts of high clouds with large optical depth. Through data analysis, the summer convective precipitation in TWNP is as strong as that in the BOB. However, the average net CRF at the TOA in the BOB (~ -36 Wm-2) is twice as big as in the TWNP (~ -17 Wm-2). The spectral analysis of cloud optical depth shows that in the BOB, the highest power is in the intra-seasonal timescale, while in the TWNP, the leading spectral peaks are less than 10 days. The radiative cooling from net CRF at the TOA could be associated with lowfrequency oscillation. The difference between the APSM regions is related to their sub-stages separating from CRF in time evolution.

Unlike other natural disasters, drought is one of the most severe threats to all living beings globally. Due to global climate change, the frequency and duration of droughts have increased in many parts of the world. Therefore, accurate prediction and forecasting of droughts are essential for effective mitigation policies and sustainable research. In recent research, the use of ensemble global climate models (GCMs) for simulating precipitation data is common. The objective of this research is to enhance the multi-model ensemble (MME) for improving future drought characterizations. In this research, we propose the use of relative importance metric (RIM) to address collinearity effects and point-wise discrepancy weights (PWDW) in GCMs. Consequently, this paper introduces a new statistical framework for weighted ensembles called the discrepancy-enhanced beta weighting ensemble (DEBWE). DEBWE enhances the weighted ensemble data of precipitation simulated by multiple GCMs. In DEBWE, we addressed uncertainties in GCMs arising from collinearity and outliers. To evaluate the effectiveness of the proposed weighting framework, we compared its performance with the simple average multi-model ensemble (SAMME), Taylor skill score ensemble (TSSE), and mutual information ensemble (MIE). Based on the Kling-Gupta efficiency (KGE) metric, DEBWE outperforms all competitors across all evaluation criteria. These inferences are based on the analysis of historical simulated data from 22 GCMs in the CMIP6 project. The quantitative performance indicators strongly support the superiority of DEBWE. The median and mean KGE values for DEBWE are 0.2650 and 0.2429, compared to SAMME (0.1000, 0.0991), TSSE (0.2600, 0.2397), and MIE (0.1550, 0.1511). For drought assessment, we computed the adaptive standardized precipitation index (SPI) for three future scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. The steady-state probabilities suggest that normal drought (ND) is the most frequent condition, with extreme events (dry or wet) being less probable., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Based on surface air temperature and precipitation, the current study examines the climate fluctuations over Sistan-and-Baluchestan Province, Iran's second-largest province. This area suffers from insufficient direct observations and a lack of climatic investigation. Three datasets were utilized including in situ data, gridded data (1984-2013), outputs of historical runs (during 1984-2013), and projections under the SSP5-8.5, SSP3-7.0, and SSP1-2.6 scenarios (in 2020-2049) of twenty-six Global Climate Models (GCMs) from the latest Coupled Model Intercomparison Project (CMIP6). The models' performance has been evaluated and ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in Multi-Criteria Decision Making (MCDM) technique including eight metrics in both seasonal and annual scales. The surface air temperature showed an increasing trend in seasonal and annual scales during 1984-2013, while the monthly precipitation trend increased for September-October-November and decreased for the other seasons and annual scale during 1984-2013. The top-ranked models for simulating surface air temperature (precipitation) were CESM2 (GFDL-ESM4), IPSL-CM6A-LR (UKESM1-0-LL), ACCESS-CM2 (GFDL-ESM4), and MIROC-ES2L (MPI-ESM1-2-LR) models in DJF, MAM, JJA, and SON seasons, respectively, while ACCESS-CM2 (CNRM-CM6-1-HR) model outperformed others in annual scale. Bias-corrected outputs of the top-ranked CMIP6 GCMs showed an increasing trend for surface air temperature in all seasons (from a 0.7 K increase in December-January-February season under SSP3-7.0 scenario to a 2.5 K increase in June-July-August season under SSP5-8.5 scenario) for period 2020-2049, comparing with that in 1984-2013 period. Bias-corrected monthly precipitation projected by top-ranked CMIP6 GCMs indicated both increasing and decreasing trends depending on selected season and scenario. This varied from a 5 mm/month decrease within December-January-February season under SSP5-8.5 scenario to a 13 mm/month increase during the March-April-May season under SSP1-2.6 scenario in 2020-2050, comparing with that from previous years., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

We conducted an analysis of 16 historical simulations from the High-Resolution Model Intercomparison Project (HighResMIP) as part of the Coupled Model Intercomparison Project (CMIP) phase 6 (CMIP6). These simulations encompass both high- and low-resolution models and aim to investigate the impact of improved horizontal resolution on mean and extreme precipitation in West Africa between 1985 and 2014. Six Expert Team on Climate Change Detection and Indices (ETCCDI) were used to charactererize extreme indices. Bias adjustment was used to detect and adjust the biases in the models. Our observations indicate that the southeastern and southwestern regions of West Africa experience the most significant precipitation, which aligns with the simulations from HighResMIP. The enhanced horizontal resolution notably influences the simulation of orographically induced rainfall in elevated areas and intensifies precipitation in various aspects. When examining the highest 1-day precipitation, our observations reveal that most of the Guinea Coast region had 1-day rainfall exceeding 100 mm. However, this was overestimated and in some simulations underestimated by HighResMIP simulations. Furthermore, an increase in horizontal resolution appears to enhance the ability of high-resolution models to replicate the observed patterns of heavy precipitation (R10mm) and very heavy rainfall (R20mm) days. Spatial and temporal analysis suggests that uncertainty exists in the simulation of extreme precipitation in both high- and low-resolution simulations over West Africa. Also, bias adjustment shows a significant bias in the simulations. To address this issue, we employed a bias adjustment approach., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

To anticipate disasters (drought, floods, etc.) caused by environmental forcing and reduce their impacts on its fragile economy, sub-Saharan Africa needs a good knowledge of the availability of current water resources and reliable hydroclimatic forecasts. This study has an objective to quantify the availability of water resources in the Nyong basin and predict its future evolution (2024-2050). For this, the SWAT (Soil and Water Assessment Tool) model was used. The performance of this model is satisfactory in calibration (2001-2005) and validation (2006-2010), with R 2 , NSE, and KGE greater than 0.64. Biases of - 11.8% and - 13.9% in calibration and validation also attest to this good performance. In the investigated basin, infiltration (GW_RCH), evapotranspiration (ETP), surface runoff (SURQ), and water yield (WYLD) are greater in the East, probably due to more abundant rainfall in this part. The flows and sediment load (SED) are greater in the middle zone and in the Southwest of the basin, certainly because of the flat topography of this part, which corresponds to the valley floor. Two climate models (CCCma and REMO) predict a decline in water resources in this basin, and two others (HIRHAM5 and RCA4) are the opposite. However, based on a statistical study carried out over the historical period (2001-2005), the CCCma model seems the most reliable. It forecasts a drop in precipitation and runoff, which do not exceed - 19% and - 18%, respectively, whatever the emission scenario (RCP4.5 or RCP8.5). Climate variability (CV) is the only forcing whose impact is visible in the dynamics of current and future flows, due to the modest current (increase of + 102 km 2 in builds and roads) and future (increase of + 114 km 2 in builds and roads) changes observed in the evolution of land use and land cover (LULC). The results of this study could contribute to improving water resource management in the basin studied and the region., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Bias correction (BC) of General Circulation Models (GCMs) variables is a common practice when it is being used for climate impact assessment studies at regional scales. The present study proposes a bias correction method (LR-Reg) that first adjusts the original GCM precipitation for local lapse rate corrections and later bias corrects the lapse rate-adjusted GCMs precipitation data with linear regression coefficients. We evaluated LR-Reg BC method in comparison to Linear Scaling (LS) and Quantile Mapping (QMap) BC methods, and NASA's downscaled NEX data for Monsoon Asia region. This study used Coupled Model Intercomparison Project Phase 6 (CMIP6)-based MIROC6 GCM precipitation with historical and projected shared socio-economic pathways (SSP) scenarios (SSP245 and SSP585) datasets. The BC comparison results show that the relative percentage reduction in mean absolute error (MAE) values of LR-Reg over LS-BC was up to 10-30% while this relative reduction in MAE values of LR-Reg was 30-50% over QMap-BC and 75-100% over NASA's NEX-data. The future projected precipitation over Monsoon Asia during dry season shows more decreased precipitation by up to 100% mostly in the south Asia while during wet season shows more increased precipitation by up to 50% mostly in the northeastern China and in the Himalayan belts with respect to the baseline condition (1970-2005). The results on the average precipitation per 0.25 degree increase in latitude analysis shows that the maximums of average monsoon precipitation during baseline period occur at 0 and 25 degree latitudes while the projected monsoon precipitation during both SSP scenarios occurs at 10 and 20 degree latitudes which clearly shows an inward shift in the latitude axis for the projected precipitation in the Monsoon Asia., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Abstract Objectives This study aimed to establish the exposure-lag-response effect between daily maximum temperature and stroke-related emergency department visits and to project heat-induced stroke impacts under global warming levels (GWL) of 2 °C and 4 °C. Methods Stroke-related emergency department visits in Taiwan from 2001 to 2020 were identified using the National Health Insurance Research Database (NHIRD). The study population consisted of 1,100,074 initial stroke cases matched with 2,200,148 non-stroke controls. We employed Distributed Lag Nonlinear Models (DLNM) in a case-crossover study to investigate the association between temperature and stroke. Generalized Estimating Equations (GEE) models with a Poisson function were used to correlate high-temperature exposure with annual stroke incidence rates. Projections were made under two global warming scenarios, GWL 2.0 °C and 4.0 °C, using Coupled General Circulation Model (GCMs). Baseline data from 1995 to 2014 were transformed for spatial distribution at the township level. Geographic Information System (GIS) spatial analysis was performed using Quantum GIS 3.2.0 software. Results DLNM exposure-lag-response effect revealed that daily maximum temperature exceeding 34 °C significantly increased the risk of stroke-related emergency department visits, particularly for ischemic stroke. Under the 2 °C GWL scenario, the frequency of days with temperatures surpassing 34 °C is projected to rise substantially by the median year of 2042, with a further increase to 92.6 ± 18.0 days/year by 2065 under the 4 °C GWL scenario. Ischemic stroke showed the highest increase in temperature-related incidence rates, notably rising from 7.80% under the GWL 2 °C to 36.06% under the GWL 4 °C. Specifically, the annual temperature-related incidence rate for ischemic stroke is expected to increase significantly by 2065. Regions such as Taichung, Hsinchu, Yilan, and Taitung demonstrated pronounced changes in heat-related ischemic stroke incidence under the GWL 4 °C. Conclusions The findings emphasize the importance of addressing temperature-related stroke risks, particularly in regions projected to experience significant temperature increases. Effective mitigation strategies are crucial to reduce the impact of rising temperatures on stroke incidence and safeguard public health.

Recurring floods, droughts, heatwaves, and other hydro-meteorological extreme events are likely to be increased under the climate change scenarios. The increased risk of these extreme events might have more exposure to the population; thus, it is important to discuss such extreme events and their projected behavior under a changing climate scenario. In the present study, we have computed the extreme precipitation and temperature indices over the 10 agro-climatic zones falling under the Ganga River Basin (GRB)utilizing a high-resolution daily gridded temperature and precipitation multi-model ensembled CMIP6 dataset (0.25° × 0.25°) under global warming levels of 1.5 °C, 2 °C, and 3 °C. We found that the annual daily minimum temperature (TNN) showed a higher rise of about 67% than the maximum temperature (TXX) of 48% in GRB. The basin also experiences a greater increase in the frequency of warm nights (TN90P) of about 67.71% compared to warm days (TX90P) of 29.1% for the 3 °C global warming level. Along with extreme indices, the population exposed due to the impact of the extreme maximum temperature has also been analyzed for progressive warming levels. Population exposure to extreme temperature event (TXX) has been analyzed with 20-year return period using GEV distribution method. The study concludes that the exposed population to extreme temperature event experienced an increase from 46.99 to 52.16% for the whole Ganga Basin. Consecutive dry days (CDD) and consecutive wet days (CWD) both show a significant increasing trend, but CWD has a significant increase in the majority of the zones, while CDD shows a significant decreasing trend for some of the zones for three warming levels periods. Extreme climate indices help to understand the frequency and intensity of extreme weather events such as heavy rainfall, droughts, and heatwaves to develop early warning systems and adaptation strategies to mitigate such events., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

This study examined the impact of climate change on climate extreme indices in the Kaduna River basin, Nigeria. Large-scale atmospheric variables derived from the Global Climate Model (GCM), Coupled Model Intercomparison Project Phase 5 (CMIP5) (CanESM2) were used to develop a high-resolution climate using a Statistical Down Scaling Model. The adapted Caussinus-Mestre algorithm for homogenizing networks of temperature series and multivariate bias correction based on an N-dimension probability function were used to homogenize and correct the climate data, respectively. Fifteen climate extreme indices were computed using RClimdex. The coefficient of variance, Kruskal-Wallis test, and the modified Mann-Kendall test were used to assess the variation and trends. Wavelet analysis was used to determine the periodicities of the indices (1980-2020). The findings revealed a significant warming trend with low variability of temperature indices. The moderate variability with an insignificant decreasing trend was found for rainfall indices. Similarly, the future climate indices indicate a continuing positive trend in the temperature extreme indices. The majority of climate indices have a periodicity of less than or equal to 10 years for high frequency, except for PRCPTOT, R10MM, R20MM, Rx5day, SDII, TN90p, and TX90p for temperature indices. The findings conclude that the periodicity pattern of climate extreme indices is related to atmospheric phenomena (such as quasi-biennial oscillation, QBO), which indicate the impact of climate change. As a result, this can serve as an early warning for possible extreme event occurrences in the basin. The CMIP6 should be used to compare with the results of this study to provide a detailed assessment of the current implication of climate change on the catchment., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Grassland ecosystems are affected by the increasing frequency and intensity of extreme climate events (e.g., droughts). Understanding how grassland ecosystems maintain their functioning, resistance, and resilience under climatic perturbations is a topic of current concern. Resistance is the capacity of an ecosystem to withstand change against extreme climate, while resilience is the ability of an ecosystem to return to its original state after a perturbation. Using the growing season Normalized Difference Vegetation Index (NDVI gs , an index of vegetation growth) and the Standardized Precipitation Evapotranspiration Index (a drought index), we evaluated the response, resistance, and resilience of vegetation to climatic conditions for alpine grassland, grass-dominated steppe, hay meadow, arid steppe, and semi-arid steppe in northern China for the period 1982-2012. The results show that NDVI gs varied significantly across these grasslands, with the highest (lowest) NDVI gs values in alpine grassland (semi-arid steppe). We found increasing trends of greenness in alpine grassland, grass-dominated steppe, and hay meadow, while there were no detectable changes of NDVI gs in arid and semi-arid steppes. NDVI gs decreased with increasing dryness from extreme wet to extreme dry. Alpine and steppe grasslands exhibited higher resistance to and lower resilience after extreme wet, while lower resistance to and higher resilience after extreme dry conditions. No significant differences in resistance and resilience of hay meadow under climatic conditions suggest the stability of this grassland under climatic perturbations. This study concludes that highly resistant grasslands under conditions of water surplus are low resilient, but low resistant ecosystems under conditions of water shortage are highly resilient., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Freshwater resources supply has always presented challenges and considering a changing climate quantifying the available water in the future is important. In the Caribbean, based on projections it is likely that the island of Trinidad would receive less intense rainfall, experience more dry days, become drier and warmer, and the water resources be decreased. In this study, the impact of a changing climate on the Navet Reservoir in Trinidad was investigated and reservoir volumes were quantified for the period 2011-2099. This period was subdivided into three time periods, 2011-2040, 2041-2070, and 2071-2099, and evaluated under the representative concentration pathways (RCPs): RCPs 2.6, 4.5, 6.0, and 8.5. Utilizing a calibrated/validated Soil Water Assessment Tool (SWAT) model for the Navet Reservoir together with projections from five general circulation models (GCMs), future monthly and seasonal reservoir volumes were estimated. The GCM precipitation and temperature data were bias-corrected using linear scaling and variance scaling methods. It was found that reservoir volumes are likely to be the lowest during the period 2041-2070 at the Navet Reservoir. Additionally, the projected reservoir volumes are reliable, resilient, and not vulnerable. These results may be used by water managers in the adaptation and mitigation of the impacts of a changing climate, thus, building resilience in the water sector., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Abstract The green synthesis of nanoparticles (NPs) gained significant impacts in various fields due to the use of eco-friendly approaches. In this study, silver nanoparticles (AgNPs) were synthesized from the aqueous extract of Hylocereus undatus fruit peel. The presence of AgNPs was analysed using characterization methods such as UV‒Vis, FTIR, GCMS, XRD, EDAX, and FESEM. The synthesized AgNPs showed greater antibacterial activity against Escherichia coli than against Streptococcus pneumoniae. The antifungal activity against Candida albicans was greater than that against Candida tropicalis. The IC50 value for the antibiofilm activity of the AgNPs was 2.81 µg/mL, whereas that of the H. undatus peel extract was 1.34 µg/mL. The invitro antioxidant activity of the AgNPs was evaluated using two different methods. The DPPH radical scavenging activity of the AgNPs and fruit peel extract was observed with IC50 values of 3.8 and 2.03 µg/mL respectively. On the other hand, nitric oxide radical scavenging activities were recorded and the IC50 values were calculated to be 2.8 and 2.3 µg/mL. The AgNPs demonstrated thrombolytic activity in human blood with 10, 32.36, and 56.25% lysis. The cytotoxicity of the AgNPs was minimal, with an IC50 of 0.2 µg/mL and the peel extract had the greatest cytotoxicity with an IC50 of 0.3 µg/mL. The findings of this study demonstrated that the synthesized AgNPs from H. undatus peel extract could be potential candidates for treating prostate cancer. Graphical abstract