Observed and future shifts in climate zone of Borneo based on CMIP6 models.

Climate change has significantly altered the characteristics of climate zones, posing considerable challenges to ecosystems and biodiversity, particularly in Borneo, known for its high species density per unit area. This study aimed to classify the region into homogeneous climate groups based on long-term average behavior. The most effective parameters from the high-resolution daily gridded Princeton climate datasets spanning 65 years (1950-2014) were utilized, including rainfall, relative humidity (RH), temperatures (Tavg, Tmin, Tmax, and diurnal temperature range (DTR)), along with elevation data at 0.25° resolution. The FCM clustering method outperformed K-Mean and two Ward's hierarchical methods (WardD and WardD2) in classifying Borneo's climate zones based on multi-criteria assessment, exhibiting the lowest average distance (2.172-2.180) and the highest compromise programming index (CPI)-based correlation ranking among cluster averages across all climate parameters. Borneo's climate zones were categorized into four: 'Wet and cold' (WC) and 'Wet' (W) representing wetter zones, and 'Wet and hot' (WH) and 'Dry and hot' (DH) representing hotter zones, each with clearly defined boundaries. For future projection, EC-Earth3-Veg ranked first for all climate parameters across 961 grid points, emerging as the top-performing model. The linear scaling (LS) bias-corrected EC-Earth3-Veg model, as shown in the Taylor diagram, closely replicated the observed datasets, facilitating future climate zone reclassification. Improved performance across parameters was evident based on MAE (35.8-94.6%), MSE (57.0-99.5%), NRMSE (42.7-92.1%), PBIAS (100-108%), MD (23.0-85.3%), KGE (21.1-78.1%), and VE (5.1-9.1%), with closer replication of empirical probability distribution function (PDF) curves during the validation period. In the future, Borneo's climate zones will shift notably, with WC elongating southward along the mountainous spine, W forming an enclave over the north-central mountains, WH shifting northward and shrinking inland, and DH expanding northward along the western coast. Under SSP5-8.5, WC is expected to expand by 39% and 11% for the mid- and far-future periods, respectively, while W is set to shrink by 46%. WH is projected to expand by 2% and 8% for the mid- and far-future periods, respectively. Conversely, DH is expected to expand by 43% for the far-future period but shrink by 42% for the mid-future period. This study fills a gap by redefining Borneo's climate zones based on an increased number of effective parameters and projecting future shifts, utilizing advanced clustering methods (FCM) under CMIP6 scenarios. Importantly, it contributes by ranking GCMs using RIMs and CPI across multiple climate parameters, addressing a previous gap in GCM assessment. The study's findings can facilitate cross-border collaboration by providing a shared understanding of climate dynamics and informing joint environmental management and disaster response efforts.

Dispersive solid phase microextraction based on magnesium oxide nanoparticles for preconcentration of auramine O and methylene blue from water samples.

In this study, we investigated the process of preconcentrate and determine trace amounts of Auramine O (AO) and methylene blue (MB) dyes in environmental water samples. For this purpose, the ultrasound-assisted dispersive-magnetic nanocomposites-solid-phase microextraction (UA-DMNSPME) method was performed to extract AO and MB from aqueous samples by applying magnesium oxide nanoparticles (MgO-NPs). The proposed technique is low-cost, facile, fast, and compatible with many existing instrumental methods. Parameters affecting the extraction of AO and MB were optimized using response surface methodology (RSM). Short extraction time, low experimental tests, low consumption of organic solvent, low limits of detection (LOD), and high preconcentration factor (PF) was the advantages of method. The PF was 44.5, and LOD for AO and MB was 0.33 ng mL-1 and 1.66 ng mL-1, respectively. The linear range of this method for AO and MB were 1-1000 ng mL-1 and 5-2000 ng mL-1, respectively. In addition, the relative standard deviation (RSD; n = 5) of the mentioned analytes was between 2.9% and 3.1%. The adsorption-desorption studies showed that the efficiency of adsorbent extraction had not declined significantly up to 6 recycling runs, and the adsorbent could be used several times. The interference studies revealed that the presence of different ions did not interfere substantially with the extraction and determination of AO and MB. Therefore, UA-DMNSPME-UV/Vis method can be proposed as an efficient method for preconcentration and extraction of AO and MB from water and wastewater samples.