Current Climate Change Research Articles

Quantitative Assessment of Forest–Tundra Patch Dynamics in Polar Urals Due to Modern Climate Change

The spatial and temporal dynamics of the Siberian larch (Larix sibirica Ledeb.) at the upper limit of its growth on the south-eastern macroslope of the Rai-Iz massif (Polar Urals, Russia) during the second half of the 20th to the beginning of the 21st century were analyzed. Current climate changes were accompanied by increased stand density on previously wooded parts of the mountain slopes and the appearance of new forest generations in lightly wooded or unforested parts of the studied area. Our original method for the automated recognition of boundaries among the key phytocoenohoras (closed forest, open forest, light forest, and tundra with single trees) is universally applicable and improves objectivity in selecting boundaries for these phytocoenohora types. With regard to the total area of the study site, the area of closed forest, open forest, and light forest, respectively, increased from 2.9% to 6.8%, from 9.6% to 13.1%, and from 7.5% to 15.6%, while the area of tundra lots with single trees decreased from 79.9% to 64.5%. Phytocoenohora type replacement in the course of the study period was characterized by a transition from forms with lower density to higher-density forms. Changes in the opposite direction were not discovered. Natural wind protection barriers for young larch tree generations included hummocks and groups of grown trees. The process of gradual tundra and forest tundra forestation then began on the leeward side of the barrier close to seed-producing trees.

Recovery of Neglected Species with Cloud Water Micro Condense Capacity as a Response to Climate Change: The Case of Sclerophyllous Boxwoods of Buxus balearica Lam. in the Southern Spanish Mediterranean

Understanding the survival needs of neglected or underutilized species (NUS) in agroforestry can offer valuable insights to mitigate climate change and biodiversity loss. This paper analyses the habitat heterogeneity of Buxus balearica populations (palaeorelict of the Mediterranean Basin) using a methodology that integrates four approaches: ecological profiling, multivariate analysis, and the clustering of populations according to environmental variables and suitability. The habitat analysis was conducted on 240 occurrence points, integrating open-source databases and germplasm collection field work. Results reveal that the distribution of B. balearica in the south of the Iberian Peninsula is mainly conditioned by thermal variations, the humidity regime, and microtopography, which makes it very vulnerable to current and future climate change scenarios. The analysis of habitat heterogeneity demonstrates its capacity to estimate genetic diversity, which provides a solid basis for future research and conservation actions. The rapid extinction process of these boxwoods is evident by comparing the suitability model under different climate scenarios. There is an urgent need to improve the current status of the species and associated landscapes, considering B. balearica as an underutilized species, and establishing a sound management plan to reinforce its populations and protect its natural habitat.

Classifying forest cover and mapping forest fire susceptibility in Dak Nong province, Vietnam utilizing remote sensing and machine learning

Forest fires can cause significant harm to the biodiversity, air quality, economy, and industries that depend on forests, which is particularly critical given the current climate change scenario. Therefore, it is crucial to predict potential fire risks, especially in Dak Nong, a province located in the highland region of Vietnam, where forest farming is prevalent. In this study, the utilization of remote sensing data from unmanned aerial vehicles (UAV) revealed a decline in forest areas while agricultural rubber and industrial crops witnessed an increase. Furthermore, the integration of SPOT satellite images with UAV and the eXtreme gradient boosting (XGBoost) classification algorithm proved highly efficient in mapping forest types in this province (OA = 81.446%, and Kappa = 0.803). To assess forest fire susceptibility in this study, a hybrid model known as Artificial bee colony-Adaptive neuro fuzzy inference system (ABC-ANFIS) was employed, which indicated that the majority of forests in the area face high to very high of fires, particularly in bamboo and dipterocarp forest areas. The present model is proposed to suggest better prevention and suppression strategies. These facts can help managers stop fires or deal with this disturbance more effectively that may occur in the future. Policymakers and researchers in different areas, such as the limestone forest in the north or the Dipterocarp forests in Vietnam, may consider replicating this study to evaluate specific wildfire risks and develop appropriate fire prevention strategies tailored to their local circumstances.

Short- and Mid-Term Forecasting of Pan-Arctic Sea Ice Volume Using Variational Mode Decomposition and Bidirectional Long Short-Term Memory

The well-documented decrease in the annual minimum Arctic sea ice extent over the past few decades is an alarming indicator of current climate change. However, much less is known about the thickness of the Arctic sea ice. Developing accurate forecasting models is critical to better predict its changes and monitor the impacts of global warming on the total Arctic sea ice volume (SIV). Significant improvements in forecasting performance are possible with the advances in signal processing and deep learning. Accordingly, here, we set out to utilize the recent advances in machine learning to develop non-physics-based techniques for forecasting the sea ice volume with low computational costs. In particular, this paper aims to provide a step-wise decision process required to develop a more accurate forecasting model over short- and mid-term horizons. This work integrates variational mode decomposition (VMD) and bidirectional long short-term memory (BiLSTM) for multi-input multi-output pan-Arctic SIV forecasting. Different experiments are conducted to identify the impact of several aspects, including multivariate inputs, signal decomposition, and deep learning, on forecasting performance. The empirical results indicate that (i) the proposed hybrid model is consistently effective in time-series processing and forecasting, with average improvements of up to 60% compared with the case of no decomposition and over 40% compared with other deep learning models in both forecasting horizons and seasons; (ii) the optimization of the VMD level is essential for optimal performance; and (iii) the use of the proposed technique with a divide-and-conquer strategy demonstrates superior forecasting performance.

The threat of a non-native oligochaete species in Iran's freshwater: assessment of the diversity and origin of Eiseniella tetraedra (Savigny, 1826) and its response to climate change.

Oligochaetes are the most abundant benthic taxa in aquatic ecosystems that play an important role in food webs. The present study aims to assess the diversity and origin of Eiseniella tetraedra as a non-native species in the Lar National Park of Iran and also its response to current and future climate change. We obtained the specimen from rivers and sequenced the mitochondrial gene Cytochrome Oxidase subunit I (COI) and combined them with 117 sequences from the Jajroud and Karaj rivers in Iran and native regions from GenBank (NCBI). We also ran Species Distribution Modelings (SDMs) using an ensemble model approach that was estimated according to two shared socio-economic pathways (SSPs): 126 and 585 of the MRI-ESM2 based on CMIP6. According to the results, all the samples examined in the current study originated from Spanish rivers, and no unique haplotype was found in the Lar National Park. Moreover, the results also show high haplotype diversity that can positively affect the success of this non-native species in different freshwater. Also, the results of SDMs depict that climate change would remarkably affect the distribution of E. tetraedra and it verifies the invasion power of E. tetraedra in Iran's freshwater ecosystems over time.

Assessing the invasion risk of Chelydra serpentina in China under current and future climate change scenarios

Chelydra serpentina, a species introduced to China for aquaculture purposes, is commonly found in its natural habitats within the country. The invasion of C. serpentina poses potential threats to both the biodiversity of China and human health. The potential distribution of C. serpentina has been simulated using the species distribution model – MaxEnt, incorporating global distribution data, climate, and land cover variables. Our simulations encompasses both current conditions and four future climate change scenarios. Currently, the potential distribution is concentrated in central, eastern, and southeastern regions of China, with the central and eastern regions facing the highest risk of invasion. Under future climate change scenarios, the distribution area may expand by 30–90%, and multiple provinces will face a more severe threat of invasion. This study presents the inaugural simulation of the potential invasion range of C. serpentina under current climatic conditions. Moreover, it reveals that climate change is likely to contribute to the expansion of its invasive range, thus furnishing a reference foundation for scientific prevention and control measures. We propose integrating citizen science and eDNA technologies into species monitoring to enhance the efficiency of detecting invasive species. This research has filled the gap in the research on the invasive distribution range of C. serpentina in China and globally, while also providing novel perspectives on the invasion control of this species.

Risk classification of low-lying coral reef islands and their exposure to climate threats

The bio-physical responses of low-lying coral islands to climate change are of concern. These islands exist across a broad range of bio-physical conditions, and vulnerabilities to rising and warming seas, ocean acidification and increased storminess. We propose a risk-based classification that scores 6 island eco-morphometric attributes and 6 bio-physical ocean/climate conditions from recent open-access data, to assign islands with respect to 5 risk classes (Very Low, Low, Moderate, High and Very High). The potential responses of 56 coral islands in Australia's jurisdiction (Coral Sea, NW Shelf and NE Indian Ocean) to climate change is considered with respect to their bio-physical attributes and eco-morphometrics. None of the islands were classed as Very Low risk, while 8 were classed as Low (14.3 %), 34 were Moderate (60.7 %), 11 were High (19.6 %), and 3 were Very High (5.4 %). Islands in the Very High risk class (located on the NW Shelf) are most vulnerable due to their small size (mean 10 Ha), low elevation (mean 2.6 m MSL), angular/elongated shape, unvegetated state, below average pH (mean 8.05), above average rates of sea-level rise (SLR; mean 4.6 mm/yr), isolation from other islands, and frequent tropical storms and marine heatwaves. In contrast, islands in the Low (and Very Low) risk class are less vulnerable due to their large size (mean 127 Ha), high elevation (mean 8.5 m MSL), sub-angular/round shape, vegetated state, near average pH (mean 8.06), near average SLR rates (mean 3.9 mm/yr), proximity to adjacent islands, and infrequent cyclones and marine heatwaves. Our method provides a risk matrix to assess coral island vulnerability to current climate change related risks and supports future research on the impacts of projected climate change scenarios. Findings have implications for communities living on coral islands, associated ecosystem services and coastal States that base their legal maritime zones on these islands.

The oxygen-tolerant reductive glycine pathway assimilates methanol, formate and CO2 in the yeast Komagataella phaffii

The current climatic change is predominantly driven by excessive anthropogenic CO2 emissions. As industrial bioprocesses primarily depend on food-competing organic feedstocks or fossil raw materials, CO2 co-assimilation or the use of CO2-derived methanol or formate as carbon sources are considered pathbreaking contributions to solving this global problem. The number of industrially-relevant microorganisms that can use these two carbon sources is limited, and even fewer can concurrently co-assimilate CO2. Here, we search for alternative native methanol and formate assimilation pathways that co-assimilate CO2 in the industrially-relevant methylotrophic yeast Komagataella phaffii (Pichia pastoris). Using 13C-tracer-based metabolomic techniques and metabolic engineering approaches, we discover and confirm a growth supporting pathway based on native enzymes that can perform all three assimilations: namely, the oxygen-tolerant reductive glycine pathway. This finding paves the way towards metabolic engineering of formate and CO2 utilisation to produce proteins, biomass, or chemicals in yeast.

Study on environmental factors affecting the quality of codonopsis radix based on MaxEnt model and all-in-one functional factor

Owing to the increasing market demand of Codonopsis Radix, the cropper blindly cultivates to expand planting area for economic benefits, which seriously affects the quality of Codonopsis Radix. Therefore, this study synthesized 207 batches of Codonopsis Radix and 115 ecological factors, and analyzed the suitable planting areas of Codonopsis pilosula under current and future climate change based on Geographic Information System (GIS) and MaxEnt model. Secondly, we evaluated the quality of Codonopsis Radix based on the all-in-one functional factor including chromatographic fingerprint, the index components, the effective compounds groups, the nutritional components, and the nutritional elements, and the quality regionalization of Codonopsis Radix was analyzed. Finally, the ecological factors affecting the accumulation of effective components of Codonopsis Radix were analyzed. This study found for the first time that the highly suitable area of Codonopsis pilosula was mainly distributed in the Weihe River system and the Bailongjiang River system in Gansu Province. There were differences in the quality of Codonopsis Radix from different ecologically suitable areas based on the all-in-one functional factors, and the comprehensive high-quality area of Codonopsis Radix was mainly distributed in Longnan and Longxi district of Gansu Province. The precipitation, temperature and altitude play a key role in the accumulation of chemical components in the 10 ecological factors affecting the distribution of Codonopsis pilosula. Under future climatic conditions, the highly suitable area of Codonopsis pilosula is decreased.

Seasonal gross primary production in response to environmental drivers from arid mangroves in the Gulf of California

Mangrove ecosystems provide multiple services, because of their Carbon (C) storage capacity they are recognized as blue carbon ecosystems. Gross Primary Productivity (GPP) is an important component of the C cycle, however is challenging to measure at multiple time and spatial scales, providing opportunity for novel and practical research using remote sensing. In northwestern Mexico mangroves find their northern most distribution in Sonora, were the North American Monsoon System that occurs from June to September is an important driver of ecosystem processes. The aim of this research was to changes of GPP at “Estero El Sargento” using remote sensing (MOD17A2H V6) and modeling (SPL4CMDL) products, and further explore environmental drivers that influence such change, for a period of three-year period (2014–2016). Our results show that in this mangrove site, GPP was not limited by precipitation, producing high values during the Pre-Monsoon season (385–490 gC m−2) than in the Monsoon season (260–311 gC m−2). Furthermore, high tide conditions, air temperature (T), and vapor pressure deficit (VPD) strongly drive GPP during the Monsoon (r2 = 0.4) and Post Monsoon (r2 = 0.6) seasonswhich was not the case for the Pre-Monsoon season. There is a clear seasonality that influences ecosystem processes, with T and VPD being the most relevant environmental drivers. The increase in T and VPD limits GPP, which is of vital importance under the current climate change conditions. This type of studies is important to the Comcaac (Seri) Nation especially with their ongoing conservation efforts.

Vulnerability assessment of Ukrainian forests as the basis of nature-based solutions for mitigation and adaptation to climate change

A wide range of climatic conditions in Ukraine causes significant regional differences in the vulnerability of forests to the current rapid climate change. The mitigation/adaptation strategy should be based on assessments of their vulnerability at the regional level.
 Phytoindication model by Prof. Y.P. Didukh was used to assess forest vulnerability. The model provides a quantitative estimation of climate as one of the major environmental factors affecting the distribution, condition and productivity of vegetation on the base of climate-related indicators – continentality, humidity and frost. For these indicators climate suitability scales were calculated. The modeling was carried out for the main forest species: Pinus sylvestris L., Quercus robur L., Fagus sylvatica L., Picea abies (L.) H. Karst, Betula pendula Roth., Alnus glutinosa (L.) Gaertn. and Robinia pseudoacacia L. Climate projections based on the Euro CORDEX time series (up to 2100) and 2 scenarios of the Representative Concentration Pathways (RCP 4.5, RCP 8.5) were used. Using Q-GIS, the maps containing zones of suitability to climate for each of the studied species were created for current climate conditions and future time series.
 The directions for strengthening the mitigation and adaptive capacity of forests are considered. The mainstream for nature-based solutions is adaptive sustainable forest management, which provides: 1) optimization of land use structure and increasing the forested area; 2) development and implementation of a national forestry program considering the priorities of climate change and low-carbon development; 3) using wood to substitute greenhouse gas intensive-materials and fossil fuels; 4) the best forestry practices through the introduction of modern Climate-Smart Forestry principles.

Modelling habitat suitability for Moringa oleifera and Moringa stenopetala under current and future climate change scenarios

Moringa oleifera Lam and Moringa stenopetala (Baker f.) Cufod are being widely promoted as multipurpose trees across the tropics for their nutritional, medicinal and soil health benefits. Different parts of these species are edible, have therapeutic values and their seeds are used for water purification. Although the two species are similar in many ways, they have contrasting distributions. However, their current promotion is not guided by adequate knowledge of the suitability of the target areas. Information is also scanty on the suitability of habitats for these species under the current and future climate change scenarios. Therefore, the objective of this study was to predict the habitat suitability of M. oleifera and M. stenopetala under current and future climate change scenarios using an ensemble of models assuming four shared socio-economic pathways, namely, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 for 2050 and 2070. The results suggest that areas that are highly suitable for M. oleifera will increase by 0.1% and 3.2% under SSP1-2.6 to SSP5-8.5 by 2050, respectively. By 2070, the area suitable for M. oleifera would likely decrease by 5.4 and 10.6% under SSP1-2.6 and SSP5-8.5 scenarios, respectively. The habitat that is highly suitable for M. stenopetala was predicted to increase by 85–98% under SSP3-7.0 and SSP5-8.5 scenarios by 2050 and by 2070, while suitable areas could increase by up to 143.6% under SSP5-8.5. The most influential bioclimatic variables for both species were mean diurnal temperature range, mean temperature of driest quarter, precipitation of wettest month, and isothermality. Additionally, soil pH, elevation and water holding capacity were influential variables in the distribution of M. oleifera, while soil pH, soil salinity and slope were influential in M. stenopetala distribution. This study has provided baseline information on the current distribution and possible future habitat suitability, which will be helpful to guide formulation of good policies and practices for promoting Moringa species outside their current range.

The role of the soil microbiome in the colonisation of glacier forefields by Antarctic pearlwort (Colobanthus quitensis) under current and future climate change scenarios

Glacier retreat in cold regions exposes new terrain for plant colonization. However, the roles of soil microbiomes in plant establishment and performance on newly-exposed forefields have rarely been assessed. Here, we compared the survival of Antarctic pearlwort (Colobanthus quitensis) individuals grown for three years in sterilised and unsterilised soils at sites initially at 30 m, 100 m and 300 m from three retreating Maritime Antarctic glaciers. We also installed open top chambers (OTCs), which increased air temperatures by ∼1.8 °C and reduced soil water potential by ≤ 4 kPa, on one forefield to test the effects of warming on C. quitensis survival and the soil microbiome. The main driver of plant performance was distance from glacier fronts, with a 32 kPa reduction in soil water potential apparently explaining reduced plant survival at 300m compared with 30 m from glaciers. Soil sterilisation had few effects on plant survival at 30 m and 100 m, but reduced survival at 300 m, which was attributable to reductions in beneficial plant-microbial interactions. Effects of OTCs on plant survival were amplified with distance from glacier and sterilisation, with plants not surviving in chambered and sterilised soil at 300 m after three years. Soil bacterial functionality altered from a phototrophic community at 30 m to a more specialized chemoheterotrophic community at 100–300 m. Fungal ortholog groups showed transfer RNA and ribosome biogenesis to be enriched in soil at 30 m, with spliceosomes and messenger RNA synthesis being more frequent at 300 m. We propose that soil microbiomes improve the environmental tolerance of C. quitensis through enhanced physiological performance, which in turn improves survival and facilitates the species’ colonization of newly-exposed glacier forefield soils. These plant-microbe interactions are likely to become increasingly important as the climate of Maritime Antarctica changes over future decades.

Carbon stocks of Geramo forest, the western escarpment of the rift valley of Ethiopia

Forests play a vital role in the global carbon balance and combating global climate change by sequestering and retaining carbon from the atmosphere in their biomass and soil. Thus, this study aims to estimate the carbon stocks in the biomass and soil along with various environmental factors in the Geramo forest in southern Ethiopia. Ninety-six plots (20 × 20 m2) were laid at a distance of 250 m along 16 line transects that were laid 300 m apart. Five 1 × 1 m2 subplots (4 at the corner and 1 at the center) were laid inside each main plot for LHG and soil data collection. The results revealed that the estimated total carbon stocks and mean carbon stock densities of the study forest were 57994 Mg h−1and 604 ± 344 Mg h−1, respectively, with a mean CO2 equivalent of 2217 ± 1262 Mg h−1. This result indicates the remarkable role of the Geramo forest in carbon stock and sequestration potential compared with other remnant forests in Ethiopia. Thus, the Geramo forest plays a crucial role in climate change mitigation through carbon sequestration, and hence, this forest can generate carbon credits as financial benefits to the nearby population in the future. The results also revealed that anthropogenic disturbances were negatively associated with the carbon stocks of the forest. Therefore, sustainable forest conservation activities are needed to conserve forest resources, protect the forest from growing anthropogenic disturbances, and sustain its current global climate change mitigation and adaptation benefits.

The water–energy–food (WEF) nexus as a tool to develop climate change adaptation strategies: a case study of the Buffalo River catchment, South Africa

Abstract The Buffalo River catchment in KwaZulu-Natal, South Africa, has limited water resource infrastructure development, and climate change is predicted to increase its water supply deficits by exacerbating water distribution inequalities. This study evaluates and optimises current climate change policy plans on the Buffalo River catchments water system to aid in assessing the sustainability of policies that address the aforementioned challenges. The water–energy–food (WEF) nexus approach, which encourages system thinking by considering interconnections among water, energy, and food resources when developing integrated natural resource management strategies, was used to perform the evaluation. The water system's reliability in meeting projected domestic, agricultural, and energy water demands under climate change conditions was used for gauging the sustainability of the development plans. Findings projected the existing water policy plans to increase the domestic water provision by >70% under climate change; however, the <3% increase in irrigation and energy generation water demand coverage yielded a significant contrast in reliability between densely populated areas and regions with extensive agricultural activities. The optimised policy plans, which improved water provision for all considered sectors increased by >20% under climate change, are thus recommended for future water resource management research and dialogue in the Buffalo River catchment.

Still Arctic?—The changing Barents Sea

The Barents Sea is one of the Polar regions where current climate and ecosystem change is most pronounced. Here we review the current state of knowledge of the physical, chemical and biological systems in the Barents Sea. Physical conditions in this area are characterized by large seasonal contrasts between partial sea-ice cover in winter and spring versus predominantly open water in summer and autumn. Observations over recent decades show that surface air and ocean temperatures have increased, sea-ice extent has decreased, ocean stratification has weakened, and water chemistry and ecosystem components have changed, the latter in a direction often described as “Atlantification” or “borealisation,” with a less “Arctic” appearance. Temporal and spatial changes in the Barents Sea have a wider relevance, both in the context of large-scale climatic (air, water mass and sea-ice) transport processes and in comparison to other Arctic regions. These observed changes also have socioeconomic consequences, including for fisheries and other human activities. While several of the ongoing changes are monitored and quantified, observation and knowledge gaps remain, especially for winter months when field observations and sample collections are still sparse. Knowledge of the interplay of physical and biogeochemical drivers and ecosystem responses, including complex feedback processes, needs further development.

Intra-uterine programming of future fertility.

The developmental origins of health and disease (DOHaD) shows that a relationship exists between parental environment at large, foeto-placental development and the risk for the offspring to develop non-transmittable disease(s) in adulthood. This concept has been validated in both humans and livestock. In mammals, after fertilization and time spent free in the maternal reproductive tract, the embryo develops a placenta that, in close relationship with maternal endometrium, is the organ responsible for exchanges between dam and foetus. Any modification of the maternal environment can lead to adaptive mechanisms affecting placental morphology, blood flow, foetal-maternal exchanges (transporters) and/or endocrine function, ultimately modifying placental efficiency. Among deleterious environments, undernutrition, protein restriction, overnutrition, micronutrient deficiencies and food contaminants can be outlined. When placental adaptive capacities become insufficient, foetal growth and organ formation is no longer optimal, including foetal gonadal formation and maturation, which can affect subsequent offspring fertility. Since epigenetic mechanisms have been shown to be key to foetal programming, epigenetic modifications of the gametes may also occur, leading to inter-generational effects. After briefly describing normal gonadal development in domestic species and inter-species differences, this review highlights the current knowledge on intra-uterine programming of offspring fertility with a focus on domestic animals and underlines the importance to assess transgenerational effects on offspring fertility at a time when new breeding systems are developed to face the current climate changes.

Isotopic variations in surface waters and groundwaters of an extremely arid basin and their responses to climate change

Abstract. Climate change accelerates the global water cycle. However, the relationships between climate change and hydrological processes in the alpine arid regions remain elusive. We sampled surface water and groundwater at high spatial and temporal resolutions to investigate these relationships in the Qaidam Basin, an extremely arid area in the northeastern Tibetan Plateau. Stable H–O isotopes and radioactive 3H isotopes were combined with atmospheric simulations to examine hydrological processes and their response mechanisms to climate change. Contemporary climate processes and change dominate the spatial and temporal variations of surface water isotopes, specifically the westerlies moisture transport and the local temperature and precipitation regimes. The H–O isotopic compositions in the eastern Kunlun Mountains showed a gradually depleted eastward pattern, while a reverse pattern occurred in the Qilian Mountains water system. Precipitation contributed significantly more to river discharge in the eastern basin (approximately 45 %) than in the middle and western basins (10 %–15 %). Moreover, increasing precipitation and a shrinking cryosphere caused by current climate change have accelerated basin groundwater circulation. In the eastern and southwestern Qaidam Basin, precipitation and meltwater infiltrate along preferential flow paths, such as faults, volcanic channels, and fissures, permitting rapid seasonal groundwater recharge and enhanced terrestrial water storage. However, compensating for water loss due to long-term ice and snow melt will be a challenge under projected increasing precipitation in the southwestern Qaidam Basin, and the total water storage may show a trend of increasing before decreasing. Great uncertainty about water is a potential climate change risk facing the arid Qaidam Basin.

Phosphoric acid activation of cow dung biochar for adsorbing enrofloxacin in water: Icing on the cake

In this study, we used different concentrations of H3PO4 to activate pristine biochar (BC) derived from cow dung (BC and BC modified with phosphoric acid at concentrations of 10% (10P-BC), 30% (30P-BC), and 50% (50P-BC)) in order to obtain cheap, high-performance adsorbents. Brunauer–Emmett–Teller analysis, scanning electron microscopy, X-ray diffraction, Fourier transform-infrared spectroscopy, X-ray photoelectron spectroscopy, organic element composition determination, and other analyses showed that activation with H3PO4 increased the porosity and hydrophilicity compared with the original BC, thereby enhancing the adsorption properties. The Langmuir isotherm model obtained the best fit and the maximum capacities for adsorbing enrofloxacin by BCs were 12.66 mg/g for BC, 51.90 mg/g for 10P-BC, 63.61 mg/g for 30P-BC, and 26.79 mg/g for 50P-BC. The main mechanisms responsible for antibiotic loading on BC were hydrogen bonding, π–π electron donor–acceptor interactions, pore filling, and electrostatic interactions. Calculations of fixed carbon retention before and after pyrolysis, and adsorption showed that activated BC had a good carbon fixation capacity and it was more capable of adsorbing enrofloxacin compared with the original BC, thereby providing a new method for removing organic pollutants from the environment and reducing carbon emissions. The cost efficiency was analyzed using the improved fuzzy comprehensive evaluation model based on the entropy method. Removal efficiency and utilization efficiency indicators were calculated for the different phosphoric acid activated BCs. The pollutant removal efficiencies were better for 10P-BC and 30P-BC, and the optimal removal efficiency was determined for 30P-BC. Given the current global climate change situation, using 10P-BC and 30P-BC could also help to meet China's carbon neutrality goals by reducing emissions of pollutants containing carbon.

WRF-Hydro for Streamflow Simulation in the MATOPIBA Region within the Tocantins/Araguaia River Basin—Brazil: Implications for Water Resource Management

The effective management of water resources in regions with a high potential for water resources, such as the Tocantins/Araguaia Basin in Brazil, is crucial in the face of current climate change and urban and agricultural expansion. In this context, this study evaluates the WRF-Hydro hydrological model to simulate the flow of the Manuel Alves Pequeno, Vermelho, and Manuel Alves Grande rivers in the MATOPIBA region (encompassing areas from the states of Maranhão, Tocantins, Piauí, and Bahia), an agricultural frontier and the most key area in terms of grain production in Brazil. The aim is to analyze the hydrological parameters of soil infiltration, surface retention depth, land surface roughness, and Manning’s channel roughness. The simulations are conducted at a spatial resolution of 3 km with a channel network of 100 m, covering a period of heavy rainfall from 13 March to 1 June 2018. For model validation, observational data from three river gauge stations of the National Water and Sanitation Agency are used, with assessments based on the Nash-Sutcliffe efficiency index, standard deviation of observations, root mean square error, percentage bias, and correlation coefficient, resulting in values of 0.69, 0.56, 4.99, and 0.83, respectively. In particular, the adjustment of the infiltration factor and surface roughness parameter has a greater contribution to improving the statistical results than the adjustment of the other two hydrological parameters. Additionally, the quality of discharge simulation at each river gauge station is correlated with the temporal distribution of simulated precipitation compared to observed data in the drainage network. Highlighting WRF-Hydro’s potential as a fine-scale model easily coupled with numerical weather prediction, this study significantly advances regional river dynamics evaluation, crucial for strategic water resource management.