Journal of Environmental & Earth Sciences

Thai Millennials’ Engagement with Carbon Footprint Tracking: Extended TAM Approach

2024-10-10T23:27:42+08:00

This study investigates the adoption of carbon footprint tracking apps (CFAs) among Thai millennials, a critical element in addressing climate change. CFAs have yet to gain significant traction among users despite offering personalized missions. Employing an extended Technology Acceptance Model (TAM) framework, we examine factors influencing CFA adoption intentions based on a sample of 30 environmentally conscious Thai millennials. Our findings indicate that perceived ease of use and enjoyment are crucial drivers of CFA adoption. Trust significantly impacts perceived usefulness, while enjoyment influences perceived ease of use. The study underscores the importance of user experience (UX) and enjoyment in driving adoption, highlighting the need for intuitive interfaces and engaging features. This research provides comprehensive insights into CFA adoption in Thailand by integrating TAM with external trust and perceived enjoyment factors. These findings offer valuable guidance for app developers, policymakers, and marketers, emphasizing the critical role of user experience and fun in fostering widespread CFA adoption. We discuss implications for stakeholders and suggest directions for future research, including larger-scale studies and cross-cultural comparisons within Southeast Asia. This research contributes to SDG 13 (Climate Action) and SDG 12 (Responsible Consumption and Production).

Assessing Water Level Variability in the Mekong Delta under the Impacts of Anthropogenic and Climatic Factors

2024-10-17T11:34:30+08:00

In recent years, the water level in the Mekong Delta (MD) has undergone changes, attributed to the impacts of anthropogenic activities and climate change. Declining water levels have had implications for various aspects of life and aquatic ecosystems in the lower basin water bodies. Analyzing long-term trends in rainfall and water levels is crucial for enhancing our understanding. This study aims to examine the evolving patterns of water level and rainfall in the region. Data on water levels and rainfall from observation stations were gathered from the National Center for Hydrometeorological Forecasting, Vietnam, spanning from 2000 to 2014. The assessment of homogeneity and identification of trend changes were conducted using the Standard Normal Homogeneity Test (SNHT) and the Mann-Kendall test. The results indicate that changes in water levels at the Tan Chau and Chau Doc stations have been observed since 2010 due to the operation of flow-regulating structures in the upper Mekong River. Following the commencement of upstream dam operations, the water level at the headwater stations of the Mekong River has been higher than the long-term average during the dry season and lower than the average during the flood season. The study findings highlight the influence of altered rainfall patterns under the impact of climate variability (ICC) on water level trends in the study area. While rainfall plays a significant role in increasing water levels during the flood season, the operation of hydropower dams (UHDs) stands out as the primary factor driving water level reductions in the study area.

Characterization of Mycoflora Associated with Catharanthus roseus Collected from Gardens in Kenitra City, Morocco

2024-11-21T14:33:47+08:00

This paper reports on the composition of fungal communities occurring on diseased tissues of Catharanthus roseus, which differed between organs. In total, ten different filamentous fungi were isolated, and the percentage of isolation varied significantly among the organs. Botrytis cinerea was the most prevalent fungus found on the plant's aboveground parts, with a frequency exceeding 50%. On twigs, the occurrence rate was 95.6%. It was isolated from leaves with a frequency of 88%, followed by Aspergillus niger (71.66 %), Alternaria alternata (67.33 %), Cladosporium herbarum (61%), Fusarium oxysporum (50.66%), Epicoccum nigrum (57.66%), Curvularia lunata (49.66%), Trichoderma harzianum (40%), and Penicillium sp. (27%). Whereas, Fusarium genus was more represented and six species were recorded: F. subglutinans (26%), F. chlamydosporium (20%), F. vertillioides (15.66%), F. solani (10%), F. oxysporum and F. nivale. Results highlighted dissimilar distribution of Fusarium species was noted on Catharanthus tissues on which F. subglutinas, F. chlamydosporium and F. oxysporum coexist on leaves and roots while F. solani was retrieved from leaves against F. nivale from roots. The floral buds and pods harbored opportunist fungi such as B. cinerea, Alternaria alternata and E. nigrum. On roots, Aspergillus, Penicillium and Fusarium were the main genera occurring with the frequencies of 26% (F. chlamydosporium), 40% (F. nivale), 72.33% (A. niger), 47.66% (A. flavus) and 37.66% (A. fumigatus). But no fungal species were detected on seeds of Catharanthus roseus. This is the first study to describe and enumerate the fungal complex associated with various symptoms on the aerial parts of Catharanthus roseus.

A Comparison among Different Machine Learning Algorithms in Land Cover Classification Based on the Google Earth Engine Platform: The Case Study of Hung Yen Province, Vietnam

2024-09-27T11:03:23+08:00

Based on the Google Earth Engine cloud computing data platform, this study employed three algorithms including Support Vector Machine, Random Forest, and Classification and Regression Tree to classify the current status of land covers in Hung Yen province of Vietnam using Landsat 8 OLI satellite images, a free data source with reasonable spatial and temporal resolution. The results of the study show that all three algorithms presented good classification for five basic types of land cover including Rice land, Water bodies, Perennial vegetation, Annual vegetation, Built-up areas as their overall accuracy and Kappa coefficient were greater than 80% and 0.8, respectively. Among the three algorithms, SVM achieved the highest accuracy as its overall accuracy was 86% and the Kappa coefficient was 0.88. Land cover classification based on the SVM algorithm shows that Built-up areas cover the largest area with nearly 31,495 ha, accounting for more than 33.8% of the total natural area, followed by Rice land and Perennial vegetation which cover an area of over 30,767 ha (33%) and 15,637 ha (16.8%), respectively. Water bodies and Annual vegetation cover the smallest areas with 8,820 (9.5%) ha and 6,302 ha (6.8%), respectively. The results of this study can be used for land use management and planning as well as other natural resource and environmental management purposes in the province.

Data to Cartography New MDE-Based Approach for Urban Satellite Image Classification

2024-09-27T14:20:34+08:00

Monitoring of the earth's surface has been significantly improved thanks to optical remote sensing by satellites such as SPOT, Landsat and Sentinel-2, which produce vast datasets. The processing of this data, often referred to as Big Data, is essential for decision-making, requiring the application of advanced algorithms to analyze changes in land cover. In the age of artificial intelligence, supervised machine learning algorithms are widely used, although their application in urban contexts remains complex. Researchers have to evaluate and tune various algorithms according to assumptions and experiments, which requires time and resources. This paper presents a meta-modeling approach for urban satellite image classification, using model-driven engineering techniques. The aim is to provide urban planners with standardized solutions for geospatial processing, promoting reusability and interoperability. Formalization includes the creation of a knowledge base and the modeling of processing chains to analyze land use.

Capital Matching, Environmental Regulation and Carbon Emission Performance

2024-09-27T15:25:41+08:00

Under the “dual carbon” goal, local governments in China have strategically focused on enhancing capital utilization efficiency and enforcing environmental regulations to improve carbon emission performance. This dual approach targets the intertwined challenges of economic development and environmental protection. Utilizing data from 266 prefecture-level cities in China from 2007 to 2019, this study systematically investigates the effects of capital matching and environmental regulation on carbon emission performance through the spatial Durbin model and the instrumental variable method. The results indicate that both capital matching and environmental regulation significantly enhance carbon emission performance. Capital matching demonstrates positive spatial spillover effects; whereas environmental regulation exhibits negative spatial spillover effects. Furthermore, there are synergistic effects between capital matching and environmental regulation that jointly enhance carbon emission performance. To address potential biases caused by endogenous environmental regulation, the study uses the proportion of environment-related words in provincial government work reports as an instrumental variable for environmental regulation. Additionally, to capture the heterogeneity in the environmental governance willingness and intensity of prefecture-level municipal governments, the study constructs heterogeneous instrumental variables. These variables are derived by multiplying the proportion of a prefecture-level city’s total industrial output value to the province’s total industrial output value with the proportion of environment-related words in the provincial government work reports. Analyses based on these instrumental variables reveal that endogenous issues in environmental regulation lead to an overestimation of its positive impact on carbon emission performance.

Evaluating the Interaction of Mycorrhizal Fungi, Azotobacter, and Biochar in Enhancing Cucumber Productivity and Soil Health

2024-09-27T15:27:39+08:00

This experiment evaluated the effects of the mycorrhizal fungus Glomus mosseae, Azotobacter chroococcum bacteria, and Biochar on the characteristics of the root system, and yield of the cucumber plant, Cucumis sativus L.; for this purpose, experiment designed: the first factor is a combination of Mycorrhizae (M) at 35 g plant^–¹, Azotobacter (A) 15 ml plant^–¹ with a microbial density of 2.2, and three concentrations (0, 5, 10%) of Biochar sprayed on the plant. The results of the research demonstrated that using mycorrhizae, Azotobacter bacteria, and phosphate rock with half the mineral recommendation (MAR) and spraying Biochar at a concentration of 10% gave the highest rate of infection of the roots with mycorrhizae, amounting to 80%, and the highest dry weight of the root system reached 84.53 g. The highest number of total bacteria was 8.74 log Cfu g m^–¹ of soil, the highest plant height reached 375.0 cm, the highest dry weight of the shoot reached 101.66 g plant^–¹, and the highest yield for the greenhouse was 4.501 ton greenhouse^–¹, followed by the treatment of adding Mycorrhiza with phosphate rock and half the mineral recommendation (MR) with Biochar at a concentration of 10%, then treatment with the addition of mycorrhizae with Azotobacter bacteria with half the mineral recommendation (AR) with 10% of Biochar. It is possible to eliminate half of the mineral recommendation by using these fertilizers, reduce the harmful impact of pollution on the environment and enhance sustainability in agriculture.

Enhanced Lead and Zinc Removal via Prosopis Cineraria Leaves Powder: A Study on Isotherms and RSM Optimization

2024-10-25T14:58:04+08:00

This study investigates the potential of Prosopis cineraria Leaves Powder (PCLP) as a biosorbent for removing lead (Pb) and zinc (Zn) from aqueous solutions, optimizing the process using Response Surface Methodology (RSM). Prosopis cineraria, commonly known as Khejri, is a drought-resistant tree with significant promise in environmental applications. The research employed a Central Composite Design (CCD) to examine the independent and combined effects of key process variables, including initial metal ion concentration, contact time, pH, and PCLP dosage. RSM was used to develop mathematical models that explain the relationship between these factors and the efficiency of metal removal, allowing the determination of optimal operating conditions. The experimental results indicated that the Langmuir isotherm model was the most appropriate for describing the biosorption of both metals, suggesting favorable adsorption characteristics. Additionally, the D-R isotherm confirmed that chemisorption was the primary mechanism involved in the biosorption process. For lead removal, the optimal conditions were found to be 312.23 K temperature, pH 4.72, 58.5 mg L−1 initial concentration, and 0.27 g biosorbent dosage, achieving an 83.77% removal efficiency. For zinc, the optimal conditions were 312.4 K, pH 5.86, 53.07 mg L−1 initial concentration, and the same biosorbent dosage, resulting in a 75.86% removal efficiency. These findings highlight PCLP’s potential as an effective, eco-friendly biosorbent for sustainable heavy metal removal in water treatment.

Growth Inhibition of Algae in Aquaculture Fishponds Using Banana Peel Powder: A Mesocosm Experiment

2024-09-27T11:07:16+08:00

Cyanobacterial blooms or algae problems in aquaculture fish–ponds are becoming a big concern to fish farmers due to reduced production of fish. Although several studies have been conducted around the globe focusing on cyanobacterial blooms in oceans and lakes, little has been done on inhibition of algal biomass impacting fish–ponds in aquaculture industry. The present study assessed the potential of banana peel ashes and potassium sulphate on algal growth inhibition within fish–ponds based on a six–weeks mesocosm experiment conducted with varying ash concentrations (i.e., 2, 4, 6, 8, 10 g·L⁻¹). This study analysed differences among treatments for the various nutrient variables (nitrates, ammonium and phosphates) at the end of the experiment. The significant experimental differences in physicochemical variables among the study weeks (i.e., 1–6 weeks), treatments (three levels, including controls) and ash concentrations using factorial repeated measures ANOVA were further tested. Moreover, algal growth was determined in order to test the efficiency of treatment n inhibiting algal growth by measuring chlorophyll–a concentration across 6 weeks. Banana peel ashes performed significantly well on inhibition of algal growth than potassium sulphate, except for controls. However, no clear patterns between pH and conductivity were observed throughout the experiment. The present study found that banana peel ashes do not have notable effects on water quality variable, particularly physicochemical parameters, which did not significantly change from first week of experiment. With banana peel ashes being the best inhibitor according to the findings of the present study, further studies are required to investigate the effects of banana peel ashes on fish within the ponds.

Assessing Carbon Sequestration and Biomass Distribution across Diverse Land Use Types in Ban Krang Subdistrict, Phitsanulok Province

2024-11-03T19:57:54+08:00

This study investigates carbon dioxide (CO₂) sequestration and biomass distribution across various plant components and land use types in Ban Krang Subdistrict, Mueang District, Phitsanulok Province, with the goal of enhancing carbon management strategies. Field surveys were conducted using 14 plots of 40x40 meters to quantify biomass and estimate CO₂ sequestration across different vegetation types. The findings reveal an average CO₂ sequestration of 122.81 Ton ha⁻¹, with aboveground biomass, particularly stems, contributing the most to carbon storage. Notably, abandoned perennial crops and mixed perennial crops demonstrated the highest sequestration rates, at 657.94 Ton ha⁻¹ and 613.00 Ton ha⁻¹, respectively. In contrast, agricultural lands such as rice paddies and cassava plantations exhibited the lowest sequestration rates, though rice paddies contributed the highest total CO₂ sequestration, amounting to 61,119.71 Tons, due to their extensive area. The study highlights the critical role of diverse and dense vegetation, particularly perennial crops, in maximizing carbon sequestration. It also underscores the potential for improving carbon storage in agricultural lands through better land management practices. The results suggest that targeted strategies should prioritize high-sequestration land use types while also enhancing carbon storage in low-sequestration areas. By optimizing land use and management practices, the region can significantly increase its carbon storage capacity, contributing to climate change mitigation and promoting long-term ecological sustainability. These insights are crucial for formulating effective carbon management strategies in Ban Krang Subdistrict, as well as in other comparable regions.

Long Term Variability of Extreme Sea Surface Temperature in the Gulf of Tonkin, China

2024-10-15T15:07:22+08:00

Till date, no study on trends in extreme sea surface temperature (SST) for different return periods has been done over the Gulf of Tonkin (GoT). Based on a 84-year (1940-2023) ERA5 Reanalysis data sets, this study for the first time, examined the spatio-temporal pattern in extreme SST for different return periods. Findings showed that more significant moderate to fast warming trends (0.1-0.16 °C per decade (dec^-1)) only existed for the 2 year return period. Temporal trends in the 99^th percentile SST are insignificant for all return periods. By using the linear regression method, the variability in extreme SST was obtained. Results showed that moderate warming trends dominated a large portion of GoT. Stronger trends, up to 0.018°C yr^-1 are noticed near Guangdong, Haikou and southern Sanya in south China. Extreme SST exhibited a slow warming trend of 0.008 °C per year (yr^-1) all through the study years. The SST is most stable in most waters in the southern GoT and few waters surrounding Dongfang. Temporal warming rates of SST revealed that 1940-1958, 1976-1994 and 2003-2012 were years of more coastal upwelling and could affect aquatic lives. The strongest warming rate of 0.07°C dec^-1 occurred during 1994-2003. The GoT appeared warmer during spring. Spatial decadal variability of SST revealed that moderate warming trends occurred in few regions in the southern GoT and in larger portion of the central and northern GoT. The rise in SST between 1980 and 2020 in the GoT is not limited to increased anthropogenic activities.

Impact of Bentonite and Humic Acid on the Growth and Flowering of Catharanthus roseus L. in Sandy Soil

2024-10-12T13:16:28+08:00

Bentonite is a very useful material for improving soil properties, which enhances the ability of plants to grow and produce in different conditions. The experiment was carried out in an agricultural nursery in one of the areas of the City of Diwaniyah, in a house covered with green netting, with a shade rate of 25%, to study the effect of bentonite and humic acid on the growth and flowering of a Catharanthus roseus L. plant in sandy soil. The experiment included two factors: the first factor was bentonite clay, and the second factor was humic acid. Using a randomized complete block design (R.C.B.D) with three replications, data were analyzed using the analysis of variance (ANOVA) method, and comparison was made according to the least significant difference (L.S.D) test at a probability level of 0.05. The experiment consisted of adding bentonite clay at 0, 2, 6, and 8 g L^–¹, humic acid at 0, 0.5, 1, and 10 g L^–¹. The results showed that adding bentonite clay and humic acid to sandy soil can have a significant positive effect on the growth and flowering of the Catharanthus roseus plant grown in poor sandy soil conditions. Bentonite, clay and humic acid were added at concentrations of 8 and 10 g L^–¹, which led to an increase in plant height and number of leaves and leaf area. They reached 30.07, 23.84 cm², 76.62, 63.42 cm² for leaf^–¹ and 24.73, 20.22 cm² for leaf^–¹, respectively. The results also showed an increase in the content of nitrogen (N), phosphorus (P), and potassium (K) in leaves by 2.27, 1.92, 1.99% and 1.51, 1.22, 1.77%. This also led to an increase in chlorophyll pigment and anthocyanin at the highest concentration and gave the highest value. Therefore, adding bentonite and humic acid together gave the highest values in vegetative and chemical characteristics, compared to treatments without addition.

Impact of Urbanization on Temperature Regime in Indian Subcontinent—A Case Study of Patna City

2024-09-29T10:37:57+08:00

Land use change ranks as the second most significant human-made factor affecting climate, following greenhouse gas emissions. Patna is rapidly expanding cities in Bihar state. Urbanization caused substantial alterations in land use patterns in Patna, driven by its rapid urban growth and increasing population. Urbanization and population growth caused a rapid increase in built structures to cater the demand, which caused reduction in vegetation, water body, and wasteland cover, due to which land cover changed. Land cover change detection plays a vital role in identifying its impact on diurnal temperature range (DTR). To study the impact, land use/ land cover change map for the city is produced from Landsat images for the study area Patna during 1995 to 2023. The supervised classification method is used to identify substantial changes in vegetation cover during 1995 and 2023 as a result of changes in land use and land cover. Landsat image supervised classification shows a growth of 47.80 percent in built-up areas in the last 28 years in the city of Patna. The classified image also shows a consistent decline of 31.74 percent in vegetation cover over the period of 28 years. Urbanization-driven changes in land use and land cover have led to a significant decrease of 20.24 percent in the near-surface DTR, average decrease of 12.54 percent in maximum temperature and an increase of 75.68 percent in minimum temperature of the city. The study offers scientific insights into how urbanization and human activities are impacting the eco-environment of the city.

Emotional Responses of Conservation Researchers to Climate Change and Its Influencing Factors

2024-10-21T13:28:20+08:00

Climate change has well-documented psychological consequences for society. However, the emotional experiences of frontline conservation professionals remain underexplored. As key knowledge producers and participants in decision-making processes, conservation researchers play a crucial role in shaping and implementing adaptation and mitigation efforts, which are pivotal for effective climate planning. Understanding their emotional responses is essential for enhancing the success of these strategies and supporting climate action. This study aims to identify the most prevalent emotions experienced by conservation researchers regarding climate change across various countries and to examine the qualitative and quantitative factors shaping these emotions. An online survey was conducted with 362 participants from 98 academic and research institutions, utilising both closed and open-ended questions to capture demographic data, climate knowledge, stances on mitigation and adaptation, and emotional responses. Data analysis revealed that feelings of powerlessness, guilt, and concern were most frequently reported, driven by a profound sense of inability to halt climate change, frustration with perceived inaction by governments and industries, and self-assessed personal shortcomings. Age and stances on climate adaptation were identified as primary factors influencing emotional responses, particularly among individuals aged 20-50 and 61-70, with opposition to adaptation correlating with stronger emotional reactions. Demographic factors such as region, place of residence, and mitigation stances played a minor role. These findings provide valuable insights into the psychological well-being of conservation researchers related to climate change.

Carbon Reduction Effect of Digital New Quality Productivity: Theoretical Analysis and Empirical Evidence

2024-09-23T10:07:50+08:00

The continuous innovation and widespread application of digital technology have expedited the transformation of productivity and presented an opportunity to achieve carbon peak and carbon neutrality. Digital new quality productivity, characterized by the integration of advanced technologies, innovative business models, a new economic framework, and ongoing innovation, stands as a superior production factor. It plays a crucial role in fostering high-quality economic growth and leading efforts to meet the “dual carbon” objectives. Using panel data from Chinese prefecture-level cities from 2011 to 2022, this study employs various econometric models to empirically examine the impact and underlying mechanisms of digital new quality productivity on carbon emission reduction. The findings reveal that: (1) There exists a significant U-shaped nonlinear relationship between digital new quality productivity and carbon emission performance, with an inflection point at 0.2750. (2) Dual objective constraints significantly moderate the relationship between digital new productivity and carbon emission performance. Setting moderate economic growth targets positively influences the effect of digital new quality productivity on carbon emission performance. (3) The impact of digital new quality productivity on carbon emission performance varies considerably based on factors such as urban location, city size, resource endowment, and specific city characteristics. It is essential to focus on nurturing digital new quality productivity, exploring the integration of balanced economic growth objectives with environmental goals, and effectively leveraging the environmental benefits derived from the advancement of digital new quality productivity tailored to local contexts.

Investigation the Effect of Exposure Aspergillus niger Isolate to the UV Radiation on Its Superphosphate Fertilizer Dissolving Efficiency in Calcareous Soil

2024-10-08T10:05:08+08:00

A laboratory experiment was conducted to demonstrate the importance of improving the efficiency of six isolates of Aspergillus niger fungi. Four isolates were exposed to UV-rays radiation at a distance of 30 cm, a wavelength of 254–255 nm during M₁₅, M₃₀, and M₄₅ minutes. Exposure periods, both of wild (no UV-rays exposure) and no A.niger (C) as controls, all six isolates were identified molecularly by polymerase chain reaction technique extracted DNA of A. niger was analyzed to ensure gene completion through multiple sequence alignment by bioinformatic programs to study the improvement of dissolving efficiency of mutant and wild A. niger. They were incubated after the addition of superphosphate fertilizer (47% P₂O₅) at 90 mg P kg^–¹ applied to soil with controls( no A. niger or no superphosphate) for I, II, III, and IV weeks of incubation periods at 28 ± 1 °C. In addition, the DNA extraction and purification by NanoDrop of Thermo Scientific-200 A280/A260 ratio was 2.01 and confirmed that the sequences of nitrogenous bases by the method of multiple sequence alignment (MSA) as compared to the reference sequence of A. niger recorded in the gene bank under the accession number LC632396. Results proved that the M₃₀ minutes exposure UV-rays radiation period was the superior dose when mutant Aspergillus niger obtained the highest amount of dissolved phosphate, reducing soil-pH with maximum biomass of A. niger during the M₃₀isolate during the third week (III).

Hydrogeochemical Processes in Basement Areas Using Principal Component in Burkina Faso (West African Sahel)

2024-08-30T09:27:08+08:00

The basement aquifers in Burkina Faso are increasingly exposed to groundwater pollution, largely due to socio-economic activities and climatic fluctuations, particularly the reduction in rainfall. This pollution makes the management and understanding of these aquifers particularly complex. To elucidate the processes controlling this contamination, a methodological approach combining principal component analysis (PCA) and multivariate statistical techniques was adopted. The study analyzed sixteen physicochemical parameters from 58 water samples. The primary objective of this research is to assess groundwater quality and deepen the understanding of the key factors influencing the spatial variation of their chemical composition. The results obtained will contribute to better planning of preservation and sustainable management measures for water resources in Burkina Faso. The results show that three principal components explain 72% of the variance, identifying anthropogenic inputs, with two components affected by mineralization and one by pollution. The study reveals that the groundwater is aggressive and highly corrosive, with calcite saturation. Water-rock interactions appear to be the main mechanisms controlling the hydrochemistry of groundwater, with increasing concentrations of cations and anions as the water travels through percolation pathways. PCA also revealed that the residence time of the water and leaching due to human activities significantly influence water quality, primarily through mineralization processes. These results suggest that rock weathering, coupled with reduced rainfall, constitutes a major vulnerability for aquifer recharge.

Sago Forests for Food Security and Handling Climate Change in Indonesia

2024-09-27T15:05:27+08:00

A crucial impact of climate change is the disruption of the agricultural sector, posing a threat to food supply for the globally increasing population. In this context, prioritizing food security in each country becomes an important concern. This study aimed to explore biomass and C-Stock content of Sago forests for handling climate change and resilience. The methodology used comprised various steps including determining the type and the hydraulic conductivity of the soil, assessing biomass and C-Stock by cutting Sago at various growth stages, weighing the wet and dry weight of each fraction, calculating the Top-Root Ratio, and determining the starch yield. The results showed that there were four types of soil namely Hydric, District, and Fluvic Gleisol, as well as Oxic Cambisole. C-Stock was 26.99 tonnes per hectare with a Top-Root Ratio of 636%, implying that above-ground biomass (AGB) was six times more than below-ground biomass (BGB) and the presence of mineral soil. Sago dry starch product ranged from 490.3–571.8 kg per tree and the potential relatively varied due to differences in the structure and composition of forests, as well as habitat and environment. Although logging remained persistent on a very small scale, early signs of disturbances were observed in hydrological conditions and fluctuations in water levels or puddles in the soil profile. This implied that conversion of Sago forests to other uses for the expansion of grain crops on a large scale, would lead to the area experiencing drought.

Development of Models for Estimating the Cost of Power Equipment Based on Supercritical Carbon Dioxide

2024-10-14T09:52:56+08:00

Power consumption increases annually, wherefore the air emissions during its production occasionally increase. One of the most promising trends of environmentally safe generation of electricity is the transition to oxygen-fuel power complexes operating on a carbon dioxide working medium, with a share of its capture up to 99%. It is worth noting that the breadth of application of power technologies is determined not only on the basis of criteria of thermal efficiency and environmental safety. The most important criterion is the indicator of economic accessibility, the failure of which does not yet allow for a large-scale transition to the use of electric power technologies with the capture and disposal of greenhouse gases. In this study, a set of multifactorial models for estimating the cost of the main generating equipment operating on supercritical carbon dioxide has been developed. it is found that an increase in the initial temperature and pressure will increase the cost of the main generating equipment operating on supercritical carbon dioxide.

Estimating Crop and Reference Evapotranspiration and Crop Factor and Some Growth Indicators for Wheat and Barley in Dhi Qar Governorate Using the CropWat Program

2024-10-22T14:03:27+08:00

Information about the average water consumption or evapotranspiration of crops is the basis for scheduling irrigation and the water requirements of plants, and choosing the appropriate crops for the region in light. This experiment was carried out to evaluate and calculate the ability of the CropWat program to estimate evapotranspiration rates, and plant consumptive water use for strategic crops in Iraq, including wheat and barley in Dhi Qar Governorate. The results of the study showed that the maximum root depth ranged between 1.20 m, and 1.10 m in the distance between the vegetative growth and flowering stages for wheat and barley crops, respectively. It was also noted that the crop evapotranspiration (ETc) values decreased at the beginning of the growing season, ranging from 0.79 mm day^–1 to 1.57 mm day^–1 for wheat and barley crops, respectively. Then, the values increased with the progress of the growing season and the increase of the vegetative mass of the plants, reaching 3.72 mm day^–1 and 3.46 mm day^–1 for wheat and barley crops, respectively. The reference evapotranspiration (ETo) values were also low in the first months of the year and were around 2.1 mm day^–1 at the beginning, then gradually increased with the progress of the months of the year, reaching the maximum reference evapotranspiration values of 10.5 mm day^–1 in the seventh month, and then the values decreased at the end of the season for wheat and barley crops.

Prioritizing Watersheds for Intervention Design Using GIS and Remote Sensing

2024-09-27T11:08:49+08:00

In many developing countries with poorly managed landscapes, soil erosion threatens the sustainability of water bodies. The main limitations of this study are the lack of daily sediment data, lithology, higher-resolution DEM data, and socioeconomic factors. Poor land use policy and resource management in the Upper Awash Sub-basin lead to soil erosion and sedimentation of hydrological infrastructure, Effective watershed prioritization requires integrating land use, hydrology, sediment load, and morphometric factors but often faces gaps, especially in the study area. This research aims to prioritise the Upper Awash Sub-Basin by its morphometric, land use and cover (LULC), and sediment yield characteristics. We used the integrated AHP-VIKOR multi-attribute decision-making method to prioritise watersheds, incorporating morphometry, LULC, and sediment load attributes in the simple matrix approach. The findings showed the following classes of erosion: exceedingly high (2722.14 km²), high (2524.46 km²), moderate (2205.48 km²), low (1611.43 km²), and extremely low (854.35 km²). Sub-watersheds WS6, WS8, WS10, WS13, and WS24 are the top priority for watershed management. The study ranked watersheds based on various attributes but encountered limitations such as the lack of daily sediment data, geological structure, and lithology. It can be concluded that this approach is very important to identify and categorize hotspots of soil erosion sub-watersheds for planners and decision-makers for conserving water and soil and for different environmental management purposes.

New MDA Transformation Process from Urban Satellite Image Classification to Specific Urban Landsat Satellite Image Classification

2024-09-27T15:04:34+08:00

In a context where urban satellite image processing technologies are undergoing rapid evolution, this article presents an innovative and rigorous approach to satellite image classification applied to urban planning. This research proposes an integrated methodological framework, based on the principles of model-driven engineering (MDE), to transform a generic meta-model into a meta-model specifically dedicated to urban satellite image classification. We implemented this transformation using the Atlas Transformation Language (ATL), guaranteeing a smooth and consistent transition from platform-independent model (PIM) to platform-specific model (PSM), according to the principles of model-driven architecture (MDA). The application of this IDM methodology enables advanced structuring of satellite data for targeted urban planning analyses, making it possible to classify various urban zones such as built-up, cultivated, arid and water areas. The novelty of this approach lies in the automation and standardization of the classification process, which significantly reduces the need for manual intervention, and thus improves the reliability, reproducibility and efficiency of urban data analysis. By adopting this method, decision-makers and urban planners are provided with a powerful tool for systematically and consistently analyzing and interpreting satellite images, facilitating decision-making in critical areas such as urban space management, infrastructure planning and environmental preservation.

Innovative Approaches in Water Decontamination: A Critical Analysis of Biomaterials, Nanocomposites, and Stimuli-Responsive Polymers for Effective Solutions

2024-11-03T19:22:55+08:00

In recent years, smart materials have emerged as a groundbreaking innovation in the field of water filtration, offering sustainable, efficient, and environmentally friendly solutions to address the growing global water crisis. This review explores the latest advancements in the application of smart materials—including biomaterials, nanocomposites, and stimuli-responsive polymers—specifically for water treatment. It examines their effectiveness in detecting and removing various types of pollutants, including organic contaminants, heavy metals, and microbial infections, while adapting to dynamic environmental conditions such as fluctuations in temperature, pH, and pressure. The review highlights the remarkable versatility of these materials, emphasizing their multifunctionality, which allows them to address a wide range of water quality issues with high efficiency and low environmental impact. Moreover, it explores the potential of smart materials to overcome significant challenges in water purification, such as the need for real-time pollutant detection and targeted removal processes. The research also discusses the scalability and future development of these materials, considering their cost-effectiveness and potential for large-scale application. By aligning with the principles of sustainable development, smart materials represent a promising direction for ensuring global water security, offering both innovative solutions for current water pollution issues and long-term benefits for the environment and public health.