Agricultural Land Research Articles

Transforming US agriculture for carbon removal with enhanced weathering

Abstract Enhanced weathering (EW) with agriculture uses crushed silicate rocks to drive carbon dioxide removal (CDR)1,2. If widely adopted on farmlands, it could help achieve net-zero emissions by 20502–4. Here we show, with a detailed US state-specific carbon cycle analysis constrained by resource provision, that EW deployed on agricultural land could sequester 0.16–0.30 GtCO2 yr−1 by 2050, rising to 0.25–0.49 GtCO2 yr−1 by 2070. Geochemical assessment of rivers and oceans suggests effective transport of dissolved products from EW from soils, offering CDR on intergenerational timescales. Our analysis further indicates that EW may temporarily help lower ground-level ozone and concentrations of secondary aerosols in agricultural regions. Geospatially mapped CDR costs show heterogeneity across the USA, reflecting a combination of cropland distance from basalt source regions, timing of EW deployment and evolving CDR rates. CDR costs are highest in the first two decades before declining to about US$100–150 tCO2 −1 by 2050, including for states that contribute most to total national CDR. Although EW cannot be a substitute for emission reductions, our assessment strengthens the case for EW as an overlooked practical innovation for helping the USA meet net-zero 2050 goals5,6. Public awareness of EW and equity impacts of EW deployment across the USA require further exploration7,8 and we note that mobilizing an EW industry at the necessary scale could take decades.

Indigenous knowledge to deter elephants damaging crop lands

Elephant and man conflict is becoming more and more common problem in Sri Lanka. As there is no solution, poor farmers face severe crops losses due to elephant attacks. Electric fences were also not effective due to rise in electricity cost and elephants get used to these methods and there are no effective methods so far. According to several ancient literature man elephant conflict was controlled by traditional and indigenous methods. Therefore, extensive literature surveys on research articles, ancient authentic texts, ancient books and news articles were conducted. Furthermore, focus group discussions with farmers were carried to extract information on the most successful methods to deter elephants from crops lands. Several successful methods were extracted and presented here in this paper to disseminate this valuable indigenous knowledge into the present generation. Methods identified were Beehive fences in the border of the farmland and when elephant touches the wires the disturbed swarm of bees attaches the elephant get into the crop’s fields. Buffers of cultivation of Chili, which is an irritant, causing elephants to cough, sneeze and eventually turn away from the crop field. Vegetable buffer zones with unpalatable crops such as sisal (Agave sisalana), chili (Capsicum frutescens) tea (Camellia sinensis), ginger (Zingiber officinale), mustard (Brassica nigra) or oilseed (Brassica napus) is another method. These unpalatable crops may not necessarily deter the elephants, but these crops will not be raided and therefore the farmers’ livelihood is ensured. When elephants crush the mustard plants, they feel the strong smell which the elephants do not like, and they turn back and go away. In addition, these crops will provide additional income to the farmers. Acoustic deterrents were used widely which are noises used to deter elephants, either by the shock value of an unexpected loud noise, or by specific noises that are known to scare elephants. Acoustic deterrents are disturbance shooting, elephant communication and Tigers on tape are few of them. Chemical deterrents such as chilli powers and chilli pasted robes are also used effectively. Physical barriers such as trenches, bamboo spike, sharp stones are also used to deter elephants. As the conclusion the above mentioned traditional and indigenous methods could be practiced with less cost and it will also be possible to gain additional income other than the main crop.

Vine Pruning Residues and Wine Fermentation By-Products: A Non-Exploited Source of Sustainable Agriculture, Albania Case

Albania, situated in southeastern Europe, enjoys a Mediterranean climate that is well-suited for grape cultivation. The vineyard area totals 7.202 million hectares. Since the 1990s, the country has experienced a resurgence in its rich winemaking traditions, which have gained considerable attention over the last decade. Alongside its significant wine production, large amounts of vine pruning waste and fermentation by-products are generated, estimated at over 50,000 t of prunings and 35,900 t of grape pomace annually. This waste is often burned, and the ash is used as fertilizer, releasing considerable CO2 emissions, and contributing to greenhouse gas levels. However, recycling these prunings into fertilizer by chipping and grinding them in the vineyard presents a sustainable choice, providing key minerals, nitrogen, phosphorus, and various micronutrients, thereby reducing the dependence on synthetic fertilizers in farming. Characterized by small plantations, the vine pruning issue needs site-specific, economically feasible solutions for the farmer. Additionally, there is unexplored potential for applying wine fermentation pressing residues as fertilizer for agricultural land or vineyards. The Albanian wine sector has significant untapped opportunities, such as employing vine pruning ash as a mineral fertilizer to help achieve sustainability goals.

The Changes in Grassland Animal Husbandry and Herdsmen’s Life in the Qinghai Pastoral Area of China Based on the Perspective of Changes in the Grassland Property Rights System

Based on the historical background of the changes made to the grassland property rights system, the first part of this study restores the changes in property rights systems in six major autonomous counties of grassland animal husbandry production in Qinghai region, while the second part qualitatively analyzes the changes in grassland animal husbandry operations and herdsmen’s life under the changes in property rights. The results show that, with the reform of the property rights system, the range of livestock grazing has changed from large-scale nomadic grazing to regional rotational grazing. The herds are mainly yaks and Tibetan sheep, accounting for more than 90%, with the proportion of Tibetan sheep being higher than that of yaks. The numbers of total livestock and those on the market first rose and then declined, showing a dynamic balance in recent 10 years, while the number of breeding female animals has increased year by year. Artificial grass planting has gradually become popularized in pastoral areas. The time span of livestock supplementary feeding has increased and is more scientific, and the output value of animal husbandry has increased year by year, showing a strong peak associated with intensification. The proportion of the population engaged in animal husbandry has decreased gradually with increasing population in the region. The income sources of herdsmen have become more and more diversified and are increasing year by year, and the Engel coefficient presents a downward trend. The human environment in pastoral areas has improved. Based on the above analysis, suggestions for the sustainable and high-quality production of animal husbandry under the current grassland property rights system are put forward, as well as for the construction of green organic agricultural and livestock product export land in Qinghai Province.

Impact of Environmental Factors of Stream Ecosystems on Aquatic Invertebrate Communities

Understanding the responses of stream ecosystems to environmental disturbances is essential for maintaining and restoring healthy ecosystems. In this study, we analyzed the associations between benthic macroinvertebrate communities and environmental factors using machine learning approaches to identify key stressors potentially influencing stream ecosystem health. Various machine learning models were evaluated, with random forest (RF) and gradient boosting machine (GBM) identified as the optimal models for predicting tolerant species (TS) and Ephemeroptera, Plecoptera, and Trichoptera (EPT) species densities. SHAP analysis revealed that watershed variables, such as elevation, flow velocity, and slope, significantly influenced EPT and TS populations. EPT population density increased with elevation and flow velocity but decreased significantly with higher levels of biochemical oxygen demand (BOD), total nitrogen (TN), and agricultural land-use proportions, with negative effects becoming evident beyond threshold levels. Conversely, TS population density showed a positive response to elevated BOD, TN, and agricultural land-use proportions, stabilizing at the threshold levels of BOD and TN, but continuing to increase with greater agricultural land use. Through machine learning, this study provides critical insights into how environmental variables are associated with the distribution of benthic macroinvertebrate communities. By identifying threshold levels of key stressors, this approach offers actionable guidance for managing agricultural runoff, enhancing riparian buffers, and implementing sustainable land-use practices. These findings contribute to the development of integrated watershed management strategies that promote the long-term sustainability of stream ecosystems.

Shorter growing seasons may moderate climate change effects on crop water demands

Abstract Rising evaporative demand (ETo) with a warming climate contributes to diminished water availability in water-stressed agricultural regions globally. While increased ETo typically necessitates increased irrigation, we explore how crop phenological response can moderate this challenge. Focusing on five key agricultural crops in California’s San Joaquin Valley, we employ coupled water balance and phenology models to project crop water demands as a function of increased ETo and changing phenology. All crops exhibited accelerated growth from a shortened growing season with warming. The shortened crop maturation period partially to fully offset increased crop water demands due to rising ETo, with the largest phenological influence for annual crops such as tomato and corn. By contrast, models that do not account for phenological changes showed increased irrigation demands of approximately 3.5-4.5% per °C of global warming primarily due to increased ETo. Integration with dynamic phenological models for the five key crops across the extent of agricultural land in the San Joaquin Valley showed a 1.6% decrease in irrigation needs under a 2°C warming scenario. While phenological change alongside plant physiological responses to increased atmospheric CO2 may help buffer the impact of climate change on crop irrigation demand, decreased crop yields with a shorter growing season and continued reliance of groundwater reserves for agricultural water use and reduced spring snowpack will threaten coupled agricultural and water security in the region.

Динамика земельного фонда Российской Федерации и Краснодарского края по категориям земель, составу и площади сельскохозяйственных угодий

The presented study is aimed at quantifying the dynamic characteristics of the land fund of the Russian Federation and the Krasnodar Territory in the period from 2018 to 2023. The work analyzes statistical data characterizing the distribution of land by category, changes in the composition and area of agricultural land. The methodological approach used makes it possible to identify spatial and temporal trends and differentiate them at the level of the territorial units under consideration. An analysis of official data from the State (national) Land Status and Use report revealed key trends in land transformation by category and agricultural land. At the federal level, there is a steady tendency to reduce agricultural land in parallel with an increase in the areas of specially protected natural territories and forest resources. This situation requires careful analysis from the point of view of ensuring the country's food security. In the Krasnodar Territory, known as a region with intensive agricultural production, an in-depth analysis of the dynamics of land categories revealed the main trends, taking into account possible causal factors affecting changes in the structure of land use. The results obtained made it possible to evaluate the effectiveness of existing land use strategies and identify potential ways to increase the area of agricultural land. Based on the analysis, specific recommendations are formulated to optimize spatial development both for the whole country and for the Krasnodar Territory, identifying the goal as sustainable and efficient use of land resources. Further research should focus on clarifying the contribution of individual factors and developing adaptive land-use strategies taking into account changing climatic conditions.

Modelling and Estimation of Average Annual Soil Loss in Ika South Local Government Area of Delta State, Nigeria

Soil-related phenomenon and the Sustainable Development Goals (SDGs) particularly SDG-15 are strictly tied. A healthy soil ecosystem encourages the existence of life on Earth and for agricultural purposes. One of the key factors that is contributing to unhealthy soil ecosystems is soil erosion. The research involves the assessment and modelling of soil erosion using the Revised Universal Soil Loss Equation (RUSLE II) with the sole aim of ascertaining the annual Soil loss within the study area, this will be a veritable tool in estimating soil loss in farming systems and in supporting the achievement of the SDGs. It provides a concrete estimation of the distribution of soil erosion at Ika South LGA, through the combination of the influencing factors such as rainfall aggressivity, soil erodibility, topography, vegetation cover, and soil conservation practices. The soil loss estimated at Ika South ranges from 0 to 49119.93 t/ha/year. Results have shown that 5% of the surface area displays a high rate of soil loss, and it represents zones with moderate to severe soil erosion. These areas are mainly situated in moderate to very high slope where the runoff is high. This loss is favoured by the other factors of erosion, which are also combined to accelerate erosion losses significantly (58% of the total area has a very high rainfall erosivity), moderately erodible soils (49% of the soils show a K factor between 0.128 and 0.27t ha H/ha MJ mm), 78% of the soil have nearly level to gently undulating plains, and 14% of the areas representing steep slopes. The results revealed that, there is a probability that the rate of erosion will increase in the future in this area which pose a great threat to the achievement of the SDG-15. Therefore, proper land-use planning should be adopted such as cropping pattern for agricultural land in local area. Accurate planning should be done as a means for restoring degraded vegetation.

Factors affecting the net ecosystem productivity of agroecosystems on mineral soils: a meta-analysis

ABSTRACT To optimize agricultural land management for soil carbon sequestration, it is necessary to identify whether agroecosystems are accumulating or gaining carbon. This can be done by determining an agroecosystem’s net ecosystem productivity (NEP). This study collated data from 40 papers, containing 242 annual measurements of NEP, to assess the impact of climate, soil type and management on the annual NEP of croplands and managed grasslands. Croplands lost significantly more carbon (110 g Cm−2) than managed grasslands (29.9 g Cm−2) and there was little statistical influence of climate, soil, or management practice on annual NEP. For agroecosystems to sequester carbon, there should be a shift in focus toward implementing management practices that increase carbon retention within agroecosystems.

Water Consumption, Quantity and Quality of Wastewater and Sewage Sludge from Polish Dairies

The peculiarity of the wastewater produced in Polish dairies stems from the frequency and specific technology of cottage cheese production. The aim of this study was to determine the water consumption and the quantity and quality of wastewater and sewage sludge discharged from Polish dairies based on the size of the plant and the production profile of the plant to characterize the wastewater treatment plants (WWTPs). Data were collected from eighteen dairies. Most of them have their own WWTP. Water consumption ranged from 1.5 litres (L) of water per litre of milk processed to 3.71 L/L. The specific volume of wastewater ranged from 1.18 to 5.78 L per L of milk processed. The raw wastewater concentrations were comparable to those of dairy wastewater in other European countries. Despite the disposal of domestic wastewater in WWTPs, the results of the sanitary examinations of the sludge showed it was suitable for agricultural purposes. Its heavy metal also made it applicable on agricultural land. The ratio of the sludge to raw milk processing was between 0.137 and 7.927 kg of sludge per 100 L of milk processed. The amount of sludge produced per pollutant (BOD) load removed ranged from 0.404 to 18.895 kg/kg BODremoved.

Integration of Deep Learning with Fox Optimization Algorithm for Early Detection and Classification of Tomato Leaf and Fruit Diseases

Tomato is a common vegetable crop extensively cultivated in the farming lands in India. The hot climate of India is perfect for its development, but particular weather conditions along with many other aspects affect the growing of tomato plants. Apart from these natural disasters and weather conditions, plant diseases consist a major issue in crop production. Precisely classifying leaf and fruit diseases in tomato plants is a vital step toward computerizing processes. Traditional disease detection models for tomato crops often fall short in predictability. To address this, Machine Learning (ML) and Deep Learning (DL) models have been developed, presenting advanced classification capabilities and the ability to manage the vast variability in agricultural data that conventional computer vision models struggle with. This work presents an Integration of DL with Fox Optimization Algorithm (FOA) for the Recognition and Classification of Tomato Leaf and Fruit Diseases (IDLFOA-DCTLFD). The major objective of the proposed IDLFOA-DCTLFD model is to enhance the detection and classification outcomes of tomato leaf and fruit diseases. At the initial stage, the Median Filter (MF) model is used for pre-processing and the Efficient Channel Attention-SqueezeNet (ECA-SqueezeNet) model is employed for feature extraction. For the hyperparameter tuning process, the proposed IDLFOA-DCTLFD technique implements the FOA. Finally, a Wasserstein Generative Adversarial Network (WGAN) is utilized for the detection of tomato leaf and fruit diseases. The IDLFOA-DCTLFD method is experimentally examined in a tomato leaf and fruit dataset. The experimental validation of the IDLFOA-DCTLFD methodology portrayed a superior accuracy value of 98.02%, surpassing the existing techniques.

Analysis of the Seasonal Change on the Sediment Transport in the Primary Channel of Saddang Irrigation Area

Irrigation channels are a vital component of an agricultural system, functioning to distribute water to agricultural land and support food security. The Saddang irrigation area, one of the main irrigation regions in Indonesia, plays a crucial role in enhancing agricultural productivity. However, the sediment accumulation in irrigation channels can significantly impact water distribution efficiency and environmental quality. The current research aims to analyze the influence of flow parameters during the rainy and dry seasons, examine the relationship between seasonal changes and sediment transport, and assess the impact of sediment discharge in the primary channel of the Saddang irrigation area. The tests conducted included sieve analysis, specific gravity, sediment concentration, and hydrometer analysis. Based on the research results, the average sediment discharge during the rainy season in the primary channel of the Saddang irrigation area is 2,702 tons/day, while during the dry season, the average sediment discharge is 100 tons/day. The ratio of the average sediment discharge between the rainy and dry seasons is 27:1. Additionally, linear equations were obtained to predict sediment discharge in the primary channel of the Saddang irrigation area. For the rainy season, the linear equation used is y = 857.67x - 1618.3, while for the dry season, it is y = 38.811x - 79.937. These equations have a validation rate of 98% between the linear equation and the actual calculation results, indicating high accuracy in modeling sediment discharge in the channel.

Influence of the Doyang Hydro Electric Project on land use land cover, land surface temperature and socio-economic conditions in Wokha district, Nagaland: India

ABSTRACT The Doyang Hydro Electric Project (DHEP) with a 75 MW power generation capacity was completed in 2000 on the Doyang river at Wokha district of Nagaland, India. This study analyses the changes in land use and land cover (LULC) and land surface temperature (LST) in the district from 1991 to 2021. Six LULC classes were analysed: forest land, water body, urban body, agricultural land, barren land, and shifting cultivation using supervised classification. The findings indicate significant LULC changes over the 30-year period. Urban areas expanded by 198.44%, from 10.42 km2 in 1991 to 31.15 km2 in 2021. Forest cover declined by 2.85%, while water bodies saw a dramatic increase of 133.3%. The regression analysis reveals a strong correlation between LULC changes and LST, with urban and barren lands contributing to higher temperatures, while forested areas, water bodies, agricultural lands, and shifting cultivation are associated with lower LST. A household survey conducted in three villages influenced by the DHEP revealed substantial socio-economic, agricultural, and environmental impacts. A paired sample t-test confirmed a significant decrease in agricultural activity, with a p-value of 0.000. These findings highlight the need for sustainable land management practices and consideration of socio-environmental impacts of large-scale infrastructure projects.

Effective Mapping of Fresh Water Aquaculture Ponds and its expansion in Agricultural Land using Time Series Data Based on Google Earth Engine Cloud Platform

Effective Mapping of Fresh Water Aquaculture Ponds and its expansion in Agricultural Land using Time Series Data Based on Google Earth Engine Cloud Platform

Isolation, screening, and characterization of heavy metal-resistant bacteria from solid waste dumping sites in Central Gondar, Northwest, Ethiopia.

Heavy metal pollution is one of the more recent problems of environmental degradation caused by rapid industrialization and human activity. The objective of this study was to isolate, screen, and characterize heavy metal-resistant bacteria from solid waste disposal sites. In this study, a total of 18 soil samples were randomly selected from mechanical sites, metal workshops, and agricultural land that received wastewater irrigation. Isolation and screening of the isolates were based on multiple heavy metal (copper (Cu), chromium (Cr), and lead (Pb)) resistance potential. Morphological, biochemical, and 16S rRNA gene sequencing techniques were used to identify the isolates. The minimum inhibitory concentration (MIC) of the potential isolates was further examined at various concentrations (3, 6, 12, 25, 50, and 100 µg/mL). Each isolate's ability to biodegrade and resist antibiotics was also examined. About 21 bacterial isolates were obtained. Among these, six potential isolates (Agri10-2Is2, Agri10-3Is2, Agri10-3Is1, AL10-1Is2, AL10-3Is1, and GA10-2Is1) were selected. The isolates displayed varied colony morphologies and biochemical characterization features. Phylogenetic tree results revealed that Agri10-2Is2, Agri10-3Is2, Agri10-3Is1, AL10-1Is2, AL10-3Is1, and GA10-2Is1 were identified as Bacillus subtilis, Bacillus subtilis, Bacillus species, Bacillus tequilensis, Klebiesella species, and Cronobacter sakazakii, respectively. Every isolate gave a different MIC value. The biodegradation capacity of Agri10-2Is2, Agri10-3Is2, Agri10-3Is1, AL10-1Is2, AL10-3Is1, and GA10-2Is1 was 92.2%, 92.57%, 92.37%, 92.66%, 92.85%, and 92.52% against Cu; 95.07%, 94.07%, 93.07%, 93.4%, 91.4%, and 94.4% on Cr; and 95.51%, 94.53%, 95.62%, 96.87%, 94.86%, and 97.09% against Pb, respectively. All isolates were found to be resistant to the tested antibiotics. This study concludes that the selected bacterial isolates could be potential agents for bioremediation of heavy metal-polluted environments.

Forewarned Is Forearmed: Documentation on the Invasion Risk of Asclepias speciosa in Greece and Europe

Biological invasions threaten biodiversity and agroecosystems, and early warning systems can minimise the spread of invasive alien species with limited resources. This study documents the presence of the alien plant Asclepias speciosa Torr., native to North America, that was first discovered in 2022 on Mount Vrontou, Central Macedonia, Northern Greece. This is the second European record of this alien species, after Lithuania, confirming its adaptability to contrasting European biogeographical regions. To enable future monitoring, this study provided new data on morphological traits of the species (above-ground parts), climatic tolerance (precipitation and temperature regimes), habitats with co-occurring species, pollinators, current reproductive potential, and seed germination at controlled temperatures (10 °C, 15 °C, and 20 °C). The high probability of misidentification with the highly invasive A. syriaca in European inventories supports the theory that A. speciosa may have been present in Europe long before it was officially reported. The lack of an EU-mandated reassessment of A. syriaca monitoring raises concerns regarding the potential invasion risk of A. speciosa in European natural and semi-natural areas or agricultural lands. Inspection mechanisms, early warning systems, and preventive measures are therefore essential to protect local biodiversity and agriculture from potential A. speciosa invasion, a risk that may be exacerbated by climate change.

Multi-scale influences on Escherichia coli concentrations in shellfish: From catchment to estuary.

Sustainability of bivalve shellfish farming relies on clean coastal waters, however, high levels of faecal indicator organisms (FIOs, e.g. Escherichia coli) in shellfish results in temporary closure of shellfish harvesting beds to protect human health, but with economic consequences for the shellfish industry. Active Management Systems which can predict FIO contamination may help reduce shellfishery closures. This study evaluated predictors of E. coli concentrations in two shellfish species, the blue mussel (Mytilus edulis) and the Pacific oyster (Crassostrea gigas), at different spatial and temporal scales, within 12 estuaries in England and Wales. We aimed to: (i) identify consistent catchment-scale or within-estuary predictors of elevated E. coli levels in shellfish, (ii) evaluate whether high river flows associated with rainfall events were a significant predictor of shellfish E. coli concentrations, and the time lag between these events and E. coli accumulation, and (iii) whether operation of Combined Sewer Overflows (CSO) is associated with higher E. coli concentrations in shellfish. A cross-catchment analysis gave a good predictive model for contamination management (R2=0.514), with positive relationships between E. coli concentrations and river flow (p=0.001), turbidity (p=0.002) and nitrate (p=0.042). No effect was observed for catchment area, the number of point source discharges, or agricultural land use type. 64% of all shellfish beds showed a significant relationship between E. coli and river flow, with typical lag-times of 1-3 days. Detailed analysis of the Conwy estuary indicated that E. coli counts were consistently higher when the CSO had been active the previous week. In conclusion, we demonstrate that real-time river flow and water quality data may be used to predict potential risk of E. coli contamination in shellfish at the catchment level, however, further refinement (coupling to fine-scale hydrodynamic models) is needed to make accurate predictions for individual shellfish beds within estuaries.

Urban growth dynamics and its influence on land surface temperature in Bhubaneswar metropolitan city: a 1990–2021 analysis

This study investigates the impact of urbanization on land use and land cover (LULC) changes and their consequent effects on land surface temperature (LST) in Bhubaneswar, India, over a 30-year period from 1990 to 2021. It uses Landsat satellite imagery from Thematic Mapper (TM) and Operational Land Imager (OLI) sensors, along with correlation analysis, to assess the spatial and temporal dynamics of LULC and their influence on LST. The analysis reveals a significant transition in LULC, with a 60.91% overall change observed during the study period. Built-up areas increase substantially, from 18.83% to 43.17%, while vegetation cover and agricultural land, decline from 28.34% to 12.03% and 34.18% to 21.60%, respectively. Results indicate a direct correlation between increased built-up land and elevated LST, while vegetation cover shows a negative correlation with LST, as measured by the Normalized Difference Vegetation Index (NDVI). Conversely, the Normalized Difference Built-up Index (NDBI) exhibits a positive correlation with LST, highlighting the thermal impact of urban expansion. These findings underscore the critical role of sustainable urban planning in mitigating the adverse effects of urban heat islands and guiding future development policies in Bhubaneswar. The study’s outcomes provide a scientific basis for urban planners to design strategies that balance urban growth with environmental sustainability, aiming to reduce the city’s rising temperatures and promote a resilient urban ecosystem.

Tracking metal pollution from illegal gold mining: a health risk assessment in Edfu, Egypt

Over the past decade, there has been an increase in small-scale gold mining in the arid southern region of Egypt. Miners extract ore from the Eastern Desert and transport it to Nile Valley farms, where ample water facilitates the processing. In Edfu, Egypt, the lack of economic opportunities prompted resource-constrained farmers to transform their agricultural lands into gold mines. The study utilized a multifaceted approach that integrated various methodologies, including remote sensing technologies, field surveys, chemical analyses, and statistical methods. The study aimed to assess the concentrations of carcinogenic agents and determine the potential human health risks associated with these agents in soil and fish samples collected within the city boundaries. The study examined correlations between various heavy metals (HMs), such as Ni, Pb, Cd, Cr, Cu, and Hg, in Soilsamples collected in 2020 and 2022. The results revealed direct proportional relationships among specific HMs. The Index of Geoaccumulation (Igeo) and Pollution Load Index (PLI) revealed significantly elevated values in both years, indicating potential environmental degradation. Although no carcinogenic hazards were identified, non-carcinogenic risks related to ingestion were observed for both adults and children exposed to mercury (Hg), copper (Cu), and arsenic (As). Contamination Factor (CF) values were also significantly high. Ecological risks were observed in both Soiland water, as well as in Nile Tilapia samples. Hazard Quotients (HQ) calculated for Nile Tilapia indicated potential risks for both adults and children, particularly associated with elevated arsenic (As) levels. This transformation elicited concerns regarding environmental and health implications, leading us to undertake a thorough investigation.

Differences in the storage of soil organic carbon in Brazil’s agricultural land: A meta-analysis

Differences in the storage of soil organic carbon in Brazil’s agricultural land: A meta-analysis