Journal of Advanced Research in Alternative Energy, Environment and Ecology

Modeling the effect of Climate Change on Agriculture: Crop yield Productivity and Food Security

2025-10-20T11:21:43+00:00

A major challenge to global agricultural systems, climate change has a substantial impact on
food security and crop output efficiency. The intricate relationships between shifting climatic
factorsâ€”such as rising temperatures, modified precipitation patterns, and an increase in the
frequency of extreme weather eventsâ€”and agricultural output are examined in this study.
Climate projection models and crop simulation tools are used to evaluate the possible effects of
various climate change scenarios on important staple crops in various agro ecological zones.
Regional differences in yield results are revealed by the analysis; some regions may have sharp
drops in output, while others may see brief increases as a result of longer growing seasons or
more COâ‚‚ fertilization. Additionally, the study looks at how socioeconomic factors affect
adaptive ability and emphasizes the significance of technical innovation and coordinated policy
responses. This paper offers an integrative review of the current body of literature regarding the
effects of climate change on crop yields, specifically with focus on the use of climate, hydrology,
and crop yield models. Current research suggests that higher-resolution climate models hold
promising potential in improving the future accuracy of climate projections. In addition, the use
of stochastic projections from a range of climate models is important for model uncertainty
treatment and risk management strategy formulation. While certain areas will experience more
favorable water availability, such change will have a profound impact on water use efficiency
and resource allocation. Although crop yields will be enhanced through the irrigation expansion
or intensification, such measures are at the risk of speeding up environment. Soils having a high
water-holding capacity may assist reduce the negative effects of drought and enable crop output
maintenance in future scenarios where water supply declines. However, water availability and
overall agricultural output are expected to decrease as temperatures rise and precipitation
patterns become more variable. Although increasing the amount of irrigated farmland may
increase overall crop yield, this could have negative effects on food quality and environmental
sustainability. Conditions are changing due to rising temperatures, changing precipitation
patterns, an increase in extreme weather events, and higher atmospheric CO 2 levels, which are
jeopardizing food security and reducing crop yields, particularly in low-income, agriculturally
dependent areas. In addition to yields, the health of the soil, the availability of water, and the
frequency of pests and illnesses are all impacted by this climate change. Longer growing seasons
or CO 2 fertilization may provide short-term benefits in some areas, but overall effects are
expected to be detrimental. One natural phenomenon that profoundly impacts the earth's climate
is the greenhouse effect. Near the earth's surface, it creates the extremely warm and pleasant
environment the fact that has allowed humans and other living forms to grow and thrive. despite
the elevated concentration of greenhouse gases (GHGs), such as sulfur hexafluoride (SF6), hydro
fluorocarbons (HFCs), per fluorocarbons (PFCs), carbon dioxide (CO2), water vapor (H2O),
methane (CH4), nitrous oxide (N2O), and others

Future Perspectives of Clay Based Nanocomposites as Sustainable Materials

2025-10-23T09:17:15+00:00

Environmental toxicity and prevailing health sector issues raised there after have sensitised research communities to provide some sustainable solutions. Advanced materials with intelligent behaviour are such fas cinating materials to address some environmental and health issues. Among these nanocomposite hydrogel matrices made of naturally oc curring polysaccharides and nanocomponents composed of metal based nanoparticles, metal oxides, organic, carbon and clay have acquired prime position owing to their advanced and tunable characteristics as well as their biogenic origin. Nanocomposites being advanced materials possess various superior properties such as improved mechanical/ten sile properties, porosity, thermal stability, resistance toward chemical degradation and re-usability. Such properties are mainly incorporated in the composite matrix due to nano components of reinforcing mate rials added. These materials find a diverse range of applications such as tunable and sustained drug delivery system, bone/tissue engineering matrices, food packaging film, bioelectronics, management of tissue wounds, bio-imaging, energy storage, water treatment, biosensors and industry aligned materials depending upon their core characteristics. Polysaccharides provide an encapsulating system for nanoparticles to form a hybrid composite with integrated properties of all compo nents. The Present study focuses on the properties and applications of polysaccharide based nanocomposite with special attention given for clay based nanocomposites as sustainable materials in different fields.

Intelligent Decision Framework for Climate Resilient Agriculture

2025-10-27T05:19:42+00:00

Climate volatility amplifies smallholder decision un- certainty in India, influencing when and what to plant. Purely data-driven advisories often fail due to behavioral barriers such as loss aversion, default bias, and limited foresight. This paper proposes a Behavioral-Aware Decision Support System (BDSS) that integrates behavioral economics principles into an intelligent recommendation architecture. The model combines climate prediction, IoT sensor data, and behavioral models to optimize adaptive recommendations. A multi-agent simulation with 200 virtual farmers and ten growing seasons demonstrates that BDSS improves adoption of climate-smart practices by 18%, reduces water usage by 10%, and lowers yield variance by 12% compared to a standard DSS. The study highlights how embedding behavioral mechanisms in DSS can bridge the gap between information availability and farmer action, fostering sustainable and climate-resilient agriculture.

Adverse Effects of Climate Change on Human and Animal Lifestyles: A Socio-Ecological Perspective

2025-10-27T05:21:49+00:00

Climate change represents one of the most pressing challenges to both human society and natural ecosystems, as it profoundly alters patterns of daily life. This paper examines the adverse effects of climate change on the lifestyles of humans and animals from a socio-ecological perspective, highlighting how these effects go beyond issues of survival to encompass subtle but significant transformations in routines, behaviors, and social structures. Focusing on food security, occupational shifts, health outcomes, migration behavior, and cultural practices, the study synthesizes current research and real-world case studies to demonstrate the interconnected ways in which climate instability disrupts the fabric of social and ecological communities. Evidence shows that humans are compelled to change dietary habits, occupational roles, and social rituals in response to environmental instability, while animals are forced to adapt migration routes, feeding patterns, and breeding cycles under ecological stress. The paper discusses the critical parallels between human and animal adaptations, as well as the cascading effects such changes have on both groupsâ€™ welfare and survival. Key recommendations emphasize the adoption of sustainable and climate-resilient strategies, such as diversified agriculture, urban green infrastructure, enhanced health systems, and conservation corridors, to support both human and animal adaptation in the face of accelerating change. By applying a socio-ecological lens, this research underscores the urgent need for integrated, cross-disciplinary approaches to mitigate the ongoing and future impacts of climate change on all aspects of life.

Climate Change and Forestry Protection

2025-10-27T06:38:49+00:00

Climate change and forest ecosystems are closely interlinked. Forests regulate global climate by cycling carbon, but climate change greatly alters forest structure and ecosystem functions. Increasing temperatures, shifting precipitation, and more extreme weather events are disrupting ecological balance, causing species range shifts, wildfires, insect outbreaks, and loss of habitat. Healthy forests mitigate climate change by absorbing carbon dioxide, regulating local climate, and supporting biodiversity. Protecting and expanding forests remains vital for climate policy. This paper examines the impacts of climate change on forests, their role in carbon sequestration, reviews international and regional policy frameworks, highlights successful case studies, and discusses challenges and future directions for resilient, sustainable forestry management.

Predictive Analysis of Seismic Activity Using Historical and Real-Time Earthquake Data

2026-01-12T06:19:42+00:00

Earthquakes are among the most unpredictable and destructive natural disasters, causing massive loss of life and property across the globe. Accurate seismic prediction has long been a major scientific challenge due to the complex and nonlinear nature of tectonic processes. In this study, machine learning techniques are applied to analyse historical earthquake data from California to predict the magnitude and probability of future seismic events. The dataset used consists of earthquake records with a magnitude of 3.0 or higher, including parameters such as latitude, longitude, depth, number of seismic stations, and time of occurrence. Various machine learning algorithms — including Linear Regression, Multiple Linear Regression, Decision Tree Regressor, K-Nearest Neighbours (KNN), Support Vector Machine (SVM), Naive Bayes, and K-Means Clustering — were implemented and compared to evaluate their predictive performance. The results demonstrate that machine learning models can effectively capture hidden patterns within seismic data and provide reliable magnitude predictions. Among the tested models, regression-based approaches and SVM showed the best accuracy and consistency. This research highlights the potential of data-driven models in enhancing earthquake forecasting systems, supporting early warning mechanisms, and contributing to disaster risk reduction.

Flood Susceptibility Assessment using Remote Sensing and GIS: A Case Study of the 2025 Punjab Floods

2026-01-12T06:34:28+00:00

Natural disasters have become more common and destructive due to climate change, particularly in South Asia. Recent severe flooding has resulted in widespread relocation and financial loss in India. The 2025 floods in Punjab, which impacted every district, revealed significant weaknesses in health, education, infrastructure, and agriculture. Flood susceptibility modelling has become crucial for risk reduction because floods cannot be completely avoided. Effective tools for mapping flood-prone areas and assisting with data-driven disaster management are provided by remote sensing (RS) and GIS technology. This study
emphasises how crucial flood susceptibility assessments based on RS and GIS are for directing planning, mitigation, and long-term resilience initiatives.

Timeseries Forecasting of Delhi’s Air Quality Index Using Statistical and Neural Network Models

2025-10-27T05:35:09+00:00

Delhi consistently experiences severe air quality

episodes, with particulate loads frequently breaching recom-
mended limits. Anticipating the Air Quality Index (AQI) with

adequate lead time is central to timely advisories, exposure man-
agement, and responsive control actions. This work assembles a

comparative forecasting framework spanning statistical baselines,
machine learning, and deep sequence models to predict AQI
along with PM2.5 and PM10 (both in Î¼g/m3

). The study evaluates

classical time-series tools (ARIMA, Prophet), non-linear regres-
sors (Support Vector Regression, Random Forest), and recurrent

neural networks (Long Short-Term Memory). Using five years of
hourly observations, we adopt a uniform pipeline for cleaning,
scaling, and strictly forward-in-time validation. Empirical results
show LSTM and Random Forest deliver consistent gains over the
statistical baselines, capturing rapid fluctuations and seasonal
shifts more faithfully. Overall, the analysis underscores the value
of hybrid, data-driven approaches for reliable urban air quality
forecasting and supports targeted mitigation in highly polluted
settings.

Ballistic Impact Protective Body Armour Vest: A Critical Review

2025-10-23T11:31:16+00:00

Personal safety of the military, law enforcement, and security officials is an important aspect that is dependent on the use of ballistic impact protective body armour vests when there is the risk of high velocity threats. The given study approaches a thorough review of the fibres employed in the process of ballistic armour fabrication, their mechanical characteristics, energy absorption ability, and effects under conditions of impact.

The study considered the key factors while choosing the fibres for body armour like tensile strength, flexibility, weight, resistance to the environment and cost effectiveness. It also discusses new methods of increasing energy absorption, e.g. by means of topology change of the fibres, addition of nanoparticles, shear-thickening fluids and fancy fibre networks like 3D weaving or hybrid composite materials. These are the measures which are supposed to enhance the ratio of protection, comfort, and mobility in armour design. The benefits and shortcomings of various commercialised fibres such as aramid (Kevlar, Twaron), ultra-high molecular weight polyethylene (UHMWPE), and polybenzoxazole (PBO) etc for the applications of ballistic protection are also highlighted in the present study.

The general outline of a typical ballistic vest testing procedure is presented in order to demonstrate the way in which the quality of materials and design is tested. The study is concluded with the information about the latest achievements in ballistic protection and directions of the future, such as smart materials, sustainable options in protection, and the integration of wearable technologies. This review will be helpful to the researchers, designers, and manufacturers who are concerned with developing the usefulness and functionality of the ballistic protective body armour.

The Interplay Between Climate Change and Agricultural Productivity

2026-01-09T11:25:15+00:00

Climate change presents one of the greatest threats to global agriculture, influencing not only crop productivity but also food security and rural livelihoods. Rising temperatures, irregular precipitation, and extreme weather events are intensifying pressure on farming systems while exacerbating soil degradation, pest outbreaks, and water scarcity. This study investigates the relationship between climate variability and agricultural outcomes using both empirical data and recent literature. A dataset of climatic and agricultural indicators was analysed to assess correlations and model predictive capacity for crop yield and food security. Results showed weak linear relationships and limited predictive accuracy, underscoring the complexity of climate–agriculture dynamics. Alongside the data analysis, the paper reviews technological and policy innovations such as precision agriculture, drone applications, intelligent monitoring systems, and forestry conservation. The findings highlight the urgent need for integrated, climate-smart strategies that combine scientific innovation with inclusive governance to ensure sustainable food production in an era of rapid environmental change.

Stubble Burning: Environmental, Socio-eco nomic Impacts and Pathways for Sustainable Alternatives

2026-01-12T05:26:24+00:00

Stubble burning of paddy residues in the Indo-Gangetic Plain continues to be a major source of seasonal air pollution, regional haze, and soil degradation. This paper reviews the environmental and socio economic impacts of stubble burning, synthesizes evidence on sustainable alternatives (mechanical in-situ solutions such as the Happy Seeder, biological decomposers including the Pusa Decomposer, and valorization pathways like biochar and bioenergy), and proposes a field-evaluation framework to assess technology adoption. Evidence indicates that mechanized in-situ solutions and microbial decomposers
can substantially reduce open burning and associated emissions while improving soil health; however, adoption is constrained by access, cost, timeliness, and farmer perceptions. We propose a mixed-methods experimental design to quantify agronomic outcomes, emissions reductions, and farmer acceptability to inform policy incentives and scale-upstrategies.

Impact of Deforestation on Climate Change: Devasatation of Uttrakhand

2026-01-12T06:50:01+00:00

Deforestation, or the large-scale cutting of forests, has emerged as one of the most important environmental challenges of the modern era. This study explores the causes, consequences, and potential solutions to forest cutting across different regions of the world. The major drivers identified include agricultural expansion, urbanisation, Illegal logging, and industrial development. The environmental impacts are profound, ranging from biodiversity loss, soil erosion, and disruption of water cycles to the acceleration of climate change through increased greenhouse gas emissions. Social and economic consequences also arise, particularly affecting indigenous communities and local livelihoods dependent on forest resources.

The Double-Edged Sword: Climate Change’s Impact on Global Agriculture and Pathways to a Resilient Future

2026-01-12T07:06:49+00:00

The global agricultural sector stands at a critical nexus in the climate crisis, functioning as both a significant contributor to greenhouse gas emissions and a primary victim of their climatic consequences. This paper synthesises the current scientific consensus on the multifaceted relationship between climate change and agriculture. It first establishes the dual role of agriculture, detailing its contributions to anthropogenic emissions through livestock, fertiliser use, and land-use change. It then provides a comprehensive review of the severe impacts of climate change on agricultural systems, including reduced crop yields, increased
water stress, proliferation of pests and diseases, and threats to livestock and fisheries, all of which undermine global food security. Subsequently, the paper explores a suite of adaptation strategies designed to build resilience, from on-farm practices like crop diversification and precision agriculture to systemic changes in water and soil management. It also examines mitigation pathways to reduce the sector’s climate footprint, focusing on sustainable land management, emissions reduction from livestock and fertilisers, and demand-side measures such as reducing food waste. Finally, the paper analyses the crucial role of policy, governance, and investment in facilitating this transition, highlighting the importance of international frameworks like the Paris Agreement and the urgent need to bridge the significant financing gap with both public and private capital. The paper concludes that a rapid, systemic transformation of global agri-food systems, integrating both adaptation and mitigation, is not only essential for ensuring future food security but is also a non-negotiable component of the global solution to climate change