The agricultural sector faces challenges such as water scarcity, energy inefficiency, and declining productivity, particularly in arid regions. Traditional irrigation methods contribute to resource depletion and environmental impacts. Solar-powered smart irrigation systems integrate precision irrigation with renewable energy, improving water use and productivity. In Pakistan, where agriculture contributes 19% of gross domestic product and employs 40% of the workforce, these challenges are severe, especially in water-scarce areas like the Cholistan Desert. This study examines the impact of solar-powered smart irrigation on agricultural productivity, water conservation, and energy efficiency in the Cholistan Desert. Using a quantitative cross-sectional design, data were collected from 384 farmers via structured questionnaires. Statistical analyses, including multiple linear regression, paired sample t-tests, and Structural Equation Modeling (SEM), were conducted. Findings show significant improvements in crop yield (from 3.0 to 4.8 tons/hectare) and reductions in water and energy consumption. Regression analysis highlighted strong positive effects on yield and efficiency, while SEM confirmed reduced environmental impact and operational costs. The study concludes that solar-powered irrigation enhances productivity, conserves resources, and promotes sustainability. Policymakers should provide financial incentives, invest in renewable infrastructure, and implement training programs to support adoption. Collaborative efforts are essential for sustainable agriculture in arid regions.

In this cross-sectional study, an investigation was conducted by collecting primary data from 379 household heads to examine the impact of social safety nets on household-level food security in the Torghar district of Northern Khyber Pakhtunkhwa, Pakistan. The comprehensive analysis encompassed the univariate, bivariate, and multivariate levels. The bivariate analysis revealed issues and shortcomings related to access to social safety nets, particularly within the Zakat system. These issues included corruption and nepotism, which hindered poverty alleviation strategies and the well-being of vulnerable households. Additionally, complex bureaucratic procedures and regulations impeded social interventions, and political factors posed a substantial obstacle. At the multivariate level, the study identified the specific factors contributing to food insecurity. Respondents from extended family systems, individuals aged between 46 and 55 years, and those with religious education were found to be more vulnerable to food insecurity. While social safety nets held promise for addressing food sustenance challenges among local low-income citizens, the negative impacts of political involvement, favoritism, and nepotism were evident and required urgent attention. These findings emphasize the need for coordinated efforts among the government, social safety net officials, and community to identify and rectify these existing issues. Fostering a sense of ownership and responsibility regarding the role and implementation of social safety nets towards achieving food security is crucial to enhancing their viability and effectiveness, ensuring continuous support for those in need.

Climate change is a major global challenge affecting migration patterns, particularly in coastal communities vulnerable to sea-level rise, flooding, and extreme weather. Pakistan, with its extensive coastline and diverse environmental conditions, faces significant climate-induced migration issues, especially in Karachi, Thatta, Gwadar, Badin, and Muzaffargarh. This study aims to investigate the impact of climate change on migration patterns in these five selected regions of Pakistan. By analyzing climate variables and socio-economic factors, the research seeks to provide a localized understanding of how climate change drives population movements. A cross-sectional survey design was employed to gather data from 350 participants across these regions. Stratified random sampling ensured representation from each area, and data were collected using a structured questionnaire administered online. Statistical analyses included multiple linear regression, logistic regression, and structural equation modeling (SEM). This study found a strong positive relationship between climate change variables (sea level rise, temperature increases, and flooding) and migration patterns. Both direct impacts of climate change and indirect socio-economic factors influenced the likelihood of migration. The SEM analysis revealed that climate awareness partially mediates the relationship between climate change and migration. In conclusion, climate change significantly drives migration in Pakistan’s coastal communities, with both direct environmental impacts and socio-economic conditions playing crucial roles. Enhanced climate awareness and comprehensive adaptation strategies are essential. Policies should focus on climate resilience through infrastructure improvements, early warning systems, and socio-economic support programs. Strengthening education and economic opportunities is vital to build community resilience and effectively manage climate-induced migration.

This study addresses the integration of agricultural practices, technological innovations, and energy policies to achieve carbon neutrality in Mardan, Pakistan. A cross-sectional design was employed, collecting data from 400 stakeholders using stratified random sampling. The analysis involved descriptive statistics, correlation analysis, structural equation modeling (SEM), Chi-square tests, and multiple regression analysis to explore the relationships between agricultural sustainability practices (ASPs), green technology implementation (GTI), energy policy measures (EPMs), and carbon-free development (CFD). The findings indicate strong positive correlations between ASPs, GTI, EPMs, and CFD, with a relatively high positive correlation coefficients. SEM path coefficients further confirmed the significant positive effects of ASPs on CFD. It is concluded that integrating sustainable farming practices, green technologies, and effective energy policies significantly advances carbon-free development in Mardan. Policymakers should prioritize promoting sustainable farming, investing in green technologies, and implementing robust energy policies with subsidies for renewable energy and carbon pricing mechanisms to foster carbon-neutral development.

Utilizing the power of sunlight through agro-photovoltaic fusion systems (APFSs) seamlessly blends sustainable agriculture with renewable energy generation. This innovative approach not only addresses food security and energy sustainability but also plays a pivotal role in combating climate change. This study assesses the feasibility and impact of APFS implementation in District Dir Lower, Pakistan, a region significant for its agriculture and energy needs. A quasi-experimental design was employed, comparing outcomes between a treatment group (with an APFS) and a control group (without an APFS). Stratified random sampling was used to select 400 participants, including farmers, residents, local authorities, and community leaders. Data were collected using structured questionnaires and analyzed employing paired t-tests, linear regression, analysis of variance (ANOVA), and Chi-square tests. The results show that the treatment group with an APFS exhibited significant improvements in farming practices (mean change = 4.20 vs. 2.80). Linear regression indicated a strong positive effect of APFSs on renewable energy production. The ANOVA results demonstrated significant mitigation of environmental challenges, and the Chi-square test showed a strong association between APFS implementation and community sustainability, resilience, and prosperity. It is concluded that APFS implementation significantly enhances farming practices, renewable energy production, and environmental sustainability, contributing to the resilience and prosperity of agricultural communities in District Dir Lower. These findings advocate for the broader adoption of APFSs in similar contexts to integrate sustainable agriculture with renewable energy generation.

This study aims to examine the socio-economic determinants of human negligence in wildfire occurrences across Pakistan’s peri-urban and rural regions. Increasingly frequent and severe wildfires, driven by climate change, socio-economic conditions, and human negligence, have become a pressing issue. Rising global temperatures and changing precipitation patterns have created drier conditions, while unsafe human activities—such as improper disposal of flammable materials and unsafe agricultural burning—further escalate wildfire risks. These issues are particularly pronounced in Pakistan, where high poverty levels, limited resources, and low education contribute to dangerous behaviors. Weak governance and poor policy enforcement further exacerbate the problem. Data were collected using a cross-sectional survey from 500 participants across five regions. Multiple regression analysis revealed that higher poverty levels significantly increased negligence, whereas higher education and improved access to resources reduced it. Structural Equation Modeling (SEM) highlighted the critical roles of local governance, policy enforcement, and community engagement in mitigating wildfires. Correlation analysis indicated an inverse relationship between wildfire risk awareness and negligent behavior. Chi-square tests demonstrated a strong connection between wildfires and migration patterns, underscoring the socio-economic instability caused by these events. Finally, linear regression showed that wildfires significantly impact regional climate indicators, emphasizing the need for integrated management strategies. This study offers valuable insights into the socio-economic factors driving wildfires in Pakistan and provides guidance for developing targeted mitigation strategies.