https://journals.bilpubgroup.com/index.php/jees/issue/feed Journal of Environmental & Earth Sciences 2025-10-09T10:11:18+08:00 Managing Editor:Tina Guo jees@bilpubgroup.com,jees@bilpublishing.com Open Journal Systems <p>ISSN: 2661-3190 (Online)</p> <p>Email: jees@bilpubgroup.com</p> <p>Follow the journal: <a style="display: inline-block;" href="https://twitter.com/jees_Editorial" target="_blank" rel="noopener"><img style="width: 20px; position: relative; top: 5px; left: 5px;" src="https://journals.bilpubgroup.com/public/site/Twitter _logo.jpg" alt="" /></a></p> https://journals.bilpubgroup.com/index.php/jees/article/view/11802 Examining Resource Dependency and Socioeconomic Disparities: A Case Study of Sustaining Rural Livelihoods in India 2025-09-16T10:36:33+08:00 Preeti Jakhwal preetijakhwal98@gmail.com Himanshu Sahu Himanshusahudehradun@gmail.com Aman Srivastava amansrivastava1397@gmail.com Arun Pratap Mishra arunpratap7371@gmail.com Amit Kumar amit@wii.gov.in Kiran Rawat kiranrawat2662@gmail.com Mriganka Shekhar Sarkar mriganka.bio@gmail.com Sachin Sharma sachinbsi2012@yahoo.co.in Upaka Rathnayake Upaka.Rathnayake@atu.ie <p>Rural communities in developing countries often struggle with resource dependency, economic challenges, and poor infrastructure, and villages in Uttarakhand, India, are no exception. This study aims to examine the socioeconomic factors influencing forest conservation, assess livelihood dependency on forest resources, and evaluate how socioeconomic status shapes sustainable forest management in Shishambara and Buddhi villages in Dehradun. The study employed purposive and random sampling covering 10% of households, using structured surveys, interviews, field observations, market surveys, and focus group discussions. The survey reveals an agriculture-dominated livelihood, engaging 60% in Buddhi and 65% in Shishambara, alongside private-sector jobs and daily wage labour. Literacy rates differ significantly, with Buddhi at 72% and Shishambara at 58%. Despite accessibility to LPG connections, traditional cooking fuels like fuelwood and cow dung remain predominant, utilized by 70% of households in Buddhi and 75% in Shishambara. Most homes are Pakka, yet only 18.8% in Buddhi and 22% in Shishambara have toilets. Public transport is scarce, leaving villagers reliant on private vehicles. These findings underscore the need for policies that address resource management, improve basic services, and support sustainable development, offering a road map for uplifting rural livelihoods and bridging infrastructure gaps.</p> 2025-10-14T00:00:00+08:00 Copyright © 2025 Preeti Jakhwal, Kiran Rawat, Himanshu Sahu, Aman Srivastava, Arun Pratap Mishra, Amit Kumar, Mriganka Shekhar Sarkar, Sachin Sharma, Upaka Rathnayake https://journals.bilpubgroup.com/index.php/jees/article/view/9835 Response Surface Methodology and Deep Learning Modelling for the Removal of Pb2+ ions from Wastewater Using Apple Pomace 2025-08-07T17:33:24+08:00 Great C. Chazuza 22288261@dut4life.ac.za Felicia O. Afolabi feliciaa@dut.ac.za Paul Musonge paulm@dut.ac.za <p>Recent studies have demonstrated a growing global interest in utilising agricultural waste to remediate wastewater. This stems from growing apprehensions about high levels of heavy metals, especially Pb<sup>2+</sup> ions, in wastewater produced by industrial processes such as mining, paint production, oil refining, smelting, and electroplating. This study examined apple pomace's Pb<sup>2+</sup> ions adsorption from wastewater. Response Surface Methodology (RSM) was employed, utilising the central composite face-centred design (CCFD) with three variables: initial concentration (1–50 mg/L), adsorbent dosage (0.1–1 g), and particle size (75–425 µm) to formulate a mathematical model for the biosorption of Pb<sup>2+</sup> ions on apple pomace. An artificial neural network (ANN) was developed using data generated from the RSM design. The CCFD and ANN models showed considerable efficacy in the adsorption process, exhibiting correlation coefficient values of 0.9921 and 0.9999, respectively. The isotherm and kinetic studies were performed, and the Freundlich Isotherm model best fitted the equilibrium data, with a correlation coefficient of 0.972 and a q<sub>e</sub> of 5.145 mg/g. Additionally, the pseudo-second-order model proved to be the most appropriate for the kinetic data, with an R<sup>2</sup> of 0.9996. These results confirm that apple pomace functions as an effective, low-cost, and environmentally and sustainably biosorbent for the removal of Pb<sup>2+</sup> ions from wastewater. Both RSM and ANN models exhibited high predictive capability for the biosorption process. While ANN provides more flexibility in modelling complex non-linear relationships, it is prone to overfitting, particularly with limited datasets, and this was addressed through a 5-fold cross-validation technique.</p> 2025-10-10T00:00:00+08:00 Copyright © 2025 Great C. Chazuza, Felicia O. Afolabi, Paul Musonge