Two of the most pressing sustainability issues are the depletion of fossil energy resources and the emission of atmospheric green house gases like carbon dioxide to the atmosphere. The aim of this study was to assess energy budgeting and carbon footprint in transgenic cotton-wheat cropping system through peanut intercropping with using 25-50% substitution of recommended dose of nitrogen (RDN) of cotton through farmyard manure (FYM) along with 100% RDN through urea and control (0 N). To quantify the residual effects of previous crops and their fertility levels, a succeeding crop of wheat was grown with varying rates of nitrogen, viz. 0, 50, 100, and 150 kg ha(-1). Cotton + peanut-wheat cropping system recorded 21% higher system productivity which ultimately helped to maintain higher net energy return (22%), energy use efficiency (12%), human energy profitability (3%), energy productivity (7%), carbon outputs (20%), carbon efficiency (17%), and 11% lower carbon footprint over sole cotton-wheat cropping system. Peanut addition in cotton-wheat system increased the share of renewable energy inputs from 18 to 21%. With substitution of 25% RDN of cotton through FYM, share of renewable energy resources increased in the range of 21% which resulted into higher system productivity (4%), net energy return (5%), energy ratio (6%), human energy profitability (74%), energy productivity (6%), energy profitability (5%), and 5% lower carbon footprint over no substitution. The highest carbon footprint (0.201) was recorded under control followed by 50 % substitution of RDN through FYM (0.189). With each successive increase in N dose up to 150 kg N ha(-1) to wheat, energy productivity significantly reduced and share of renewable energy inputs decreased from 25 to 13%. Application of 100 kg N ha(-1) to wheat maintained the highest grain yield (3.71 t ha(-1)), net energy return (105,516 MJ ha(-1)), and human energy profitability (223.4) over other N doses applied to wheat. Application of 50 kg N ha(-1) to wheat maintained the least carbon footprint (0.091) followed by 100 kg N ha(-1) (0.100). Our study indicates that system productivity as well as energy and carbon use efficiencies of transgenic cotton-wheat production system can be enhanced by inclusion of peanut as an intercrop in cotton and substitution of 25% RDN of cotton through FYM, as well as application of 100 kg N ha(-1) to succeeding wheat crop.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s10661-015-4516-4 | DOI Listing |
Data Brief
February 2025
CREA - Council for Agricultural Research and Economics, Research Centre for Agriculture and Environment, I-40128 Bologna, Italy.
Farming practices such as soil tillage, organic/mineral fertilization, irrigation, crop selection and residues management influence multiple ecosystem services provided by agricultural systems. These practices exhibit complex, non-linear interrelationships that affect crop productivity, water quality, and non-carbon dioxide greenhouse gases (GHG) emissions, possibly offsetting their benefits regarding soil organic carbon (SOC) sequestration. Current methodologies from the Intergovernmental Panel on Climate Change (IPCC) for assessing the impacts of alternative farming practices on GHG emissions rely on global or country-specific coefficients.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Zoology and Environment Sciences, Faculty of Science, University of Colombo, Colombo, 03, Sri Lanka.
There is increasing scientific interest in the potential links between meditation practice and pro-environmental behaviours. The present research investigates relationships between meditation experience (temporal variables of meditation, five facets of trait mindfulness), positive lifestyle habits (PLH), quality of life (QoL) and per-head carbon footprint (CF) among 25 skilled meditators. Self-reported validated questionnaires were given to a group of native speakers of Sri Lanka to collect data on meditation experience, PLH, and perceived QoL.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Business Administration, College of Business Administration, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.
Improving energy efficiency is crucial for smart factories that want to meet sustainability goals and operational excellence. This study introduces a novel decision-making framework to optimize energy efficiency in smart manufacturing environments, integrating Intuitionistic Fuzzy Sets (IFS) with Multi-Criteria Decision-Making (MCDM) techniques. The proposed approach addresses key challenges, including reducing carbon footprints, managing operating costs, and adhering to stringent environmental standards.
View Article and Find Full Text PDFData Brief
February 2025
Department of Agricultural Sciences, Faculty of Agriculture and Forestry, University of Helsinki, Latokartanonkaari 5, 00014, Finland.
High Nature Value (HNV) farming systems occur in areas where the major land use is agriculture and are characterized by their significance in promoting biodiversity and ecosystem services due to their extensive land use. Despite their importance for ecological and socio-economic resilience of rural regions, these systems are often overlooked in Life Cycle Assessment (LCA) studies due to challenges in data compilation, especially from small local farms and because of the diversity of production. To address this gap, we established an international collaborative network across Europe, involving professionals directly engaged with farmers, farmer associations, and researchers to collect data on HNV farms employing a developed questionnaire examining inputs and outputs, farm structures, and herd characteristics.
View Article and Find Full Text PDFAtomic-scale changes can significantly impact heterogeneous catalysis, yet their atomic mechanisms are challenging to establish using conventional analysis methods. By using identical location scanning transmission electron microscopy (IL-STEM), which provides quantitative information at the single-particle level, we investigated the mechanisms of atomic evolution of Ru nanoclusters during the ammonia decomposition reaction. Nanometre-sized disordered nanoclusters transform into truncated nano-pyramids with stepped edges, leading to increased hydrogen production from ammonia.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!