Your search found 2 records
1 Dutta, S. K.; Singh, D.; Sood, Aditya. 2011. Effect of soil chemical and physical properties on sorption and desorption behavior of lead in different soils of India. Soil and Sediment Contamination, 20(3):249-260. [doi: https://doi.org/10.1080/15320383.2011.560979]
Soil chemicophysical properties ; Sorption ; Desorption ; Lead ; Statistical methods ; Analytical methods ; Multiple regression analysis ; Models ; Soil sampling ; Chemical composition / India
(Location: IWMI HQ Call no: e-copy only Record No: H043832)
(0.25 MB)
Lead (Pb) is a non-biodegradable contaminant, present in the environment, especially near lead-based industrial sites, agricultural lands, and roadside soils. Bioavailability of Pb in the soil is controlled by the sorption and desorption behavior of Pb, which are further controlled by the soil chemical and physical properties. In this study, sorption and desorption amounts of Pb in soil were compared with soil physical (sand, silt, clay content) and chemical (pH; electrical conductivity, EC; percent organic carbon, (%OC);cation exchange capacity, CEC) properties. Twenty-six surface soils (0–5cm), expected to vary in physical and chemical properties, were collected from different parts of India and were treated with known concentration of Pb solution (40 µg/L). The amount of Pb sorbed and desorbed were measured and correlated with soil properties using simple linear regressions. Sorption was significantly (p = 0.05) and positively correlated with pH, and %OC; desorption was significantly (p = 0.05) negatively correlated with the same two factors. Stepwise multiple regressions were performed for better correlations. Predicted sorption and desorption amounts, based on multiple regression equations, showed reasonably good fit (R2 = 0.79 and 0.83, respectively) with observed values. This regression model can be used for estimation of sorption and desorption amounts at contaminated sites.
2 Ajebe, M. 2024. Elusive trade-off: the solution to energy poverty and GHG [Greenhouse Gas] emissions in Africa. Environmental and Sustainability Indicators, 21:100320. [doi: https://doi.org/10.1016/j.indic.2023.100320]
Energy poverty ; Greenhouse gas emissions ; Fossil fuels ; Finance ; Multiple regression analysis ; Data analysis ; Infrastructure ; Economic growth / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H052600)
https://www.sciencedirect.com/science/article/pii/S2665972723000971/pdfft?md5=a31b05689bac35a3675c3ad1db123936&pid=1-s2.0-S2665972723000971-main.pdf
https://vlibrary.iwmi.org/pdf/H052600.pdf
https://vlibrary.iwmi.org/pdf/H052600.pdf
(4.27 MB) (4.27 MB)
A groundbreaking strategy known as "coopetition" has emerged to provide energy access to underserved populations in Africa while reducing greenhouse gas emissions. This approach, applied across 54 African nations, combines cooperation and competition, supported by a comprehensive financial framework encompassing financial development, foreign direct investment (FDI), and official development assistance (ODA). Utilizing advanced moderated multiple regression analysis with data from reliable international sources and IBM SPSS Statistics (Version 28.0.1.1 (14)), this study highlights the strong connection between financial resources, energy poverty, and emissions. Inadequate financial support hinders renewable energy adoption and policy development, contributing to rising emissions. The research explores how coopetition modifies the relationship between ODA and energy poverty while reinforcing links between coopetition, ODA, and reduced emissions. Notably, the study challenges conventional wisdom by debunking the direct influence of financial development and foreign direct investment on energy poverty and emissions. Instead, it underscores the importance of transparent regulations, robust financial structures, and risk mitigation in advancing sustainable energy solutions.
Powered by DB/Text WebPublisher, from
