Spatial modelling of gaseous emissions from two municipal solid waste dump sites

Araiza-Aguilar, Juan Antonio; Rojas-Valencia, María Neftalí

doi:10.1080/00207233.2018.1535870

Cited by 12 publications

(12 citation statements)

References 20 publications

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“…This method is simple and has been widely used in providing trace gas emission rates for dispersion models with the purpose of assessing environmental impacts and health risks (e.g. Tagaris et al, 2003;Paraskaki and Lazaridis, 2005;Pagé et al, 2007;Moolla et al, 2013;Cai et al, 2015;Abdul-Wahab et al, 2016;Araiza-Aguilar and Rojas-Valencia, 2018). In the cited papers, emission rates of target odorous or toxic trace compounds were calculated by using various LFG production models and applying Equation (4).…”

Section: Lfg Production Modellingmentioning

confidence: 99%

Trace gas emissions from municipal solid waste landfills: A review

2021

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Section: Lfg Production Modellingmentioning

confidence: 99%

Trace gas emissions from municipal solid waste landfills: A review

2021

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“…The residual errors were found to be 11.81 nm, 0.041, 1.23 mV, and 3.44% for PS, PDI, ZP, and EE, respectively. Such small residual error values indicate that the observed results were very close to the predicted ones, thus ensuring good model fitting and efficient optimization [ 64 , 65 ].…”

Section: Resultsmentioning

confidence: 99%

Fabrication and optimization of itraconazole-loaded zein-based nanoparticles in coated capsules as a promising colon-targeting approach pursuing opportunistic fungal infections

Adel

Fahmy

Elsayed

et al. 2023

Drug Deliv. and Transl. Res.

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Itraconazole (ITZ), a broad-spectrum antifungal drug, was formulated into colon-targeting system aiming to treat opportunistic colonic fungal infections that commonly infect chronic inflammatory bowel diseases (IBD) patients due to immunosuppressive therapy. Antisolvent precipitation technique was employed to formulate ITZ-loaded zein nanoparticles (ITZ-ZNPs) using various zein: drug and aqueous:organic phase ratios. Central composite face-centered design (CCFD) was used for statistical analysis and optimization. The optimized formulation was composed of 5.5:1 zein:drug ratio and 9.5:1 aqueous:organic phase ratio with its observed particle size, polydispersity index, zeta potential, and entrapment efficiency of 208 ± 4.29 nm, 0.35 ± 0.04, 35.7 ± 1.65 mV, and 66.78 ± 3.89%, respectively. ITZ-ZNPs were imaged by TEM that revealed spherical core–shell structure, and DSC proved ITZ transformation from crystalline to amorphous form. FT-IR showed coupling of zein NH group with ITZ carbonyl group without affecting ITZ antifungal activity as confirmed by antifungal activity test that showed enhanced activity of ITZ-ZNPs over the pure drug. Histopathological examination and cytotoxicity tests ensured biosafety and tolerance of ITZ-ZNPs to the colon tissue. The optimized formulation was then loaded into Eudragit S100-coated capsules and both in vitro release and in vivo X-ray imaging confirmed the success of such coated capsules in protecting ITZ from the release in stomach and intestine while targeting ITZ to the colon. The study proved that ITZ-ZNPs is promising and safe nanoparticulate system that can protect ITZ throughout the GIT and targeting its release to the colon with effectual focused local action for the treatment of colon fungal infections. Graphical Abstract

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“…In 2007, a study conducted in Kathmandu also found the coefficient of correlation to be 0.94 (Dangi et al 2011). Though there are other socioeconomic variables (population density, income, GDP) for forecasting the MSW generation, the population trend is widely used by researchers (Khan and Burney 1989;Wei et al 2013;Ghinea et al 2016;Azadi and Karimi-Jashni 2016;Araiza-Aguilar et al 2020). The coefficient of 0.956 obtained for solid waste generation of KMC is also near to the study conducted in Mexico, which found a coefficient of 0.975 (Araiza-Aguilar et al 2020).…”

Section: Resultsmentioning

confidence: 99%

Forecasting municipal solid waste generation using linear regression analysis: A case of Kathmandu Metropolitan City, Nepal

Khanal

2023

Multidiscip. Sci. J.

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There is lack of study predicting the Municipal Solid Waste (MSW) output scientifically and accurately for least developed countries like Nepal. Previous studies have primarily relied on the tentative amount of waste generation linked with the number of vehicles involved in waste collection and transfer to the landfill site. This study used linear regression analysis to forecast the solid waste generation of Kathmandu Metropolitan City (KMC) by undertaking past population data and solid waste generation.. The SPSS analysis resulted in a strong relationship between population and solid waste generation with a coefficient of 0.956. A linear regression validation was performed to ensure that the derived formula is statistically significant. The finding indicates the r squared (R2) value to be 0.913, leading the waste prediction model to be very strong. The prediction equation of 0.659X - 204222.952 resulted in an average waste generation of KMC as 1006 t/d on average till 2035 with an average per capita/d waste generation of 0.54 kg. The current MSW generation of KMC is found to be 766 t/d and predicted to reach 1259 t by 2035. The information can be helpful for the municipality and urban planning authorities to make strategies for effective management of waste generated in KMC, creating less burden at the Banchare Danda landfill site.

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Spatial modelling of gaseous emissions from two municipal solid waste dump sites

Cited by 12 publications

References 20 publications

Trace gas emissions from municipal solid waste landfills: A review

Trace gas emissions from municipal solid waste landfills: A review

Fabrication and optimization of itraconazole-loaded zein-based nanoparticles in coated capsules as a promising colon-targeting approach pursuing opportunistic fungal infections

Forecasting municipal solid waste generation using linear regression analysis: A case of Kathmandu Metropolitan City, Nepal

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