Composting modelling : towards a better understanding of the fundamentals, applications for enhanced nutrient recycling, greenhouse gas reduction, and improved decision-making

Cette thèse de doctorat vise à consolider, développer et appliquer nos connaissances sur la modélisation du compostage, dans le but de fournir des informations, des outils et des perspectives accessibles et utilisables pour les chercheurs et les décideurs. L'espoir est que les travaux développés tout au long de cette thèse puissent aider à optimiser les procédés de compostage, notamment en réduisant les émissions de gaz à effet de serre (GES) et en améliorant le recyclage des nutriments. A ce titre, la thèse est divisée en trois phases : (1) la phase 1 est une consolidation et un développement des notions fondamentales de la modélisation du compostage, (2) suivie de la phase 2, où la modélisation de la perte de nutriments et des émissions de GES est étudiée, (3) avec la phase 3 qui est axée sur la manière d'assurer que ce travail puisse être utilisé par les décideurs et acteurs dans le milieu de compostage. Dans la première phase, une revue complète et systématique de l'ensemble de la littérature sur la modélisation du compostage a été entreprise (chapitre 2), cherchant à fournir une meilleure compréhension du travail qui a été fait et sur la direction des travaux futurs. Ceci a été suivi d'une étudie détaillée des approches de modélisation cinétique actuelles, notamment par rapport aux facteurs de corrections cinétiques appliqués à travers le domaine (chapitre 3). La phase 2 s'est ensuite focalisée sur les notions spécifiques relatives aux émissions de GES et aux pertes de nutriments lors du compostage, et à la modélisation de ces phénomènes. Cette thèse présente les réacteurs expérimentaux et le plan conçu pour suivre et évaluer le processus de compostage (chapitre 4), ainsi que le modèle de compostage compréhensif développé pour prédire avec précision les émissions et la transformation des nutriments pendant le compostage (chapitre 5). Enfin, la phase 3 visait à rendre ces informations facilement et largement utilisables. Cela a commencé par une évaluation des meilleures pratiques pour développer des modèles et des systèmes d'aide à la décision pour la prise de décision environnementale (chapitre 6), suivi par le développement de nouvelles approches de modélisation cinétique simples (chapitre 7), culminant avec le développement, l'ajustement paramétrique et la validation d'un modèle de compostage parcimonieux (chapitre 8). Grâce à ce travail, une base consolidée de l'état actuel de la modélisation du compostage a été développée, suivie par l'exploration et le développement de connaissances et d'outils à la fois fondamentaux et applicables.This PhD thesis aims consolidating, developing, and applying our knowledge on composting modelling, with the goal of providing accessible and usable information, tools, and perspectives for researchers and decision-makers alike. The hope is that the work developed throughout this dissertation can help in optimizing composting, notably by reducing greenhouse gas (GHG) emissions and improving nutrient recycling. As such, the thesis is divided into three phases: (1) phase 1 is a consolidation and development of the fundamentals of composting modelling, (2) followed by phase 2, where the modelling of nutrient loss and GHG emissions is investigated, (3) with phase 3 focusing on how to ensure that this work can be used by decision-makers. In the first phase, a comprehensive and systematic review of the entirety of the literature on composting modelling was undertaken (chapter 2), seeking to provide a better understanding on the work that has been done and guidance on where future work should focus and how it should be approached. This review then raised some interesting questions regarding modelling approaches, notably regarding modelling of composting kinetics, which was studied in detail through the evaluation of current modelling approaches (chapter 3). Phase 2 then focused on the specific notions relating to GHG emissions and nutrient loss during composting, and how to model these phenomena. This section starts with a presentation of the experimental reactors and plan designed to monitor and evaluate the composting process (chapter 4), followed by the comprehensive composting model developed to accurately predict emissions and nutrient transformation during composting (chapter 5). Finally, phase 3 aimed to make this information easily and widely usable, especially for decision-makers. This started with a review on the best practices to develop models and decision support systems for environmental decision-making (chapter 6), followed by the development of novel simple kinetic modelling approaches (chapter 7), culminating with the development, calibration, and validation of a parsimonious composting model (chapter 8). Through this work, a consolidated basis of the current state on composting modelling has been developed, followed-up by the exploration and development of both fundamental and applicable knowledge and tools

Book of Abstracts XVIII Congreso de Biometría CEBMADRID

Abstracts of the XVIII Congreso de Biometría CEBMADRID held from 25 to 27 May in MadridInteractive modelling and prediction of patient evolution via multistate models / Leire Garmendia Bergés, Jordi Cortés Martínez and Guadalupe Gómez Melis : This research was funded by the Ministerio de Ciencia e Innovación (Spain) [PID2019104830RBI00]; and the Generalitat de Catalunya (Spain) [2017SGR622 and 2020PANDE00148].Operating characteristics of a model-based approach to incorporate non-concurrent controls in platform trials / Pavla Krotka, Martin Posch, Marta Bofill Roig : EU-PEARL (EU Patient-cEntric clinicAl tRial pLatforms) project has received funding from the Innovative Medicines Initiative (IMI) 2 Joint Undertaking (JU) under grant agreement No 853966. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA and Children’s Tumor Foundation, Global Alliance for TB Drug Development non-profit organisation, Spring works Therapeutics Inc.Modeling COPD hospitalizations using variable domain functional regression / Pavel Hernández Amaro, María Durbán Reguera, María del Carmen Aguilera Morillo, Cristobal Esteban Gonzalez, Inma Arostegui : This work is supported by the grant ID2019-104901RB-I00 from the Spanish Ministry of Science, Innovation and Universities MCIN/AEI/10.13039/501100011033.Spatio-temporal quantile autoregression for detecting changes in daily temperature in northeastern Spain / Jorge Castillo-Mateo, Alan E. Gelfand, Jesús Asín, Ana C. Cebrián / Spatio-temporal quantile autoregression for detecting changes in daily temperature in northeastern Spain : This work was partially supported by the Ministerio de Ciencia e Innovación under Grant PID2020-116873GB-I00; Gobierno de Aragón under Research Group E46_20R: Modelos Estocásticos; and JC-M was supported by Gobierno de Aragón under Doctoral Scholarship ORDEN CUS/581/2020.Estimation of the area under the ROC curve with complex survey data / Amaia Iparragirre, Irantzu Barrio, Inmaculada Arostegui : This work was financially supported in part by IT1294-19, PID2020-115882RB-I00, KK-2020/00049. The work of AI was supported by PIF18/213.INLAMSM: Adjusting multivariate lattice models with R and INLA / Francisco Palmí Perales, Virgilio Gómez Rubio and Miguel Ángel Martínez Beneito : This work has been supported by grants PPIC-2014-001-P and SBPLY/17/180501/000491, funded by Consejería de Educación, Cultura y Deportes (Junta de Comunidades de Castilla-La Mancha, Spain) and FEDER, grant MTM2016-77501-P, funded by Ministerio de Economía y Competitividad (Spain), grant PID2019-106341GB-I00 from Ministerio de Ciencia e Innovación (Spain) and a grant to support research groups by the University of Castilla-La Mancha (Spain). F. Palmí-Perales has been supported by a Ph.D. scholarship awarded by the University of Castilla-La Mancha (Spain)

Multivariate Analysis in Management, Engineering and the Sciences

Recently statistical knowledge has become an important requirement and occupies a prominent position in the exercise of various professions. In the real world, the processes have a large volume of data and are naturally multivariate and as such, require a proper treatment. For these conditions it is difficult or practically impossible to use methods of univariate statistics. The wide application of multivariate techniques and the need to spread them more fully in the academic and the business justify the creation of this book. The objective is to demonstrate interdisciplinary applications to identify patterns, trends, association sand dependencies, in the areas of Management, Engineering and Sciences. The book is addressed to both practicing professionals and researchers in the field

Bioaerosol Emission From MSW Open Dumpsites And The Impact On Exposure And Associated Health Risks

The activities associated with the open dumping of municipal solid waste emit air pollutants, including bioaerosols that contaminates the air around dumpsites, rendering it unsafe for dumpsite workers and residents living near dumpsites. Quantitative data on the exposure to bioaerosols from open dumpsites are scarce, thus impeding the development of effective interventions that would reduce the risk of respiratory diseases among dumpsite workers and residents living near dumpsites. The specific objectives for this study included (i) to identify the key working areas and activities of the workers at open dumpsites; (ii) to identify the most important groups of local residents that may be affected by contaminated air due to the waste management activities carried out at open dumpsites; (iii) to obtain background information regarding the respiratory health condition of the workers and the local residents in order to determine the extent to which they suffer respiratory diseases that may be related to exposure to the contaminated air from dumpsite; (iv) to measure the concentrations of bioaerosols at key locations on the open dumpsite to determine the impact of different waste management activities and seasonal variations on bioaerosol concentrations; (v) to analyse the bioaerosol data and to compare the ambient concentrations to concentrations at the controls; (vi) to quantify the potential health risk associated with exposure to pathogenic bioaerosols from the open dumpsites using the Quantitative Microbial Risk Assessment (QMRA) tool. A cross sectional respiratory health survey was conducted in the study area between 12th -27th January 2017 with a total 414 respondents (workers = 149, resident = 145 and control = 120). A six-stage Anderson sampler and the SKC button sampler were used to measure ambient bioaerosol concentration and exposure concentration during key activities at the dumpsite respectively. The four bioaerosols indicator groups (total bacteria, gram-negative bacteria, Aspergillus fumigatus and total fungi) measured were expressed as cfu m-3. Using the Markov chain model, the deposition of inhaled bioaerosols in the workers lungs was computed. The infection risk estimates were computed using the beta-Poisson dose response model and the results reported within the QMRA framework. The result of the cross-sectional survey shows that cough was the most reported by the respondents. In all, up to 27% of respondents reported one or more symptoms of cough and phlegm and up to 8.7% reported three or more symptoms (cough, phlegm, asthma etc.). On the dumpsite, while chronic cough particularly affected smokers, it had a prevalence of 38%. Chronic phlegm and asthma was prevalent at 31% and 2% respectively. Only chronic cough and chronic phlegm showed prevalence that were significantly higher that the controls (p 5 years showed was not associated chronic cough, chronic phlegm asthma. Among residents, chronic cough particularly affected the non-smokers and had the prevalence of 31.7%. Chronic phlegm and asthma was prevalent at 28.9% and 8.2% respectively. Only chronic cough and chronic phlegm showed significantly higher prevalence compared to the control (p < 0.001). Daily exposure duration was also associated with chronic cough with odds ratio of 1.2 (95% CI 1.1–1.3, p < 0.001) but not with chronic phlegm and asthma. The frequent visit of a resident to the dumpsite had an associated odds ratio of 3.8 (95% CI 1.6–8.4, p < 0.001), 4 (95% CI 1.1-14.4, p < 0.05) and 6.8 (95% CI 1.3-33, p < 0.01) for chronic cough, chronic phlegm and asthma respectively, when compared to the controls. Only years of work <10 years showed associated with chronic cough with odds ratio 4.2 (95% CI 1.4–12.4, p < 0.01) when compared to the controls. At the 95th percentile, the ambient concentration of total bacteria was 2189 cfu m-3, gram-negative bacteria 2352 cfu m-3, total fungi 824 cfu m-3 and Aspergillus fumigatus 300 cfu m-3, and were significantly higher in magnitude than the control by 2-3 log (p< 0.05). The concentration of bioaerosols at the active operational area was the highest in comparison to the other three sampling locations. However, there were no significant differences in concentration across the four sampling points for total bacteria, gram-negative bacteria and the total fungi. Aspergillus fumigatus, on the other hand, recorded a drastic decrease in concentrations up to 80-81% between the active operational area and the boundary. The particle size distribution shows that the workers were at risk of inhaling air contacting 41%, 46%, 63%, 76% of total bacteria, gram-negative bacteria, total fungi and Aspergillus fumigatus respectively, that were of sizes capable of penetrating deep into the tracheobronchial and the pulmonary region of the lungs, posing a greater human health risk. This study has shown that exposure to bioaerosols were also associated with specific activities undertaken at the dumpsite. Workers were exposed to bioaerosol concentrations up to 106 cfu m-3 during scavenging, waste sorting and site monitoring. These concentrations were 3-log higher than the mean concentration measured in the ambient air. The result shows that on a daily basis, workers were likely inhaling bioaerosols at concentrations ranging from 8.9 × 105 -1.8 × 107 cfu m-3 of total bacteria, 4.0× 105-8.1× 106 cfu m-3 of gram-negative bacteria and 3.29× 105-1.5× 106 cfu m-3 of Aspergillus fumigatus that were of sizes capable of penetrating deep into the tracheobronchial and the pulmonary region of the lungs when undertaking scavenging, waste sorting and site monitoring. These concentrations were higher than expected limit by the UK Environment Agency. The result of the QMRA showed that that the activities at the dumpsite may contribute more to the likelihood of workers developing either respiratory infection or GI infection than anything else. The infection risk from inhaling contaminated air containing spores of Aspergillus fumigatus were in the magnitude of (10-1) all locations and activity types on the dumpsite. However, the risk of infection from ingesting E.coli O157:H7 from ambient exposures across all locations on the dumpsite ranged from 10-3-10-2 for the conservative and 10-4-10-3 for the least conservative of pathogen-indicator ratio. While the risk of infection due to undertaking scavenging, waste sorting and dumpsite monitoring were in the magnitude of 10-1. Overall, this study suggests that the high prevalence of respiratory disease among the workers and the residents are indications of exposure to contaminants in the air from the dumpsite, which includes bioaerosols, as the prevalence were similar among the workers and the residents. The risk estimates show that of infection from bioaerosols were high irrespective the activity the workers undertook at the dumpsite

Pro-environmental behaviour impacts and their relationship to insurance claim frequency through individual household and municipal-level analyses

The primary objective of the research has been to determine the relationship between pro-environmental behaviour (PEB) and risk-mitigating behaviours. Chapter 2 approached the objective by comparing a direct measurement of individual household behaviours and motivations to insurance claim frequency scores. Chapter 3 approached the objective by measuring municipal actions based on milestones completed for carbon mitigation as an indirect proxy for pro-environmental behaviour at a municipal level. The milestone data was then compared to the same insurance claim frequency scores. The outcome of both studies did not identify a clear link between pro-environmental and risk-mitigating behaviour through behavioural spillover. Instead, Chapter 2 found that at a community level data resolution, age, income, education, or place of residence do not influence the PEBs of an individual. Also, Chapter 2 found that the intentions of an individual do not reflect their behaviour. Chapter 3 models did not show significant evidence of any relationship between the milestone data and the frequency of insurance claims for a municipality, indicating an absence of spillover. This study suggests that within the bounds of such a program, municipalities are experiencing either a lack of motivation for the initial behaviour or barriers to subsequent behaviours are too large. Considering both papers, in order to fully assess and understand the relationship between PEBs and risk-mitigating behaviour, additional research is necessary

2011 Annual Research Symposium Abstract Book

2011 annual volume of abstracts for science research projects conducted by students at Trinity College

The impact of crude oil-led economic growth on health and its determinants

Background and aims: There is a close connection between the demographic and epidemiological transitions which many countries undergo. Shifts in population structure and population health go hand in hand. In theory, increased economic capacity in a country generates resources for development of infrastructure and basic amenities and, in turn, health improvement. Countries that have oil resources to exploit, might expect the economic benefits to drive health improvement. However, limited evidence suggests that crude oil and other natural resources may not guarantee population health benefits. The thesis sought evidence for a pathway from oil resources to population health improvement in two linked quantitative studies. The first study was an international comparison. The second focused on Nigeria as a case study country with crude oil abundance, yet relatively poor economic performance. Methods: A theoretical model was developed to describe how oil resources could drive social, economic, and infrastructure transition, and ultimately health improvement. In the first phase study, evidence for this relationship between crude oil resources and population health was assessed globally via panel models and the relationship between oil-led economic growth and population health was assessed via cross-sectional models. Data were drawn from the World Health Organisation and United States energy information administration (n = 156 countries) and were analysed using structural equation modelling. The panel models spanned from 2000 to 2015, at 5-year intervals while the cross-sectional models explored the 2000-2015 growth in oil economy on health and its determinants in 2015. In the second phase, relationships between oil-led economic growth at state-level and household-level with health and its determinants were explored in Nigeria (n=38,522 households). Multilevel modelling was used to allow for the nested structure of the data. Results: The panel analysis in the phase one study showed that the relationship between all the markers for crude oil resources and health/determinants were not statistically significant, except for crude oil export and access to basic sanitary facility (Coefficient = -0.01, p0.05) or access to basic sanitary facilities (Coefficient = 0.01; p>0.05), over the study period. There was also no significant association between oil-based income and health over the study period: for infant mortality (Coefficient = 0.05; p>0.05) and for life expectancy (Coefficient = -0.01; p>0.05). Income group was not significant in these relationships. However, the cross-sectional analysis in the phase one study showed that the oil-rent contribution to GDP measure of oil-led economic growth was directly associated with health determinants. For example, there was a significant positive association with access to drinking water sources in low-income (Coefficient = 0.48; p<0.05) and high-income countries (Coefficient = 0.53; p<0.05). There was also a significant positive association with access to sanitary facilities in low-income countries (Coefficient = 0.38; p<0.05) but this was not found in high-income countries. Results were inconsistent between markers of health and relationships were sensitive to the measure of oil-led economic growth. This study also found that crude oil export measure of oil-led economic growth was directly associated with some markers of population health: with infant mortality (Coefficient = -0.10; p<0.05) in high-income countries and with life expectancy (Coefficient = -0.20; p<0.05) for low-income-countries. There was no significant association between oil-led economic growth and household deaths in Nigeria (Coefficient = -0.0001; p>0.05). However, oil-led economic growth did seem to be related to the type of household sanitary facilities available, indicating a possible role in improving infrastructure related to health. For example, greater oil-led economic growth was associated with the likelihood of households having flush toilet relative to no facility (Coefficient = 0.005; p<0.05). Yet, there was no significant association with other markers such as water supply for example. Overall, the results showed very weak support for a well-trodden pathway from oil to improved population health, via improved infrastructure. If anything, they supported the pathway in already higher income countries only. Conclusion: Within the necessary caveats of a very methodologically challenging study, the conclusion of these analyses must be that having oil wealth does not readily translate to population health improvement. Measurement of all steps on the pathway was difficult, but the results hint that the mediating effects of institutions are important influences. Channelling crude oil wealth into health improvement requires strong institutions as seen with high-income countries. Where these are absent, governments (particularly in low-income countries) seem to have failed to convert their oil revenues to population health benefits. The implications are that appropriate models of managing oil revenue should be established. Without strong governance, the social, economic and environmental harms from crude oil activities may actually outweigh the benefits. Since governance and priority setting determines the amount of oil revenue allocated for health improvement in a country, the potential remains for oil to be a positive resource for population health

Mining microbial compost communities for lignocellulose degrading proteins

The production of second generation biofuels from agricultural residues is an attractive alternative to the use of conventional first generation feedstocks, which are also important food resources. However, these alternative feedstocks predominately consist of lignocellulose, the main structural component of the plant cell wall, and expensive physicochemical and enzymatic pre-treatments are required before fermentation into biofuel. Therefore, the discovery of novel enzymes capable of deconstructing lignocellulose, in conditions that would be amenable to industry, is an important goal. The work, presented in this thesis, has explored the degradation of lignocellulose by a community of composting microbes, enriched for growth on wheat straw. Culturable members of the community, were isolated and assessed for their enzymatic activities towards lignin, cellulose and xylan. From these studies, a promising Ascomycota was identified, Graphium sp., which was capable of utilising both crystalline cellulose and xylan as carbon sources for growth. Transcriptomic studies were performed on Graphium sp. with and without wheat straw present, representing the first molecular information generated from an organism of this genus. From this 680 putative proteins were annotated as containing carbohydrate active domains. Proteomics added further depth to the analysis, with investigations focused on secreted proteins both located in the culture supernatant and bound to the insoluble lignocellulose substrate. Six secreted proteins were identified as targets for further analysis, and three of these were successfully isolated either from the native host, or a heterologous system. This included a lytic polysaccharide monooxygenase that appeared active on both chitin and cellulose, and a GH7 whose activity on cellulose was demonstrated. An intriguing protein, which showed low homology to a dioxygenase, was also expressed, though its role in the lignocellulose degrading environment has yet to be established

Identifying and Ranking Landfill Sites for Municipal Solid Waste Management: An Integrated Remote Sensing and GIS Approach

Disposal of municipal solid waste (MSW) is one of the significant global issues that is more evident in developing nations. One of the key methods for disposing of the MSW is locating, assessing, and planning for landfill sites. Faisalabad is one of the largest industrial cities in Pakistan. It has many sustainability challenges and planning problems, including MSW management. This study uses Faisalabad as a case study area and humbly attempts to provide a framework for identifying and ranking landfill sites and addressing MSW concerns in Faisalabad. This method can be extended and applied to similar industrial cities. The landfill sites were identified using remote sensing (RS) and geographic information system (GIS). Multiple datasets, including normalized difference vegetation, water, and built-up areas indices (NDVI, NDWI, and NDBI) and physical factors including water bodies, roads, and the population that influence the landfill site selection were used to identify, rank, and select the most suitable site. The target area was distributed into 9 Thiessen polygons and ranked based on their favorability for the development and expansion of landfill sites. 70% of the area was favorable for developing and expanding landfill sites, whereas 30% was deemed unsuitable. Polygon 6, having more vegetation, a smaller population, and built-up areas was declared the best region for developing landfill sites and expansion as per rank mean indices and standard deviation (SD) of RS and vector data. The current study provides a reliable integrated mechanism based on GIS and RS that can be implemented in similar study areas and expanded to other developing countries. Accordingly, urban planning and city management can be improved, and MSW can be managed with dexterity

ALS-NSCORT 2005 Annual Report

An overview of the ALS-NSCORT projects for the year 2005. 169 pages