La presente investigación busca evaluar el efecto de la innovación tecnológica sobre la productividad laboral en el sector manufacturero peruano, para esto, se recogen los datos proporcionados por la Enterprise Survey en los años 2010 y 2017 a fin de compararlos a partir de un análisis del proceso de innovación, desde sus determinantes hasta sus implicancias sobre el desempeño de las empresas. Los hallazgos encontrados muestran que: la inversión en innovación en el año 2010 se explica fundamentalmente por el tamaño de la empresa, la participación de mercado, actividad exportadora, diversificación y número de trabajadores; mientras que en el 2017 se explica básicamente por el tamaño de empresa y la actividad exportadora. Además, esta inversión influye positivamente sobre la innovación tecnológica en sí misma vía productos y procesos teniendo un mayor impacto sobre la primera en el caso del 2010 y sobre la segunda en el 2017. Finalmente, los resultados sugieren la existencia de un efecto positivo y significativo del gasto en I+D sobre la productividad laboral en el año 2010 mientras que en el año 2017 esta variable es positiva pero no significativa. Asimismo, el efecto de la innovación tecnológica producto de la inversión en I+D no es significativa sobre la productividad laboral en ninguno de los dos años estudiados debido a que Perú al encontrarse en América latina, las empresas se encuentran lejos de la frontera del conocimiento y muchas de sus “innovaciones” son imitaciones de tecnología desarrollada previamente por otros países desarrollados. / This research seeks to evaluate the effect of technological innovation on labor productivity in the Peruvian manufacturing sector, for this, the data provided by the Enterprise Survey in 2010 and 2017 are collected in order to compare them based on a process analysis of innovation, from its determinants to its implications on the performance of companies. The findings show that: investment in innovation in 2010 is mainly explained by the size of the company, market share, export activity, diversification and number of workers; while in 2017 it is basically explained by the size of the company and the export activity. In addition, this investment positively influences technological innovation in itself via products and processes having a greater impact on the first in the case of 2010 and the second in 2017. Finally, the results suggest the existence of a positive and significant effect of R&D spending on labor productivity in 2010 while in 2017 this variable is positive but not significant. Likewise, the effect of technological innovation as a result of investment in R&D is not significant on labor productivity in any of the two years studied due to Peru being in Latin America, companies are far from the frontier of knowledge and many of its “innovations” are imitations of technology previously developed by other developed countries. / Tesis

<p>Rolling contact fatigue (RCF) is a common cause of failure in tribological machine components such as rolling-element bearings (REBs). Steels selected for RCF applications are subject to various material processes in order to produce martensitic microstructures. An effect of such material processing is the retention of the austenitic phase within the steel microstructure. Retained austenite (RA) transformation in martensitic steels subjected to RCF is a well-established phenomenon. In this investigation, a novel approach is developed to predict martensitic transformations of RA in steels subjected to RCF. A criteria for phase transformations is developed by comparing the required thermodynamic driving force for transformations to the energy dissipation in the microstructure. The method combines principles from phase transformations in solids with a damage mechanics framework to calculate energy availability for transformations. The modeling is then extended to incorporate material alterations as a result of RA transforming within the material. A continuum damage mechanics (CDM) FEM simulation is used to capture material deterioration, phase transformations, and the formation of internal stresses as a result of RCF. Crystal lattice orientation is included to modify energy requirements for RA transformation. Damage laws are modified to consider residual stresses and different components of the stress state as the drivers of energy dissipation. The resulting model is capable of capturing microstructural evolution during RCF.</p> <p>The development and stability of internal stresses caused by RA transformation in bearing steel material was experimentally investigated. Specimens of 8620 case carburized steel were subjected to torsional fatigue at specific stress levels for a prescribed number of cycles. X-ray diffraction techniques were used to measure residual stress and RA volume fraction as a function of depth in the material. A model is set forth to predict compressive residual stress in the material as a function of RA transformation and material relaxation. Modeling results are corroborated with experimental data. In addition, varying levels of retained austenite (RA) were achieved through varying undercooling severity in uniformly treated case carburized 8620 steel. Specimens were characterized via XRD and EBSD techniques to determine RA volume fraction and material characteristics prior to rolling contact fatigue (RCF). Higher RA volume fractions did not lead to improvement in RCF lives. XRD measurements after RCF testing indicated that little RA decomposition had occurred during RCF. The previously established RCF simulations were modified to investigate the effects of RA stability on RCF. The results obtained from the CDM FEM captured similar behavior observed in the experimental results. Utilizing the developed model, a parametric study was undertaken to examine the effects of RA quantity, RA stability, and applied pressure on RCF performance. The study demonstrates that the energy requirements to transform the RA phase is critical to RCF performance.</p>

<p dir="ltr">Rolling contact fatigue (RCF) is one of the leading causes of failure in critical tribological components such as rolling element bearings (REBs), gears, cam and followers, etc. This is especially paramount for advanced aerospace applications where REB components need to operate for billions of RCF cycles before routine maintenance or inspection is performed. The rolling motion between the rolling elements and raceway produces RCF, wherein a complex, non-proportional, alternating contract stress is applied over a small material volume. Moreover, the highly localized stress occurs on the same length scale as microstructural features such as carbides, inclusions, grain size, hardness gradients from carburization, surface roughness, thereby amplifying their effect on fatigue performance. Therefore, the objective of this dissertation is to investigate critical microstructural modifications and their effects on RCF performance via experiments and computational modeling.</p><p dir="ltr">Initially, an investigation was undertaken to investigate surface roughness effects on RCF. The surface roughness of various REBs was measured through optical surface profilometry and used to construct rough surface pressure distributions, which were then used in a continuum damage mechanics (CDM) finite element (FE) framework. The results demonstrated that life is reduced as lambda ratio decreases. It was also observed that a 2-parameter Weibull cumulative distribution function can describe the relationship between the near surface orthogonal shear stress concentration and ratio of surface failures.</p><p dir="ltr">Next, the enhancement to RCF life from grain size refinement of through hardened bearing steels was studied. To capture the effects of grain refinement, torsion stress-life data of various grain size were used in the RCF model. A predictive life equation for different grain sizes was constructed based on the exponential trend observed between grain size and life from the simulation data. The life equation was then used to calculate the quotient of RCF at two different grain sizes. This quotient was defined as the life improvement ratio and it was observed that this investigation’s ratios compared well with existing life improvement ratios from RCF experiments.</p><p dir="ltr">Hardness gradient is a common microstructural modification to improve RCF life of tribo-components. Variation of hardness gradients is prevalent in case hardened (i.e. case carburized) bearing materials. Therefore, the CDM-FE RCF model was modified to investigate the effects of various hardness gradient types and depths on fatigue life improvement. The simulation results enabled the identification of potentially optimal gradients aimed to mitigate manufacturing challenges and provided the foundation for the construction of a general fatigue life equation.</p><p dir="ltr">A fundamental study to understand the impact various common RCF failure criteria have on RCF life estimation was then conducted using computational modeling. To capture the variation of a material’s resistance to fatigue, the critical CDM damage parameters were assumed to follow a probabilistic distribution instead of a singular value. The CDM-FE model was modified to consider the shear reversal, the octahedral shear stress, the maximum shear stress, the Fatemi-Socie criteria, and the Dang Van multi-axial fatigue parameter as failure criteria. Simulation life results revealed that the CDM-FE model with shear reversal and Fatemi-Socie criteria best match empirical predictions from well-established RCF life theory. Notably, the Fatemi-Socie exhibited the best agreement over all operating conditions.</p><p dir="ltr">The next investigation focused on the cleanliness of aerospace-quality bearing steels. Torsion fatigue experiments established the stress-life (S-N) relation for three common aerospace quality bearing steels. The S-N data was later used to calibrate the RCF model’s damage equation, which considered the Fatemi-Socie criteria following conclusions from a previous investigation. Simulation results were observed to corroborate well with RCF experiments that were conducted for all three materials, while noting the simulations offered a significant time saving. As a result, a subsequent investigation focused on establishing the stress-life relationship for one of the aerospace quality bearing steels through a combined experimental and analytical approach. Good corroboration was observed between simulations and experiments at three contact pressures. This finding is particularly significant as it strengthens the reliability of computational RCF model as an efficient means to assess the RCF performance of bearing materials.</p><p dir="ltr">Furthermore, the detailed investigation on RCF performance of each critical microstructural modifications and their respective effect greatly improves the state-of-the-art. The findings emanating from the various investigations offer informed fatigue design recommendations that aid in the selection of rolling element bearings for critical tribological and aerospace applications.</p>

Efficient ground handling at airports greatly adds to the performance of the entire air transportation network. In this network, airports are connected via aircraft that rely on passenger and crew connections, successful local airport operations, and efficient ground handling resource management. In addition, airport stakeholders’ decision-making processes must take into account various time scales (look-ahead times), process estimates, and both limited and multiple-dependent solution spaces. Most airlines have created integrated hub and operations control centers to monitor and adapt tactical operations. Despite this, decisions in such control centers should be made quickly in case of disruption. The decisions should also include the interests of various airline departments and local stakeholders. Taking into account the Airport Collaborative Decision Making (A-CDM) concept, the joint venture between Airports Council International Europe (ACI EUROPE) - European Organization for the Safety of Air Navigation (EUROCONTROL) - International Air Transport Association (IATA) - Civil Air Navigation Services Organization (CANSO), this study creates different tools to manage turnaround in normal and disrupted contexts, hence facilitating decision-making in an Airport Operations Control Center (AOCC) and a Hub Control Center (HCC). This research focuses on the airline role in the collaborative decision-making process. Regarding A-CDM milestones, turnaround time estimation is computed by four modeling methodologies, namely Critical Path Method (CPM), Project Evaluation and Review Technique (PERT), Fuzzy Critical Path Method (FCPM), and Analytical Convolution in deterministic and nondeterministic domains. In addition, the study develops mathematical models to return the airline schedule to its original plan in the event of delays. Chance-constrained and Robust optimization are also created for optimal decision-making when airlines confront uncertainty during real-world operations. The study also develops a novel Hybrid Shuffled Frog-Leaping Algorithm (SFLA)-Grasshopper Optimization Algorithm (GOA) to expedite the process of finding recovery solutions, allowing AOCC and HCC for real-time applications to send this information to the relevant departments. In comparison to common linear solvers, the solution process is sped up by 18 percent and the quality of the solutions is enhanced by 24 percent on average. Initial results are generated in less than 2 minutes, and global optimal results are achieved in near 15 minutes allowing the system to be applied in real-time applications.:Abstract 1 Introduction 1.1 Problem Description 1.1.1 Decision Scope 1.1.2 Airport Collaborative Decision Making (A-CDM) 1.1.3 Total Airport Management 1.1.4 Ground Handlers 1.1.5 Turnaround Management 1.2 Aims and Objectives 1.3 Thesis Contribution 1.4 Structure 2 Literature Review 2.1 Turnaround 2.2 Ground Handling 2.3 Flights and Networks 2.4 Apron and Gate Assignment 2.5 Scopes Combination 2.5.1 Gate Assignment and Turnaround 2.5.2 Gate Assignment and Flights 2.5.3 Gate Assignment and Ground Handling 2.5.4 Turnaround and Flights 2.5.5 Turnaround and Ground Handling 2.5.6 Flights and Ground Handling 2.6 Turnaround Operations 2.7 Conclusion 3 Turnaround Definition 3.1 Turnaround in A-CDM System 3.2 Turnaround and Ground Handling 3.3 Turnaround Operations 3.3.1 In-Block (INB) and Acceptance (ACC) 3.3.2 Deboarding (DEB) and Boarding (BOA) 3.3.3 Fueling (FUE) 3.3.4 Catering (CAT) 3.3.5 Cleaning (CLE) 3.3.6 Unloading (UNL) and Loading (LOA) 3.3.7 Water service (WAT) and Toilette (TOI) 3.3.8 Finalization (FIN) 4 Total Turnaround Time (TTT) Calculation 4.1 Critical Path Method (CPM) 4.2 Project Evaluation and Review Technique (PERT) 4.3 Fuzzy Critical Path Method (FCPM) 4.3.1 Fuzzy Numbers and Fuzzy Sets 4.3.2 Fuzzy Membership Functions of Turnaround Tasks 4.3.3 Probability-possibility Transformation of Turnaround Tasks 4.3.4 Fuzzy Critical Path Method (FCPM) in Total Turnaround Time (TTT) Calculation 4.3.5 Discussion 4.4 Analytical Convolution 4.4.1 Convolution Method 4.4.2 Monte Carlo (MC) Simulation Evaluation 4.4.3 Application of Convolution in Turnaround Control 5 Disruption Management 5.1 Airline Disruption Management 5.1.1 Airport Operations Control Center (AOCC) 5.1.2 Delay in the Airline Networks 5.1.3 Recovery Options 5.2 Deterministic Model 5.2.1 Mathematical Model 5.2.2 Solution Approaches 5.2.3 Problem Setting 5.3 Non Deterministic Model 5.3.1 Stochastic Arrivals 5.3.2 Stochastic Duration 6 Conclusion 6.1 Discussion around Research Questions 6.1.1 Integration of All Actors 6.1.2 Turnaround Time Prediction 6.1.3 Quick and Robust Reaction 6.2 Future Research 6.2.1 Scope Development 6.2.2 Algorithm Development 6.2.3 Parameter Development List of Acronyms List of Figures List of Tables Bibliography Acknowledgement

The goal of this dissertation is to analyze the impact of the innovative effort on innovation, and this on the productivity of Brazilian companies. This is a firm-level analysis using data crossover from the Technological Innovation Survey (PINTEC) and the Annual Industrial Survey (PIA), both developed by Brazilian Institute of Geography and Statistics (IBGE), in the period from 2006 to 2008. The research aims to contribute to the empirical debate to understand the pattern of the current Brazilian innovative process, considering the sectors specifications and their levels of technological intensity. Is made an theoretical analysis of the literature, that explicit the various theories of innovation, its determinants and its relationship with productivity, showing that, although very different in their conceptions, there is a currently consensus about the importance of technological innovation on industrial performance. Is also made an empirical research on the relationship between innovation activities, innovation and productivity, using the CDM model and econometric strategy to answer these questions. The results shows that, despite the fact that few companies in Brazil innovate and invest in innovation (especially in direct investment in R&D activities), the probability to innovate increases with a higher level of investment in innovative activities, and that the level of productivity is positively affected by product or process innovation. These results also happen with the industries samples of lower and higher technological intensity, but, for that last ones, the innovation impact on productivity not shown significant. / O objetivo desta dissertação é analisar o impacto do esforço inovativo sobre a inovação, e desta sobre a produtividade das empresas brasileiras. Trata-se de uma análise em nível da firma que utiliza o cruzamento dos dados da Pesquisa de Inovação Tecnológica (PINTEC) e da Pesquisa Industrial Anual (PIA), ambas elaboradas pelo Instituto Brasileiro de Geografia e Estatística (IBGE), no período de 2006 a 2008. A pesquisa visa contribuir para o debate empírico ao compreender o padrão do processo inovativo brasileiro atual, considerando as especificações setoriais e de seus níveis de intensidade tecnológica. É feita uma análise da literatura teórica, que explicita as várias teorias da inovação, dos seus determinantes e de sua relação com a produtividade, evidenciando que apesar de muito diferente em suas concepções, há atualmente um consenso tecnológico sobre a importância da inovação sobre o desempenho industrial. Também é feita uma investigação empírica acerca da relação entre atividades inovativas, inovação e produtividade, utilizando-se o modelo CDM como estratégia econométrica para responder essas questões. Os resultados encontrados evidenciam que, apesar da constatação de que poucas empresas do Brasil inovam e investem em inovação (principalmente no que se refere ao investimento direto em atividades de P&D), a probabilidade de inovar aumenta com um maior nível de investimento em atividades inovativas, e que o nível de produtividade é influenciado positivamente, na média, pela inovação, seja ela de produto ou processo. Esses resultados também acontecem com os recortes em indústrias de intensidades tecnológicas mais baixas e mais altas, porém, para estas últimas, o impacto da inovação sobre a produtividade não se mostrou significativo. / Mestre em Economia

Standardized, collaborative decision-making processes have already been implemented at some network-relevant airports, and these can be further enhanced through data-driven approaches (e.g., data analytics, predictions). New cost-effective implementations will also enable the appropriate integration of small and medium-sized airports into the aviation network. The required data can increasingly be gathered and processed by the airports themselves. For example, Automatic Dependent Surveillance-Broadcast (ADS-B) messages are sent by arriving and departing aircraft and enable a data-driven analysis of aircraft movements, taking into account local constraints (e.g., weather or capacity). Analytical and model-based approaches that leverage these data also offer deeper insights into the complex and interdependent airport operations. This includes systematic monitoring of relevant operational milestones as well as a corresponding predictive analysis to estimate future system states. In fact, local ADS-B receivers can be purchased, installed, and maintained at low cost, providing both very good coverage of the airport apron operations (runway, taxi system, parking positions) and communication of current airport performance to the network management. To prevent every small and medium-sized airport from having to develop its own monitoring system, we present a basic concept with our approach. We demonstrate that appropriate processing of ADS-B messages leads to improved situational awareness. Our concept is aligned with the operational milestones of Eurocontrol’s Airport Collaborative Decision Making (A-CDM) framework. Therefore, we analyze the A-CDM airport London–Gatwick Airport as it allows us to validate our concept against the data from the A-CDM implementation at a later stage. Finally, with our research, we also make a decisive contribution to the open-data and scientific community.

The current generation of sequencing technologies has led to significant advances in identifying novel disease-associated mutations and generated large amounts of data in a highthroughput manner. Such data in conjunction with clinical routine data are proven to be highly useful in deriving population-level and patient-level predictions, especially in the field of cancer precision medicine. However, data harmonization across multiple national and international clinical sites is an essential step for the assessment of events and outcomes associated with patients, which is currently not adequately addressed. The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is an internationally established research data repository introduced by the Observational Health Data Science and Informatics (OHDSI) community to overcome this issue. To address the needs of cancer research, the genomic vocabulary extension was introduced in 2020 to support the standardization of subsequent data analysis. In this review, we evaluate the current potential of the OMOP CDM to be applicable in cancer prediction and how comprehensively the genomic vocabulary extension of the OMOP can serve current needs of AI-based predictions. For this, we systematically screened the literature for articles that use the OMOP CDM in predictive analyses in cancer and investigated the underlying predictive models/tools. Interestingly, we found 248 articles, of which most use the OMOP for harmonizing their data, but only 5 make use of predictive algorithms on OMOP-based data and fulfill our criteria. The studies present multicentric investigations, in which the OMOP played an essential role in discovering and optimizing machine learning (ML)-based models. Ultimately, the use of the OMOP CDM leads to standardized data-driven studies for multiple clinical sites and enables a more solid basis utilizing, e.g., ML models that can be reused and combined in early prediction, diagnosis, and improvement of personalized cancer care and biomarker discovery.

Organisational and individual Health and Safety (H&S) competence is an essential element to the successful completion of a construction project in a safe way and without hazards to the health of all workforce. Under the Construction (Design and Management) (CDM) Regulations 2007, the client should take reasonable steps to ensure that the appointed duty-holders and engaged people are H&S competent to design, build or co-ordinate the project. Although the CDM Regulations 2007 and its Approved Code of Practice (ACoP) have established ‘Core Criteria’ to guide the client to assess duty-holders’ H&S competence in the outset of a project, it is still difficult for most inexperienced clients to discharge the duty of making the key decisions in H&S competence assessment. In order to help the client implement H&S competence assessment, it is important to develop a tool that can effectively and efficiently support the client to make reasonable decisions in the selection of H&S competent duty-holders. According to the findings of the case study of existing formal H&S competence assessment schemes undertaken as part of this work, H&S competence assessment was characterised as a subjective, qualitative and non-linear regulation-compliance checking process. In addition, the case study helped identify the latent shortcomings in the ‘Core Critiera’ and the operational drawbacks in current practice of implementing H&S competence assessment. Based on a review of Information Technology (I.T.) and Artificial Intelligence (A.I.) applications in construction, Knowledge-Based System (KBS) is identified as being a suitable tool to support decision-making in H&S competence assessment, mainly due to its appropriateness to solve regulation-compliance checking problems and support subjective and qualitative decision-making process. Following a decision-making framework for H&S competence assessment, a KBS decision-support model was developed, applying three mechanisms to support the reasonable decision-making for H&S competence assessment. In order to develop an appropriate and practical KBS for H&S competence assessment, a textual knowledge base was developed, specifying the minimum satisfaction standards and a rating indicator system for ‘Core Criteria’. As a result, an online KBS was developed using Java Server Pages (JSP) technology and MySQL. The online KBS applied the textual knowledge base to support the screen, rating, ranking and reporting decision-supporting mechanisms. Simultaneously, the case inquiry and expert inquiry facilities were also included in the KBS for effective decision-making. Finally, construction experts and practitioners in H&S management evaluated the validity and usability of the KBS through a questionnaire survey. The prototype KBS was borne out to be an effective and efficient decision-support tool for H&S competence assessment and have the potential to be applied in practice.

隨著社會的進步，非營利組織在現代社會中所扮演之角色愈顯重要，非營利組織在美國是最大的雇主。非營利組織的蓬勃發展，引發一場全球結社革命，形成與公部門和私部門鼎足而立的第三部門。我國自1987年解嚴以來，政治力釋放，人民團體法規的訂定加上社會多元的發展，非營利組織的成立可說是方興未艾，其活動包括社會服務、政策倡導、教育文化、工商發展與醫療衛生等多項範疇，對國家社會之影響可謂至鉅。由於非營利組織的蓬勃發展，展現了民間豐沛的社會力量，一股由下而上的社會力量就此展開，在政治、社會、文化與教育等多種層面之影響下，在全台各地如雨後春筍般，紛紛地設立。成為居民終身學習（lifelong learning）及形塑公民社會（civil society）的場所，亦擴大非營利組織影響之層面。 　　Drucker稱二十一世紀為社會福利事業的世紀，非營利組織未來十年之三大挑戰：（1）能因應轉變的領導者（2）多樣化地生活與促進多樣化（3）合作、聯盟和夥伴關係。其中第二項挑戰包括通往成長、知識的取得和發展的可能性，並將我們國家各個種族所有領域的經理人、全體教師與學生、管理團隊、工作者和顧客結合在一起。團隊建立之管理方式在今日已成為普遍且廣受矚目的管理策略，因此，非營利組織團隊之研究，將益顯重要，Drucker在《非營利機構的經營之道》（Managing the Non-Profit Organization）一書中，亦談到機構愈成功，就愈需要建立起團隊。 　　綜上述，本研究以台灣CDM專業協會的行政團隊發展為研究對象，再進行實務對象的選擇，進行深入探究，了解上述行政團隊，從過去到現在的發展情形、運作績效及其管理；同時瞭解在非營利組織中，偶爾會運用團隊的概念，那麼這個團隊是否是理論上「團隊」，如果不符合理論上團隊的定義，該如何運用團隊建立的步驟來建立真正的團隊，以及適合的種類；其次，如何形塑成高績效團隊，以增進團隊績效。 　　本研究經深度訪談及參與觀察等方式，整理出如下的研究結論與發展： 　　1.台灣CDM專業協會行政團隊的經營的專業性。 　　2.在團隊的發展過程中，台灣CDM專業協會在不同階段有不同的困境， 促使組織做出制度變革或調整的動力。 　　3.台灣CDM專業協會的經營方面，以及在協助與促成議題的推動方面也頗 有貢獻，至於在經營的困境主要是人的問題，反應在因人設事以及成 員對台灣CDM專業協會角色與定位之摸索等。 　　4.台灣CDM專業協會對於行政團隊的管理是傾向一種自我管理的尊重心 態，領導者的領導風格比較不是權威式領導。另外，績效管理這部分在 台灣CDM專業協會是比較鬆散的，可能與非營利組織對於「績效」這兩 個字比較敏感有關。在激勵管理這部分，未來台灣CDM專業協會領導者 應該深思如何讓工作變得更有意義、更具激發性。 　　5.從台灣CDM專業協會領導權、決策、目標、互賴程度、合作情形、意見 表達、責任歸屬、權限、整體氣氛、績效衡量等面向來看是否符合團隊 之定義，其中台灣CDM專業協會有些是不太符合，如同Montebello與 Buzzotta兩人所言，團隊概念在今日常被普遍地誤解，許多自稱為團 隊的組織充其量只是同一組織、工作下的人群組合而已。 　　6.如何灌輸及教育大家對於團隊的認識，也是未來實施前的先決條件。至 於團隊建立的步驟可從清晰的目標與使命、團隊文化的型塑、領導者與 成員的支持、因素考量、選擇適當的成員、相關的訓練與活動、團隊會 議等方面著手進行。在訪談過程中發現現任秘書長對於台灣CDM專業協 會的誕生頗有貢獻，從一個理念化為真正的行動，其中扮演一個重要的 角色。

Considerando a grande importância do seqüestro de carbono (C) nos solos florestais, observa-se pequena quantidade de projetos de MDL que incluem esse compartimento como agente da mitigação do aquecimento global. Isso ocorre pelo fato da quantificação dos estoques de C do solo representar maiores desafios se comparada aos demais componentes dos ecossistemas florestais. Sabendo-se das dificuldades econômicas e ambientais envolvidas na adoção desse tipo projeto e da importância das florestas na mitigação da mudança do clima, o objetivo desse trabalho foi avaliar o desempenho de metodologias para a obtenção do estoque de C do solo em duas áreas de reflorestamento e suas respectivas linhas de base (usos do solo anteriores aos plantios, i.e. pastagens e vegetações nativa), como base para diminuir a relação custo-benefício de projetos de MDL. Para alcançar o objetivo principal, a presente pesquisa foi composta das seguintes etapas: (i) estudo da variabilidade espacial do C do solo em uma área de reflorestamento com espécies nativas, estabelecida em Cotriguaçú/MT (Área I) e em uma cronossequência de plantio de eucalipto, localizada em Avaré/SP (Área II); (ii) determinação do tamanho da parcela e do nº ideal de amostras a partir da dependência espacial do C nos reflorestamentos; (iii) estimativa dos teores de C e densidades do solo (Ds) pela Espectroscopia de Reflectância no Infravermelho Próximo (NIRS) e Médio (MIRS), visando a redução dos custos analíticos sem prejuízo da qualidade dos resultados; e (iv) cálculo dos estoques de C do solo nas áreas e estimativa do balanço de carbono do projeto de MDL conduzido na Área II, utilizando a ferramenta EX-ACT (Ex-Ante Carbon Balance Tool). Os resultados obtidos confirmaram a existência de importante variabilidade espacial do C do solo nas áreas e dependência espacial forte em todos os sistemas de manejo estudados. A análise do número ideal de amostras de solo indicou que a coleta de cinco pontos por parcela é tão precisa quanto uma amostragem com mais pontos. O tamanho ideal das parcelas variou de 361-841 m2 nos plantios da Área I e de 900-3721 m2 nos plantios da Área II. O desempenho dos métodos NIRS e MIRS na estimativa do teor de C dos solos foi bastante satisfatório, principalmente quando os modelos testados foram calibrados com quantidades entre 5-10% do conjunto de dados total. Os resultados da estimativa da Ds foram um pouco inferiores aos do C. Os estoques de C do solo obtidos na Área I foram superiores aos da Área II. Considerando apenas o solo, é possível afirmar que o potencial de geração de créditos de C é maior no reflorestamento com espécies nativas sob solo argiloso do que no reflorestamento com eucalipto em solo arenoso. O balanço de C do projeto conduzido na Área I indicou o seqüestro de quase três milhões de toneladas de CO2eq em 40 anos. Espera-se que este estudo contribua para o aumento da inclusão do solo em projetos de MDL, uma vez comprovada a possibilidade de redução dos custos associados à obtenção e determinação dos estoques de C nesse compartimento / Considering the great importance of carbon sequestration (C) in forest soils, there are few CDM projects that include this compartment as an agent of global warming mitigation. This occurs because the quantification of soil C stocks represents a bigger challenge when compared to other components of forest ecosystems. Considering the economic difficulties and environmental issues involved in adopting this type of project and the importance of forests in mitigating climate change, the objective of this study was to evaluate the performance of methods for obtaining soil C stocks in two forestry areas and their respective baselines (land use prior to planting, i.e. pastures and native vegetation) as a basis for reducing the cost-benefit ratio of CDM projects. To achieve the main objective, this research was composed of the following steps: (i) estimating the spatial variability of soil C in an area reforested with native species, established in Cotriguaçú, MT (Area I) and a Eucalyptus chronosequence, located in Avaré, SP (Area II), (ii) determining the optimal amount of soil samples and the plot size from the soil C spatial dependence range in the reforestation areas, (iii) estimating soil C content and bulk density (BD) by Near and Mid Infrared Reflectance Spectroscopy (NIRS and MIRS, respectively) to reduce analytical costs without affecting the quality of the results, and (iv) calculating soil C stocks in both areas and estimating the carbon balance of a CDM Project conducted in Area II, using EX-ACT (\"Ex-Ante Carbon Balance Tool\"). The results confirmed the existence of significant soil C spatial variability in both areas and a strong spatial dependence at all plots. The analysis of the optimal number of soil samples indicated that the sampling procedure with five points per plot is as accurate as intensive sampling. The optimum size of plots ranged from 361-841 m2 at Area I plantations and from 900-3721 m2 at Area II. The performance of MIRS and NIRS to estimate the soil carbon content was very satisfactory, especially when the models were calibrated with amounts between 5-10% of the total data set. The estimations of BD were slightly less precise than those of soil C content. The soil C stocks obtained at Area I were higher than Area II. Considering only the soil compartment, it is clear that the potential for C credit generation in a reforestation with native species on a clayey soil is higher than in a reforestation with eucalyptus on a sandy soil. The C balance of the CDM project conducted in Area I is expected to sequester almost three million tones of CO2 eq in 40 years. We hope this study contributes to the increased inclusion of soil in CDM projects, by confirming the feasibility of reducing the costs associated with both sampling and analytical procedures