This study initially presents historical trends in both the capitalized value and market value of farmland in the eight states comprising the Corn Belt and Lake States production regions as defined by the USDA. An econometric analysis of annual real cash rents per acre prior to determining the capitalized value of farmland in the eight states is then conducted. Two distributed lag models were hypothesized. The comparison of regression results of these two distributed lag models indicates that current year real cash rent can be best explained by current year real net farm income, lagged real net farm income over a period of years, and real cash rent in the previous year. A spreadsheet simulation model is used to project capitalized farmland values in each state as well as regional averages over the 2012-2015 period. These projections reflect alternative assumptions regarding future trends in real net farm income at the state level as well as the rate on 10-year constant maturity U.S. government bonds to assess the potential sensitivity of capitalized farmland values under adverse economic conditions. The projected trends in capitalized farmland values under two alternative stress scenarios reflecting higher interest rates levels and lower net farm income levels indicates that capitalized farmland values are particularly sensitive to interest rate fluctuations since cash rent expectations of landlords are based on current and lagged historical profit performance.

The presence and spread of invasive tree species have caused great ecological and economic damages. Previous studies usually ignored the role of socioeconomic factors and seldom treated presence and abundance as different phenomena. Using Classification and Regression Trees (CART) analysis, important driving factors affecting the presence and abundance of invasive tree species in Mississippi were identified. Then these selected important factors were spatially analyzed using a spatial lag model at the plot and county levels. The empirical results from the spatial lag model showed that: 1) presence was associated with elevation, ownership, population density and per capita annual income; 2) abundance was related to stand age, elevation, growing stock and per capita annual income. These findings suggested that socioeconomic factors besides ecological factors played a significant role and factors affecting the presence and abundance were different. Thus, management prescriptions to monitor and control invasions should depend on difference factors.

Pollution studies have sought to understand the relationships between adverse health effects and harmful exposures. Many environmental health studies are predicated on the idea that each exposure has both acute and long term health effects that need to be accurately mapped. Considerable work has been done linking air pollution to deleterious health outcomes but the underlying biological pathways and contributing sources remain difficult to identify. There are many statistical issues that arise in the exploration of these longitudinal study designs such as understanding pathways of effects, addressing missing data, and assessing the health effects of multipollutant mixtures. To this end this dissertation aims to address the afore mentioned statistical issues. Our first contribution investigates the mechanistic pathways between air pollutants and measures of cardiac electrical instability. The methods from chapter 1 propose a path analysis that would allow for the estimation of health effects according to multiple paths using structural equation models. Our second contribution recognizes that panel studies suffer from attrition over time and the loss of data can affect the analysis. Methods from Chapter 2 extend current regression calibration approaches by imputing missing data through the use of moving averages and assumed correlation structures. Our last contribution explores the use of factor analysis and two-stage hierarchical regression which are two commonly used approaches in the analysis of multipollutant mixtures. The methods from Chapter 3 attempt to compare the performance of these two existing methodologies for estimating health effects from multipollutant sources.

The repo rate, which is the key interest rate, set by the central banks has been declining for many years and hitting zero in Sweden in late 2014. We analyse the effectiveness on the economy from a change in the repo rate, comparing two time periods with high and low repo rate environments. We use quarterly data on GDP and its components, between 1994 and 2019. For analysing the effectiveness, we use multiple Auto Regressive Distributed Lag (ARDL) modelling to compute a total of 12 models. In our findings, we saw that the effectiveness of a change in repo rate has been increased in the low repo rate environment, making it harder to increase the rate without harming the economy but also increasing the effect of a decrease in the repo rate. Also, we found that the investment component of GDP may exhibit extra high effectiveness in the low repo rate environment. This method of analysing the repo rates impact on the economy could be used for decision makers regarding monetary policies.

<p>Land use planning has gained popularity as a travel demand management strategy for the last two decades. Many urban authorities in North America have adopted smart growth policies in order to curb auto use and promote sustainable forms of travel, namely, public transit, bicycle and walking. The purpose of this study is to examine whether someone’s travel behavior is influenced by the characteristics of the built environment where one lives and works. The study area is Halifax Regional Municipality, Nova Scotia, Canada. Two aspects of travel are analyzed for a weekday: total distance travelled by auto and average tour complexity. Separate models are developed for worker and non-worker by applying ordinary least square and spatial lag modeling techniques. The built environment variables are measured near home and workplace and at different geographical scales. The average auto distance and tour complexity are separately regressed against the built environment variables while personal characteristics, household attributes, preferences for residential location and transport mode, and meteorological conditions of survey days are accounted for. The results of auto distance models suggest that people living and working in high accessibility areas with mixed land uses make shorter travel by auto, which supports the claims of smart growth proponents. The built environment variables make significant contribution to the fitness of auto distance models. In case of tour complexity models, built environment variables also appear to be significant but with lower contribution to model <em>R²</em>. The results suggest that non-workers, who live in poor accessibility areas, make more complex tours. Workers living in poorly accessible neighborhoods and working in highly accessible areas make complex commuting and work-based, non-work tours. It means that, workers compensate poor neighborhood accessibility by trip chaining near workplace. The findings would be helpful to evaluate the existing growth strategies in Halifax Regional Municipality. In addition, it makes several contributions to the literature.</p> / Master of Arts (MA)

Yes / This paper demonstrates a non-Fourier prediction methodology of triple-layer human skin tissue for determining skin burn injury with non-ideal properties of tissue, metabolism and blood perfusion. The dual-phase lag (DPL) bioheat model is employed and solved using joint integral transform (JIT) through Laplace and Fourier transforms methods. Parametric studies on the effects of skin tissue properties, initial temperature, blood perfusion rate and heat transfer parameters for the thermal response and exposure time of the layers of the skin tissue are carried out. The study demonstrates that the initial tissue temperature, the thermal conductivity of the epidermis and dermis, relaxation time, thermalisation time and convective heat transfer coefficient are critical parameters to examine skin burn injury threshold. The study also shows that thermal conductivity and the blood perfusion rate exhibits negligible effects on the burn injury threshold. The objective of the present study is to support the accurate quantification and assessment of skin burn injury for reliable experimentation, design and optimisation of thermal therapy delivery.

In this dissertation, four distinct but in some ways related topics, mostly related to experimental and theoretical investigations of friction and adhesion of elastomeric materials, are presented. First, an experimental and theoretical study of the interaction between elastic beams and granular media under compressive loading is performed. Buckling loads of beams with different dimensions and boundary conditions within granular media of different depths and grain sizes are measured, and theoretically approximated using the Ritz energy approach, based on the concept of beam on an elastic foundation. Several nondimensional parameters and a scaling law are derived to characterize different interaction regimes between the beams and granular support. The findings from this work is believed to be helpful for improved understanding of interactions between elastic beams and surrounding elastic foundation with applications to piles, oil pipelines, and robotic needle insertion into soft tissues. Second, the role of axial compliance on the friction of extensible strips is investigated. Significant changes were observed in the static and kinetic friction of strips, when the effective axial compliance was changed. The underlying causes of the changes in the frictional response are explained and quantitatively predicted using an extended shear lag model. We believe that this study provides insights into the effect of axial compliance on the frictional response of materials, paving the way for design and optimization of systems where the static and kinetic friction forces play an important role. Third, the effect of normal force and rate on the kinetic friction of two different elastomers, namely acrylic and silicone-based elastomers is evaluated. A custom-built pendulum test setup was used to perform the friction test in dynamic conditions. Two substantially different responses with respect to the change in normal force were observed and the role of different contributions to the frictional response of viscoelastic materials, i.e. bulk hysteresis friction, adhesion friction, and cohesion friction, are discussed. Different scenarios such as modifying the surface by using graphite powder, reducing test velocity, and also performing drop tests to characterize the surface hysteresis of the elastomers, were considered to further explore the origin of frictional responses of the elastomers. This study could improve insights gained from Dynamic Mechanical Analysis (DMA) data when obtaining and interpreting the effect of normal force on kinetic COF of elastomers with potential applications to tires, shoes, etc. where friction plays an important role. Last, a generalized scaling law, based on the classical fracture mechanics approach, is developed to predict the bond strength of adhesive systems. The proposed scaling law, which depends on the rate of change of bond area with compliance, is in apparent discrepancy with the previously reported scaling relationship that depends on the ratio of area to compliance. This distinction can have a profound impact on the expected bond strength of systems, particularly when failure mechanism changes or the compliance of the load train is increased. Furthermore, the shear lag model is implemented to derive a closed-form relation for the system compliance and the conditions where the two models deviate from each other are discussed and demonstrated. The results obtained from this approach could lead to a better understanding of the relationship between the bond strength and the geometry and mechanical properties of adhesive systems, with applications to different types of adhesive joints such as bio-inspired adhesive, biomedical adhesive tapes, and structural adhesive joints. / Ph. D.

This paper analyzes if neighborhood income inequality has an effect on informal regulation of environmental quality, using census tract - level data on industrial air pollution exposure from EPA's Risk Screening Environmental Indicators and income and demographic variables from the American Community Survey and EPA's Smart Location Database. Estimating a spatial lag model and controlling for formal regulation at the states level, we nd evidence that overall neighborhood inequality - as measured by the ratio between the fourth and the second income quintile or the neighborhood Gini coefficient - increases local air pollution exposure, whereas a concentration of top incomes reduces local exposure. The positive coefficient of the general inequality measure is driven by urban neighborhoods, whereas the negative coefficient of top incomes is stronger in rural areas. We explain these findings by two contradicting effects of inequality: On the one hand, overall inequality reduces collective action and thus the organizing capacities for environmental improvements. On the other hand, a concentration of income at the top enhances the ability of rich residents to negotiate with regulators or polluting plants in their vicinity. / Series: Ecological Economic Papers

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This thesis employs the Autoregressive Distributed Lag model (ARDL), Toda-Yamamoto causality analysis, and ordinary least square (OLS for robust estimation) techniques to empirically investigate the impact of economic growth and energy consumption on the environment in Nigeria from 1980 to 2020. The results of cointegration demonstrate a long-term link between the model's input variables. The outcome of the first objective of the study shows that trade and economic development in Nigeria worsen the state of the environment. Environmental quality is accelerated by financial development; nevertheless, FDI is proven to be insignificant in predicting environmental quality. The result demonstrates that FDI and energy use both have the potential to significantly speed up the rate of environmental degradation. Nevertheless, trade has a negligible impact on the environment in the country, and financial development slows down environmental deterioration. The study also finds that the combination between energy and economic development improves Nigeria's environmental quality. The outcome of the fourth objective shows that economic expansion and energy consumption have a favorable impact on the environment. Additionally, environmental degradation, energy use, and economic growth are all causally related. Moreover, the outcome of the robust estimation reveals a positive and significant relationship between economic growth and energy consumption in the environment. Therefore, the study suggests economic policies with environmental control measures. This could be through an emphasis on the use of other alternatives of low-emission energy, that will mitigate the level of C02 and enhance energy utilization for a better environment in the nation.