Analysis of spring break-up and its effects on a biomass feedstock supply chain in northern Michigan

Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility.

Analysis of atmospheric transport and the effects of seasonal and interannual transport variability on measurements made at the Pico Mountain observatory

A non-hierarchical K-means algorithm is used to cluster 47 years (1960–2006) of 10-day HYSPLIT backward trajectories to the Pico Mountain (PM) observatory on a seasonal basis. The resulting cluster centers identify the major transport pathways and collectively comprise a long-term climatology of transport to the observatory. The transport climatology improves our ability to interpret the observations made there and our understanding of pollution source regions to the station and the central North Atlantic region. I determine which pathways dominate transport to the observatory and examine the impacts of these transport patterns on the O3, NOy, NOx, and CO measurements made there during 2001–2006. Transport from the U.S., Canada, and the Atlantic most frequently reaches the station, but Europe, east Africa, and the Pacific can also contribute significantly depending on the season. Transport from Canada was correlated with the North Atlantic Oscillation (NAO) in spring and winter, and transport from the Pacific was uncorrelated with the NAO. The highest CO and O3 are observed during spring. Summer is also characterized by high CO and O3 and the highest NOy and NOx of any season. Previous studies at the station attributed the summer time high CO and O3 to transport of boreal wildfire emissions (for 2002–2004), and boreal fires continued to affect the station during 2005 and 2006. The particle dispersion model FLEXPART was used to calculate anthropogenic and biomass-burning CO tracer values at the station in an attempt to identify the regions responsible for the high CO and O3 observations during spring and biomass-burning impacts in summer.

UNDERSTANDING FARMERS’ PERCEPTIONS AND THE EFFECTS OF SHEA TREE Vitellaria paradoxa DISTRIBUTION IN AGROFORESTRY PARKLANDS OF THE UPPER WEST REGION, GHANA

Agroforestry parklands represent a vast majority of the agricultural landscape under subsistent-oriented farming in semi-arid West Africa. Parklands are characterized by the growth of well- maintained trees (e.g., shea) on cultivated fields as a result of both environmental and human influences. Shea (Vitellaria paradoxa) provides a cultural and economic benefit to the local people of Ghana, especially women. Periods between traditional fallow rotation systems have reduced recently due to agricultural development and a demand for higher production. As a result, shea trees, which regenerate during fallow periods, has decreased over the landscape. The aim of this study was to determine beneficial spatial distributions of V. paradoxa to maintain high yields of staple crops, and how management of V. paradoxa will differ between male and female farmers as a result of farmer based needs and use of shea. Vegetation growth and grain yield of maize (Zea mays) associated with individual trees, clumped trees, and open fields were measured. Soil moisture and light availability were also measured to determine how V. paradoxa affected resource availability of maize in either clumped or scattered distributions of V. paradoxa. As expected, light availability increased as measurement locations moved farther away from all trees. However, soil moisture was actually greater under trees in clumps than under individual trees. Maize stalk height and cob length showed no difference between clumped and single trees at each measurement location. Grain yield per plot and per cob increased as measurement locations moved farther from single trees, but was actually greater near clumped trees that in the open field subplots. Cob length and maize stalk height increased with greater light availability, but grain yield per cob or per plot showed no relationship with light, but were not affected by soil moisture. Conversely, grain yield increased with increasing soil moisture, but had no relationship with light availability. Initial farming capital is the largest constraint to female farmers; therefore the collection of shea can help provide women with added income that could meet their specific farming needs. Our data indicate that overall effects of maintaining clumped distributions of V. paradoxa provided beneficial microclimates for staple crops when compared to single trees. It is recommended that male and female farmers allow shea to grow in clumped spatial distributions rather than maintaining scattered, individual trees.