APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Free Troposphere Ozone and Carbon Monoxide over the North Atlantic for 2001-2011

Carbon Monoxide (CO) and Ozone (O3) are considered to be one of the most important atmospheric pollutants in the troposphere with both having significant effects on human health. Both are included in the U.S. E.P.A list of criteria pollutants. CO is primarily emitted in the source region whereas O3 can be formed near the source, during transport of the pollution plumes containing O3 precursors or in a receptor region as the plumes subside. The long chemical lifetimes of both CO and O3 enable them to be transported over long distances. This transport is important on continental scales as well, commonly referred to as inter-continental transport and affects the concentrations of both CO and O3 in downwind receptor regions, thereby having significant implications for their air quality standards. Over the period 2001-2011, there have been decreases in the anthropogenic emissions of CO and NOx in North America and Europe whereas the emissions over Asia have increased. How these emission trends have affected concentrations at remote sites located downwind of these continents is an important question. The PICO-NARE observatory located on the Pico Mountain in Azores, Portugal is frequently impacted by North American pollution outflow (both anthropogenic and biomass burning) and is a unique site to investigate long range transport from North America. This study uses in-situ observations of CO and O3 for the period 2001-2011 at PICO-NARE coupled with output from the full chemistry (with normal and fixed anthropogenic emissions) and tagged CO simulations in GEOS-Chem, a global 3-D chemical transport model of atmospheric composition driven by meteorological input from the Goddard Earth Observing System (GEOS) of the NASA Global Modeling and Assimilation Office, to determine and interpret the trends in CO and O3 concentrations over the past decade. These trends would be useful in ascertaining the impacts emission reductions in the United States have had over Pico and in general over the North Atlantic. A regression model with sinusoidal functions and a linear trend term was fit to the in-situ observations and the GEOS-Chem output for CO and O3 at Pico respectively. The regression model yielded decreasing trends for CO and O3 with the observations (-0.314 ppbv/year & -0.208 ppbv/year respectively) and the full chemistry simulation with normal emissions (-0.343 ppbv/year & -0.526 ppbv/year respectively). Based on analysis of the results from the full chemistry simulation with fixed anthropogenic emissions and the tagged CO simulation it was concluded that the decreasing trends in CO were a consequence of the anthropogenic emission changes in regions such as USA and Asia. The emission reductions in USA are countered by Asian increases but the former have a greater impact resulting in decreasing trends for CO at PICO-NARE. For O3 however, it is the increase in water vapor content (which increases O3 destruction) along the pathways of transport from North America to PICO-NARE as well as around the site that has resulted in decreasing trends over this period. This decrease is offset by increase in O3 concentrations due to anthropogenic influence which could be due to increasing Asian emissions of O3 precursors as these emissions have decreased over the US. However, the anthropogenic influence does not change the final direction of the trend. It can thus be concluded that CO and O3 concentrations at PICO-NARE have decreased over 2001-2011.

An Investigation of Waste Glass-Based Geopolymers Supplemented with Alumina

An increased consideration of sustainability throughout society has resulted in a surge of research investigating sustainable alternatives to existing construction materials. A new binder system, called a geopolymer, is being investigated to supplement ordinary portland cement (OPC) concrete, which has come under scrutiny because of the CO2 emissions inherent in its production. Geopolymers are produced from the alkali activation of a powdered aluminosilicate source by an alkaline solution, which results in a dense three-dimensional matrix of tetrahedrally linked aluminosilicates. Geopolymers have shown great potential as a building construction material, offering similar mechanical and durability properties to OPC. Additionally, geopolymers have the added value of a considerably smaller carbon footprint than OPC. This research considered the compressive strength, microstructure and composition of geopolymers made from two types of waste glass with varying aluminum contents. Waste glass shows great potential for mainstream use in geopolymers due to its chemical and physical homogeneity as well as its high content of amorphous silica, which could eliminate the need for sodium silicate. However, the lack of aluminum is thought to negatively affect the mechanical performance and alkali stability of the geopolymer system. Mortars were designed using various combinations of glass and metakaolin or fly ash to supplement the aluminum in the system. Mortar made from the high-Al glass (12% Al2O3) reached over 10,000 psi at six months. Mortar made from the low-Al glass (<1% Al2O3) did not perform as well and remained sticky even after several weeks of curing, most likely due to the lack of Al which is believed to cause hardening in geopolymers. A moderate metakaolin replacement (25-38% by mass) was found to positively affect the compressive strength of mortars made with either type of glass. Though the microstructure of the mortar was quite indicative of mechanical performance, composition was also found to be important. The initial stoichiometry of the bulk mixture was maintained fairly closely, especially in mixtures made with fine glass. This research has shown that glass has great potential for use in geopolymers, when care is given to consider the compositional and physical properties of the glass in mixture design.