Mitigation of High Alkalinity in Leachates of Aged Steel Slag

Steel slag, an abundant by-product of the steel-making industry, after it is aged, has a huge potential for use as an aggregate in road construction. However, the high pH of steel slag seepage (pH≥12) is a major impediment in its beneficial use. Analyses on aged steel slag samples demonstrated that the alkalinity producing capacity of aged steel slag samples strongly correlated to Ca(OH)2 dissolution and that prolonged aging periods have marginal effects on overall alkalinity. Treatment methods that included bitumen-coating, bathing in Al(III) solutions and addition of an alum-based drinking water treatment residual (WTR) were evaluated based on reduction in pH levels and leachate alkalinity. 10% (wt./wt.) alum-based drinking water treatment residual (WTR) addition to slag was determined to be the most successful mitigation method, providing 65−70% reduction in alkalinity both in batch-type and column leach tests, but final leachate pH was only 0.5−1 units lower and leachates were contaminated by dissolved Al(+III) (≥3−4 mM). Based on the interpretation of calculated saturation indices and SEM and EDX analyses, formation of calcium sulfoaluminate phases (i.e., ettringite and monosulfate) was suggested as the mechanism behind alkalinity mitigation upon WTR-modification. The residual alkalinity in WTR-amended slag leachates was able to be completely eliminated utilizing a biosolids compost with high base neutralization capacity. In column leach tests, effluent pH levels below 7 were maintained for 58−74 pore volumes worth of WTR-amended slag leachate using 0.13 kg compost (dry wt.) per 1 kg WTR-amended slag on average; also, dissolved Al(+III) was strongly retained on the compost.

The Indistinct Edge: Reconnecting Experience in Nature and Architecture

This thesis explores how architectures sense of place is rooted in the natural environment. The built environment has been constructed to protect and sustain human culture from the weathering of nature. Separating experience from the natural environment removes a sense of place and belonging in the natural and reinforces architectural dominance. This separation distinguishes the natural world as an article of spectacle and gives the human experience an unnatural voyeurship to natural changes. By examining the fusion of architectural and natural edges this thesis analyzes how the human experience can reconnect with a naturalistic sense of place through architecture, blending the finite edge where architecture maintains nature, and adapting buildings to the cycles of the environment. Removing dominance of man-made spaces and replacing them with the cohabitation of the edge between built and natural forms.

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.