Cooperative and market-based solutions to pollution abatement problems

This work concerns itself with the possibility of solutions, both cooperative and market based, to pollution abatement problems. In particular, we are interested in pollutant emissions in Southern California and possible solutions to the abatement problems enumerated in the 1990 Clean Air Act. A tradable pollution permit program has been implemented to reduce emissions, creating property rights associated with various pollutants.

Before we discuss the performance of market-based solutions to LA's pollution woes, we consider the existence of cooperative solutions. In Chapter 2, we examine pollutant emissions as a trans boundary public bad. We show that for a class of environments in which pollution moves in a bi-directional, acyclic manner, there exists a sustainable coalition structure and associated levels of emissions. We do so via a new core concept, one more appropriate to modeling cooperative emissions agreements (and potential defection from them) than the standard definitions.

However, this leaves the question of implementing pollution abatement programs unanswered. While the existence of a cost-effective permit market equilibrium has long been understood, the implementation of such programs has been difficult. The design of Los Angeles' REgional CLean Air Incentives Market (RECLAIM) alleviated some of the implementation problems, and in part exacerbated them. For example, it created two overlapping cycles of permits and two zones of permits for different geographic regions. While these design features create a market that allows some measure of regulatory control, they establish a very difficult trading environment with the potential for inefficiency arising from the transactions costs enumerated above and the illiquidity induced by the myriad assets and relatively few participants in this market.

It was with these concerns in mind that the ACE market (Automated Credit Exchange) was designed. The ACE market utilizes an iterated combined-value call market (CV Market). Before discussing the performance of the RECLAIM program in general and the ACE mechanism in particular, we test experimentally whether a portfolio trading mechanism can overcome market illiquidity. Chapter 3 experimentally demonstrates the ability of a portfolio trading mechanism to overcome portfolio rebalancing problems, thereby inducing sufficient liquidity for markets to fully equilibrate.

With experimental evidence in hand, we consider the CV Market's performance in the real world. We find that as the allocation of permits reduces to the level of historical emissions, prices are increasing. As of April of this year, prices are roughly equal to the cost of the Best Available Control Technology (BACT). This took longer than expected, due both to tendencies to mis-report emissions under the old regime, and abatement technology advances encouraged by the program. Vve also find that the ACE market provides liquidity where needed to encourage long-term planning on behalf of polluting facilities.

Formal methods for control synthesis in partially observed environments : application to autonomous robotic manipulation

Modern robots are increasingly expected to function in uncertain and dynamically challenging environments, often in proximity with humans. In addition, wide scale adoption of robots requires on-the-fly adaptability of software for diverse application. These requirements strongly suggest the need to adopt formal representations of high level goals and safety specifications, especially as temporal logic formulas. This approach allows for the use of formal verification techniques for controller synthesis that can give guarantees for safety and performance. Robots operating in unstructured environments also face limited sensing capability. Correctly inferring a robot's progress toward high level goal can be challenging.

This thesis develops new algorithms for synthesizing discrete controllers in partially known environments under specifications represented as linear temporal logic (LTL) formulas. It is inspired by recent developments in finite abstraction techniques for hybrid systems and motion planning problems. The robot and its environment is assumed to have a finite abstraction as a Partially Observable Markov Decision Process (POMDP), which is a powerful model class capable of representing a wide variety of problems. However, synthesizing controllers that satisfy LTL goals over POMDPs is a challenging problem which has received only limited attention.

This thesis proposes tractable, approximate algorithms for the control synthesis problem using Finite State Controllers (FSCs). The use of FSCs to control finite POMDPs allows for the closed system to be analyzed as finite global Markov chain. The thesis explicitly shows how transient and steady state behavior of the global Markov chains can be related to two different criteria with respect to satisfaction of LTL formulas. First, the maximization of the probability of LTL satisfaction is related to an optimization problem over a parametrization of the FSC. Analytic computation of gradients are derived which allows the use of first order optimization techniques.

The second criterion encourages rapid and frequent visits to a restricted set of states over infinite executions. It is formulated as a constrained optimization problem with a discounted long term reward objective by the novel utilization of a fundamental equation for Markov chains - the Poisson equation. A new constrained policy iteration technique is proposed to solve the resulting dynamic program, which also provides a way to escape local maxima.

The algorithms proposed in the thesis are applied to the task planning and execution challenges faced during the DARPA Autonomous Robotic Manipulation - Software challenge.

From lakes to lungs : assessing microbial activity in diverse environments

All major geochemical cycles on the Earth’s surface are mediated by microorganisms. Our understanding of how these microbes have interacted with their environments (and vice versa) throughout Earth's history, and how they will respond to changes in the future, is primarily based on studying their activity in different environments today. The overarching questions that motivate the research presented in the two parts of this thesis -- how do microorganisms shape their environment (and vice versa)? and how can we best study microbial activity in situ? -- have arisen from the ultimate goal of being able to predict microbial activity in response to changes within their environments both past and future.

Part one focuses on work related to microbial processes in iron-rich Lake Matano and, more broadly, microbial interactions with the biogeochemical cycling of iron. Primarily, we find that the chelation of ferrous iron by organic ligands can affect the role of iron in anoxic environmental systems, enabling photomixotrophic growth of anoxygenic microorganisms with ferrous iron, as well as catalyzing the oxidation of ferrous iron by denitrification intermediates. These results imply that the ability to grow photomixotrophically on ferrous iron might be more widespread than previously assumed, and that the co-occurrence of chemical and biological processes involved in the coupled biogeochemical cycling of iron and nitrogen likely dominate organic-rich environmental systems.

Part two switches focus to in situ measurements of growth activity and comprises work related to microbial processes in the Cystic Fibrosis lung, and more broadly, the physiology of slow growth. We introduce stable isotope labeling of microbial membrane fatty acids and whole cells with heavy water as a new technique to measure microbial activity in a wide range of environments, demonstrate its application in continuous culture in the laboratory at the population and single cell level, and apply the tool to measure the in situ activity of the opportunistic pathogen Staphylococcus aureus within the environment of expectorated mucus from cystic fibrosis patients. We find that the average in situ growth rates of S. aureus fall into a range of generation times between ~12 hours and ~4 days, with substantial heterogeneity at the single-cell level. These data illustrate the use of heavy water as a universal environmental tracer for microbial activity, and highlight the crucial importance of studying the physiology of slow growth in representative laboratory systems in order to understand the role of these microorganisms in their native environments.