Bayesian calibration of mechanistic aquatic biogeochemical models and benefits for environmental management

Aquatic biogeochemical models have been an indispensable tool for addressing pressing environmental issues, e.g., understanding oceanic response to climate change, elucidation of the interplay between plankton dynamics and atmospheric CO₂ levels, and examination of alternative management schemes for eutrophication control. Their ability to form the scientific basis for environmental management decisions can be undermined by the underlying structural and parametric uncertainty. In this study, we outline how we can attain realistic predictive links between management actions and ecosystem response through a probabilistic framework that accommodates rigorous uncertainty analysis of a variety of error sources, i.e., measurement error, parameter uncertainty, discrepancy between model and natural system. Because model uncertainty analysis essentially aims to quantify the joint probability distribution of model parameters and to make inference about this distribution, we believe that the iterative nature of Bayes' Theorem is a logical means to incorporate existing knowledge and update the joint distribution as new information becomes available. The statistical methodology begins with the characterization of parameter uncertainty in the form of probability distributions, then water quality data are used to update the distributions, and yield posterior parameter estimates along with predictive uncertainty bounds. Our illustration is based on a six state variable (nitrate, ammonium, dissolved organic nitrogen, phytoplankton, zooplankton, and bacteria) ecological model developed for gaining insight into the mechanisms that drive plankton dynamics in a coastal embayment; the Gulf of Gera, Island of Lesvos, Greece. The lack of analytical expressions for the posterior parameter distributions was overcome using Markov chain Monte Carlo simulations; a convenient way to obtain representative samples of parameter values. The Bayesian calibration resulted in realistic reproduction of the key temporal patterns of the system, offered insights into the degree of information the data contain about model inputs, and also allowed the quantification of the dependence structure among the parameter estimates. Finally, our study uses two synthetic datasets to examine the ability of the updated model to provide estimates of predictive uncertainty for water quality variables of environmental management interest.     

Improvement of air quality by means of transportation system management

Under the United States federal Clean Air Act Amendments of 1977, states must implement transportation system management (TSM) tactics in urban areas that have not attained national ambient air quality standards for carbon monoxide and photochemical oxidants. This paper provides a preliminary assessment of the effectiveness and feasibility of using TSM tactics to improve air quality. Based on this assessment, the authors conclude that TSM measures should be effective in eliminating localized carbon monoxide problems, but that such measures are not likely to contribute significantly toward reducing regional oxidant levels. In addition, because most individual TSM tactics can have only marginal impacts on regional motor vehicle emissions, coordinating the planning and implementation of a portfolio of TSM measures will be an essential element of an effective TSM program for improving air quality.     

A modification to Kruithof's double-factor method

A modification of Kruithof's double-factor algorithm (sometimes called the Furness iterative method) that takes into account zones which lie outside the boundary of a traffic network is examined analytically. Basically the revised algorithm allows certain rows and columns of the base traffic matrix to be only proportionally scaled while the remaining rows and columns which have pre-specified row and column totals are scaled in the usual biproportional way. This paper shows that all the properties (such as uniqueness, reversibility, existence) which hold for the traditional biproportional transformation also hold for the modified transformation under certain positivity assumptions.     

The Horsepower Reserve Formulation of Driveability for a Vehicle Fitted With a Continuously Variable Transmission

Summary A systematic methodology is developed for choosing the optimum ratio trajectory of a continuously variable transmission in a passenger vehicle. The optimum CVT ratio schedule is formulated as a constrained optimization problem with maximum fuel economy as the objective function and driveability concerns and physical limitations included as the constraints. The key notion to achieving good driveability is the introduction and definition of a horsepower reserve function that creates a consistent and desirable vehicle response under different driving conditions. Simulation results compare the optimized schedule's performance with several other possible ratio schedules, including the minimum brake specific fuel consumption map. Results from the optimized schedule indicate only a mild tradeoff between driveability and fuel economy relative to the other ratio schedules. The ratio optimization problem formulation and solution provide a novel and unique approach for systematically addressing driveability and fuel economy considerations associated with a continuously variable transmission.     

Comment: Tankers' modification economics: Is there an arbitrage?

In this paper we address the following question: how much is a ship-owner willing to pay in order to convert his single-hull vessel to a double-hull vessel? Our research is motivated by a recent article in Tradewinds, according to which owners have become reluctant in scrapping their vessels by turning them into double hull from single hull. We apply a structural no-arbitrage condition for deriving and estimating 'good-deal' bounds.     

An application of shock wave theory to traffic signal control

A real time control policy minimizing total intersection delays subject to queue length constraints at an isolated signalized intersection is developed in this paper. The policy is derived from a new traffic model which describes the simultaneous evolution of queue lengths of two conflicting traffic streams, controlled by a traffic light, in both time and space. The model is based on the examination of shock waves generated upstream of the stop lines by the intermittent service of traffic at the signal. The proposed policy was tested against the existing pre-timed control policy at a high volume intersection and it was found superior, especially when demands increase well above the saturation level.