Landfill space consumption dynamics in the Lower Rio Grande Valley by grey integer programming-based games

The Lower Rio Grande Valley (LRGV) region in South Texas emerges as a warehouse and transportation center between Central America and the US with positive growth impacts due to the North American Free Trade Agreement (NAFTA). In 10 years time, a 39.8% population increase has resulted in a 25% boost in solid waste per capita disposal rate in the region. A landfill space shortage drives a need for landfill operators to understand their optimal management strategies in this highly-competitive market. Initially, a strategic plan for optimal solid waste pattern distribution minimizes net costs for cities. This is accomplished through a grey integer programming algorithm that encapsulates all uncertainty present in the solid waste system. Secondly, a series of grey integer submodels construct payoff matrices for a zero-sum two-person game. The ensuing game theoretic analysis is critical for evaluating optimal pricing strategies for tipping fees available to the most significant regional landfills (e.g. Browning-Ferris Industries (BFI) and City of Edinburg) as they compete over disposal contracts. The BFI landfill intrinsically benefits from its competitive pricing policy and central location to solid waste generators. The City of Edinburg landfill, on the other hand, wishes to secure its lucrative solid waste management revenue. It desires a gaming strategy backed by optimality that integrates ambiguity in solid waste generation, design capacity boundaries, and unitary shipping costs. Results show that a two-tiered analysis via grey integer programming-based games may pave the way for 'grey Nash equilibria' pricing tactics that will help the Edinburg landfill maintain its waste contracts.     

INEQUITIES FOR SMALL FOOD PROCESSING PLANTS RESULTING FROM LIQUID WASTE TREATMENT REGULATIONS1

ABSTRACT: The cost of the liquid wast treatment measures required to meet federal as well as typical state and local regulations was examined for dairy processing plants of various sizes. Federal effluent standards were found to produce higher estimated capital costs per unit of raw material for smaller plants, even with relaxed requirements for smaller plants. State regulations limiting the effluent BOD₅- concentration were also found to result in inequitable costs for smaller processors. These inequities result from economies of scale and not such factors as level of process technology employed or amount of waste produced per unit of raw material. In contrast, applying an example sewer surcharge formula did not produce inequities from economies of scale.     

From policy mix to policy networks: assessing climate and land use policy interactions in Mato Grosso,Brazil

ABSTRACT

In the climate and land use fields, policy mixes are complex in terms of the levels of governance, actors, and roles. They consist of policy instruments that target different actors and address multiple goals across several policy sectors and levels. The analysis of these complex arrangements extends beyond purely technical efficiency criteria, as several sources of tension between instruments may be identified, such as conflicting interests, goals, and approaches to implementation. The proliferation of governance networks complicates the understanding of actors’ interactions, the types of authority influencing the outcomes of policy mixes, and importance of different levels of governance. This article provides a framework to address these analytical challenges, particularly the interconnected networks of policy actors and policy instruments. It draws on polycentric governance literature to analyse how power matters in policy networks. This includes identifying distinct types of power, actors’ position, and variables that explain patterns of conflict, competition, convergence, and divergence in policy choices and outcomes. The framework is applied to the climate and land use policies implemented in the state of Mato Grosso, Brazil. Several methods were used to clarify these variables and to characterise policy mixes being implemented in the region, including social network analysis.     

Repeated geographic divergence in behavior: a case study employing phenotypic trajectory analyses

Environmental effects on behavior have long been a focus of behavioral ecologists. Among the important drivers of behavior is predation environment, which can include the presence/absence of predators, differences in resource availability, and variation in individual density. Environments with predators are often more ecologically complex and “risky” than those without predators. Populations from these environments are sometimes more active and explorative than populations from low-risk, less complex environments. To date, most comparative studies of behavior are limited to within-species comparisons of populations from divergent environments, but neglect comparisons between species following speciation, thus limiting our understanding of post-speciation behavioral evolution. Brachyrhaphis fishes provide an ideal system for studying correlations between divergent environments and behavior within and between species. Here, we test for differences in two behavioral traits—activity and exploration —between sister species Brachyrhaphis roseni and Brachyrhaphis terrabensis that occur in divergent predation environments. Species differed in activity and exploration, with higher activity and exploration levels in populations that co-occur with predators. Furthermore, we found drainage-by-species interactions, indicating that the nature of divergence varied geographically. Using the recently developed phenotypic trajectory analysis (PTA), we quantified this difference and found that, while the geographically isolated populations of sister species tended to evolve in parallel, the magnitude of divergence between species differed between drainages. Our results highlight the utility of PTA for multivariate behavioral data and corroborate past predictions that complex and risky environments are correlated with increased activity and exploration levels and that divergence continues post-speciation.     

Sensitivity analysis of Phast’s atmospheric dispersion model for three toxic materials (nitric oxide, ammonia, chlorine)

We present the results of a parametric sensitivity analysis of a widely used model for atmospheric dispersion of toxic gases, in order better to understand the influence of user-adjustable parameters on model outputs. We have studied 60 min continuous release scenarios for three different products (nitric oxide, ammonia and chlorine), chosen to cover a range of physical characteristics and storage conditions. For each product, we have broken down base-case scenarios into a number of sub-scenarios corresponding to different release conditions which determine physical phenomena (flow rate, release angle, release elevation and atmospheric stability class). The use of statistical tools to analyze the results of a large number of model executions allows us to rank model parameters according to their influence on the variability of a number of model outputs (distances and concentrations), on a per-scenario and per-product basis. Analysis of the results allows us to verify our understanding of the modeling of cloud dispersion.