Optimal Pollution Trading Without Pollution Reductions: A Note1

García, Jorge H., Matthew T. Heberling, and Hale W. Thurston, 2011. Optimal Pollution Trading Without Pollution Reductions: A Note. Journal of the American Water Resources Association (JAWRA) 47(1):52‐58. DOI: 10.1111/j.1752‐1688.2010.00476.x Abstract: Various kinds of water pollution occur in pulses (e.g., agricultural and urban runoff). Ecosystems, such as wetlands, can serve to regulate these pulses and smooth pollution distributions over time. This smoothing reduces total environmental damages when “instantaneous” damages are marginally increasing. This paper introduces a water quality trading model between a farm (a pulse‐pollution source) and a firm (a more steady pollution source) where the object of exchange is the “temporary” retention of runoff as opposed to total runoff reductions. The optimal trading ratio requires firm emissions to be offset by more than a proportional retention of the initial agricultural runoff pulse. The reason is twofold: (1) emissions are steady or constant over time and, in this sense, have relatively larger environmental impact; and (2) certain kinds of runoff management cause delayed environmental damages.     

Using stochastic volatility models to analyse weekly ozone averages in Mexico City

In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.     

Predator–prey models: an application for the plankton dynamics of lake Geneva

In this paper we present a hierarchical Bayesian analysis for a predator–prey model applied to ecology considering the use of Markov Chain Monte Carlo methods. We consider the introduction of a random effect in the model and the presence of a covariate vector. An application to ecology is considered using a data set related to the plankton dynamics of lake Geneva for the year 1990. We also discuss some aspects of discrimination of the proposed models.     

Polyhydroxyalkanoates: Biosynthesis from Alternative Carbon Sources and Analytic Methods: A Short Review

Journal of Polymers and the Environment - In recent decades, the global accumulation of plastics and the resulting pollution, as well as the increase in the price of oil, have driven studies aimed...     

Hydrothermal carbonization of biomass and waste: A review

Environmental Chemistry Letters - The replacement of traditional and non-renewable resources by shifting towards renewable-based strategies is a strategy implemented by the European Union...     

Phycobiliproteins extract from Spirulina protects against single-dose cadmium-induced reproductive toxicity in male mice

Environmental Science and Pollution Research - Cadmium (Cd) is known for its many toxic effects on male population such as hypogonadism and fertility difficulties, which are oftenly associated with...     

Correction to: Socioeconomic Risks of Extreme El Niño Event-Related Road Damages in Peru

Environmental Modeling & Assessment -     

Database-driven models of the world's Large Marine Ecosystems

We present a new methodology for database-driven ecosystem model generation and apply the methodology to the world's 66 currently defined Large Marine Ecosystems. The method relies on a large number of spatial and temporal databases, including FishBase, SeaLifeBase, as well as several other databases developed notably as part of the Sea Around Us project. The models are formulated using the freely available Ecopath with Ecosim (EwE) modeling approach and software. We tune the models by fitting to available time series data, but recognize that the models represent only a first-generation of database-driven ecosystem models. We use the models to obtain a first estimate of fish biomass in the world's LMEs. The biggest hurdles at present to further model development and validation are insufficient time series trend information, and data on spatial fishing effort.     

SIMULATING FLOW IN REGIONAL WETLANDS WITH THE MODFLOW WETLANDS PACKAGE1

ABSTRACT: As part of the Comprehensive Everglades Restoration Plan (CERP), various water supply projects have been proposed in a region located between the Miami metropolitan area and the extensive regional wetland systems that are part of the Everglades or remnant Everglades. A ground water flow model of the surficial aquifer within northern Miami‐Dade County was constructed using MODFLOW to evaluate the effects of these projects on water levels in the wetlands and the underlying surficial aquifer. The new Wetlands package was used to conjunctively simulate overland flow through these wetlands and the shallow ground water system. Comparisons of simulated to measured ground water levels and wetland stages were very satisfactory, where computed and measured water levels agreed within 0.5 ft over most of the period of record at nearly all of the monitoring sites. Temporal trends in water levels were also replicated. It was concluded that the assumptions and methodologies inherent to the Wetlands package were suitable for simulating regional wetland hydrology within the Everglades area.     

Sexual and natural selection in a continuous time model

We call sexual selection the selection attributable only to the mating system, to distinguish it from other forms of selection (i.e. viability or fertility) which we call natural selection. We introduce a new continuous time model of sexual selection and we explore its relationship with natural selection. This model is an extension of the model proposed by Hoppensteadt [Hoppensteadt, F., 1977. Mathematical Theories of Populations: Demographics, Genetics and Epidemics. SIAM] and considers the three genotypes determined by two alleles in a locus, each with its own mortality and fertility rates, and the respective mating preferences.