Robert A. Goldstein

THE ILWAS MODEL: FORMULATION AND APPLICATION

The Integrated Lake-Watershed Acidification Study (ILWAS) model was developed to predict changes in surface water acidity given changes in the acidity of precipitation and dry deposition. The model routes precipitation through the forest canopy, soil horizons, streams and lakes using mass balance concepts and equations which relate flow to hydraulic gradients. The physical-chemical processes which change the acid-base characteristics of the water are simulated by rate (kinetic) and equilibrium expressions and include mass transfers between gas, liquid and solid phases. The aqueous constituents simulated include: pH, alkalinity, the major cations (Ca2+ Mg2+, K+, Na+, and NH4+) and anions (SOinf4sup2−, NOinf3sup−, Cl−, F−), monomeric Al and its inorganic and organic complexes, organic acid analogues and dissolved inorganic carbon (CT). Since free hydrogen ion (H+) (and hence pH) is not conserved, its concentration is derived from the solution alkalinity and the total concentrations of inorganic C, organic acid, and monomeric Al.The ILWAS model has been used to predict changes in the acidity of Woods Lake (typical lake pH 4.5 to 5.0) and Panther Lake (typical lake pH 6 to 7) given reductions in total atmospheric S loads. The two basins are located within 30 km of each other in the Adirondack Mountains and receive similar acidic deposition. The response to a halving in the total atmospheric S load was basin-specific: In Panther Lake, little pH change occurred even 12 yr after the load reduction; in Woods Lake, the change was considerably larger.Hypothesis testing with the model has shown that the routing of water through soils (shallow versus deep flow) largely determines the extent to which incident precipitation is neutralized. Analysis of the two lake basins using the model and field data showed the watersheds to be net suppliers of base to the through-flowing water, although internal watershed production of strong acidity did occur. This internal production of acidity was approximately two-thirds the amount of the atmospheric load.

Modeling the Global Carbon Cycle: Nitrogen fertilization of the terrestrial biosphere and the “missing” CO2 sink

The discrepancy between estimates of net terrestrial CO2 emissions derived from (1) inverse modeling of the ocean/atmosphere system and (2) modeling of land use change, better known as the “missing” CO2 sink, suggests that some changing environmental factor, such as CO2, anthropogenic N emissions, or climate, has fertilized terrestrial ecosystems. To address this question, we herein describe and apply GLOCO, a global carbon cycle model. GLOCOs ocean submodel combines a box diffusion model with representations of chemical equilibria and biological processes to simulate the distributions and cycling of inorganic and organic carbon, phosphate, and alkalinity. The terrestrial submodel divides the biosphere into seven natural biomes with dynamic carbon and nitrogen cycling in both vegetation and soils. Anthropogenic influences on the functioning of the carbon and nitrogen cycles, such as fossil fuel combustion, forestry, and agricultural development, are also incorporated in the model. Our analysis confirms previous suggestions that because temperate and boreal forests are N limited, CO2 fertilization of these forests is less than predicted by short-term CO2 response factors. Modeling of temperate/boreal forest fertilization by anthropogenic N deposition suggests that CO2 is initially sequestered at a C:N ratio of ∼100, rather than the steady state value for the ecosystem of ∼30. If N deposition is to account for the 40–70% of the fertilization of the terrestrial biosphere not explainable by CO2 fertilization and temperature increases, then we estimate that 26-30 Tg N yr−1 of anthropogenic deposition in the temperate and boreal zones would be required. Recent anthropogenic NOx and NH3 deposition fluxes at northern temperate latitudes have been estimated to be 20–28 Tg N yr−1. Thus fertilization by anthropogenic N emissions likely constitutes a significant portion of the missing CO2 sink.

INTEGRATED LAKE-WATERSHED ACIDIFICATION STUDY: SUMMARY

An integrated, interdisciplinary, intensive study of three forested watersheds in the Adirondack Park region of New York State was started in 1977 to quantify the relationship between the deposition of atmospheric acids and surface water acidity. A general mechanistic theory of lake-watershed acidification that takes into account the production and consumption of acidity by watershed processes, as well as atmospheric inputs of acidity, was developed. This theory is formulated as a mathematical simulation model.

The development and application of a simplified ozone modeling system (SOMS)

Abstract This paper describes the development and evaluation of a computationally efficient semi-empirical photochemical model that can be used as a screening tool to obtain quick estimates of the effect of a large number of VOC and NO x emission control strategies on ozone concentrations. Selected control strategies can subsequently be examined with a more complex model. The model is one component of an ozone management system, the regional ozone decision model (RODM), designed to examine the costs and environmental consequences of alternate ozone abatement strategies. The model was developed by systematic simplification of a detailed photochemical model. At each step of the simplification, the simplified model was tested against observations and against results from the detailed model. The first major simplification was the introduction of a highly parameterized chemistry mechanism, originally developed by Azzi et al. (1992 Proc. 11th Int. Clean Air Conf., 4th Regional IUAPPA Conf. ). This modification resulted in a factor of 5 improvement in the computational efficiency of the model. The model with the simplified chemistry was then tested by applying it to a photochemical oxidant episode in the San Joaquin Valley of California. Further improvements in computational speed and efficiency were obtained by uncoupling the chemistry from the transport of VOC and NO x .

Inferring ecological risk from toxicity bioassays

Results from toxicological bioassays can express the likely impact of environmental contamination on biochemical function, histopathology, development, reproduction and survivorship. However, justifying environmental regulatory decisions and management plans requires predictions of the consequent effects on ecological populations and communities. Although extrapolating the results of toxicity bioassays to potential effects on the ecosystem may be beyond the current scientific capacity of ecology, it is possible to make detailed forecasts at the level of a population. We give examples in which toxicological impacts are either magnified or diminished by population-dynamic phenomena and argue that ecological risk assessments should be conducted at a level no lower than the population. Although methods recently proposed by EPA acknowledge that ecological risk evaluations should reflect population-level effects, they adopt approaches from human health risk analysis that focus on individuals.

Big Moose Basin: simulation of response to acidic deposition

The ILWAS model has been enhanced for application to multiple-lake hydrologic basins. This version of the model has been applied to the Big Moose basin, which includes Big Moose Lake and its tributary streams, lakes, and watersheds. The basin, as defined, includes an area of 96 km2, with over 20 lakes and ponds, and 70 km of streams. Hydrologic and chemical calibrations have been made using data from seven sampling stations. When total atmospheric sulfur loading to the basin is halved, the model predicts, after four years of simulation, a decreasing sulfate concentration and to a lesser extent a rising alkalinity at Big Moose Lake outlet. At the end of four years, the results show an increase in pH of 0.1 to 0.5 pH units depending upon season.

Lake-watershed acidification in the North Branch of the Moose River: introduction

AbstractAn integrated analysis of a terrestrial-aquatic ecosystem, the North Branch of the Moose River in the Adirondack region of New York, was conducted. This basin contains a large number of interconnected surface waters that exhibit marked gradients in pH and acid neutralizing capacity (ANC). As a result, the basin has been the focus of research activity, including the Regional Integrated Lake-Watershed Acidification Study (RILWAS). The objective of the current analysis was to use the North Branch of the Moose River as a case study to: 1.Evaluate processes regulating the acid-base chemistry of surface waters.2.To assess the effects of surface water acidification on fish populations. The observations of this study were consistent with the model of surface water acidification developed during the Integrated Lake-Watershed Acidification Study (ILWAS). The processes depicted in the original ILWAS simulation model were adequate to describe the acid-base chemistry of surface waters in the North Branch of the Moose River. However, the reduction of SO42− in lake sediments, a process not represented in the original model, proved to be a significant source of acid neutralizing capacity (ANC) for some of these waters. As a result, reduction processes were added to the model.Analysis of in-situ bioassay and survey data indicate that acid-sensitive fish species have disappeared from the more acidic areas of the basin over the last half century. Paleoecological analyses indicate that pH has decreased from the high 5s to about 5 in Big Moose Lake during this period. ILWAS model simulations indicate that the pH of Big Moose Lake would increase by at least 0.1 to 0.5 pH units (depending on the season) in response to a 50% reduction in total atmospheric S deposition.Considerable variability in processes regulating acid/base chemistry was evident in the North Branch of the Moose River. Therefore, regional assessments of past or possible future effects of acidic deposition require widespread application of ILWAS theory within the Adirondack region and other potentially acid-sensitive areas.

The Development of a Model to Examine Source-Receptor Relationships for Visibility on the Colorado Plateau

This paper describes the development and application of the Visibility and Haze in the Western Atmosphere (VISHWA) model to understand the source-receptor relationships that govern chemical species relevant to visibility degradation in the western United States. The model was developed as part of a project referred to as Visibility Assessment for Regional Emission Distributions (VARED), the objective of which is to estimate the contributions of various geographical regions, compounds, and emission sources to light scattering and absorption by particles on the Colorado Plateau. The VISHWA model is a modified version of a comprehensive Eulerian model, known as the Acid Deposition and Oxidant Model.1 The modifications were designed to obtain the computational efficiency required to simulate a one-year period at about 1/25th of real time, and at the same time incorporate mechanistic features relevant to realistic modeling of the fate and transport of visibility degrading species. The modifications included use of a condensed chemical mechanism; incorporation of reactions to simulate the formation of secondary organic particles; and use of a semi-Lagrangian advection scheme to preserve concentration peaks during advection. The model was evaluated with 1992 air quality data from Project MOHAVE (Measurements of Haze and Visual Effects) intensive experiments. An important conclusion of this evaluation is that aqueous-phase oxidation of SO2 to sulfate in nonprecipitating clouds makes a significant contribution to observed sulfate levels during winter as well as summer. Model estimates of ambient sulfate for the winter intensive were within a factor of 2 of the observations for 75% of the values. The corresponding statistic for the summer intensive was 90%. Model estimates of carbon were within a factor of 2 of the limited set of observations.

The PIRLA project (Paleoecological Investigation of Recent Lake Acidification): an introduction to the synthesis of the project

Collected sets of papers synthesizing data derived from the PIRLA project (Paleoecological Investigation of Recent Lake Acidification) will appear in coming issues of the Journal of Paleolimnology. This paper is designed to highlight these forthcoming papers, review the development and objectives of PIRLA, and acknowledge the many who have supported PIRLA in so many crucial ways.

Examination of model uncertainty and parameter interaction in a global carbon cycling model (GLOCO)

Abstract Simulation models play an important role in understanding the causes and consequences of climate change. In order to make full use of these models, it is necessary to establish the magnitude and sources of uncertainty associated with their predictions. This information can be used to achieve a better understanding of the simulated systems, to increase the reliability of model predictions, to guide field surveys and laboratory experiments, and to define realistic values that should be used in scientific, economic, and political discussions of future conditions. In this paper, a new tree-structured density estimation technique that extends the ability of Monte Carlo-based analyses to explore parameter interactions and uncertainty in complex environmental models was applied. The application of the technique is demonstrated using the GLOCO global carbon cycle model. The paper demonstrates that there are numerous distinct parameter combinations that can meet fairly stringent calibration criteria, and they are concentrated in relatively small subsets of the parameter space. These different subsets can be viewed as representing different ecological systems that achieve the same calibration or performance goals in fundamentally different ways. It is also shown that the simulated responses of these systems to future environmental change can lead to different conclusions regarding the interaction between factors affecting environmental processes, such as the growth of vegetation. Together, these results show how the tree-structured density estimation technique can be applied to gain a broader understanding of model performance and of ecosystem responses to change.