Eutrophication Prediction Using a Markov Chain Model: Application to Lakes in the Yangtze River Basin,China

Lake eutrophication is harmful and difficult to predict due to its complex evolution. As an alternative to existing mechanistic models, a Markov chain model was developed to predict the development of lake eutrophication based on an 11-year dataset in 41 lakes of the Yangtze River Basin. This model was validated using a real-time update strategy and was demonstrated to be reliable. Based on the dataset, the lake eutrophication dynamics from 2000 to 2010 were analyzed. Lakes with different trophic states from 2011 to 2050 and their responses to different water management practices were simulated based on the developed model. The simulation results show that lake eutrophication would worsen from 2011 to 2040; however, eutrophication could be significantly alleviated by changing 100 km² of hypereutrophic lakes into eutrophic lakes per year from 2010 to 2020. The nutrient conditions in most of the lakes in the Yangtze River Basin show that phosphorus control would be more efficient than nitrogen control in eutrophication management practices. This case study demonstrates the utility of Markov chain models in using prior information to predict the long-term evolution of lake eutrophication at large spatial scales. The Markov chain technique can be easily adapted to predict evolutionary processes in other disciplines.     

Adaptation to Climatic Variability and Change: Asian Perspectives on Agriculture and Food Security

The impacts of climate change on potential rice production in Asia are reviewed in the light of the adaptation to climatic variability and change. Collaborative studies carried out by IRRI and US-EPA reported that using process-based crop simulation models increasing temperature may decrease rice potential yield up to 7.4% per degree increment of temperature. When climate scenarios predicted by GCMs were applied it was demonstrated that rice production in Asia may decline by 3.8% under the climates of the next century. Moreover, changes in rainfall pattern and distribution were also found suggesting the possible shift of agricultural lands in the region. The studies however have not taken the impacts of climatic variability into account, which often produce extreme events like that caused by monsoons and El Niño. Shifts in rice-growing areas are likely to be constrained by land-use changes occurring for other developmental reasons, which may force greater cultivation of marginal lands and further deforestation. This should be taken into account and lead to more integrated assessment, especially in developing countries where land-use change is more a top-down policy rather than farmers' decision. A key question is: To what extent will improving the ability of societies to cope with current climatic variability through changing design of agricultural systems and practices help the same societies cope with the likely changes in climate?     

Aerosol Scavenging: Model Application and Sensitivity Analysis in the Indian Context

Sulfate aerosols have been found to bethe major contributors to precipitation acidity. Thus,in view of the long-term ecological repercussions theyhave on aquatic ecosystems and their acidity-potential,the present analysis focuses on a case study applicationof the layer-averaged aerosol-scavenging model (Okita et al., 1996) for predicting values of the wet scavengingcoefficient and sulfate concentrations in precipitationsamples on the basis of the information available forsome selected Indian cities. Through sensitivityanalysis (Pandey et al., 1997) the scavengingcoefficient has been found to be very strongly dependenton precipitation intensity. Comparison of modelpredictions has been done with the measured values forDelhi, Mumbai, Calcutta and Chennai in India.     

Soil Organic Carbon (SOC) Equilibrium and Model Initialisation Methods: an Application to the Rothamsted Carbon (RothC) Model

Carbon (C) emissions from anthropogenic land use have accelerated climate change. To reduce C emissions, dynamic models can be used to assess the impact of human drivers on terrestrial C sequestration. Model accuracy requires correct initialisation, since incorrect initialisation can influence the results obtained. Therefore, we sought to improve the initialisation of a process-based SOC model, RothC, which can estimate the effect of climate and land-use change on SOC. The most common initialisation involves running the model until equilibrium (‘spin-up run’), when the SOC pools stabilise (method 1). However, this method does not always produce realistic results. At our experimental sites, the observed SOC was not at equilibrium after 10 years, suggesting that the commonly used spin-up initialisation method assuming equilibrium might be improved. In addition to method 1, we tested two alternative initialisations for RothC that involved adjusting the total or individual SOC pool equilibrium values by regulating the C input during the entire spin-up initialisation period (method 2) and initialising each SOC pool with recently measured SOC values obtained by SOC fractionation (method 3). Analysis of the simulation accuracy for each model initialisation, quantified using the root mean square error (RMSE), indicated that a variant of method 2 that involved adjusting the equilibrium total SOC to observed values (method 2-T) generally showed less variation in the individual SOC pools and total SOC. Furthermore, as total SOC is the sum of all SOC pools, and because total SOC data are more readily available than the individual SOC pool data, we conclude that method 2-T is best for initialising RothC.     

Exploring the Nexus Between Oil Availability and Economic Growth: Insights from Non-Linear Model

Environmental Modeling & Assessment - The reemergence of the resource curse issue as a stylized fact in the economies during the past two decades is due to the negative link between the growth...     

Monitoring Ecosystems in the Sierra Nevada: The Conceptual Model Foundation

Monitoring at large geographic scales requires a framework for understanding relationships between components and processes of an ecosystem and the human activities that affect them. We created a conceptual model that is centered on ecosystem processes, considers humans as part of ecosystems, and serves as a framework for selecting attributes for monitoring ecosystems in the Sierra Nevada. The model has three levels: 1) an ecosystem model that identifies five spheres (Atmosphere, Biosphere, Hydrosphere, Lithosphere, Sociocultural), 2) sphere models that identify key ecosystem processes (e.g., photosynthesis), and 3) key process models that identify the "essential elements"that are required for the process to operate (e.g., solar radiation), the human activities ("affectors") that have negative and positive effects on the elements (e.g., air pollution), and the "consequences"of affectors acting on essential elements (e.g., change in primary productivity). We discuss use of the model to select attributes that best reflect the operation and integrity of the ecosystem processes. Model details can be viewed on the web at http://www.r5.fs.fed.us/sncf/spam_report/index.htm(Appendix section).     

Participation of the Czech Agricultural and Food Inspection in the program monitoring of contaminants in the food chain

Regional branches of the Czech Agricultural and Food Inspection participated in the data collection of contaminant agents in processed food and plant raw materials. The project was managed within the framework of the Governmental programme for environmental care in the Czech Republic. The data have been collected since 1984. PC data computering started in 1992 and was used to determine places of occurrence in map form.     

Assessing the wildlife habitat value of New England salt marshes: I. Model and application

We developed an assessment model to quantify the wildlife habitat value of New England salt marshes based on marsh characteristics and the presence of habitat types that influence habitat use by terrestrial wildlife. Applying the model to 12 salt marshes located in Narragansett Bay, RI resulted in assessment scores that ranged over a factor of 1.5 from lowest to highest. Pre-classifying the results based on marsh size and morphology helped to compare assessment scores between marshes, and demonstrated that even the lower ranking marshes had substantial habitat value. Stepwise multiple regression analysis of assessment scores and model components demonstrated that salt marsh morphology, the degree of anthropogenic modification, and salt marsh vegetative heterogeneity were significant variables and accounted for 91.3% of the variability in component scores. Our results suggest that targeting these components for restoration may lead to improved assessment scores for our study marshes. We also examined the use of lower resolution remote sensing data in the assessment in order to minimize the time and effort required to complete the model. Scores obtained using smaller-scale, lower resolution data were significantly lower than those obtained using larger-scale, higher resolution data (df = 11; t = 2.2; p < 0.001). The difference was significantly positively correlated with the portion of the assessment score that could be attributed to trees, pools, and pannes and marsh size (r (2) =0.50, F = 4.6, p = 0.04), and could indicate a bias against smaller, more heterogeneous marshes. We conclude that potential differences need to be weighed against the time benefit of using this type of data, bearing in mind the marsh size and the goals of the assessment. Overall, our assessment can provide information to aid in prioritizing marshes for protection and restoration, identify marshes that may harbor significant biodiversity, or help monitor changes in habitat value over time.     

Integrity of Tailings Infrastructure and Information Management: A GIS-Based Conceptual Model

Managing the integrity of tailings infrastructure is an important aspect of handling mine tailings. Unfortunately, little research is directed towards its efficient modeling. This paper presents salient aspects of tailings management. It proposes an integrated geographic information systems (GIS)-based conceptual model for efficient handling of these aspects. The paper also discusses the various integrated modules and comments on the systematic implementation of the model to achieve desired results. The modules include: structural integrity management (SIM), release impact assessment (RIA), and hazardous risk assessment and control (HRAC).     

Assessing the wildlife habitat value of New England salt marshes: II. Model testing and validation

We tested a previously described model to assess the wildlife habitat value of New England salt marshes by comparing modeled habitat values and scores with bird abundance and species richness at sixteen salt marshes in Narragansett Bay, Rhode Island USA. As a group, wildlife habitat value assessment scores for the marshes ranged from 307-509, or 31-67% of the maximum attainable score. We recorded 6 species of wading birds (Ardeidae; herons, egrets, and bitterns) at the sites during biweekly survey. Species richness (r (2)=0.24, F=4.53, p=0.05) and abundance (r (2)=0.26, F=5.00, p=0.04) of wading birds significantly increased with increasing assessment score. We optimized our assessment model for wading birds by using Akaike information criteria (AIC) to compare a series of models comprised of specific components and categories of our model that best reflect their habitat use. The model incorporating pre-classification, wading bird habitat categories, and natural land surrounding the sites was substantially supported by AIC analysis as the best model. The abundance of wading birds significantly increased with increasing assessment scores generated with the optimized model (r (2)=0.48, F=12.5, p=0.003), demonstrating that optimizing models can be helpful in improving the accuracy of the assessment for a given species or species assemblage. In addition to validating the assessment model, our results show that in spite of their urban setting our study marshes provide substantial wildlife habitat value. This suggests that even small wetlands in highly urbanized coastal settings can provide important wildlife habitat value if key habitat attributes (e.g., natural buffers, habitat heterogeneity) are present.     

Integrated Traffic and Emission Simulation: a Model Calibration Approach Using Aggregate Information

Environmental impacts of road traffic have attracted increasing attention in project-level traffic planning and management. The conventional approach considers emission impact analysis as a separate process in addition to traffic modeling. This paper first introduces our research effort to integrate traffic, emission, and dispersion processes into a common distributed computational framework, which makes it efficient to quantify and analyze correlations among dynamic traffic conditions, emission impacts, and air quality consequences. A model calibration approach is particularly proposed when on-road or in-lab instantaneous emission measurements are not directly available. Microscopic traffic simulation is applied to generate dynamic vehicle states at the second-by-second level. Using aggregate emission estimation as standard reference, a numerical optimization scheme on the basis of a stochastic gradient approximation algorithm is applied to find optimal parameters for the dynamic emission model. The calibrated model has been validated on several road networks with traffic states generated by the same simulation model. The results show that with proper formulation of the optimization objective function, the estimated dynamic emission model can capture the trends of aggregate emission patterns of traffic fleets and predict local emission and air quality at higher temporal and spatial resolutions.     

Marginal Abatement Costs and Marginal Welfare Costs for Greenhouse Gas Emissions Reductions: Results from the EPPA Model

Marginal abatement cost (MAC) curves, relationships between tonnes of emissions abated and the CO₂ (or greenhouse gas (GHG)) price, have been widely used as pedagogic devices to illustrate simple economic concepts such as the benefits of emissions trading. They have also been used to produce reduced-form models to examine situations where solving the more complex model underlying the MAC is difficult. Some important issues arise in such applications: (1) Are MAC relationships independent of what happens in other regions?, (2) are MACs stable through time regardless of what policies have been implemented in the past?, and (3) can one approximate welfare costs from MACs? This paper explores the basic characteristics of MAC and marginal welfare cost (MWC) curves, deriving them using the MIT Emissions Prediction and Policy Analysis model. We find that, depending on the method used to construct them, MACs are affected by policies abroad. They are also dependent on policies in place in the past and depend on whether they are CO₂-only or include all GHGs. Further, we find that MACs are, in general, not closely related to MWCs and therefore should not be used to derive estimates of welfare change. We also show that, as commonly constructed, MACs may be unreliable in replicating results of the parent model when used to simulate GHG policies. This is especially true if the policy simulations differ from the conditions under which the MACs were simulated.     

Holling's Figure-Eight Model: A Technical Reevaluation in Relation to Climate Change and Biodiversity

Holling proposed a four-phase conceptual model of ecosystem dynamics that includes exploitation, conservation, and destructive and renewal components to explain the failure of many natural resource management schemes. The model is drawn as a sideways figure-eight i.e. . There are two dimensions in this model, connectivity (abscissa) and the amount of capital stored in the system (ordinate). This conceptual model has been suggested as a guide to thinking about the impact of climate change on biodiversity, but the two dimensions are insufficient and the alignment of the figure-eight model is problematic when compared with actual data. Kay has adjusted the dimensions of the figure-eight model and renamed the abscissa as exergy stored and the ordinate as exergy consumed. We realign the original figure-eight model, labeling the abscissa as carbon stored and the ordinate as nutrients, such that the relative values of both axes are in qualitative agreement with data from four different studies. This new alignment is then shown to fit relatively well with Holling's original labels. This revision of the figure-eight model brings Holling's model into agreement with observations and provides insight into the linkages between biodiversity and climate change.     

Development of Noise Simulation Model for Stationary and Mobile Sources: A GIS-Based Approach

In the rapidly urbanizing country like India, the transportation sector is growing rapidly, which lead to overcrowded roads producing air and noise pollution. Noise of a particular region is influenced by the volume of traffic on the highway, in addition to other causative factors like existing infrastructure and industrial setup etc. In the present paper, a geographical information system (GIS)-based noise simulation model has been developed to generate noise levels in Versova region of Mumbai, India. The study area comprises effect of infrastructure, road network, traffic volume, and various mechanical components like sewage pumping station and wastewater treatment facility. Various meteorological parameters and effect of land use and land cover on noise attenuation are also considered in the model. In this way, commutative noise prediction for point as well as mobile sources has been presented in the study. GIS-based noise simulation has been calibrated with observed noise levels during day and night time with correlation of 0.84 and 0.74, respectively.     

Atrazine Transport Within a Coastal Zone in Southeastern Puerto Rico: a Sensitivity Analysis of an Agricultural Field Model and Riparian Zone Management Model

Agrichemical runoff from farmland may adversely impact coastal water quality. Two models, the Agricultural Policy/Environmental eXtender (APEX) and the Riparian Ecosystem Management Model (REMM), were used to evaluate the movement of the herbicide atrazine to the Jobos Bay National Estuarine Research Reserve from adjacent fields. The reserve is located on Puerto Rico’s southeast coast. Edge-of-field atrazine outputs simulated with the APEX were routed through a grass-forest buffer using the REMM. Atrazine DT₅₀ (half-life) values measured in both field and buffer soils indicated that accelerated degradation conditions had developed in the field soil due to repeated atrazine application. APEX simulations examined both the measured field and buffer soil atrazine DT₅₀ and the model’s default value. The use of the measured field soil atrazine degradation rate in the APEX resulted in 33 % lower atrazine transport from the field. REMM simulations indicated that the buffer system had the potential to reduce dissolved atrazine transport in surface runoff by 77 % during non-tropical storm events by increasing infiltration, slowing transport, and increasing time for pesticide degradation. During a large runoff event due to a tropical storm that occurred close to the time of an atrazine application, the REMM simulated only a 37 % reduction in atrazine transport. The results indicate that large storm events soon after herbicide application likely dominate herbicide transport to coastal waters in the region. These results agree with water quality measurements in the reserve. This study demonstrated the sensitivity of these models to variations in DT₅₀ values in evaluating atrazine fate and transport in the region and emphasizes that the use of measured DT₅₀ values can improve model accuracy.     

Modeling of Ecological Footprint and Climate Change Impacts on Food Security of the Hill Tracts of Chittagong in Bangladesh

This paper presents an integrated and dynamic model for the management of the uplands of the Hill Tracts of Chittagong to predict food security and environmental loading for gradual transition of shifting agriculture land into horticulture crops and teak plantation, and crop land into tobacco cultivation. Food security status for gradual transmission of shifting agriculture land into horticulture crops and teak plantation, and crop land into tobacco cultivation is the best option for food security, but this causes the highest environmental loading resulting from tobacco cultivation. Considering both food security and environmental degradation in terms of ecological footprint, the best option is gradual transition of shifting agriculture land into horticulture crops which provides moderate increase in the food security with a relatively lower environmental degradation in terms of ecological footprint. Crop growth model InfoCrop was used to predict the climate change impacts on rice and maize production in the uplands of the Hill Tracts of Chittagong. Climate change impacts on the yields of rice and maize of three treatments of temperature, carbon dioxide and rainfall change (+0 °C, +0 ppm and +0 % rainfall), (+2 °C, +50 ppm and 20 % rainfall) and (+2 °C, +100 ppm and 30 % rainfall) were assessed. The yield of rice decreases for treatment 2, but it increases for treatment 3. The yield of maize increases for treatments 2 and 3 since maize is a C₄ plant. There is almost no change in food security at upazila (sub-district) level for the historical climate change scenario, but there is small change in the food security at upazila levels for IPCC climate change scenario.     

Transition to Lead-Free Products in the US Electronics Industry: A Model of Environmental,Technical, and Economic Preferences

The European Union’s Restriction on the Use of Certain Hazardous Substances (Directive 2002/95/EC) targeted at electronic products took effect in 2006. In contrast, the USA has no comparable national policy on these products. To understand corporate responses to policy differences across jurisdictions, we conducted a structured-questionnaire survey of individuals in 109 companies that are representative of the US electronics industry. The results reveal that 70% of these companies have already adopted lead-free solder for electronics with 49% of the total preferring the SnAgCu formulation, despite uncertainties associated with environmental impacts of this alternative alloy. We use a modified life cycle impact assessment method based on endpoint modeling approach to derive weighting factors that represent the respondents’ value system for tradeoffs among environmental impacts. We use a modified fuzzy Technique for Order Preference by Similarity to Ideal Solution approach to evaluate technical criteria dominance in declared preferences. A statistical model of corporate behavior is also presented. The results provide the first systematic framework that accounts for environmental impact, technological challenge, and business strategy concurrently toward formulating a comprehensive national policy for materials selection in electronic products.     

Development of a Local-Scale Spatially Refined Multimedia Fate Model (LSRMFM) for Urban-Scale Risk Assessment: Model Formulation, GIS-Based Preprocessing, and Case Study

A local-scale spatially refined multimedia fate model (LSRMFM) was developed to evaluate in detail the multimedia transport of organic compounds at a spatial level. The model was derived using a combination of an advection?Cdispersion?Creaction partial differential equation, a steady-state multimedia fugacity model, and a geographical information system. The model was applied to predicting four major volatile organic compounds that are produced as emissions (benzene, toluene, xylene, and styrene) in an urban and industrial area (the 50?×?50-km area was divided into 0.5?×?0.5-km segments) in Korea. To test the accuracy of the model, the LSRMFM was used to predict the extent of dispersion and the data compared with actual measured concentrations and the results of a generic multimedia fate model (GMFM). The results indicated that the method developed herein is appropriate for predicting long-term multimedia pollution. However, the comparison study also illustrated that the developed model has some limitations (e.g., steady-state assumption) in terms of explaining all the observed concentrations, and additional verification and study (e.g., validation using a large observed data set, integration with a more accurate runoff model) would be desirable. In comparing LSRMFM and GMFM, discrepancies between the LSRMFM and GMFM outputs were found, as the result of geographical effects, even though the environmental parameters were identical. The geographical variation for LSRMFM output indicated the existence of considerable local human and ecological risks, whereas the GMFM output indicated less average risk. These results demonstrate that the model has the potential for improving the management of pollutant levels under these refined spatial conditions.