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The spread of infectious diseases such as COVID-19 in a typical oil and gas facility setting, the health of employees, their families and their communities, is of real concern to the industry. In this work, a suitable predictive, agent-based model is used to predict the spread of COVID-19 in different settings as well as to evaluate strategies to block the spread. The agent-based modelling work is based on the simulation platform, Complex Organization and Bifurcation Within Environmental Bounds, or COBWEB. COBWEB simulates how a system of autonomous agents adapts to variation and sudden changes in the resource base or other features of their environment. Previous COBWEB simulation results illustrate that the tool is useful for predicting the evolution of COVID-19 spread and the effectiveness of various preventive actions including self-isolation of symptomatic people, social/physical distancing, effective PPE use, and ‘shielding’ (physical isolation) of the high-risk population. We adapted model parameters to better represent uncertainty about what might be expected in such a setting, in particular by shifting the distribution of risk severity towards ineffective PPE use, self-isolation and poor social distancing, which expectedly shows upward trend of the spread of the COVID-19. Ultimately, governments and industry can apply the predicted trends, as well as apply the model to specific settings, to make more informed decisions on the additional measures and preventative strategies to curb the spread of COVID-19.

Climate change may impact the energy sector directly and indirectly. The objective of this study is to develop a systematic approach for assessing impacts of climate change and adaptation response as well as the growing population on energy economy and greenhouse gas emissions. Such an approach was based on regional energy systems characterization, climate change scenario analysis, vulnerability assessment, energy systems modeling, and climate change policy analysis. The developed methodology is then applied to the Toronto-Niagara Region, Canada. The results suggested that, through modeling energy demand sensitivity to temperature variations within an energy systems management framework, the approach can effectively reflect the impacts from climate change and adaptation response, not only on energy demands and supplies but also on various energy-related technologies and greenhouse gas emissions. It can reflect the system's interactive and dynamic complexities quantitatively; thus, it could provid...

In this study, a large-scale dynamic optimization model (University of Regina Energy Model, UREM) has been developed for supporting long-term energy systems planning in the Region of Waterloo. The model can describe energy management systems as networks of a series of energy flows, transferring extracted/imported energy resources to end users through a variety of conversion and transmission technologies over a number of periods. It can successfully incorporate optimization models, scenario development and policy analysis within a general framework. Complexities in energy management systems can be systematically reflected; thus, the applicability of the modeling process can be highly enhanced. Four scenarios (including a reference case) are considered based on different energy management policies and sustainable development strategies for in-depth analysis of interactions existing among energy, socio-economy and environment in the Region. Useful solutions for the planning of energy management systems have been generated, reflecting trade-offs among energy-related, environmental and economic considerations. They are helpful for supporting (a) adjustment or justification of the existing allocation patterns of energy resources and services, (b) allocations of renewable energy resources, (c) formulation of local policies regarding energy consumption, economic development and energy structure, and (d) analysis of interactions among economic cost, system efficiency, emission mitigation and energy-supply security. Results also indicate that UREM can help tackle dynamic and interactive characteristics of the energy management system in the Region of Waterloo and can address issues concerning cost-effective allocation of energy resources and services. Thus, it can be used by decision makers as an effective technique in examining and visualizing impacts of energy and environmental policies, regional/community development strategies and emission reduction measures within an integrated and dynamic framework. Copyright © 2008 John Wiley & Sons, Ltd.

Green roofs are touted as an environmental technology for urban areas due to their many benefits (Lundholm et al. 2008). Although the design and the benefits have been reported in many reports and articles, they are reviewed here for those who are unfamiliar with this technology. Green roofs, or more formally, green roof infrastructure, is a technology that allows for the growth of vegetation on a roof while protecting the building envelope from leakage and root penetration. A green roof is more than a layer of soil piled on the roof, planted in the way that you might plant a garden. The technology consists of multiple layers that include the plants and growing medium or substrate, but also a drainage layer for storing water that was not used by the plants and a waterproof, root-repellent membrane (Figure 1).

The purpose of this study was to investigate the effect of green roofs and green walls on air pollution in urban Toronto. The research looked at the synergistic effects on air pollution mitigation of different combinations of vegetation by manipulating quantities of trees, shrubs, green roofs and green walls in the study area. The effects of these manipulations were simulated with the Urban Forest Effects (UFORE) model developed by the USDA Forest Service Northeastern Regional Station. While UFORE contains several modules, Module—D quantifies the levels of air pollution for contaminants such as NO2, S02, CO, PM10 and ozone as well as hourly pollution removal rates and the economic value of pollutant removal. Six vegetation scenarios were developed within the Toronto study area to compare different subsets of vegetation and their effect on air contaminants. Results of the study indicate that grass on roofs (extensive green roofs) could augment the effect of trees and shrubs in air pollution mitigation, placing shrubs on a roof (intensive green roofs) would have a more significant impact. By extension, a 10–20% increase in the surface area for green roofs on downtown buildings would contribute significantly to the social, financial and environmental health of all citizens.

This paper addresses the impact of roof-to-envelope ratio on overall energy savings of a green roof design over conventional roof designs. Simulations were performed using a modified version of the Environmental System Performance program simulator, developed at the University of Strathclyde. The modified design employed a model developed by Columbia University and the Goddard Institute of Space Science which models the evapotranspiritive effect of a green roof calculated using the Bowen ratio; that is, the ratio of sensible heat flux to the surrounding air to the latent heat flux resulting from evapourative energy losses. The resulting heat flux term is proportional to the external surface convection, but inversely proportional to the surface Bowen ratio, which is held constant and chosen to match experimental results obtained for a given roof design. The present study performed simulations for the month of July in a Toronto climate on square warehouse style one, two, and three-story buildings, with windows occupying 10% of the area of each wall. For the first set of simulations, the internal building load of each story was set to zero, and the roof–envelope ratio was increased by increasing the building width and length. For the final simulations, several roof–envelope ratios were chosen, and the internal load of each story was increased from 0 to 50,000 W. As the roof–envelope ratio increases, the cooling load of the upper floor for multi-story designs approaches the entire building cooling load. This indicates the importance of upper zone cooling in total building energy reductions. Furthermore, the total energy savings of a green-roofed building over a conventional roofed building were far more significant for single-story structures. A 250 × 250 m green-roof design with 50,000 W internal loading was found to have percentage energy savings of 73%, 29%, and 18%, for a one, two, and three-story design, respectively.

The author is a member of Environment Canada's Adaptation and Impact Research Group, located in the Centre for Environment at the University of Toronto. His primary research interests include the use of ecological technologies in adapting urban areas to atmospheric change, the impacts of climate change on the energy sector, and the characteristics of adaptable systems. His current work on ecological technologies includes green roofs, vertical gardens and living machines. Dr Bass has been involved in two major projects, in Ottawa and Toronto, to evaluate the impact of green roofs on the urban heat island, energy consumption, stormwater runoff and water quality. Currently, Dr Bass is conducting research on integrating green roof infrastructure with other vegetation strategies at a community scale, simulating the impact of a green roof on the energy consumption of individual buildings.

Subsurface characterization is an important requirement in the decision-making process of selecting a remediation technique for petroleum-contaminated sites. The soil type distribution is one of the most important site characteristics, because it affects selection of the site remediation technique. The visualization of soil type distribution and also the contaminant concentration distribution in the subsurface can help the decision-maker understand the site and select the proper remediation technique. In this paper, we describe the software Soil-Visual (1.0, 1.1), which is used for visualizing the soil sampling data, the soil type distribution, and contaminant concentration distribution of a contaminated site. This software has two functions: (1) to determine the soil particle size distribution and contaminant concentration distribution of the entire site from limited soil sampling data; and (2) to visualize the multi-dimensional soil type distribution and contaminant concentration distribution data of each soil layer on a two-dimensional map. The red-green-blue (RGB) color illustration method has been used in this software to convert the multi-dimensional soil sampling data into a bitmap. Key words: RGB bitmap, soil classification, visualization

Indoor environmental health is now recognized as an important factor in preventing respiratory health problems in the United States. It is also a concern in Canada due to the amount of time that Canadians spend indoors because of cold weather and the potential for increased time indoors during the summer if the climate warms. The negative health effects are often labeled as sick building syndrome, but diagnosing a building or its occupants as sick is complicated by the variety of symptoms, the presence of chronic versus acute symptoms and social and psychological (socio-psychological) factors that may reduce the effectiveness of an engineering solution. As a case study, the contribution of various factors to indoor environmental health, in three buildings at the University of Toronto, was examined using five different methods. The results indicate that the inhabitants of the buildings consider features other than air quality in considering building health such as design, maintenance, funding cuts and socio-psychological factors.

One objective of the International Geosphere-Biosphere Programme is to provide a scientific basis for sustainable development policies. Land use change and ecohydrology are important components of this scientific basis, but predicting change is difficult because of the scale and complexity of the interactions between non-linear ecohydrological and socio-economic processes at different spatial and temporal scales. A systems framework, the Ecosystem Approach, has been developed to conceptualize these interactions for the purpose of providing information for sustainable development policy. The Ecosystem Approach combines the dynamics of the Holling figure-eight model -- a conceptual model of dynamics that stresses discontinuous change and destruction as an internal property of the system - and the properties of self-organizing systems with the socio political aspects of decision making. The Ecosystem Approach highlights the problems of managing change in complex systems when that change may involve unpredictable shifts to a different attractor. Although there are methods available to detect the occurrence of such shifts, both detection and modelling are complicated by the presence of semi-stable attractors. When a model or an ecosystem is on a semi-stable attractor, it may appear to remain stable for an extended period prior to changing as a consequence of inherent instabilities. When the shift to a new attractor occurs, it is quite sudden and unpredictable. A technical discussion on prediction under conditions of semi-stability and chaos is included because it enhances our understanding of the role of surprise in ecosystems, as well as the utility of simulation models. The principles of the Ecosystem Approach are derived from the theoretical discussion and an example of a land use policy in the Huron Natural Area in south-western Ontario. These principles provide a clear role for scientific research, and particularly simulation modelling, within the larger context of policy and land use management.

Policy makers in Canada have suggested that the scientific community should develop an indicator of biodiversity change that can be implemented quite quickly without a major new investment in monitoring systems. We propose that such an indicator can be developed from the theory of species gradients in community ecology. The term 'species gradients' refers to the increasing diversity of species through time under stable conditions, and the increasing diversity of species with the increased use of available resources. This theory is reviewed under four different headings: evolutionary ecology, the energy theory, the resource productivity theory and the thermodynamic mechanism. The theoretical arguments provide a basis to propose detection of the 'leaky ecosystem' as an indicator of biodiversity. We propose that it is possible to detect the leaky energetics of ecosystems by means of routinely available observations of outgoing longwave radiation.

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.

Climatic change and decision making in the economic and political sector are discussed. The incorporation of uncertainty into the decision making process is described.

Climate change presents problems for risk assessment procedures due to the difficulty of assigning a measure of probability to any future scenario. Grey systems theory provides an alternative means of quantifying uncertainty based on interval numbers. Within a mathematical programming model, grey systems theory provides a means for working with uncertainties that are not amenable to stochastic or fuzzy quantification. An example of forestry and agricultural expansion in the Mackenzie River Basin is used to illustrate grey mathematical programming in a hop, skip and jump formulation. In this example, climatic constraints are implicitly contained in other parameters which did not incorporate the different components of uncertainty associated with meteorological observations. These components can be combined into a numerical interval that can be used in determining a grey number. However, most of these uncertainties are negligible in climatic data sets due to the number of observations. Nevertheless, these uncertainties point to some of the problems in assessing the risks of climate change, and a grey mathematical programming algorithm is useful for assessing the sensitivity of a decision to climatically sensitive parameters.

In this paper, a differentiated prediction model (DPM) was combined with an interval analysis approach for the prediction of weather variables under uncertainty. The DPM was used for general trend prediction, and interval analysis was used for reflecting seasonal variations and residual terms. A case study of prediction for monthly average temperature and precipitation in Wuhan, China, was provided based on 22 years of observation data. The results indicated that uncertainties existing in weather-related processes could be effectively reflected through this hybrid approach. The predicted intervals for temperature and precipitation appear to contain most of the relevant observed values.

In assessing the risks associated with climate change,downscaling has proven useful in linking surfacechanges, at scales relevant to decision making, tolarge-scale atmospheric circulation derived from GCMoutput. Stochastic downscaling is related to synopticclimatology, weather-typing approaches (classifyingcirculation patterns) such as the Lamb Weather Typesdeveloped for the United Kingdom (UK), the EuropeanGrosswetterlagen (Bardossy and Plate, 1992) and thePerfect Prognosis (Perfect Prog) method from numericalweather prediction. The large-scale atmosphericcirculation is linked with site-specific observationsof atmospheric variables, such as precipitation, windspeed or temperature, within a specified region. Classifying each day by circulation patterns isachieved by clustering algorithms, fuzzy rule bases,neural nets or decision trees. The linkages areextended to GCM output to account for climate change. Stochastic models are developed from the probabilitydistributions for extreme events. Objective analysiscan be used to interpolate values of these models toother locations. The concepts and some applicationsare reviewed to provide a basis for extending thedownscaling approach to assessing the integrated riskof the six air issues: climate change, UV-B radiation,acid rain, transport of hazardous air pollutants, smogand suspended particulates.

Phosphorus has been identified as the limiting nutrient and a primary cause of both nuisance and hazardous algal blooms in the North American Great Lakes and other water bodies. Urban areas contributed phosphorus from wastewater treatment plants and through stormwater runoff. Phosphours reduction was the key element of the first Great Lakes Water Quality Agreement, between Canada and the United States in 1972. Although the measures that were enacted to reduce phosphorus were successful at reducing algal blooms, the problem reemerged in the last ten years. The largest hazardous algal bloom on Lake Erie occurred in 2011 and the first hazardous algal bloom on Lake Superior occurred in 2012. Nuisance algae have become a problem for infrastructure and recreation in the nearshore habitats of Lakes Erie and Ontario and to a lesser extent in tthe nearshore habitat of Lake Huron. Fuzzy cognitive mapping (FCM) has been used to describe and analyze theflow of phosphorus through Lake Erie (2009), through agricultural production into Lake Erie (2010) and most recently, through urban areas into Lake Erie. FCM represents the flow and linkages with algal blooms and eutrophication as a network of nodes and linkages. Each node is a driver, a final receptor, or a stressor (a mid-point that both receives and contributes phosphorus to the system). FCM is a modelling strategy that has proven to be very effective for complex systems where data are not available to describe the many processes and flows, yet where an urgent need for action has been established to cope with a problem. FCM is a process where diverse groups of experts work in teams to map out the system. These maps also include weights for each linkage that describe the strength of the linkage, the confidence in the linkage, the scientific certainty, the spatial and temporal extent of the relationship and other relevant factors. The various team maps can then be aggregated into one map through different methods such as averaging the weights or genetic algorithms. A stakeholder workshop was convened in March, 2013 to create several different maps that illustrate the linkages between urbanization, phosphorus, algal blooms and eutrophication. The aggregate maps highlight the multiple drivers and the complexity of the flows through the stressors. Maps might typically contain 90 nodes and 140 linkages. The analysis of the maps provides insight as to the most important nodes in these networks, sggesting where measures to control the flow of phosphorus might have the largest impact. The aggregation and analysis of the maps was done with the Fuzzy Aggregated Linakges Within Environmental Bounds (FALWEB) software, which was developed for fuzzy cognitive maps.

A study of integrated climate change impact assessment and adaptation study for agricultural and timbering activities in Mackenzie Basin, Canada, was conducted through development/application of an inexact dynamic optimization (IDO) model that can reflect complex system features and a related fuzzy relation analysis (FRA) method that is useful for comprehensive assessment of impact patterns. The IDO approach allows uncertain information to be effectively communicated into the optimization process. The resulting solutions are presented as intervals which can be directly interpreted to generate adaptation alternatives. The method also has low computational requirements since its solution algorithm does not lead to more complicated intermediate submodels. Through this IDO approach, uncertain, dynamic and interactive features of the study system can be effectively reflected. The FRA method provides a viable means for synthetic analysis of general climate change impact pattern based on the IDO outputs. The method is helpful for obtaining insight into the interrelations between different system components. The results indicate that complex natures of climate change impacts have been effectively reflected through the proposed approaches. Generally, temporal variations of land characteristics and thus land use activities exist due to changes in climatic, economic and environmental conditions.

The ongoing drought in the Sahel region of West Africa highlights the vulnerability of food-producing systems to climate change and variability. Adaptation to climate should therefore increase the sustainability of agriculture under a long-term drought. Progress towards sustainability and adaptation in the the Senegal River Basin is hampered by an existing set of social and ecological relationships that define the control over the means of production and how people interact with their environment. These relationships are sensitive to the technological inputs and the administration of food production, or the factor bias in the different policy alternatives for rural development. One option is based on state-controlled, irrigated plantations to provide rice (Oryza) for the capital, Dakar. This policy emphasizes a top-down management approach, mechanized agriculture and a reliance on external inputs which strengthens the relationships introduced during the colonial period.

It is appropriate to consider water quantity and water quality as two facets of water resources. Both facets are intimately connected to the hydrological cycle, which itself is a component of the Earth’s climate System. Since human activities and health are so connected to water resources, it is essential to determine how far into the future we can predict the condition of the water resources of a region with a sufficient level of confidence. When predictions are not possible, resilience must be built into a water System so that human (and natural) needs are not negatively affected. Even when skillful predictions are possible, they are seldom completely accurate. Thus uncertainty needs to be included when scientific analyses and predictions are used for water resource planning and management, particularly for issues such as adaptation or risk management. The prediction of weather and climate are essential aspects of planning for water resources in changing environmental conditions.

Indoor environmental health is now recognized as an important factor in preventing respiratory health problems in the United States. It is also a concern in Canada due to the amount of time that Canadians spend indoors because of cold weather and the potential for increased time indoors during the summer if the climate warms. The negative health effects are often labeled as sick building syndrome, but diagnosing a building or its occupants as sick is complicated by the variety of symptoms, the presence of chronic versus acute symptoms and social and psychological (socio-psychological) factors that may reduce the effectiveness of an engineering solution. As a case study, the contribution of various factors to indoor environmental health, in three buildings at the University of Toronto, was examined using five different methods. The results indicate that the inhabitants of the buildings consider features other than air quality in considering building health such as design, maintenance, funding cuts and socio-psychological factors.

The Holling figure-eight model is proposed as a description of ecosystem dynamics that can incorporate the complex behavior that is germane to realistic biological systems. The figure-eight includes the two phases of exploitation and conservation as well as destructive events, such as fire, and system reorganization following such an event. The Holling figure-eight is underlain by two goal functions: the maximization of exergy consumption, the maximization of exergy storage and the emergence of a self-organized critical state at the conservation state.

The International Geosphere-Biosphere Program — Biological Aspects of the Hydrological Cycle (IGBP-BAHC) is concerned with the role of the biosphere in the hydrological cycle over a range of space and time scales. One crucial emphasis in this exercise involves ‘upscaling’ or aggregating the processes in the soil-vegetation-atmosphere interface from the patch scale of ecology to the mesoscale, larger regional scales and the continental scale. In time the upscaling must move from hours to decades and even longer time periods. A second emphasis involves the ‘downscaling’ of low-resolution climatic and meteorological data to high-resolution grids that are suitable for ecological and hydrological research. These two emphases are described along with prototype models for upscaling and downscaling. Other issues such as the incorporation of land surface heterogeneity in upscaling and the classification of atmospheric circulation patterns in downscaling are discussed along with other aspects related to these emphases are presented in greater detail. In particular the discussion of the downscaling component in BAHC summarizes the results of the most recent workshops (BAHC, 1993a and b).

Neither the Framework Convention on Climate Change (FCCC) nor the Vienna (Ozone Layer) Convention seriously considers adaptation. Indeed, such a consideration may be unnecessary-especially with regard to food security. Agriculture has been and is one of the most adaptable of human production systems. Only an extremely adaptable system could have expanded world food production sufficiently to meet most of the needs engendered by world population growth in the last two centuries. Yet the persistence of drought and hunger in the developing world suggests otherwise. However, this failure is not principally due to climate. It is rooted in the separation of the producers from the means of production and the separation of the techniques of production from the local ecology. This is the perspective of ecological (eco)-political economy (Yapa, 1982).