Comprehensive examination preparation and study guide

¶ … environmental systems in the past five years. Summarize the techniques used, the assumptions and limitations faced, the potential for error and how it was minimized, and the lessons learned.

Scope/Direction of the Research

The scope of the study extended to a review of relevant studies published within the last 5 years to provide an overview and recapitulation of the techniques that have been used in recent years to study the development of environmental systems, the assumptions and limitations that have been encountered along the way, the potential for error and how it was minimized, and the lessons learned from these efforts. The development of environmental systems includes various geospatial technologies, alternative energy systems, and other technological solutions that are designed to interact with and monitor the earth's natural environment. This analysis is followed by a summary of the research and important findings in the conclusion.

Potential Limitations of the Research

A potential limitation of this research project was the lack of relevant scholarly studies on this topic as well as the 5-year time constraint involved which excluded several on-point studies from being included in the analysis. The search protocols employed for this purpose included Boolean searches using key words such as "environmental systems," "quantifiable risk," "risk management," "analytical methods," and various permutations of these search terms in reliable online research resources such as EBSCO and Questia, using various delimiters such as the timeframe of the published studies. Another potential limitation of the research concerned the potential for recent innovations in research approaches used to study the development of environmental systems in the pasts 5 years to be overlooked during the research process, especially given the lag between original research and the time required to be published in a peer-reviewed journal. Finally, a potential limitation encountered during the research process was dynamic nature of the technologies that are currently being used, with innovations being introduced on a daily basis that can have profound effects on the utility of existing research methods.

Purpose of the Research

The purpose of this study, as noted above, was to compare and contrast the research approaches used to study the development of environmental systems in the past 5 years, as well as the assumptions and limitations that have been experienced, the potential for error in such systems and how they were minimized, as well as what lessons were learned from these efforts.

Summary of Research Techniques used to Study Environmental Systems

Quantitative Risk Assessment

It has become axiomatic in the business world and scientific community alike that in order to improve something, it must first be measured and this is also the case with the quantitative research techniques that have been used in recent years to develop environmental systems. According to Neuman (2003), quantitative research uses "information in the form of numbers" (p. 542). Environmental management research uses a variety of quantitative research methods for risk assessment applications, including potential risk to human health as well as the environment as a result of anthropomorphic activities (Autenrieth, 2012). Likewise, quantitative risk assessment of environmental risk factors is a fundamental unit of analysis for environmental researchers (Leyk, Phillips, Smith & Nuckols, 2011). The quantitative data that results from these analyses can provide decision-makers with the information they need to conduct the requisite cost-benefit and what-if type scenario analyses, and to allow scarce resources to be focused where they will provide the maximum return on their investment (Autenrieth, 2012). Moreover, because the quantitative risk assessment method can use existing epidemiological data to measure the impact of exposure of different environmental threats on different populations, no new research is required to use this method with archived data (Corvalan, Briggs & Zielhuis, 2009).

Other increasingly popular applications of quantitative risk-assessment research methods for environmental management research include formulating timely and efficient responses to environmental disasters such as oil spills (Autenrieth, 2012). In sum, then, the quantitative risk assessment approach is "the application of a statistical relation between exposure and the associated health outcome to assess either the health risk to a population or the exposure level associated with a given risk" (Corvolan et al., 2009, p. 120).

Biomonitoring

Biomonitoring research that uses quantitative data has also become an increasingly valuable tool for environmental systems development. According to Vandenberg, Chahoud, Padmanabhan, Paumgartten and Schoenfelder (2010), biomonitoring research involves collecting the quantitative data that is needed to conduct toxin exposure assessments, an approach they maintain helps to identify health threats that might otherwise go undetected. In this regard, Lakind, Barraj, Tran and Aylward (2008) report that, "The risk assessment paradigm, which serves as the basis for public health evaluations and actions with respect to environmental chemicals, requires not only an assessment of the potential toxicity of a chemical but also an estimate of human exposure" (p. 61). With respect to their application in environmental system development and analyses, biomonitoring relies on human-produced evidence to provide the data needed to formulate expert interpretations and recommendations. In this regard, Lakind et al. define biomonitoring as "the direct measurement of chemicals or their metabolites in blood, urine, or other bodily fluids or tissues, is becoming an increasingly common exposure assessment tool" (2008, p. 61). The application of biomonitoring research methods fro environmental systems to date have confirmed their efficacy and a growing body of evidence supports the use of biomonitoring for other environmental system development efforts as well (Vandenberg et al., 2010).

Geographic Information Systems

Other research methods used to develop environmental systems in recent years that have relied on quantitative data include geospatial technologies such as geographic information science or systems, remote sensing and global positioning systems (Lambert, Munro-Stasiuk, Czajkowski, Benko et al., 2008). In recent years, geospatial technologies have been applied to the development of environmental systems for forestry, water use, wildlife management and agricultural practice, among others (Hoalst-Pullen & Patterson, 2010). According to Satapathy, Katpatal and Wate (2008), geospatial information technology systems are increasingly important research tools that can help decision makers better understand the implications of current and projected human activity on the environment. According to the definition provided by Suit, geospatial technologies are "an amalgamation of several technologies, including but not limited to remote sensing, GIS, GPS, and related fields such as computer mapping, spatial modeling, and data visualization" (p. iii). The use of geospatial data dates to the mid-to late 20th century, but serious environmental management development systems were not realized until around the turn of the century (Sui, 2007).

These geospatial research methods represent the cutting-edge of environmental system development today, and new applications continue to be identified (Sui, 2007). For example, Haining, Kerry and Oliver (2010) report that, "Geostatistics is a distinctive methodology within the field of spatial statistics. In the past, it has been linked to particular problems (e.g., spatial interpolation by kriging) and types of spatial data (attributes defined on continuous space)" (p. 7). Originally developed in France in the 1960s (Goodchild, 2008) for use in the mining industry (Gething, Noor, Gikandi et al., 2008), geostatistics has become the most widely used research method by geostatisticians because of the fundamental nature of the quantitative data that is involved (Haining et al., 2010).

The research method used by geostatisticians, though, is distinguished by several differences from the methods that are generally used by geographers for analyzing spatial variations that are associated with regional data (Haining et al., 2010). In this regard, geostatistics include a wide array of tools and modeling methods that can be used with researching various environmental management scenarios including:

1. Prediction;

2. Determination of the scale of spatial variation;

3. Design of sampling for primary data collection;

4. Smoothing of noisy maps;

5. Region identification;

6. Multivariate analysis; and,

7. Probability mapping (Haining et al., 2010).

The application of geostatistics to environmental research also has a growing body of evidence in support of its efficacy and continued use for these purposes (Haining et al., 2010), a process that will likely accelerate in the future as access to timely geospatial data becomes more widespread. Moreover, this process is being facilitated by the placement of geospatial research tools in "the cloud," in online venues. In this regard, Internet-based GIS has describes GIS services that employ the Internet as their primary means of accessing data, conducting spatial analyses, and providing interactive services related to geographic information (Yao & Zou, 2008). Geostatistics are also increasingly being used to help identify optimal placements for wind turbine generators in wind farms throughout the United States and elsewhere (Dincer & Rosen, 2007). According to Dincer and Rosen, "Energy and exergy efficiency models for wind generating systems are used to produce exergy monthly maps. With these map for a specific system, exergy efficiencies in any location in a considered area can be estimated using interpolation" (p. 196).

ISO 14001

Besides the foregoing approaches, a growing number of companies around the world are basing their environmental system development efforts on the analytical framework provided by ISO 14001 (Zsoka, 2007). The ISO 14001 framework provides a number of auditing and other analytical tools that companies can use to qualitatively and quantitatively evaluate their compliance with governmental regulations as well as the provisions of ISO 14001 itself (ISO 14000 essentials, 2012). Although the research tools provided by the ISO 14001 framework are both qualitative and quantitative, this approach is consistent with the guidance provided by Neuman (2003) who points out that, "Both qualitative and quantitative research use several specific research techniques (e.g., survey, interview, and historical analysis), yet there is much overlap between the type of data and the style of research. Most qualitative-style researchers examine qualitative data and vice versa" (p. 16). Indeed, researchers have used qualitative and quantitative surveys to assess consumer reactions to proposed environmental initiatives at the local level (Neuman, 2003).

In fact, quantitative and qualitative research methods are characterized by a number of similarities that lend themselves to environmental systems analyses and development (as well as some differences) (Neuman, 2003). The distinct differences in the qualitative and quantitative research suggest that the use of quantitative data for environmental system development is highly appropriate, but that such data must be interpreted by taking into account a wide range of potentially qualitative factors that will not be possible using one approach to the exclusion of the other research approach (Neuman, 2003).

A summary of the foregoing research methods for environmental system development is provided in Table 1 below.

Table 1

Summary of Research Methods Used for Environmental System Development: Past Five Years to Date

Research Method

Description

Operation

Quantitative risk-assessment methods

1. Risk assessment for potential risk to human health;

2. Risk assessment for potential damage to the environment from manmade activities;

3. Formulating timely and efficient responses to environmental disasters such as hazardous waste spills and their management.

4. Biomonitoring and exposure assessments of environmental threats to human health (Vandenberg.et al., 2010).

Two types are quantitative risk assessment methods are available that make it valuable for environmental system analyses:

1. Risk analysis. The first type of quantitative risk assessment involves computation of the risk corresponding to a given level of exposure or dose; for example expressed in terms of excess risk or the number of extra disease cases.

2. Hazard analysis. The second type involves calculation of the exposure or dose corresponding to a given level of risk; for example the exposures estimated to cause adverse health outcomes in a certain percentage of exposed subjects (Carvalan et al., 2009).

Geospatial data

Geospatial technologies is an umbrella term that includes:

1. Remote sensing,

2. GIS,

3. GPS,

4. Computer mapping,

5. Spatial modeling,

6. Data visualization (Yao & Zou, 2008); and,

7. Wind farm siting (Dincer & Rosen, 2007).

.In addition, Internet-based GIS is becoming increasingly accessible to business, governments and consumers around the world as well (Yao & Zou, 2008).

These technologies rely on global information and positioning systems to create maps and three-dimensional visualizations, among other applications (Yao & Zou, 2008). The use of geospatial data by geostatistics for environmental system development include the following:

1. Prediction;

2. Determination of the scale of spatial variation;

3. Design of sampling for primary data collection;

4. Smoothing of noisy maps;

5. Region identification;

6. Multivariate analysis; and,

7. Probability mapping (Haining et al., 2010)

ISO 14001 framework

The standards and guidelines in the ISO 14001 framework that address specific environmental aspects, include the following:

1. Labeling,

2. Performance evaluation,

3. Life cycle analysis, and

4. Communication and auditing (ISO 14000 essentials, 2012, para 1).

The two standards, ISO 14001:2004 and ISO 14004:2004 deal with environmental management systems (EMS). ISO 14001:2004 provides the requirements for an EMS and ISO 14004:2004 provides general EMS guidelines (ISO 14000 essentials, 2012).

In sum, then, the research methods used during the past 5-year period have included conventional risk-assessment methods using quantitative data as well as biomonitoring techniques, geospatial data analytical methods such as geostatistics, and the qualitative and quantitative methods provided by the ISO 14000 family of environmental management evaluation and auditing tools. Each of these systems has its respective advantages and drawbacks, though, and these issues are discussed further below as they apply to their application in developing environmental systems.

Assumptions and Limitations Encountered in Developing Environmental Systems

Assumptions. Any type of research enterprise will require some fundamental assumptions about the phenomenon being modeled, and the enormous array of variables that affect environmental systems makes such research problematic from the outset. Indeed, identifying what should be measured and how it should be measured requires a comprehensive knowledge of the most salient environmental factors that are involved, but even the most careful approach cannot predict every possible outcome in such complicated systems.

Limitations. Many of the limitations that have been encountered in developing environmental systems using geospatial data have been associated with a paucity of timely and accessible data, as well as expert interpretation of this data (Satapathy et al., 2008). Although there are a growing number of uses for geospatial data, Satapathy and his colleagues (2008) cite a lack of access to such timely data, at least in India. This view is countered by the report from Sui (2007) that found geospatial data is readily accessible, at least in the United States, and that these technologies will continue to redefine how environmental systems are developed in the future. Furthermore, Goodchild and Janelle (2004) report that a number of other research tools have become available in recent years that provide geospatial data directly to researchers and consumers alike, including Space Imaging Inc. IKONOS (launched in 1999) and Digital Globe's Quickbird (launched in 2001). Both of these systems provide commercial satellite imagery products that are offered to the general public and the research community (Goodchild & Janelle, 2004). Despite its increasing availability, there remains a lack of expert interpretation of geospatial data that takes into account the specialized needs of local communities (Brinegar & Popick, 2010).

According to Brinegar and Popick, the world's 200 or so countries are defined by arbitrary geopolitical lines drawn on the globe, and these boundaries continue to shift, making the analysis and interpretation of geospatial data especially challenging. In this regard, Brinegar and Popick report that the need for defined areas is an essential requirement for developing environmental systems that take into account population growth trends and other human factors, but these analyses are complicated by the fact that such human-created boundaries tend to change over time. According to these analysts, "Unfortunately, human-defined boundaries vary over time and among data sources, complicating geographic inquiries. Spatial data issues occur, for example, when municipal boundaries expand and diverge from static census blocks, or when variables of interest are recorded in noncontiguous geographic units" (Bringer & Popick, 2010, p. 273).

These are increasingly salient issues in the application of geospatial data to environmental systems that focus on anthropomorphic impacts over time. This type of research has become possible in recent years through sophisticated modeling applications that include both geospatial as well as temporal data in formulating a variety of potential scenarios (Goodchild, 2008). Indeed, Goodchild even goes so far as to characterize this type of environmental system research as a "paradigm shift" and emphasizes that this trend is driven in large part by the introduction of specialized software for this purpose, among other compelling reasons. According to Goodchild, this trend is "driven in part by a new abundance of spatiotemporal data, in part by the development of improved methods of analysis and improved software tools, and in part by the realization that the dynamic aspects of the Earth's surface are in many ways more interesting and important than the static aspects" (2008, p. 312).

Moreover, although several approaches have been developed to help resolve these constraints, there remains a need for comparative studies to determine the accuracy of these models in real-world settings (Bringer & Popick, 2010). These arbitrary geopolitical national boundaries have also adversely affected the ability of geospatial data to be used for environmental system development for more effective disease control methods (Leyk et al., 2011). .In this regard, Leyk and his associates (2011) emphasize that recent attempts to analyze geospatial data over time have been impacted by the influence of regional risk factors include climate and the prevailing socioeconomic conditions. According to these researchers, "Often the unit of analysis for such studies are administrative reporting units (states or larger) used in disease reporting, resulting in highly aggregated outcomes with limited representation of the underlying environmental phenomenon that might be more realistically reflected by analytical units defined by natural barriers, ecological systems, and other important factors in pathogen occurrence, exposure, and transmission" (Leyk et al., 2011, p. 224).

Similarly, a recent study by Goovaerts (2010) confirmed the challenges of using geostatistics for epidemiological applications based on regional or national boundaries that can shift. While there are some indications that geostatistics can be used for a wide range of environmental systems analyses, there have been some problems in applying the methods that were originally developed for analyzing earth properties to health-related research precisely because of these arbitrary boundaries. In this regard, Goovaerts emphasizes that, "Transferring methods originally developed for the analysis of earth properties to health science presents several methodological and technical challenges. These arise because health data are typically aggregated over irregular spatial supports (e.g., counties) and consist of a numerator and a denominator (i.e., rates)" (p. 32).

Potential for Error and Resolution Techniques

According to Benz and Newman (1998), the potential for error in quantitative analysis can be minimized by the use of computer-based applications, but humans remain a potential for error at every step of the process. Moreover, there may be some trial-and-error involved in formulating quantitative metrics that accurately measures what is intended. In this regard, Benz and Newman report that, "Some types of data are more difficult to quantify and, therefore, are not quantified; while other types of data are not initially quantified but are quantified at a later point" (1998, p. 111).

Once accurate quantifiable measures are identified and applied, though, the results of such quantitative research, including the use of these methods with geospatial database analyses, can then be used by the researcher for a wide variety of environmental management applications, including system development, implementation and administration (Hoalst-Pullen & Patterson, 2010). It should be noted, though, that geospatial databases are not free from errors and each image from space may include a minor positional error that will affect the cumulative accuracy of the mapping and other models that are generated (Goodchild, 2008).