Research techniques for studying environmental systems development

¶ … 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.

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).

Nevertheless, this potential for error is typically resolved by further statistical analysis that will smooth the data and allow for informed human interpretation. In this regard, Goodchild (2008) reports that although the precise positions of GIS-located objects can be distorted in absolute terms, the general shapes of these objects will be generally retained. Although this concept extends to elevation data as well, there are some constraints involved in the interpretation of the data but statistical methods provide a reasonably acceptable estimation of elevation nevertheless (Goodchild, 2008). In many ways, these methods continue to build on the work of previous researchers and while the use of some of them such as geospatial analyses are of fairly recent origin, some valuable lessons have been learned in their use and these issues are discussed further below.

Lessons Learned

Perhaps the overriding theme that emerged from the review of the literature concerned the wide variety of research methods that have been used in various ways for environmental system analysis and development. Although of these research methods was shown to have its respective strengths, they were also shown to be balanced by corresponding weaknesses or constraints when they are applied to real-world settings. The use of strictly quantitative methods, for example, in analyzing environmental systems provides researchers with the data they need to formulate expert interpretations that are sorely needed by others who want to apply these findings to their own unique situations.

Other lessons learned from the review of the literature included the inaccuracies that can be introduced in the research through the vagaries of arbitrary geopolitical boundaries, a constraint that becomes especially pronounced over time. Although specialized software applications have been developed that taken such variations in time into account, there remains a need for human interpretation of the data that results in order to make these findings relevant and credible. In sum, then, the most important lessons learned to date include the following:

1. Biostatistical research methods must include interpretation of quantitative data by experts in the field;

2. The use of both quantitative and qualitative research methods provides a more holistic perspective of environment issues and their impact on humans; and,

3. Although geospatial data is becoming increasingly accessible, some regions of the world continue to lack access to such data, as well as the expertise needed to apply appropriate research methodologies in ways that can provide them with the insights they need at the local level.

As the body of evidence concerning the effectiveness of the various research methods continues to grow, additional lessons learned will help define a set of best industry practices that can help organizations of all sizes and types develop improved environment systems that are based on real-time information and expert analyses.

Conclusion

By and large, the research showed that environmental research involves quantitative methods that are used to analyze natural and anthropomorphic patterns over time, a process that has been facilitated greatly in recent years by the introduction of specialized software tools that can use geospatial data that is also becoming increasingly accessible. Although the use of quantitative risk assessment and biomonitoring research methods is fairly well established and both enjoy widespread acceptability, there is less confidence in some of the other research methods reviewed, especially the use of geospatial data over time given the vagaries of human occupation in a given region. Taken together, recent trends in the use of quantitative data provided by geospatial technologies as well as biomonitoring research methods have provided researchers with a robust set of information upon which to make qualitative assessments. Just as more and more so-called "apps" are being developed for smartphones in a "build-it-and-they-will-come" mentality, the research also showed that as access to reliable geospatial data increases, there will likely be researchers lining up to use this information. It is reasonable to conclude that beyond the foregoing research methods, additional innovative approaches will be forthcoming in the years ahead that will use geospatial data in ways that can benefit local environmental sustainability efforts because there is money to be made in this industry and these research methodologies are the modern tools of the trade.