Policy Analysis A Comparative Hierarchical Decision Framework on Toxics Use Reduction Effectiveness for Electronic and Electrical Industries H A I - Y O N G K A N G , †,| OLADELE OGUNSEITAN,‡ ANDREW A. SHAPIRO,§ AND J U L I E M . S C H O E N U N G * ,† Department of Chemical Engineering and Materials Science, University of California, Davis, California 95616, Department of Environmental Health, Science and Policy, University of California, Irvine, California 92612, and Department of Chemical Engineering and Materials Science, University of California, Irvine, California 95612
Analytic Hierarchical Process (AHP) has been used in this study as a decision-making model to investigate the potential benefits of implementing a Toxics Use Reduction Act (TURA) in California, based on outcome measures of similar programs in other states, with a focus on the Massachusetts TURA established in 1989. A comparative assessment of trends in the Toxic Release Inventory (TRI) characteristics, economic and census statistics, and the environmental performance of electronics and electrical industries in the two states indicated that programs already implemented in California are effective in achieving the goals of the generic Massachusetts TURA. The results of this study provide a crucial baseline for evaluating the effectiveness of industry-targeted waste reduction policies such as California’s new Universal Waste regulation, which covers the disposal of domestic electronic products, effective February 9, 2006.
Introduction The rapid development of consumer-oriented electrical and electronic technologies and the decrease in the useful life of these consumer electronic devices has created a large waste stream of obsolete electronic equipment (1). Used electronics contain significant amounts of metals such as mercury, lead, cadmium, chromium, and arsenic. Cathode ray tubes (CRTs), for instance, are one of the largest sources of lead (Pb) in the municipal solid waste stream (2). Furthermore, these metals are listed as hazardous substances by the Resource Conservation and Recovery Act (RCRA) (3). Also, plastics used in electronic equipment contain polybrominated diphenyl ethers (PBDEs), which are used as flame retardants, but these materials are reported as hazardous to humans (4, 5). As a * Corresponding author phone: 530-752-5840; fax: 530-752-9554; e-mail:
[email protected]. † Department of Chemical Engineering and Materials Science, UC Davis. ‡ Department of Environmental Health, Science and Policy, UC Irvine. § Department of Chemical Engineering and Materials Science, UC Irvine. | E-mail:
[email protected]. 10.1021/es060739u CCC: $37.00 Published on Web 12/13/2006
2007 American Chemical Society
result, the European Union recently banned the use of all PBDEs in electronic products starting from the year 2006 (6). There are many efforts to reduce the use of toxic chemicals and the generation of toxic chemical waste to protect human health and the environment at various levels. Toxic use reduction encompasses changes in materials or processes that reduce, avoid, or eliminate the use of toxic chemicals or the generation of hazardous waste or emissions. Changes in technology that can facilitate toxic use reduction include recycling/reuse of toxic waste, changing to nontoxic or less toxic new materials, product reformulation, and production unit redesign or modification (7). Generally, these efforts are encouraged by government regulation and lead to management activities that try to reduce the costs of liability for the treatment of toxic waste by private companies. The intended benefits of these efforts accrue to improve human health and environmental quality. Industries can benefit from reductions in toxic waste, as companies can find ways to reduce their raw materials usage and find new opportunities to reuse/recycle their waste, which can result in significant savings in both raw material and waste management costs (7). Various legislative strategies have been developed to minimize the generation of toxic waste and to reduce the use of toxic substances in manufactured products. Examples of legislation at the federal level include the Resource Conservation and Recovery Act (RCRA, 1976), which was designed to control hazardous waste by imposing management requirements on generators and transporters of hazardous waste, and the Emergency Planning & Community Right-To-Know Act (EPCRA) of 1986, which instituted the Toxic Release Inventory System (TRI) (8). At the international level, the Parliament of the European Union started the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) program in 2003 (9). The purposes of REACH are to maintain and enhance the competitiveness of the EU chemical industry, as well as to protect human health and the environment through reduction in toxics use and hazardous wastes generation. At the state level, Massachusetts and Oregon established the Toxics Use Reduction Act and the Toxic Use and Hazardous Waste Reduction Act (TUHWR), respectively, in 1989, (7, 10) and New Jersey enacted the Pollution Prevention Act in 1991 (11). These Acts require that users of toxic substances report the quantity of toxic materials they use and the amount of toxic waste they produce, if beyond specified threshold amounts, as defined by each Act (7, 10, 11). The Massachusetts, TURA has attracted the attention of legislators in other states, such as California, because the results indicate that this legislation has led to a marked reduction in waste generation. For example, Massachusetts claims to have achieved a 90% reduction in the releases of on-site Toxic Release Inventory (TRI) chemicals (12). The State of California is exploring the possibility of implementing a TURA-type law, despite the existence of its own Safe Drinking Water and Toxic Enforcement Act of 1986 (better known as Proposition 65) (13). This Act requires the State to publish a list of chemicals known to cause cancer or birth defects or other reproductive harm. Furthermore, Proposition 65 requires warnings to be provided on products or in buildings that contain significant amounts of the listed chemicals. This Proposition is quite different from TURA in that it does not provide as many regulations, nor does it VOL. 41, NO. 2, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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provide government assistance with compliance or with identifying TUR technologies. Proposition 65 is simpler legislation, which is more analogous to EPCRA. Thus, the purpose of this study was to explore available options for California’s initiative to reduce the human and environmental health impacts of the growing stream of electronic waste, based on comparisons of the environmental performance of the electronic and electrical industries in states with and without TURA-type legislation. The study, which relies on publicly available data from the extensive Toxic Release Inventory (TRI), analyzes the practices of toxic waste management and the U.S. Census Bureau database to characterize the size and behavior of these industries, by state. An established decision-making tool, the Analytic Hierarchy Process (AHP), was then used to evaluate the importance values associated with specific criteria of environmental performance so that a recommendation could be made to the State of California with respect to the value of implementing a generic toxic use reduction act. This application of the AHP is novel, yet suits the purpose of comparing state mandates in both a qualitative and quantitative way, as the effectiveness of legislation will depend on a variety of factors such as the size and complexity of the industrial base, and existing waste management practices.
Methods Analytic Hierarchy Process (AHP). There are several methods available for quantitative assessment of decision-making processes, including AHP (14). The AHP is a multi-criteria decision making methodology that permits subjective as well as objective factors to be considered in the process, and it provides a mechanism to break down complex trade-offs into a series of simple pairwise comparisons. This method also allows for the evaluation of consistency. The AHP has been used in various fields of decision-making including risk assessment (15), environmental decision-making (16), resources planning (17), and conflict management (18). The AHP determines the priorities of each alternative by analyzing judgmental matrices using the mathematical theory of eigenvalues and eigenvectors. The process assigns an importance value, or weight, through the use of a judgmental pairwise matrix (14). 1. Development of AHP. To develop an AHP model, the first step is to construct the problem into a hierarchy structure. Generally, on the top level, the overall goal of the problem is defined, and on the second level, the characteristic factors or criteria that contribute to achieve the goal are identified. At the bottom level, alternatives that are to be evaluated in terms of the criteria on the second level are located (19). The AHP can be performed by relevant stakeholders (an individual person or a group of persons) who have appropriate knowledge on the specific project (final goals, characteristic factors, and alternatives for the specific project). The relative importance of each characteristic factor is quantified by using a numerical fundamental scale, from 1 to 9, to compare among the factors. The results of this comparison are expressed in a square pairwise matrix. According to the importance, when two compared activities are equally important, the scale of 1 is assigned; the scale of 9 is assigned when one factor is extremely important relative to the other. 2. Construction of Pairwise Matrix. The comparison of the relative importance of each characteristic factor, using fundamental scales, is expressed as a pairwise matrix, Aw ) λmax w where λmax is the largest or principal eigenvalue and w is the eigenvector, which has a value less than 1, of matrix A. This is a well-known eigenvalue problem. The eigenvectors provide the priority ordering, and these vectors act as weighting factors at a later stage in AHP, and the eigenvalue is a measure of the consistency of the judgment (20) 374
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The result of the quantified judgment on pairs of activities i, j are represented by an n × n square matrix,
A ) (aij), i, j ) 1, 2, 3,......., n
(1)
The element aij is defined as the positive number indicating the relative importance of each activity and n is the size of the pairwise matrix or number of characteristic factors. The square matrix A is reciprocal and the elements of the principal diagonal of the matrix are 1s. An aij represents the importance of activity i over j, and ajk represents the importance of activity j over activity k, and aik, the importance of activity i over activity k, must equal aijajk ) aik for the judgment to be consistent. The alternatives that are to be evaluated are quantified and compared with respect to each of the other characteristic factors using the same logic. This step yields n square matrices according to the number of characteristic factors. Finally, by combining the previous two steps, the final result provides guidance for making a decision among alternatives. During this stage, the eigenvalues for the characteristic factors act as weighting factors. This approach allows the development of an additive weighted score that can be expressed as an overall priority value, for which a higher value is preferred
Overall_Priority ) A_P1·F1 + A_P2·F2 + ‚ ‚ ‚ + A_Pn·Fn ) n
∑A_P ‚F i
i
(2)
i)1
where A_Pi ) the priority vector (eigenvector) for each alternative and Fi ) the priority vector (eigenvector) for each characteristic factor. 3. Calibration of Pairwise Matrix. In the application of this method, aij is not an exact value, but rather a value determined by subjective judgment, such as to represent the values of stakeholders or decision makers. Because of the uncertainty associated with this assertion, it is possible that the aij values will not be consistent across different decisionmaking exercises. The consistency in a positive reciprocal matrix reflects the requirement that its maximum eigenvalues λmax should be equal to n, i.e., when, if, and only if λmax ) n (19). It is possible to estimate the departure from consistency. The variance or error incurred in estimating aij can be expressed as a consistency index (CI, see Supporting Information). The measure of inconsistency can be used to successively improve the consistency of judgments in the pairwise matrix. The consistency ratio (CR) is obtained by comparing the CI with an average random consistency index (rci) derived from a sample of randomly generated reciprocal matrixes using the scale from 1 to 9. The CR indicates the degree of inconsistency, involved during comparison of each activity, and an inconsistency (CR value) of 10% or less indicates that the adjustment is small compared to the actual values of the eigenvector entries and the degree of inconsistency is acceptable (19, 20). The CR can be expressed as follows:
CR ) (CI/random_consistency_index)
(3)
Case Study Toxic Release Inventory Data. In accordance with EPCRA, each facility that has a TRI regulated substance must report annually to the U.S. EPA the total amount of toxic chemicals that it releases, either accidentally or as a result of routine plant operations, or that is transported as waste to another location for treatment (21). TRI data are published annually, and they can be used as a distal indicator of public exposure
FIGURE 1. Total toxic waste generation over time in California, Massachusetts, Oregon, and New Jersey for the electronic and electrical industries.
FIGURE 2. Distribution in toxic waste management methods in California and Massachusetts (percent basis). Treatment: destruction as the result of a catastrophic event, remedial action or other (21). to toxic materials. Changes in reported values over time (i.e., trends) can be used to gauge industrial efforts to minimize toxic waste (8). The trends in TRI data for California, Massachusetts, Oregon, and New Jersey from 1991 to 2003, reported for the electronic and electrical industries (SIC code 36), were analyzed (Figures 1 and 2). It is clear that the amount of toxic waste reported declined over the time period only in California and Massachusetts. Therefore, the focus for further analysis was narrowed to these two states. The generation of toxic waste in Massachusetts decreased 79% (4,884 tons) and that in California decreased 65% (19,852 tons) from 1991 to 2003. The percent decrease is somewhat larger in Massachusetts than in California. For the electronics and electrical industries, the distribution in toxic waste management methods for both states, averaged over the time period of 1991 to 2003, is presented in Figure 2. There are significant differences in how these two states manage toxic waste. In California, recycling is the primary method for managing toxic waste (approximately 55% of total generated waste is recycled), whereas in Massachusetts, treatment (detoxification) is the primary method. Energy recovery is used to a small extent in both states. In Massachusetts, approximately 2.5 times as much toxic waste is (on a percentage basis) released to the environment. The data presented in Figures 1 and 2 indicate that the Massachusetts TURA enacted in 1989 can be associated with reduction in the generation of toxic waste. However, during the same time period, California also reduced toxics, although to a lesser extent, without TURA-type legislation. Between 1991 and 2003, the electronic and electrical industries reported the use of 33 chemicals in Massachusetts, compared to 45 chemicals in California. Electronic and Electrical Industries in California and Massachusetts. The goals of the TURA in Massachusetts are to promote pollution prevention, with a focus on the use of
toxic chemicals and the generation of toxic wastes in the manufacturing process, and to enhance the economic viability of firms (7). Figure 3a shows comparisons of the number of establishments in the electronic and electrical industries in California and Massachusetts, based on the North American Industrial Classification Standard (NAICS; 1997 and 2002 data) and Standard Industrial Classification (SIC; 1992 data). These data do not include the computer industry codes (22, 23). Figure 3b shows the employment of individuals in the electronic and electrical industries (22, 23). California has more than four times the number of employees in the electronic and electrical industries as Massachusetts. Figure 3c shows the value of shipments of electronic and electrical products over time in California and Massachusetts (22, 23). Similar to the trend in the number of establishments and the number of employees, 1997 shows the highest values. The California data indicate a sharp increase in value of shipments between 1992 and 1997, from $35 billion to $113 billion, and it shows a decrease to $99 billion in 2002. Also, Massachusetts shows an increase in value of shipments from $10 billion to $23 billion, in 1992 and 1997, respectively, with a decrease to $20.5 billion in 2002. As can be seen from Figure 3a-c, the size of the electronic and electrical industries (the number of establishments, the number of employees, and the value of shipments) is much larger in California than in Massachusetts. Also, over the past decade, these industries have grown.
Results The Hierarchy Structure for the Case Study. To answer the question of whether the State of California would benefit from TURA-type legislation to decrease toxic waste generation while promoting an economically viable industry, the AHP was used to analyze decision matrices using the mathematical theory of eigenvalues and eigenvectors (20). The group of VOL. 41, NO. 2, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 3. (a) Number of establishments in the electronic and electrical industries, over time, in California and Massachusetts. (Establishment: An establishment is a single physical location at which business is conducted and/or services are provided. It is not necessarily identical with a company or enterprise, which may consist of one establishement or more (22).) (b) Number of employees in the electronic and electrical industries, over time, in California and Massachusetts. (c) Value of shipments in California and Massachusetts in the electronic and electrical industries during the period 1992-2002. . experts consisted of the authors of this paper, who represent a broad range of expertise including environmental, materials, chemical, and electrical engineering, as well as microbiology and public health; the perspective taken was that of an environmental legislator. The goal of the hierarchy structure is defined as “Develop TURA in California to decrease toxic waste and promote economic strength.” (Figure 4). The authors chose eight characteristic factors that affect this goal (the second level): Public health, Minimize waste, Treatment cost, Energy recovery, Waste recycling, Amount released, Compliance reporting, and Government support. “Public health” is an indicator of whether each state has legislation in place that is designed to protect public and environmental health from toxic materials. “Minimizing waste” is evaluated on the basis of historical performance in reducing toxic waste. “Treatment cost,” “Energy recovery,” “Waste recycling,” and “Amount released” are also evaluated on the basis of historical performance. “Compliance reporting” reflects the adverse 376
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impacts on industry regarding the expenditure of time and funds needed to comply with TURA-type environmental regulations, and “Government support” reflects the degree of institutional support provided by the state government for compliance with regulations. Finally, the third level indicates the two alternatives: California’s current approach (no TURA) and Massachusetts’ current approach (TURA), referred to hereafter simply as “California” and “Massachusetts”. The matrix of pairwise and weighted comparisons of the eight characteristic factors in this case study is shown in Table 1, along with the resulting vector of priorities (eigenvectors, w), λmax , consistency index (CI), and consistency ratio (CR). The judgments are entered using the fundamental scale (20), and have been determined from the point of view of legislative authorities. The vector of priorities is the principal eigenvector of the matrix so that these priorities are unique to within multiplication by a positive constant. Each number in the first
FIGURE 4. Decomposition of the problem into a hierarchical structure.
TABLE 1. Matrix of Pairwise and Weighted Comparisons of the Characteristic Factorsa characteristic factor
1
2
3
4
5
6
7
8
eigenvector
1. Public health 2. Minimize waste 3. Treatment cost 4. Energy recovery 5. Waste recycling 6. Amount released 7. Compliance reporting 8. Government support
1 1/2 1/8 1/3 1/5 1/4 1/9 1/5
2 1 1/6 1/4 1/3 3 1/7 1/3
8 6 1 2 4 6 1/2 3
3 4 1/2 1 3 3 1/2 2
5 3 1/4 1/3 1 5 1/3 3
4 1/3 1/6 1/3 1/5 1 1/7 1/5
9 7 2 2 3 7 1 3
5 3 1/3 1/2 1/3 5 1/3 1
0.32 0.17 0.03 0.06 0.08 0.23 0.03 0.09
a
λmax ) 8.77, CI ) 0.11, CR ) 0.08.
TABLE 2. Matrices Comparing the Alternatives of “California” (CA) and “Massachusetts” (MA) with Respect to the Eight Characteristic Factors. Public health CA MA
CA 1 2
MA 1/2 1
eigenvector 0.33 0.67
Minimize waste CA MA
CA 1 2
MA 1/2 1
eigenvector 0.33 0.67
Treatment cost CA MA
CA 1 1/4
MA 4 1
eigenvector 0.80 0.20
Energy recovery CA MA
CA 1 1
MA 1 1
eigenvector 0.5 0.5
Waste recycling CA MA
CA 1 1/7
MA 7 1
eigenvector 0.88 012
Amount released CA MA
CA 1 1/9
MA 9 1
eigenvector 0.90 0.10
Compliance reporting CA MA
CA 1 1/2
MA 2 1
eigenvector 0.67 0.33
Government support CA MA
CA 1 3
MA 1/3 1
eigenvector 0.25 0.75
row matches with the characteristic factor in the first column (see Table 1). Table 1 shows that the largest eigenvalue, λmax , is 8.77, the consistency index is 0.11, and the consistency ratio is 0.08. The value of the consistency ratio is less than 0.1, which indicates good consistency in the assigned factor values (20, 24). The matrix results indicate that among the characteristic factors Public health shows the largest weighting value (eigenvector), 0.32; the second largest weighting value is Amount released, 0.23; and Treatment cost and Compliance reporting show the smallest weighting value, 0.03. Table 2 shows the pairwise comparison of “California” and “Massachusetts” with respect to how much one alternative is better than the other in satisfying each criterion in the characteristic factors (see Figure 4). There are eight 2 × 2 matrices of judgment, as the two states are compared for each factor. These eight matrices
contain judgments, with eigenvectors, that are based primarily on the historical TRI data (total toxic waste amount and toxic waste management practices in the electronic and electrical industries), from 1991 to 2003, for California and Massachusetts presented above. AHP Results. The vectors of priorities (eigenvectors) for the two alternatives, i.e., “California” and “Massachusetts”, which are obtained in each of the eight matrices (see Table 2), are multiplied (weighted) by the priority of the corresponding characteristic factors (see Table 1). The results of these operations are summed to yield the overall priorities of “California” and “Massachusetts” (Table 3). A higher overall priority value is preferred. The overall priority value for “California” is 0.51 and for “Massachusetts” is 0.40. These results indicate that within the electronic and electrical industries, toxic waste management practices in California are better than those in Massachusetts. VOL. 41, NO. 2, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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TABLE 3. Overall Priorities of “California” and “Massachusetts” Relative to Toxic Waste Management Practices in the Electronics Industry (Higher Value Is Preferred)
CA MA
Public health
Minimize waste
Treatment cost
Energy recovery
Waste recycling
Amount released
Compliance reporting
Government support
Overall priority
0.11 0.21
0.06 0.11
0.03 0.01
0.03 0.03
0.07 0.01
0.21 0.02
0.02 0.01
0.02 0.06
0.51 0.40
Discussion To develop a recommendation with respect to the merits of establishing generic toxic use reduction legislation in California, key features of the electronic and electrical industries, and historical trends in toxic waste generation and toxic waste management, have been compared for California and Massachusetts. Using AHP to calculate the importance values, further comparison has been presented relative to the ability of each state to satisfy the goal of the case study, i.e., to decrease toxic waste generation in the State of California and, at the same time, allow the electronics industry to thrive. In the time period 1992 to 2003, the size of the electronic and electrical industries in both states increased, with more significant growth in California. The value of shipments in California in 2003 in these industries increased 3-fold relative to the value in 1992; the increase in Massachusetts was only 2-fold. The states that have TURA-type laws (MA, NJ, and OR) have technical assistance programs for companies to help them reduce their toxic waste generation and use of toxic substances, but, despite Proposition 65, California does not. According to the historical TRI data, the amount of toxic waste generated in the electronic and electrical industries decreased from 1991 to 2003 only in California and Massachusetts, even though Massachusetts, Oregon, and New Jersey had TURA-type legislation. In California, recycling is the primary method for managing toxic waste, whereas in Massachusetts, treatment is the primary method. But, in Massachusetts, approximately 2.5 times as much toxic waste (on a percent basis) is released to the environment. The results of the Analytic Hierarchy Process indicate that California’s current methods show a higher overall priority value than those in Massachusetts (Table 3), however, there are notable differences across the categories evaluated. For example, Massachusetts’s policies scored higher in the categories of “Public health”, “Waste minimization”, and “Government support”; whereas California’s current strategy supported higher scores in the categories of “Treatment cost”, “Waste recycling”, “Low amount of waste released into the environment”, and “Compliance reporting”. Both states scored equally in the category of “Energy recovery”. Taken together, these scores imply that although there may be tangible benefits of generic policies such as TURA, they may be expensive and require intense levels of government oversight. Given the extent of toxic use reduction in the electrical and electronic industries in California without TURA-type legislation, it is recommended that such resources be utilized to better implement existing legislation (e.g., Proposition 65) rather than to create and establish additional generic legislation. Studies have shown, for instance, that increasing public awareness is particularly important in the campaign to minimize waste (25). Thus, California could do more to increase educational programs targeted at improving engagement with Proposition 65. Furthermore, the categories of chemicals included in the list could be broadened, and government efforts could be intensified to make the public more familiar with the epidemiological constraints guiding the association of cause and effect in terms of exposure to toxic materials and the recognition of symptoms. 378
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Industry-specific legislation is an alternative approach that could lead to more waste minimization, recycling, less environmental releases, and compliance reporting than a generic toxic use reduction campaign. The State of California can provide an excellent case study for future comparison, as the State has recently passed a set of initiatives that target the environmental concerns related to toxic substances in electronic products. Under California’s Restriction on the Use of Certain Hazardous Substances in Some Electronic Devices (Cal-RoHS) (26), beginning in 2007, a California law will ban the sale of some electronic devices, particularly computer displays, which contain certain hazardous substances. This mandate is part of California’s Electronic Waste Recycling Act (CEWRA) (27), signed into law in September of 2003, and is a derivative of the European RoHS Directive (28). In additive, the State declared cathode ray tubes (CRTs) and consumer electronic devices as Universal Waste in 2001 and 2003, respectively, (29) with full implementation just begun (February 9, 2006) (30). A third piece of legislation, AB 2901 (31), established in 2004, requires less toxics in cell phones and cell phone retailers to take back used cell phones for recycling free of charge to the customer. Retailers are required to report to the California Integrated Waste Management Board on their recycling plan. This law was scheduled to go into effect on July 1, 2006. The recent implementation of these new laws governing electrical and electronic products in California will provide an opportunity to further analyze the effectiveness of different policies for toxics waste reduction across regional and international boundaries. Similar recent initiatives in the EU could also provide another opportunity to evaluate the effectiveness of industry-specific legislation. Such analyses, however, will require detailed quantitative data, which necessitates the establishment of an effective monitoring and tracking system not currently available within the State of California.
Acknowledgments Financial support was provided by the California Policy Research Center, Project DNN06A, and the National Science Foundation, Grant CMS-0524903.
Supporting Information Available More information on detailed AHP construction and calculations for the matrices. This material is available free of charge via the Internet at http://pubs.acs.org.
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(19) Saaty, T. L.; Vargas, L. G. Model, Methods, Concepts & Application of the Analytic Hierarchy Process; Kluwer Academic Publishers: , 2001. (20) Saaty, T. L. The Analytic Hierarchy Process; McGraw-Hill: New York, 1980. (21) United States Environmental Protection Agency (USEPA). Toxic release Inventory Program; http://www.epa.gov/tri/tridata (Accessed July 2005). (22) U.S. Census Bureau. 2002 Economic Census: Manufacturing; http://www.uscensus.gov. Released date: 03.2004. (23) U.S. Census Bureau. 1997 Economic Census: Manufacturing; http://www.uscensus.gov. Last modified date: 03.2004. (24) Saaty, T. L. Fundamentals of Decision Making and Priority Theory; RWS Publication: , 1994. (25) Saphores, J.-D.; Nixon, H.; Ogunseitan, O. A.; Shapiro, A. A. Household Willingness to Recycle Electronic Waste: An Application to California. Environ. Behavior 2006, 38, 183-208. (26) California Department of Toxic Substances Control. Electronic Hazardous Waste (E-Waste); http://www.dtsc.ca.gov (Accessed Mar 2006). (27) California Electronic Waste Recycling Act. (28) European Council. Directive 2002/95/EC of the European Parliament and of the Council of 27 January 2003 on the restriction of the use of certain hazardous substance in electrical and electronic equipment. Official J. European Union L 37/ 19-L37/23. (29) California Department of Toxic Substances Control. Final Text of Regulations: Electronic Hazardous Waste Regulation; Department Reference Number R-01-06. (30) California Department of Toxic Substances Control. Fact Sheet. June 2003. Managing Universal Waste in California; California Department of Toxic Substances Control: , 2003. (31) California State Legislature. Assembly Bill No 2901.
Received for review March 28, 2006. Revised manuscript received October 26, 2006. Accepted October 30, 2006. ES060739U
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