2016 Waste Characterization Analysis

Transcription

1 Final Report 2016 Waste Characterization Analysis Pierce County Planning and Public Works Pierce County, Washington

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3 2016 Waste Characterization Analysis Pierce County Table of Contents Executive Summary Section 1 METHODOLOGY Selection of Generator Types Selection of Sampling Period Determination of the Number of Samples Selection and Alignment of Solid Waste Categories Description of the Sorting Location Materials and Equipment Organization of the Field Team Preparation of the Data Collection Sheets Preparation of the Health and Safety Plans Performing the Required Field Activities Selection of the Solid Waste Loads Selection of the Sample Cells Performing the Sort Visual Audits Data Management and Statistical Analysis Section 2 CONSIDERATIONS AND ASSUMPTIONS Considerations and Assumptions Section 3 RESULTS Results Residential Sector Results Commercial and Self-Haul Sector Results Efficiency Sector Results Comparison to 2014 and 2015 Waste Characterization Analysis Top 10 Recyclable, Recoverable and Avoidable Materials Key Conclusions

4 List of Appendices A...Detailed Results Tables B... Material Definitions List of Tables Table 3-1 Tonnage Allocation per Sector Table 3-2 Countywide Aggregate Results Table 3-3 Comparison to 2014 Study Aggregate Material Group Table 3-4 Comparison to 2014 and 2015 Study Residential Sectors Table 3-5 Comparison to 2014 and 2015 Study Commercial & Efficiency Sectors Table 3-6 Top 10 Recyclable Materials List of Figures Figure 1-1. Sample Grid Figure 3-1. Countywide Aggregate Results Figure 3-2. Residential Single Family Sector Results Figure 3-3. Residential Multifamily Sector Results Figure 3-4. Residential Self-Haul Sector Results Figure 3-5. Commercial Sector Result Figure 3-6. Commercial Self-Haul Sector Results Figure 3-7. Efficiency Sector Results

5 EXECUTIVE SUMMARY Statement of Purpose The purpose of this analysis is to provide an annual report of the makeup of our waste stream so that we can use the information to help evaluate our current programs and develop new ones. This falls in line with our recently completed Supplement to the Solid Waste Management Plan in which we have made a commitment to increase reduction, recycling and reuse as much of the waste stream as possible. This annual waste sort and analysis is a major component of the measurement goal and are in the Supplement as annual projects. The idea behind that is to collect and then use several year s data to determine trends that are beginning within our waste stream so we can adapt quickly and efficiently to make sure that we are staying proactive to reduce and recycle when possible. This report provides a comprehensive summary of the data collection process, field operations, data analysis and results of this study broken down by sector and aggregate. Process and Factors We continued to use the six waste generation sectors that we targeted in 2014and 2015; Commercial, Residential Single Family, Residential Multifamily (or Apartment Compactors), Self-Haul Residential and Commercial and Efficiency (a combination of Commercial, Multifamily and Single Family Residential). The samples chosen from these sectors were all randomly selected from all the possible routes in Pierce County. Once determined, these routes were then scheduled throughout the three week sort. This Waste Characterization was concentrated to Hidden Valley, Purdy and Fife Transfer Stations. As is the case with the target sectors, we have also chosen to use the same time period to achieve maximum consistency across the board when we start to analyze the data for trends. The time period was late summer, specifically July 25 th through August 13 th. The timing was chosen for stability in the waste stream. This time of year has the least amount of fluctuations due to holidays or spring cleanups. The process for this sort was the same as The planning process again included lengthy discussions about material categories, supply lists, staffing and setup for sorting. We targeted 180 samples, again for year to year consistency, of which we sorted 179. This included 49 self-haul sorts, 22 Residential and 27 Commercial, in which a visual and physical sort (when needed) were performed. Of these 179 sorts, approximately 38% came from Purdy and Fife, where they were weighed, before being transported to Hidden Valley for sorting. This year we found an error in our process. The error was in the statistical makeup of our Sample Allocation Model and did not account for some Commercial waste being reported with Residential waste in the historical tonnages. We are adjusting the mix over two years to correct the error. In 2017, our samples will match the true composition of the County Waste Stream. The following table shows the actual mix of the overall County Waste Stream along with the distribution of our samples: Year Residential Commercial Overall 60% 40% % 25% % 25% % 32% % 40% We also made an adjustment to the 2015 Waste Trends Analysis Report to accurately reflect some over-reporting of 30,000 tons from one of our haulers.

6 EXECUTIVE SUMMARY Results The results in detail are included in Appendix A. The results are broken down by each of the 68 categories. These categories all fall within 8 main groups; Paper, Plastic, Glass, Metal, Organics, C&D Waste, Hazardous Waste and Other Waste. The Aggregate of this year s sort is broken down with Organics making up 23%, Paper 18%, Other Waste 18%, C&D Waste at 17%, Plastic at 12%, Glass 6%, Metal 5% and Hazardous Waste 1%. The estimate for tons of waste disposed for this year is 380,000 tons. We believe that just over tons (44%) is potentially recyclable. There is also a side by side comparison with the last two year s data included, with the caveat that we are not making any conclusions or assumptions based on only two years worth of data about a possible trend.

7 Section 1 METHODOLOGY This waste characterization analysis encompassed randomly selecting solid waste samples from vehicles disposing of waste in Pierce County, Washington. These samples were collected from residential and commercial/industrial entities from various parts of the County. Each sample was then hand sorted into 68 material categories. The list of material categories was initially developed based on the material categories that were used in the 2010 Waste Characterization Study, conducted by R. W. Beck. This list was then revised based on discussions with our staff that included descriptions of solid waste materials currently being reported as being collected by the our recyclers, drop-off centers and buyback centers and future solid waste materials that the we would like to be able to track. All of the sort activities were performed with a detailed safety plan and safety equipment procurement plan to achieve a healthy work environment for the sort manager, the sample manager and crewmembers. The waste sort for this analysis was planned and executed according to the following steps: Selection of generator types; Determination of the number of samples; Selection of the solid waste categories; Description of sorting location; Procurement of the equipment; Organization of the field team; Preparation of the data collection sheets; Preparation of the health and safety plans; and Performing the required field activities. These planning elements are discussed in detail below. Data management and analysis methods are also summarized briefly. Selection of Generator Types Based on the generation types used in the 2014 Waste Characterization Analysis, we evaluated the following: Residential Generator Types: Single Family Residential; Multifamily Residential; Self-Haul Residential. Commercial/Industrial Generator Types: Self-Haul Commercial/Industrial; and Commercial/Industrial Waste Transported in Commercial Packer Trucks and Roll-off Containers. Efficiency (Commercial and Multifamily combined) All of these generator types have been accounted for in the waste characterization sort. 1-1

8 Selection of Sampling Period The waste sort field activities were conducted during a three week period from July 25 through August 13. The selection of sampling timing was made to mirror that of the 2014 and 2015 waste sorts in order to provide consistency, while taking the budgetary constraints of the overall project into consideration. The sampling period was selected based on the time of year in which yard waste quantities are likely to be at consistent levels and other seasonal and holiday variations in waste composition are negligible. Determination of the Number of Samples The number of samples that were chosen was based entirely on the 2014 waste sort. As with the sampling period, we took the same 180 sample target to provide consistency from year to year. Selection and Alignment of Solid Waste Categories The list of solid waste material categories used in this sort, along with the material category descriptions, is contained in Appendix B. This list was initially developed based on the material categories that were used in the 2010 Pierce County Solid Waste Characterization Audit, conducted by R. W. Beck and then revised based on various issues related to current and future materials being collected and needing tracking. Description of the Sorting Location The waste sorting occurred at Hidden Valley. The sorting site was located on the south side of the transfer station sufficiently close to the tipping area to allow ease of sample collection and disposal (after sorting) and other logistics. The sorting site was far enough from the facility s operations to ensure crew safety. Certain aspects of the transfer station operation during the sort were collaboratively managed by County officials and Pierce County Recycling, Composting and Disposal, LLC dba LRI as follows: A telephone only for emergency use by the sort supervisor and sort crew, was located in LRI's offices; The sort area was selected by LRI and county employees so that it was inside the transfer building near the tipping floor, but far enough away to ensure safety; and Traffic cones were provided by LRI to be placed around the sorting area to enhance the safety of the sorting crew. Close coordination was required between each entity to ensure that fieldwork was completed efficiently and with minimum disruption to normal solid waste operations. Materials and Equipment We provided the sample scale and other supplies and transported them to the sorting site. The scale used during the sorting event was digital and graduated to the nearest two tenths of a pound. Organization of the Field Team The sort manager was a county staff member. The primary responsibilities of the sort manager were: Make arrangements for supplies; Conduct training sessions covering health and safety procedures and gear; Oversee sort crew health and safety; 1-2

9 METHODOLOGY Oversee all sorting operations; Perform quality control checks during sorting activities; Clean the sorting site at the completion of the day; and Collect, as necessary, debris, which had blown from the sorting area into the surrounding area. The sample manager was also a county staff member. The primary responsibilities of the sample manager were: Supervise sample selection; Collect samples from other sites; Record all information on the data collection sheets; Perform visual audits of self-hauls; Perform quality control checks during sampling and recording activities; and Backup the sort manager for crew health and safety, cleaning the sort area and collecting debris blown from the sorting area. We hired seven extra hires to conduct the waste sort in Preparation of the Data Collection Sheets Data sheets used in connection with the field sorts were as follows: Sorting form with a list of material categories; Material categories definition form; Sample selection forms. These forms were brought by the sort manager to the sorting site each day. Preparation of the Health and Safety Plans During the study, the safety of the sort manager, sample manager, sorting crew and others who visited the sorting site was a top priority. Prior to the first sort, the safety plan was provided to all supervisors, managers and sorters. The safety plan included a discussion of safety procedures designed to help protect workers from potential hazards and enhance their comfort during the sorts. First-time workers were trained before they were allowed to begin sorting and each worker was required to sign a Sorter Training Acknowledgement Form verifying that they received training. In addition, all sorters were given daily instruction and reminders on safety procedures after the sorts began. Prior to beginning the waste sort, the sort manager and sample manager received first aid and CPR instruction. Personal protection equipment was worn by the supervisor, manager, crew and any visitors at all times during the sort. Proper use of the equipment was demonstrated by the supervisor and manager during the initial training sessions. Once the supervisor determined that no hazardous materials were present, the sorters were instructed to begin sorting. During the training sessions, the crew was educated on the potential hazards which might be encountered in the solid waste, such as syringes, needles, glass, explosives and other special or hazardous wastes. The sorting crew was instructed daily to: Always listen for instructions from the supervisor; Wear appropriate Personal Protective Equipment PPE; Not work under the influence of intoxicants or narcotics; 1-3

10 Never touch what cannot be seen; Always walk around a pile of solid waste, not through it; Be aware of heavy machinery; Watch carefully for medical waste; Be aware of heat stress and heat exhaustion; Lift a maximum of 75 pounds; Remove safety clothing and wash hands prior to eating and drinking; Handle hazardous waste as instructed in the safety plan handout; Inform the supervisor and immediately evacuate the area in the event of fire; and Contact the supervisor immediately in the event of a puncture wound, or if any object or liquid came in contact with the eyes. Performing the Required Field Activities Field implementation of the sampling plan involved work at the sorting site. Field implementation included: Selection of Solid Waste Loads; Selection of the Sample Cells; and Performing the Sort. Selection of the Solid Waste Loads The method of selecting routes for sampling depended on whether the samples originated from the haulers' trucks or from self-hauled vehicles. The procedures for selecting vehicles are discussed below: SAMPLES FROM COMMERCIAL HAULERS' ROUTES. Residential Single Family, Residential Multifamily, Commercial and Efficiency samples were selected from commercial haulers' routes using a random number generation procedure that ensured that the selected routes were inherently random. A complete listing of each route by sector and hauler, including the location of each route for all county routes was used to produce area-specific route allocation factors that, when combined with the generating sector apportionments for sample totals, resulted in area-specific sampling goals by generating sector. This direct, route-oriented approach provides more direction to haulers as to which specific route loads to set aside for sampling and ensures that a representative cross section was sorted. Once the area goal was determined, a cross-section of routes within that area was selected and sample counts were apportioned to those routes. These routes were then cross-referenced back to the data to develop a daily logistics plan that summarized which routes had been selected for sorting on that day. Planning the logistics involved carefully determining daily sample goals in order to maximize the efficiency and representative nature of the sort. The schedule was developed to take into account the number of samples, which needed to be sorted on a daily basis, along with the number of self-haul samples, which needed to be sampled daily. SELF-HAULED SOLID WASTE. There were 22 self-haul residential loads and 27 self-haul commercial loads sampled during the sort. Sample totals for residential and commercial self-haul loads were developed from a combination of historical tonnage data, generally for the years 2011 to 2014 and supplemental transfer station data. Residential and commercial self-haul samples were collected at both Purdy (and transferred) and Hidden Valley. 1-4

11 METHODOLOGY Selection of the Sample Cells Once a selected load arrived at the sorting site, it was directed to the tipping floor close to our setup, where the entire load was dumped. Then, a 200 pound sample was randomly selected from each load. This was accomplished by using a numbered grid system. An imaginary grid of 6 cells was "placed' over each load. Each cell represents a certain location and volume within each load. The grid is pictured in Figure 1-1 below. The sample manager then randomly picked a number 1-6 that corresponds with the grid schematic to determine the location of the selected cell in the grid. For example, cell number 6 is in the back third on the right-hand side of the load. Figure 1-1. Sample Grid Sample managers found that some randomly selected portions included bulky items, such as large appliances or furniture. The presence of bulky items is a random occurrence because the portion of the tipped load is randomly selected. Because these bulky items are too large to be put into a tote, they were manually set aside and weighed separately. The weight of the bulky item and a description of the item were recorded on the Sample Management Form. The bulky item was then returned to the tipping floor. Samples were collected, as deemed appropriate, by use of a loader or manually to fill carts with waste material. After the sample was acquired, each cart was weighed to be sure the total weight of each sample met the minimum weight. After the weight was confirmed, the transfer station s loader operator scooped the remainder of the tipped load as normal in the course of their duties. A label showing the date the sample was acquired and sample number were attached to each cart. The Sample Manager also completed a Sample Management Form for each sampling unit. Samples to be acquired at Purdy and Fife underwent the same process, except for transportation. All samples acquired at Purdy and Fife were weighed and labeled at the transfer station and then transported to Hidden Valley, where they were unloaded and positioned for sorting. After a sample was acquired, it was weighed, labeled and prepared for sorting. Weather, operational changes and human error sometimes produced some uncertainty about collecting the targeted number of samples, therefore back-up samples were occasionally needed and sorted to be sure a minimum number of samples were included. 1-5

12 Performing the Sort After the sample is selected and weighed, the material is placed on the sort table by the sort crew. Surrounding the sort table are containers labeled with each of the 68 material categories. The labels are color coded by material group to ensure that each material group is placed together for easy sorting and to help with the reset of containers between each sample. Each of the sort crew members are responsible for collecting and properly sorting one or more material group. For instance, one crew member may be in charge of glass and plastic. Any glass or plastic item on the table will be passed to this crew member to sort into the appropriate sub-category container, which is located in close proximity. The sort crew works as a team to separate the material and pass the material to the appropriate person. After all of the material is sorted into the proper containers, the sort manager positions themselves near the scale for the weighing out of the sample. The sort crew moves all of the containers that have material in them to the scale. The sort manager weighs out each of the containers and collects the weight of each material. During the weigh-out, the sort manager checks each of the containers to verify that the correct material was placed in each container. All samples are weighed before and after being sorted to provide a comparison (or check) to the amount of material weighed after sorting. This process is replicated for each of the samples collected during the study. Visual Audits Visual audits were conducted on self-haul routes if the Sample Manager determined that the load was open enough such that a visual audit would sufficiently capture the nature of the waste. Volume was estimated for such loads. We then combined these estimates with density factors for each specific type of material in order to transform the sample results into a by-weight composition sample and make these samples comparable to the physically sorted loads. Data Management and Statistical Analysis Data collected in the field was entered into a custom statistical results model. The data was subjected to a rigorous quality control process, in which every data point on the forms was manually checked by a person that did not perform the data entry. Automated checks were not used as a substitute for meticulous checking of the reasonableness and sensibility of each individual observation. Once the data was entered the average composition and 90 percent confidence interval for composition results was computed. This confidence interval provides a high/low range, whereby there is only a 5% chance that the true composition is above the high value and a 5% chance that the true composition is below the low value. 1-6

13 Section 2 CONSIDERATIONS AND ASSUMPTIONS Considerations and Assumptions The conclusions drawn from data collected in this study are derived from a carefully designed and implemented sampling and logistics plan. Additionally, multiple layers of quality control filters have been applied to the data to help mitigate the impact of recording or field errors from having an adverse impact on the study results. There are certain considerations and assumptions that must be reviewed carefully when interpreting the results of this study, both with regard to the results and the associated annual tonnage estimation results, which are as follows: All data provided to us for purposes of planning sample collection, including hauler route data and tonnage estimates, are assumed to be accurate based on the expertise of the respective providers. Staff sampled a cross-section, or snapshot in time, of waste generation in Pierce County. The estimates presented are indicative of conditions in the present and near future only. They are not valid for an indefinite period in the future. The results presented should not be used as a predictive tool for an estimate of the waste stream for an area broader in geography than the County (ex: the state of Washington). More extensive sampling at more locations in a broader geographic region would be required to be able to provide a more aggregated assessment of the waste stream. It is occasionally possible for the sorting crew to attempt to focus on large items for ease of collection as well as for being of a heavier weight when gathering material to create a sample. In order to deter the sort crews from taking unrepresentative material, the sample manager weighed the sample, which helped to minimize the impact of this behavior. We took care to avoid this behavior altogether in this study by leveraging a random grid superimposed on the dumped load that directs the team to a specific part of the load. The observation process of volume estimation as well as the sorting process when samples are weighed contains several sources of potential human error, namely (i) a small amount of measurement error on load dimensions, (ii) a small amount of percent by volume error for individual observations and (iii) a small amount of error related to sorting materials into the correct sub-categories. While we have been fully trained to be precise in these measurements and highly accurate in their material assignments, the potential for the compound effect of these small errors to impact computed results should be noted. 2-1

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15 Section 3 RESULTS Results have been compiled for each individual sector, as well as for the aggregate.. Appendix A fully details the individual composition results across all of these sectors and in total. This section will detail the key findings in each type of result. Throughout the course of this sort, there were several key areas of potential diversity in the waste stream that were of interest as they pertained to being able to quantify and summarize differences. These areas drove how the study was designed and executed, namely: Waste profiles of various key generating sectors (i.e., Residential, Commercial, Self-haul, etc.); Geographic (or Area) considerations; Comparison of the current waste stream relative to the 2014 Waste Characterization Analysis. Results in this section are presented in accordance with the above-targeted areas of potential diversity in the waste stream. Results Waste disposed is broken down by ton/sector in Table 3-1based on a 60% 40% split of residential and commercial waste. We have included this table in past waste characterization studies and have determined that this table and it s calculations will be useful in determining the exact makeup of the overall residential waste stream where the majority of our programs are focused. Table 3-1 Tonnage Allocation per Sector Sector Tons % Single-Family Residential 130,998 34% Multifamily Residential % Self-Haul Residential % Commercial % Self-Haul Commercial % Other 0 0% Total 380, % Composition study results for the aggregated County waste stream is summarized in Figure 3-1. The broader material groups that the analysis is based on (i.e., Paper, Plastic, Glass, Metal, Other Organics, Yard Waste, C&D Waste, Hazardous Waste and Special waste) are shown in Table 3-2, while Appendix B provides a full description of each set of material categories. Table 3-2 also breaks down our estimate of total tonnage disposed (380,000 tons) of each material category. As part of Table 3-2, the confidence intervals are provided to show the range of estimates representing 90% of possible conditions for the actual population of waste (or all waste in the County). 3-1

16 Figure 3-1. Countywide Aggregate Results Other Waste 18% Paper 18% Hazardous Waste 1% Plastic 12% C&D Waste 17% Glass 6% Metal 5% Organics 23% 3-2

17 Material Group Mean % Table 3-2 Countywide Aggregate Results Tons Disposed 90% Confidence Interval Lower Bound Upper Bound Paper 18.48% 70, % 20.48% Plastic 12.35% 46, % 13.68% Glass 5.83% 22, % 6.74% Metal 4.70% 17, % 5.37% Organics 22.55% 85, % 25.56% C&D Waste 17.30% 65, % 21.37% Hazardous Waste 0.57% 2, % 0.69% Other 18.21% 69, % 20.45% Total 100% 380,000 The key findings related to the Aggregate County waste stream are as follows: The most prevalent type of material in the County s waste stream was Organic materials, with food waste the largest component at 12.1% of the overall waste stream. Also included in this category was Other Organic Waste, which also comprised a notable portion of the waste stream at 5.4%. Paper was still the second most prevalent category of material, but down 2% from last year, comprising 18.5% of the waste stream. The types of paper in this category were quite varied, with the predominant materials consisting of Compostable Paper (11.3%) and Cardboard and Kraft Paper (2%). The Metal, Glass and Plastic Categories combined represented approximately one quarter (23%) of the County s waste stream. Material categories such as Plastic Film (4.2%), Non Compatible Plastics (4.8%) and Clear Glass Containers (2.7%) were some of the more prevalent materials found. All 3 categories fell in percentage of overall makeup of the waste stream. C&D waste comprised about 17% of the aggregated County waste stream. This number increased as construction activity continued to rise over the last year. Residential Sector Results Composition study results for the Residential Single Family and Residential Multifamily sectors and Residential Self-haul are detailed in Figures 3-2, 3-3 and 3-4, respectively. 3-1

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19 Figure 3-2. Residential Single Family Sector Results Other Waste 20% Paper 21% Hazardous Waste 0% C&D Waste 3% Plastic 16% Organics 29% Metal 4% Glass 7% 3-1

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21 Figure 3-3. Residential Multifamily Sector Results Other Waste 18% Paper 26% Hazardous Waste 1% C&D Waste 4% Organics 22% Plastic 17% Metal 5% Glass 7% Figure 3-4. Residential Self-Haul Sector Results Other Waste 17% Paper 8% Plastic 4% Hazardous Waste 0% Glass 7% Metal 7% Organics 8% C&D Waste 49% 3-1

22 The key findings related to the Residential sector are as follows: As is true for the aggregate waste stream, organics and paper comprise the two largest categories of waste in the residential waste stream in both the single family and Multifamily sectors, exactly the same as And just like 2015, they are different in which is greater. Single family has a significantly higher makeup of Organics, while Multifamily has a greater makeup of paper. Food waste made up 18.3% of the waste stream in the Single-Family sector and 13.5% of the waste stream in the Multifamily sector. As expected, Residential Self-Haul has a much higher percentage of C&D Waste, 49%, as opposed to the other residential sectors that are both just under 3%. This is by far the largest category for Residential Self-Haul. Other waste is the next highest for Self-Haul at 17%. Plastic film and Non Compatible Plastics together comprised about 12% of the Single-Family residential waste stream, about11% of the Multifamily residential waste stream and 3% of the Residential Self-Haul waste stream. With the exception of Paper and Organics as noted above, the other categories were very similar between the two non-self-haul sectors. Commercial and Self-Haul Sector Results Figure 3-5 summarizes the composition of the Commercial sector waste stream and Figure 3-6 summarize the results of Commercial Self-Haul Waste Stream. Figure 3-5. Commercial Sector Result Other Waste 18% Paper 27% Hazardous Waste 1% C&D Waste 5% Organics 22% Plastic 16% Metal 6% Glass 5% 3-2

23 Figure 3-6. Commercial Self-Haul Sector Results Other Waste 15% Paper 3% Plastic 1% Glass 2% Metal 3% Hazardous Waste 0% Organics 20% C&D Waste 56% The key findings with regard to the Commercial and Self-Haul waste streams are as follows: Organics and Paper combined represent half of the Commercial waste stream excluding Self-Haul. Of these materials, Compostable paper led the way at 15.7% with Food waste a close 2nd at 15.6%. Much like residential, the C&D Waste for Commercial Self-Haul was expected to be much higher than anything else, contributing to 56% of that sectors waste stream. C&D Waste for Commercial is 5%, roughly 2 to 1 over Residential. 3-3

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25 Efficiency Sector Results Figure 3-7 summarizes the composition of the Efficiency sector waste stream. The Efficiency Sector is a mix of Single Family Residential, Multifamily and Commercial Sectors. Figure 3-7. Efficiency Sector Results Other Waste 20% Paper 25% Hazardous Waste 1% C&D Waste 8% Plastic 15% Organics 20% Metal 5% Glass 6% The key findings with regard to the Efficiency waste stream is as follows: Paper represents one quarter of the waste stream, with Compostable paper at 14%. As with the other sectors, Organics is in the top 2 at 20%. Food waste within this is 14.6%. C&D Waste for Efficiency is roughly the same as Commercial and Residential Combined. 3-1

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27 Comparison to 2014 and 2015 Waste Characterization Analysis We conducted a similar Waste Characterization Analysis in 2014 and 2015 and aligned both categories and time of sort to provide an apples to apples comparison as we move forward with yearly sorts. Tables 3-3, 3-4 and 3-5 summarize the results of the two studies across the major generating sectors. This is just to illustrate the way we will view annual data side by side. Table 3-3 Comparison to 2014 Study Aggregate Material Group Aggregate Paper 21.7% 20.4% 18.5% Plastic 15.8% 12.7% 12.4% Glass 5.6% 6.0% 5.8% Metal 4.0% 4.5% 4.7% Organics 23.4% 25.7% 22.6% C&D Waste 12.2% 12.8% 17.3% Hazardous Waste 1.5% 1.0%.6% Other Waste 15.9% 17.2% 18.2% Total 100.1% 100.3% 100.1% 3-1

28 Table 3-4 Comparison to 2014 and 2015 Study Residential Sectors Material Group Single Family Residential Multifamily Residential Self-Haul Residential Paper 23.1% 21.7% 20.7% 26.6% 25.7% 25.6% 19.1% 13.5% 7.7% Plastic 18.6% 15.0% 16.1% 17.3% 15.9% 16.9% 11.7% 7.5% 3.6% Glass 6.8% 7.1% 6.8% 6.2% 7.5% 6.9% 1.0% 3.2% 7.3% Metal 4.5% 4.0% 4% 5.4% 4.4% 5.5% 3.9% 5.8% 6.7% Organics 27.2% 31.3% 29.6% 20.5% 21.5% 21.7% 4.5% 23.8% 8.2% C&D Waste 3.6% 2.9% 2.7% 4.1% 2.9% 3.8% 26.4% 18.7% 49.5% Hazardous Waste 1.3% 1.0%.6% 0.7% 0.8% 1.3% 3.6% 0.5%.2% Other Waste 15.0% 17.5% 19.6% 19.3% 21.6% 18.5% 29.8% 27.0% 16.9% Total 100.0% 100.5% 100.1% 100.0% 100.3% 100.2% 100.0% 100.0% 100.1% Table 3-5 Comparison to 2014 and 2015 Study Commercial & Efficiency Sectors Material Group Commercial Self-Haul Commercial Efficiency Paper 25.0% 27.0% 27.3% 5.9% 6.2% 3.3% 25.8% 24.3% 25.5% Plastic 16.3% 14.8% 15.9% 1.5% 1.0% 1.5% 18.5% 14.3% 14.9% Glass 6.0% 7.9% 5.3% 0.1% 1.8% 1.9% 7.9% 4.7% 5.8% Metal 3.2% 3.4% 5.6% 1.9% 6.3% 2.9% 3.9% 4.5% 5.6% Organics 29.9% 26.7% 22.2% 17.4% 3.2% 19.8% 24.7% 28.0% 20.1% C&D Waste 5.6% 3.7% 4.9% 61.7% 77.1% 55.7% 3.4% 5.7% 7.7% Hazardous Waste 1.2% 0.7%.8% 0.1% 0.1% 0% 2.3% 3.2%.6% Other Waste 12.9% 16.3% 18.1% 11.5% 4.4% 15% 13.5% 15.4% 19.9% Total 100.0% 100.6% 100.1% 100.0% 100.0% 100.1% 100.0% 100.1% 100.1% We are not making any decisions based on these three years alone. We will wait for at least 5 years worth of annual data before analyzing for trends. However, some of the observations that we see (as a % of the total waste stream) are: Organics are down in all sectors except multifamily. Food waste is the driving factor of this increase. Paper consumption is down in all residential sectors for the second year. 3-2

29 Plastic consumption is up a small amount across all sectors. The amount of glass in the waste stream has gone down in all sectors. C&D Waste is down slightly in Single Family, up slightly in multifamily and has made a significant hike in the Self-Haul Residential sector. It is down in both Commercial sectors, but has increased in the Efficiency sector. It is important to keep in mind that these percentages are interrelated and a spike in one type of material in the waste stream generally translates into a decline in other materials, as a percent of total. Total waste for 2016 is higher than it was in Population has increased slightly, so disposal per capita, we are very close to the same for 2015 and The overall change in Hazardous waste is very small. As is the overall change in Metal. Both have some significant movement within some of the sectors, but they balance out in the aggregate. Top 10 Recyclable, Recoverable and Avoidable Materials Table 3-6 Top 10 Recyclable Materials 90% Confidence Interval Material Mean % Tons Disposed Lower Bound Upper Bound Food Waste 14.6% 55, % 19.9% Plastic Film 5.3% 20, % 6.3% Cardboard & Kraft Paper 4.0% 15, % 5.8% Untreated Lumber 3.8% 14, % 7.8% Clear Glass Containers 3.4% 13, % 5.0% Mixed Recyclable Paper 3.3% 12, % 4.6% Yard Waste 3.0% 11, % 6.4% Textiles & Leather 2.7% 10, % 4.0% Pop & Water Bottles & Other Bottles & Jugs 2.5% 9, % 3.1% Treated Wood Waste 1.4% 5,320.6% 2.6% Total 44.1% 167,428 Finally, Table 3-6 summarizes the Top 10 Materials in the our waste stream that could be Recycled, Reused, or Reduced. It is important to note that these materials are not necessarily the Top 10 materials in the waste stream. Rather, they are the Top 10 materials by weight when the potential for diversion of all of the materials in the waste stream is taken into consideration. Overall, these potential materials amount to just under 45% of the waste currently disposed, or about 167,000 tons disposed annually. Food waste is the biggest equating to 14.6% of the waste stream. 3-3

30 Key Conclusions The following are the key conclusions and findings of the analysis: Food waste is the largest material in the waste stream. It is estimated that more than 46,000 tons of food waste and 85,000 tons of Organics are disposed annually. Nearly 42% of all waste is comprised of Paper, Plastic, Metal and Glass. In general, the composition of waste across Sectors and Areas is relatively similar, with the obvious exception of Self-Haul waste, which is heavy on C&D material. HHW dropped to a touch over half a percent of overall waste disposed annually. That is about half of the amount from Over 44% of the waste currently disposed in the County is made up of 10 of the materials with the greatest recycling potential, totaling approximately 167,000 tons disposed annually. 3-4

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32 Appendix A 2016 Waste Characterization Analysis Detailed Results Aggregate 90% Confidence Interval Material Categories % Comp. Lower Bound Upper Bound Paper 1 Newspaper 0.48% 0.39% 0.58% 2 Cardboard & Kraft Paper 1.97% 1.66% 2.32% 3 Paperboard 1.04% 0.89% 1.21% 4 Magazine/Catalogs 0.56% 0.45% 0.68% 5 Cartons and Coated Paperboard 0.69% 0.58% 0.81% 6 Aseptic Packages 0.10% 0.08% 0.12% 7 Mixed Recyclable Paper 1.88% 1.59% 2.20% 8 Contaminated Paper 11.28% 9.93% 12.71% 9 Other Non-Recyclable Paper 0.46% 0.36% 0.58% Total Paper 18.48% 16.56% 20.48% Plastic 10 Pop and Water Bottles 0.92% 0.80% 1.05% 11 All other Bottles and Jugs 0.92% 0.79% 1.05% 12 Compatible Plastic Containers 0.60% 0.50% 0.71% 13 Non-Compatible Plastics 4.83% 4.26% 5.44% 14 StyrofoamTM 0.65% 0.56% 0.75% 15 Plastic Shopping Bags 0.21% 0.17% 0.24% 16 Plastic Film 4.23% 3.74% 4.74% Total Plastic 12.35% 11.08% 13.68% Glass 17 Clear Glass 2.68% 2.28% 3.10% 18 Brown Glass 1.10% 0.91% 1.30% 19 Green Glass 0.75% 0.61% 0.90% 20 Other Glass 1.31% 0.98% 1.68% Total Glass 5.83% 4.99% 6.74% Metal 21 Steel Cans 0.76% 0.66% 0.88% 22 Aluminum Cans 0.60% 0.51% 0.68% 23 Aerosol Cans 0.17% 0.14% 0.21% 24 Large Appliances 0.19% 0.13% 0.26% 25 Other Ferrous Metals 2.45% 2.00% 2.96% 26 Other Non-Ferrous Metals 0.52% 0.44% 0.61% Total Metal 4.70% 4.07% 5.37% Organics 27 Food Waste: Edible/Program Compatible 2.54% 2.15% 2.96% 28 Food Waste: Edible/Non-Compatible 5.50% 4.76% 6.29% 29 Food Waste: Inedible/Compatible 3.17% 2.71% 3.65% 30 Food Waste: Inedible/Non-Compatible 0.73% 0.60% 0.87% 31 K-Cups 0.25% 0.20% 0.30% 32 Yard Waste 3.65% 2.77% 4.65% 33 Land Clearing Debris 1.35% 0.87% 1.92% 34 Other Organic Waste 5.36% 4.36% 6.46% Total Organics 22.55% 19.68% 25.56% C&D Waste 35 Gypsum Wallboard 2.17% 1.54% 2.91% 36 Concrete 0.69% 0.48% 0.92% 37 Insulation 0.89% 0.61% 1.22%

33 Appendix A 2016 Waste Characterization Analysis Detailed Results 38 Carpet 2.04% 1.44% 2.74% 39 Untreated Lumber 4.22% 3.21% 5.36% 40 Treated Wood Waste 2.93% 2.29% 3.65% 41 Asphalt Roofing 2.97% 2.02% 4.11% 42 Pallets 0.03% 0.02% 0.05% 43 Other Construction Debris 1.36% 0.97% 1.81% 44 Asphalt 0.00% 0.00% 0.00% Total C&D Waste 17.30% 13.58% 21.37% Hazardous Waste 45 Paints/Adhesives 0.05% 0.04% 0.07% 46 Cleaners 0.00% 0.00% 0.00% 47 Pesticides/Herbicides 0.00% 0.00% 0.00% 48 Vehicle & Equipment Fluids 0.02% 0.02% 0.03% 49 Car Batteries 0.00% N/A N/A 50 Alkaline Batteries 0.05% 0.04% 0.07% 51 Other Batteries 0.01% 0.00% 0.01% 52 Fluorescent Light Tubes & Compacts 0.01% 0.00% 0.01% 53 Gasoline 0.00% 0.00% 0.00% 54 Explosives 0.02% 0.02% 0.03% 55 Medical Waste 0.08% 0.06% 0.10% 56 Medicine (Rx Only) 0.03% 0.02% 0.03% 57 E-Cycle Program 0.05% 0.04% 0.07% 58 All Other E-Waste 0.22% 0.17% 0.29% 59 Other Hazardous Waste 0.02% 0.01% 0.03% Total Hazardous Waste 0.57% 0.46% 0.69% Other Waste 60 Tires 0.01% 0.01% 0.01% 61 Mattresses/Box Springs 0.51% 0.36% 0.69% 62 Furniture/Bulky 2.78% 1.94% 3.76% 63 Small Appliances 0.95% 0.72% 1.21% 64 Textiles and Leather 3.35% 2.84% 3.90% 65 Diapers 3.47% 2.92% 4.07% 66 All Other Waste 4.51% 3.92% 5.13% 67 Liquids 1.24% 1.04% 1.46% 68 Fines 1.38% 1.16% 1.62% Total Other Waste 18.21% 16.07% 20.45% Total 99.99%

34 Appendix A 2016 Waste Characterization Analysis Detailed Results Residential - Single Family Cat. 90% Confidence Interval No. Material Categories % Comp. Lower Bound Upper Bound Paper 1 Newspaper 0.51% 0.39% 0.65% 2 Cardboard & Kraft Paper 0.81% 0.66% 0.99% 3 Paperboard 1.09% 0.91% 1.29% 4 Magazine/Catalogs 0.64% 0.46% 0.85% 5 Cartons and Coated Paperboard 0.59% 0.50% 0.70% 6 Aseptic Packages 0.15% 0.12% 0.19% 7 Mixed Recyclable Paper 1.64% 1.38% 1.93% 8 Contaminated Paper 14.97% 14.20% 15.75% 9 Other Non-Recyclable Paper 0.30% 0.22% 0.39% Total Paper 20.71% 19.73% 21.70% Plastic 10 Pop and Water Bottles 0.90% 0.79% 1.02% 11 All other Bottles and Jugs 1.08% 0.96% 1.21% 12 Compatible Plastic Containers 0.81% 0.66% 0.98% 13 Non-Compatible Plastics 5.80% 5.32% 6.30% 14 StyrofoamTM 0.98% 0.87% 1.10% 15 Plastic Shopping Bags 0.29% 0.25% 0.34% 16 Plastic Film 6.21% 5.84% 6.59% Total Plastic 16.08% 15.26% 16.92% Glass 17 Clear Glass 3.28% 2.91% 3.67% 18 Brown Glass 1.33% 1.07% 1.61% 19 Green Glass 1.24% 0.96% 1.56% 20 Other Glass 0.94% 0.65% 1.30% Total Glass 6.79% 6.06% 7.56% Metal 21 Steel Cans 1.11% 0.97% 1.26% 22 Aluminum Cans 0.53% 0.46% 0.61% 23 Aerosol Cans 0.22% 0.17% 0.27% 24 Large Appliances 0.02% 0.01% 0.03% 25 Other Ferrous Metals 1.26% 0.99% 1.56% 26 Other Non-Ferrous Metals 0.81% 0.64% 1.00% Total Metal 3.95% 3.49% 4.43% Organics 27 Food Waste: Edible/Program Compatible 3.86% 3.34% 4.41% 28 Food Waste: Edible/Non-Compatible 7.71% 6.97% 8.50% 29 Food Waste: Inedible/Compatible 5.21% 4.68% 5.76% 30 Food Waste: Inedible/Non-Compatible 1.03% 0.82% 1.28% 31 K-Cups 0.47% 0.38% 0.57% 32 Yard Waste 3.28% 2.38% 4.32% 33 Land Clearing Debris 0.20% 0.10% 0.32% 34 Other Organic Waste 7.78% 6.57% 9.09% Total Organics 29.55% 27.70% 31.43% C&D Waste 35 Gypsum Wallboard 0.48% 0.27% 0.75%

35 Appendix A 2016 Waste Characterization Analysis Detailed Results 36 Concrete 0.26% 0.17% 0.39% 37 Insulation 0.24% 0.13% 0.39% 38 Carpet 0.11% 0.07% 0.18% 39 Untreated Lumber 0.56% 0.41% 0.73% 40 Treated Wood Waste 0.87% 0.61% 1.18% 41 Asphalt Roofing 0.11% 0.06% 0.18% 42 Pallets 0.00% N/A N/A 43 Other Construction Debris 0.06% 0.03% 0.09% 44 Asphalt 0.00% 0.00% 0.00% Total C&D Waste 2.71% 2.06% 3.45% Hazardous Waste 45 Paints/Adhesives 0.09% 0.05% 0.14% 46 Cleaners 0.00% N/A N/A 47 Pesticides/Herbicides 0.01% 0.00% 0.01% 48 Vehicle & Equipment Fluids 0.00% N/A N/A 49 Car Batteries 0.00% N/A N/A 50 Alkaline Batteries 0.07% 0.06% 0.09% 51 Other Batteries 0.02% 0.01% 0.03% 52 Fluorescent Light Tubes & Compacts 0.00% 0.00% 0.01% 53 Gasoline 0.00% 0.00% 0.00% 54 Explosives 0.03% 0.02% 0.04% 55 Medical Waste 0.06% 0.04% 0.09% 56 Medicine (Rx Only) 0.04% 0.03% 0.06% 57 E-Cycle Program 0.00% 0.00% 0.00% 58 All Other E-Waste 0.22% 0.14% 0.32% 59 Other Hazardous Waste 0.05% 0.03% 0.08% Total Hazardous Waste 0.60% 0.46% 0.76% Other Waste 60 Tires 0.02% 0.01% 0.04% 61 Mattresses/Box Springs 0.00% N/A N/A 62 Furniture/Bulky 0.00% N/A N/A 63 Small Appliances 1.28% 0.83% 1.82% 64 Textiles and Leather 4.39% 3.80% 5.03% 65 Diapers 5.73% 4.91% 6.61% 66 All Other Waste 4.89% 4.55% 5.24% 67 Liquids 1.36% 1.09% 1.67% 68 Fines 1.93% 1.62% 2.26% Total Other Waste 19.60% 18.24% 21.00% Total 99.99%

36 Appendix A 2016 Waste Characterization Analysis Detailed Results Residential - Multifamily Cat. 90% Confidence Interval No. Material Categories % Comp. Lower Bound Upper Bound Paper 1 Newspaper 1.03% 0.73% 1.39% 2 Cardboard & Kraft Paper 2.73% 2.19% 3.32% 3 Paperboard 1.95% 1.63% 2.29% 4 Magazine/Catalogs 1.13% 0.62% 1.79% 5 Cartons and Coated Paperboard 1.52% 1.15% 1.95% 6 Aseptic Packages 0.12% 0.07% 0.18% 7 Mixed Recyclable Paper 3.34% 2.58% 4.20% 8 Contaminated Paper 13.51% 12.22% 14.86% 9 Other Non-Recyclable Paper 0.24% 0.16% 0.33% Total Paper 25.57% 23.83% 27.35% Plastic 10 Pop and Water Bottles 1.67% 1.43% 1.91% 11 All other Bottles and Jugs 1.49% 1.26% 1.73% 12 Compatible Plastic Containers 0.99% 0.66% 1.38% 13 Non-Compatible Plastics 6.68% 5.63% 7.80% 14 StyrofoamTM 0.83% 0.71% 0.96% 15 Plastic Shopping Bags 0.31% 0.25% 0.37% 16 Plastic Film 4.94% 4.45% 5.45% Total Plastic 16.89% 15.33% 18.52% Glass 17 Clear Glass 3.71% 2.94% 4.56% 18 Brown Glass 1.74% 1.25% 2.31% 19 Green Glass 0.73% 0.46% 1.06% 20 Other Glass 0.68% 0.37% 1.08% Total Glass 6.85% 5.78% 8.00% Metal 21 Steel Cans 0.91% 0.81% 1.01% 22 Aluminum Cans 0.98% 0.83% 1.14% 23 Aerosol Cans 0.23% 0.16% 0.30% 24 Large Appliances 0.00% N/A N/A 25 Other Ferrous Metals 2.70% 1.64% 4.02% 26 Other Non-Ferrous Metals 0.65% 0.48% 0.85% Total Metal 5.46% 4.24% 6.82% Organics 27 Food Waste: Edible/Program Compatible 2.69% 2.10% 3.34% 28 Food Waste: Edible/Non-Compatible 6.55% 5.88% 7.25% 29 Food Waste: Inedible/Compatible 3.02% 2.40% 3.70% 30 Food Waste: Inedible/Non-Compatible 1.01% 0.71% 1.37% 31 K-Cups 0.26% 0.19% 0.35% 32 Yard Waste 1.13% 0.54% 1.93% 33 Land Clearing Debris 0.72% 0.24% 1.46% 34 Other Organic Waste 6.28% 4.56% 8.27% Total Organics 21.67% 19.65% 23.75%

37 Appendix A 2016 Waste Characterization Analysis Detailed Results C&D Waste 35 Gypsum Wallboard 0.04% 0.01% 0.08% 36 Concrete 0.64% 0.26% 1.18% 37 Insulation 0.01% 0.00% 0.02% 38 Carpet 0.59% 0.24% 1.10% 39 Untreated Lumber 1.04% 0.53% 1.71% 40 Treated Wood Waste 1.50% 0.92% 2.22% 41 Asphalt Roofing 0.00% N/A N/A 42 Pallets 0.00% N/A N/A 43 Other Construction Debris 0.00% 0.00% 0.01% 44 Asphalt 0.00% 0.00% 0.00% Total C&D Waste 3.82% 2.50% 5.40% Hazardous Waste 45 Paints/Adhesives 0.02% 0.01% 0.05% 46 Cleaners 0.01% 0.00% 0.02% 47 Pesticides/Herbicides 0.00% N/A N/A 48 Vehicle & Equipment Fluids 0.04% 0.01% 0.07% 49 Car Batteries 0.00% N/A N/A 50 Alkaline Batteries 0.10% 0.07% 0.14% 51 Other Batteries 0.00% 0.00% 0.00% 52 Fluorescent Light Tubes & Compacts 0.00% 0.00% 0.00% 53 Gasoline 0.00% 0.00% 0.01% 54 Explosives 0.05% 0.02% 0.10% 55 Medical Waste 0.05% 0.02% 0.09% 56 Medicine (Rx Only) 0.03% 0.01% 0.06% 57 E-Cycle Program 0.08% 0.03% 0.16% 58 All Other E-Waste 0.89% 0.41% 1.55% 59 Other Hazardous Waste 0.00% N/A N/A Total Hazardous Waste 1.28% 0.73% 1.99% Other Waste 60 Tires 0.00% N/A N/A 61 Mattresses/Box Springs 0.00% N/A N/A 62 Furniture/Bulky 0.00% N/A N/A 63 Small Appliances 0.83% 0.44% 1.35% 64 Textiles and Leather 4.57% 3.40% 5.91% 65 Diapers 4.75% 3.70% 5.93% 66 All Other Waste 4.78% 4.38% 5.20% 67 Liquids 1.53% 1.17% 1.94% 68 Fines 1.98% 1.31% 2.79% Total Other Waste 18.45% 16.84% 20.12% Total %

38 Appendix A 2016 Waste Characterization Analysis Detailed Results Residential Self-Haul Cat. 90% Confidence Interval No. Material Categories % Comp. Lower Bound Upper Bound Paper 1 Newspaper 0.00% 0.00% 0.01% 2 Cardboard & Kraft Paper 3.34% 1.66% 5.57% 3 Paperboard 0.15% 0.06% 0.29% 4 Magazine/Catalogs 0.01% 0.01% 0.03% 5 Cartons and Coated Paperboard 0.10% 0.04% 0.21% 6 Aseptic Packages 0.00% 0.00% 0.00% 7 Mixed Recyclable Paper 0.23% 0.09% 0.44% 8 Contaminated Paper 2.43% 0.98% 4.50% 9 Other Non-Recyclable Paper 1.41% 0.45% 2.90% Total Paper 7.68% 3.98% 12.46% Plastic 10 Pop and Water Bottles 0.27% 0.11% 0.51% 11 All other Bottles and Jugs 0.23% 0.08% 0.46% 12 Compatible Plastic Containers 0.02% 0.01% 0.04% 13 Non-Compatible Plastics 2.46% 1.24% 4.08% 14 StyrofoamTM 0.12% 0.05% 0.22% 15 Plastic Shopping Bags 0.02% 0.01% 0.04% 16 Plastic Film 0.45% 0.22% 0.76% Total Plastic 3.58% 1.98% 5.64% Glass 17 Clear Glass 2.48% 0.90% 4.81% 18 Brown Glass 0.05% 0.02% 0.11% 19 Green Glass 0.28% 0.09% 0.59% 20 Other Glass 4.50% 1.45% 9.11% Total Glass 7.31% 2.95% 13.43% Metal 21 Steel Cans 0.16% 0.06% 0.30% 22 Aluminum Cans 0.28% 0.12% 0.51% 23 Aerosol Cans 0.01% 0.00% 0.03% 24 Large Appliances 0.86% 0.25% 1.82% 25 Other Ferrous Metals 5.28% 2.15% 9.70% 26 Other Non-Ferrous Metals 0.14% 0.05% 0.26% Total Metal 6.73% 3.12% 11.57% Organics 27 Food Waste: Edible/Program Compatible 0.38% 0.14% 0.73% 28 Food Waste: Edible/Non-Compatible 1.25% 0.48% 2.40% 29 Food Waste: Inedible/Compatible 0.33% 0.13% 0.63% 30 Food Waste: Inedible/Non-Compatible 0.02% 0.01% 0.05% 31 K-Cups 0.04% 0.01% 0.08% 32 Yard Waste 5.52% 1.97% 10.72% 33 Land Clearing Debris 0.00% N/A N/A 34 Other Organic Waste 0.61% 0.23% 1.19% Total Organics 8.16% 3.73% 14.10% C&D Waste

39 Appendix A 2016 Waste Characterization Analysis Detailed Results 35 Gypsum Wallboard 1.93% 0.62% 3.93% 36 Concrete 0.07% 0.02% 0.15% 37 Insulation 3.60% 0.96% 7.85% 38 Carpet 6.73% 2.29% 13.26% 39 Untreated Lumber 15.56% 6.69% 27.27% 40 Treated Wood Waste 9.73% 4.23% 17.18% 41 Asphalt Roofing 5.91% 1.74% 12.32% 42 Pallets 0.00% N/A N/A 43 Other Construction Debris 5.98% 2.12% 11.62% 44 Asphalt 0.00% N/A N/A Total C&D Waste 49.51% 35.09% 63.97% Hazardous Waste 45 Paints/Adhesives 0.01% 0.00% 0.01% 46 Cleaners 0.00% N/A N/A 47 Pesticides/Herbicides 0.00% N/A N/A 48 Vehicle & Equipment Fluids 0.03% 0.01% 0.06% 49 Car Batteries 0.00% N/A N/A 50 Alkaline Batteries 0.02% 0.01% 0.05% 51 Other Batteries 0.00% 0.00% 0.00% 52 Fluorescent Light Tubes & Compacts 0.02% 0.01% 0.04% 53 Gasoline 0.00% N/A N/A 54 Explosives 0.00% 0.00% 0.00% 55 Medical Waste 0.00% 0.00% 0.00% 56 Medicine (Rx Only) 0.02% 0.00% 0.03% 57 E-Cycle Program 0.00% 0.00% 0.00% 58 All Other E-Waste 0.00% 0.00% 0.01% 59 Other Hazardous Waste 0.00% N/A N/A Total Hazardous Waste 0.10% 0.04% 0.18% Other Waste 60 Tires 0.00% N/A N/A 61 Mattresses/Box Springs 1.81% 0.56% 3.74% 62 Furniture/Bulky 9.43% 3.92% 16.99% 63 Small Appliances 1.53% 0.50% 3.11% 64 Textiles and Leather 2.24% 0.83% 4.32% 65 Diapers 0.56% 0.17% 1.17% 66 All Other Waste 0.76% 0.32% 1.39% 67 Liquids 0.59% 0.21% 1.17% 68 Fines 0.02% 0.01% 0.04% Total Other Waste 16.93% 9.36% 26.20% Total %