- Email: [email protected]
A goal-oriented characterization of urban waste
Waste Management & Research (1995) 13, 207-218
A GOAL-ORIENTED CHARACTERIZATION OF URBAN WASTE L. Y. Maystre and F. Viret Institute of Environmental Engineering, Ecole Polytechnique F~d~rale de Lausanne, EPFL, 1015 Lausanne, Switzerland (Received 15 June 1993, accepted in revised form 16 December 1993)
More stringent requirements for the protection of the environment coupled with new incentives for materials recovery, lead modern waste management practice on the line of a more differentiated approach. Separation, or more precisely, non-mixing at the source, is one of the most promising strategies. However, before deciding which categories of urban waste should be collected separately, it is useful to have more detailed knowledge regarding the characteristics of waste. A 5-year investigation has produced enough information to answer such questions as "if one decides to convert food and garden waste to compost instead of burning them, how much less cadmium would be released into the atmosphere?" or, "if the quantities of mercury released into the environment should be drastically reduced, which categories of waste should be collected and treated separately?" This paper discusses sampling and analytical techniques and defines what is a representative sample. It presents the methods applied to determine the annual flow of various chemical elements from 52 waste categories from a European urban area. The results determined through this approach are compared to the total outputs in the gas, wastewater, cinders and fly ashes of the incinerator which currently burns these wastes. Key Words--Waste analysis, waste composition.
1. Approaches in waste analysis Traditionally, waste composition has been determined as waste comes out of a collection truck--mixed, crushed and shredded. Although larger pieces can still be identified through rough hand sorting, a large fraction of sieved material can no longer be recognized and separated. The statistical analysis of the identifiable categories (paper, glass, metal, plastics, etc.) is evidently biased by this important non-determinable fraction. The possible approaches to waste characterization have been described previously (Brunner & Ernst 1986): (l) Statistical information about goods that will later become waste. This approach is only applicable at a national level and is strongly biased by the m a n y different lag times involved for goods to turn into waste. The results are too general and approximate. (2) Analysis of gases, fly ashes, cinders and wastewater from an incineration plant. This approach is fairly precise and reliable, because these outputs are homogeneous, provided the plant operates in a steady state. Its drawbacks are the costs involved and the absence of any indication of breakdown of a pollutant flow between the 0734-242X/95/030207 + 12 $08.00/0
© 1995 ISWA
208
L. Y Maystre & E Viret
different waste categories. Sampling over 24 h provides no indication about weekly or seasonal variations. (3) Direct sorting of waste. In order to avoid the criticism mentioned above, a sampling technique was developed by the Institute for Environmental Engineering at EPFL to reduce the fraction of fine indeterminable material to less than 2% of the total waste. The techniques and procedures are described in detail elsewhere (Maystre et al. 1994).
2. Sampling procedure At present in Switzerland, waste is normally collected in plastic bags. The specific weight of the bags lies between 0.08 and 0.12 kgl -~. If a bag is opened and sorted before being compressed and shredded, it is possible to make a very detailed hand sorting. This was tested during a 1-month preliminary campaign: about 200 bags with a total weight of about 800 kg were collected just before the regular truck collection and hand sorted in "status nascendi". Forty-seven categories of waste could thus be identified and weighted for each bag. The unidentifiable category of dusts was 2% by weight. The cumulated percentages were calculated for each category. The standard deviation of the cumulated percentages diminished steadily and remained nearly constant above 300 kg of total weight of waste. In other words, 300 kg was found to be the minimum weight for a sample to give reliable data of the percentages of each category. If waste is normally collected twice weekly, it is necessary to analyse samples from the same origin on the 2 week days because waste is collected domestically in weekly cycles. Thus the minimum "quantum" of waste from one given origin to be sorted to obtain reliable data is about 600 kg. A l-year campaign was undertaken in 1986 in the metropolitan area of Geneva: 52 tonnes of waste were collected during four periods of 5 weeks, in various areas of differing housing types and were hand sorted and weighted in 47 different categories (Diserens & Maystre 1988, Maystre & Diserens 1989, Leroy el al. 1992). Socio-economic status proved to be insignificant (tin cans containing sardines and tin cans containing caviar are both tin cans!), but housing type proved to be a significant parameter--the content of grass and leaves from areas of individual housing varies seasonally. Some categories appeared to be inadequate, thus additional campaigns were made in 1988 and 1989 with identification of 52 categories (some of the previous 47 being merged, others split). The results presented in this paper refer to these 52 categories.
3. Analytical procedures The main advantage of sorting waste into a large number of categories is the production of truly homogeneous categories. Small samples can thus be analysed at reasonable cost, with the confidence of getting realistic and reproducible data regarding the content of particular elements. From each category of waste, three samples of I00-500 g were taken and dried at 105°C for 24h, then ground to 0.2ram. The parts of the RENTSCH 2M1 grinder in contact with the sample were made of Cr-Ni, thus no bias is possible, since the investigated elements were five metals (Cu, Zn, Cd, Hg and Pb) and two anions (F and Cl) which are currently considered deleterious to the environment. The 0.2 mm powder samples were dissolved in nitric acid for the determination of
Goal-oriented characterization o f urban waste
209
Cu, Zn, Cd and Pb by flame atomic absorption, and through cold vapour atomic absorption for Hg. For F and C1, the samples were burnt with Oz (Sch6ninger method) and the eluant was analysed using ionic chromatography. The precision of the results depends on the quantity of a waste category put into solution and analysed, as well as on the dilution factor. For the determination of F, the dilution factor was systematically high and therefore the analytical threshold was 50 ppm for most waste categories. For the determination of the concentration of Hg, the threshold was, in most cases, 1 ppm. The concentrations of the other elements were nearly always above the corresponding threshold value. 4. Results
The results of Table 1 refer to the weighted average of waste from the regular collection of housing and small trade urban areas. Waste from large department stores and from industries are not included in this table--they were investigated separately for the purpose of the research. Table 2 converts the percentages and concentrations into quantities expressed in gtonne -~, e.g. 2.27g Cd in waste (about 40% of 5.84gtonne -~) are to be found in waste category number 37 (toys, ball-point pens, plastic cups, buckets, disposable shavers, etc.). Disposable nappies contribute for: 0.033 weight fraction × (l -0.534) dry part x (0.15 x 2900+0.85 ×1850) =30.6 g CI per tonne of waste as collected.
of CI
5. Discussion
The reliability of the data of Table 2 can be tested through an input-output balance of a WTE plant. Direct sampling was carried out at the WTE plant of Geneva, during a period of 9 h on 27 May 1986 (Baccini & Diener 1986). Six 90-min sampling periods produced six series of results which are presented in Table 3. Between 1986 and 1989, the percentages in weight of the waste categories changed by less than 20%, many of them by less than 10%. Therefore, a comparison of the global outputs on 27 May 1986 with the inputs as determined in the 1989 campaign may be accepted, granted a weaker accuracy is tolerated. Input flows are calculated as weighted averages of the data of Table 2 (for housing and small trade urban areas) and the corresponding data for large department stores and for industrial areas, which are not reproduced in this paper. Values have been rounded off and an uncertainty interval of 30% selected for the calculation of the probable minimum and maximum data for input flows (g tonne-~) of waste as collected. This 30% uncertainty combines an estimated 10% uncertainty regarding the hand sorting, an estimated 10% uncertainty about the analytical results (only three samples for each determination), and a 10% uncertainty concerning moisture content. For outputs, the adopted minimum and maximum values are equal to the average values of Table 3 _+ 1 S.D. (rounded values). Maximum and minimum values for inputs and outputs are presented in Table 4. The concentration of F (Table 1) is below the analytical threshold for most waste categories. Therefore, the input value for F should be considered as unreliable and the output value is probably closer to reality. For the other chemical elements, the intervals overlap but it is not possible to certify that output values are closer to reality than input values, or the contrary. This is due to at least three reasons:
2 3 4 5 6 7 7a 7b 8 9 9a 9b 9c 10 11 12 13 14 15 16 16a 16b 16c 16d 16e 16f 17 18 19
1
N
Vegetable and foodstuffs Meat scraps Natural tissues Synthetic tissues Nylon stockings Unweaved sanitary Disposable nappies Polyethylene Cellulose Various textiles Glass Lead capsules Aluminium capsules Plastic capsules Newspaper Packing paper Other paper Other cardboard Packing cardboard Household aluminium Aluminium aerosols Lacquers without C F C s Deodorants with CFCs Shaving foam without CFCs Various products without CFCs Lacquers with CFCs Aluminium Aluminium tubes Aluminium pastry trays Aluminium covers
I 2 3 4 5 6
16a 16b E E 25a 20 18 18 19
29 50a 4 9 B 20 29 10 11 12 13 14 15
Class or material
N*
0.009 0.011 0.066 0.019 0.037 0.858
0.997 0.002 0.001 0.000
0.150 0.850
Fraction of material
0.247 0.211 0.274
0.001 0.001 0.001
0.121 0.011 0.116 0.032 0.032 0.002 0.001
0.170 0.204 0.166 0.289 0.172 0.303 -
0.005 0.096
0.261 0.017 0.006 0.007 0.00 I 0.002 0.033
Composition
0.231 0.005
0.360 0.534
0.114
0.739 0.450 0.205 0.231
Humidity
% by weight
-
0 200 4,700 4,700 6,950
-
0 0 0 0 0
200 2,900 2,267 2,633 3,267 2,300 2,300 2,700
2,900 1,850 1,700 200
3,733 23,000 1,867 1,700 2,000 2,700
CI (thousands)
-
0 0 0 0 0 0 0 0
-
0 0 500 0
0 0 0 500 0 0
F
5.0 39.0 9.0 9.0 4.7
5.0
5.0
39.0 14.6 12.0 44.3 280.0 72.0 84.3 12.0
14.6 13.0 8.7 7.9
28.3 23.6 57.7 8.7 9.0 12.0
Cu
4.4 37.0 29.0 29.0 14.0
116.0
•4.0
37.0 57.5 41.0 26.7 35.0 75.3 59.7 44.0
57.5 70.5 42.9 3.6
74.0 95.7 104.3 42.9 55.0 41.5
Zn
0 0 0 0 0
0
5.2 1.4 0.5 0.5 2.3
0
3.0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0
Hg
4.4
1.5 2.0 2.2 0.8 1.4 1.5 2.5 2.1 8.4 2.3 2.2 3.6
3.2 3.9 2.0 2.2 1.0 3.5
Cd
Average concentration of chemical elements (ppm)
TABLE 1 Mass and composition of 52 waste categories analysed in MSW from Geneva
39 82 24 19 10 28
continued
30 18 27 27 72
30 30
74 309 19 11 999,000 18 74 23 316 39 70 43 24
Pb
t,o
26 27 28 29 30 30a 30b 31 32 33 34 35 36
2O 21 22 22a 22b 22c 23 24 25 25a 25b 25c 25d 25e
30a 30b 31 32 33 34 35 36
25a 25b 25c 25d 25e 26 26 27 28 29
22a A 28 23 26
20 21
N*
Aluminium beverage cans Aluminium scraps Non-ferrous metals Non-ferrous metals Copper (electrical cables) Chlorinated plast. (elect. sheaths) Iron food cans Iron covers Iron aerosols Lacquers with CFCs Dusting products without CFCs Ironing products without CFCs Oven detergents without C F C s Paints without CFCs Iron Iron beverage cans Iron scraps Plastic bottles (PVC) Polyethylene bottles Solid moulded boxes PVC PE Rubbish bags Supermarket bags Over-packing Plastics from foodstuffs Rigid pots (yoghurts) Polystyrene
Class or material
0.210 0.790
0.008 0.033 0.039 0.019 0.013 0.888
0.930 0.035 0.035
Fraction of material
0.038 0,237 0.064 0.087 0.188 0.113
0.032 0.030 0.059 0.060 0.072
0.074 0.031 0.050
0.156 0.100 0.070
Humidity
% by weight
0.011 0.006 0.010 0.012 0.009 0.002
0.001 0.016 0.006 0.006 0.005
0.013 0.002 0.001
0.002 0.001 0.003
Composition 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0
0 0 0 0
F
583,333 1,000 4,100 2,600 35,500 126,000 1,450 1,500
500 500 0 223,333 2,900
0 223,333 750 500
200 2,200
CI (thousands)
4.1 80.0 200.0 91.0 17.5 54.5 41.0 8.7
5.0 5.0 9.5 5.0 5.0 313.0 313.0 7.0 4.6 14.6
1,792.0 999,500 4.6 199.0 313.0
39.0 2.0
Cu
15.7 77.5 362.5 435.0 45.0 69.0 267.0 45.5
4.4 12.0 1.8 1.0 20.0 328.5 328.5 7.3 21.7 57.5
21.7 202.0 328.5
46,827
37.0 17.0
Zn
1.2 1.8 5.8 6. l 8.6 5.2 4.6 5.2
5.2 1,1 1.1 1.0 3.5 4.1 4,1 1.0 0.7 1.5
0.7 3.0 4.1
10,0
1.4 53.0
Cd
18 84
21 24 89 10
0 0 0 0
continued
8 16 470
30 30 30 30 30 520 520 15 8 74
8 380 520
30,010
Pb
1.1 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0
0
0 0
Hg
Average concentration of chemical elements (ppm)
T A B L E 1 (continued) M a s s a n d c o m p o s i t i o n o f 52 w a s t e c a t e g o r i e s a n a l y s e d in M S W f r o m G e n e v a
to
7
44 45 46 46a 46b 47 47a
43
42
39 40 41
37a 37b
37 37a 37b 38
47a
46a 46b
15 10 44 45
33 15 10
32 15
14 33 15 C D
N*
N
Plastic scraps Synthetic mousse Moulded pieces Cigarette packets Cardboard Plastic Aluminium Tetra Brik without aluminium Tetra Brik with aluminium Packaging composites AI + plastic Polyethylene Aluminium Pack. comp. AI + plast. + paper Polyethylene Aluminium Paper Packaging composites AI + paper Aluminium Paper Paper + paraffin wax Cardboard + paraffin wax Batteries Zinc-carbon batteries Alkaline batteries Medicament packaging Solid medicaments (medications)
Class or material
0.100
0.440 0.560
0.400 0.600
0.600 0.100 0.300
0.900 0.100
0.810 0.020 0.170
0.079 0.921
Fraction of material
0.087
0.173 0.195 0.030
0.136
0,128
0.065 0.096 0.121
0.002
0.003 0.001 0.002
0.002
0.001
0.004 0.007 0.001
0.002
0.019
0.070
0.177
Composition
Humidity
% by weight
0 0
0
0 0
0 0 0 0
0 0 0
0 0
0 0 0 40 40
F
4,267
32,551 593
2,700 2,267 1,933 1,633
35,500 2,700 2,267
2,600 2,700
2,300 35,500 2,700 300 400
91,000 2,450
CI (thousands)
6.8
2,724.7 8,097.7
12.0 12.0 209.7 12.3
34.0
95,305 114,881
44.0 41.0 77.3 23.3
45.0 44.0 41.0
435.0 44.0
91.0 12.0
17.5 12.0 12.0
59.7 45.0 44.0 50.0 50.0
283.0 39.4
Zn
84.3 17.5 12.0 15.0 15.0
155.0 19.0
Cu
1.4
5.3 19.6
3.6 2.5 4.4 1.7
8.6 3.6 2.5
6.1 3.6
2.2 8.6 3.6 0.0 0.0
7.9 138.0
Cd
0
72 836
0 0 0 0
0 0 0
0 0
0 0 0 0 0
0 0
Hg
Average concentration of chemical elements (ppm)
T A B L E 1 (continued) M a s s a n d c o m p o s i t i o n o f 52 w a s t e c a t e g o r i e s a n a l y s e d in M S W f r o m G e n e v a
c'onthlued
102 15
24 23 263 15
21 24 23
590 24
43 21 24 3 3
288 259
Pb
~'
.~ .~
Liquid medicaments (medications) Glass Plastic Paper/cardboard Aluminium Electronic material Toxics Cleaning products Paints Various products Polyethylene PVC Glass Tin plate Wood-leather-rubber scraps Wood Leather Rubber Inert materials Others
Class or material
0.810 0.054 0.136
0.470 0.180 0.100 0.150 0.010 0.040 0.050
0.380 0.280 0.160 0.020 0.060
Fraction of material
0.275 0.369
0.150
0.030 0.080
Humidity
0.057 0.024
0.017
0.003 0.006
Composition
0 0 0 867 0
0 0 0 0 0 0 0
867 0 0 0 0 0
F
1,850 4,600 13,000 1,733 3,500
2,500 1,300 4,400 2,900 223,333 200 500
1,300 200 2,900 2,300 6,950 7,567
CI (Thousands)
13.0 74.5 28.0 35.3 112.0
0.7 1.9 0.6 14.6 4.6 7.9 313.0
1.0 7.9 14.6 84.3 4.7 30,333
Cu
70.5 436.5 7,028.0 97.0 324.3
906.0 4.3 18.0 57.5 21.7 3.6 328.5
15.3 3.6 57.5 59.7 14.0 17,689
Zn
2.0 4.9 8.4 2.5 4.5
1.2 0.2 0.2 1.5 0.7 0.8 4.1
0.8 0.8 1.5 2.2 2.3 509.0
Cd
0 0 0 0 0.7
0 0.6 0 0 0 0
0 0 0 0 0 0
Hg
Average concentration of chemical elements (ppm)
309 372 197 2,055 311
8 11 1 74 8 11 520
4 11 74 43 72 29,805
Pb
N, rank number of waste category: N*. number of the waste category of reference: A. B, pure metal: C, D, chemical composition indicated by manufacturer: E. chemical analysis could not be made; 0, concentration below threshold of applied analytical technique; -. no determination made: concentrations are given in ppm with the exception of CI (given in thousands); a-g, subclasses of a category: CFC. chlorofluorocarbons: PVC, polyvinyl chloride: PE, polyethylene.
50a 50b 50c 51 52
49a 49b 49c 29 28 9 26
47b 9 29 13 19 48
47b
48 49 49a 49b 49c 49d 49e 49f 49g 50 50a 50b 50c 51 52
N*
N
% by weight
T A B L E 1 (continued) M a s s a n d c o m p o s i t i o n o f 52 w a s t e c a t e g o r i e s a n a l y s e d in M S W f r o m G e n e v a
,7"
b~ ta~
~"
~.
.,, ,.~ ~.
~.
~"
Class or material
Vegetable and foodstuffs Meat scraps Natural tissues Synthetic tissues Nylon stockings Unweaved sanitary Disposable nappies Various textiles Glass Newspaper Packing paper Other paper Other cardboard Packing cardboard Household aluminium Aluminium aerosols Aluminium tubes Aluminium pastry boats Aluminium covers Aluminium beverage cans Aluminium scraps Non-ferrous metals Iron food cans Iron covers Iron aerosols Iron beverage cans Iron scraps PVC bottles
N
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 0.261 0.017 0.006 0.007 0.001 0.002 0.033 0.005 0.096 0.121 0.011 0.116 0.032 0.032 0.002 0.001 0.001 0.001 0.001 0.002 0.001 0.003 0.013 0.002 0.001 0.001 0.016 0.006
Composition 0 0 0 2.65 0 0 0 1.92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
F 253.9 215.1 9.5 9.0 1.2 3.1 30.6 6.5 19.1 228.0 23.1 316.8 53.0 60.2 4.0 0.1 3.9 4.4 3.5 0.4 1.2 21.8 8.9 1.2 0.6 0.3 0.0 1239.9
CI 1.93 0.22 0.29 0.05 0.01 0.01 0.20 0.03 0.75 1.21 0.39 27.16 1.66 2.21 0.02 0.02 0.01 0.01 0.00 0.07 0.00 102.25 2.36 0.73 0.37 0.18 0.11 0.03
Cu 5.03 0.89 0.53 0.23 0.03 0.05 1.04 0.16 0.34 4.12 0.23 3.39 1.74 1.56 0.06 0.2 0.02 0.03 0.01 0.07 0.01 121.50 2.39 0.76 0.39 0.19 0.11 0.12
Zn 0.218 0.036 0.010 0.012 0.001 0.004 0.029 0.008 0.079 0.251 0.018 0.812 0.053 0.058 0.005 0.001 0.000 0.000 0.001 0.003 0.029 0.026 0.035 0.009 0.005 0.002 0.016 0.004
Cd 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Hg
Standardized flux of chemical elements (g tonne-~)
TABLE 2 Contribution of 52 waste categories to the total flux of elements in MSW from Geneva
continued
2.64 0.77 0.12 0.10 O.Ol 0.03 4.17 0.07 181.38 2.35 2.77 3.73 1.60 1.13 0.04 0.01 0.02 0.03 0.04 0.03 0.05 77.87 4.50 1.21 0.62 0.30 0.23 0.04
Pb
7~
bJ
Polyethylene bottles Solid moulded boxes Rubbish bags Supermarket bags Over-packing Plastics from foodstuffs Rigid pots (yoghurts) Polystyrene Plastic scraps Cigarette packets Tetra Brik without A1 Tetra Brik with AI Packaging comp. A1 + plastic Pack. comp. AI + plast. + paper Pack. composites AI + paper Paper + paraffin wax Cardboard + paraffin wax Batteries Medicament (medications) packaging Electronic material Toxics Wood-leather-rubber scraps Inert material Others
29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
N, rank number of waste category.
Total for the stratum considered
Class or material
N
1.000
0.006 0.005 0.011 0.006 0,010 0.012 0.009 0.002 0.019 0.002 0.004 0.007 0.001 0.001 0.002 0.003 0.001 0.002 0.002 0.003 0.006 0.017 0.057 0.024
Composition
41.4
0 0 0 0 0 0 0 0 0 0 0.15 0.24 0 0 0 0 0 0 0.72 0 0 0 35.69 0
F
5289
15.8 560.6 44.6 12.1 345.6 1322.9 10.4 2.3 167.8 5.5 1.1 2.4 2.3 21.3 4.4 4.8 1.2 21.3 4.2 19. I 25.1 50.8 71.4 52.6
C1
236.1
0.08 0.29 2.17 0.42 0.17 0.57 0.29 0.01 0.53 0.13 0.05 0.09 0.07 0.01 0.02 0.52 0.01 8.34 0.02 76.50 0.10 0.27 1.46 1.68
Cu
382.7
0.31 0.29 3.94 2.02 0.44 0.72 1.91 0.07 1.04 0.10 0.18 0.30 0.35 0.04 0.08 0.19 0.02 154.62 0.05 44.61 2.50 14.98 3.99 4.87
Zn
5.84
0.008 0.008 0.063 0.028 0.084 0.054 0.033 0.008 2.269 0.005 0 0 0.005 0.006 0.005 0.011 0.001 0.019 0.002 1.284 0.006 0.044 0.102 0.068
Cd
0.74
0 0.0011 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.7275 0 0 0.0003 0 0 0.0110
Hg
Standardized flux of chemical elements (g tonne -~)
T A B L E 2 (continued) Contribution of 52 waste categories to the total flux of elements in MSW from Geneva
470.3
0.40 0.07 5.10 2.74 0.20 0.25 0.63 0.02 4.64 0.07 0.01 0.02 0.47 0.02 0.04 0.65 0.01 0.08 0.05 75.17 0.24 4.29 84.62 4.68
Pb
I'J
.,.t
e~
reed s med s
S
0.04 0.01 1.00 0.!4
0 7203 967
137 24
6292 953 690 148 176 76 7 2 37
C1
0
54 12 36 7 46 20 0.7 0.2
F
207 38
0
.
0.8 0.3 20 6 185 37 I 0.5 -0.01
Cu
.
545 89
0
13 3 317 63 209 63 6 3 -0.04
Zn
.
7 1.6
0
.
0.4 0.2 5.9 1.5 1.1 0.3 0.11 0.06 - I E-05
Cd
.
1.2 0.5
0
0.7 0.5 0.39 0.13 0.05 0.02 0.02 0.004 0
Hg
337 63
0
6 1 11 24 216 58 3 2 0.01
Pb
• no analysis was made: 0, flow was considered to be nil: med, mean: dif, calculated from the differences in concentration over a l-day period: s, standard deviation.
Scrap iron and large objects 11=6 Total u r b a n waste 11=6
0.78 0.18 0.02 0.00 0.16 0.03 0.0005 0.0001 -
Smoke n=6 Filter dust n=6 Clinker (dust & u n b u r n t n=6 Economizer 11=6 Cooling tub
reed s reed s med s med s dif
Final mass
Incineration products
Flux of chemical elements (g t o n n e ~)
TABLE 3 O u t p u t flows of WTE, G e n e v a
.t'-,
1-o
217
Goal-oriented characterization o f urban waste
TABLE 4 Input and output (g tonne-~) of waste as collected Elements
F
C1
Cu
Zn
Cd
Hg
Pb
Input
min max
25 50
3600 6600
150 270
250 470
4.0 7.0
0.4 0.9
310 570
Output
min max
110 165
6200 8200
170 250
450 630
5.5 8.5
0.7 1.7
280 400
(1) Chemical analyses of some categories may be biased, but it is impossible to know which ones; (2) It is impossible to know if the waste composition of 27 May 1986 was similar to the annual average; (3) Slight changes in the composition of waste certainly occurred between 1986 and 1989, but it is difficult to evaluate their influence. The reliability of output values is an important issue, since they are used to evaluate the environmental impact of W T E plants (Pictet et al. 1992). New products brought on to the market inevitably change the composition of waste, with a lag of a few weeks to 1 year. The comparison between 3 years has shown that this change was not very rapid. However, it is likely that the new trends for more "ecological" products, for example, the introduction of new labels such as the German "Blue Angel", will change the waste composition over the next 5 years. New collection practices change the waste composition, e.g. collection of non-mixed waste (glass, paper and cardboard, plastics, etc.). In addition, the obligation to bring back waste to selling points (e.g. batteries) or to special deposit centres (e.g. refrigerators, neon tubes, etc.), will also considerably modify the composition of the remaining mixed waste. Conclusion The investigation made in Geneva has helped define a new strategy for waste management with more intensive recycling (Simos 1990), and will remain a valuable point of comparison for future investigations of waste characterization. References Baccini, P. & Diener, H. P. (1986) Etude de la gestion des d~chets du canton de Gen~ve, Flux des substances (Waste Management in Geneva: Material balance study of municipal incineration). EA WAG-project 30-330, Dtibendorf, Switzerland. Brunner, Paul H. & Ernst, W. R. (1986) Alternative methods for the analysis of municipal solid waste. Waste Management & Research 4, 147-160. Diserens, Th. & Maystre, L. Y. (1988) Les emballages plastiques dans les d6chets (Plastic packaging materials in wastes). Sn,iss Plastics 5, 18-21. Leroy, D., Giovannoni, J. M. & Maystre, L. Y. (1992) Sampling method to determine a household waste composition variance. Waste Management & Research 10, 3-12. Maystre, L. Y. & Diserens, Th. (1989) Analyse de la composition des d6chets m6nagers et assimil~s du canton de Gen~ve (Analysis of the composition of MSW in Geneva). Techniques, Sciences, Mbthodes 3, 179-185.
218
L. Y. Maystre & E Viret
Maystre, L. Y. et al. (1994) DOchets Urbahls, Nature et Caractkrisation (Urban Wastes, Nature and Characterization). Presses Polytechniques et Universitaires Romandes, Switzerland. Pictet, J., Giovannoni, J. M. & Maystre, L. Y. (1992) Impact assessment of urban waste processing systems using a multibox model. Water, Air and Soil Pollution 63, 155-178. Simos, J. (1990) Evaluer I'Impact sur I'Environnement (Evahtation of the hnpact on the Envh'onment). Presses Polytechniques et Universitaires Romandes, Switzerland.
A GOAL-ORIENTED CHARACTERIZATION OF URBAN WASTE L. Y. Maystre and F. Viret Institute of Environmental Engineering, Ecole Polytechnique F~d~rale de Lausanne, EPFL, 1015 Lausanne, Switzerland (Received 15 June 1993, accepted in revised form 16 December 1993)
More stringent requirements for the protection of the environment coupled with new incentives for materials recovery, lead modern waste management practice on the line of a more differentiated approach. Separation, or more precisely, non-mixing at the source, is one of the most promising strategies. However, before deciding which categories of urban waste should be collected separately, it is useful to have more detailed knowledge regarding the characteristics of waste. A 5-year investigation has produced enough information to answer such questions as "if one decides to convert food and garden waste to compost instead of burning them, how much less cadmium would be released into the atmosphere?" or, "if the quantities of mercury released into the environment should be drastically reduced, which categories of waste should be collected and treated separately?" This paper discusses sampling and analytical techniques and defines what is a representative sample. It presents the methods applied to determine the annual flow of various chemical elements from 52 waste categories from a European urban area. The results determined through this approach are compared to the total outputs in the gas, wastewater, cinders and fly ashes of the incinerator which currently burns these wastes. Key Words--Waste analysis, waste composition.
1. Approaches in waste analysis Traditionally, waste composition has been determined as waste comes out of a collection truck--mixed, crushed and shredded. Although larger pieces can still be identified through rough hand sorting, a large fraction of sieved material can no longer be recognized and separated. The statistical analysis of the identifiable categories (paper, glass, metal, plastics, etc.) is evidently biased by this important non-determinable fraction. The possible approaches to waste characterization have been described previously (Brunner & Ernst 1986): (l) Statistical information about goods that will later become waste. This approach is only applicable at a national level and is strongly biased by the m a n y different lag times involved for goods to turn into waste. The results are too general and approximate. (2) Analysis of gases, fly ashes, cinders and wastewater from an incineration plant. This approach is fairly precise and reliable, because these outputs are homogeneous, provided the plant operates in a steady state. Its drawbacks are the costs involved and the absence of any indication of breakdown of a pollutant flow between the 0734-242X/95/030207 + 12 $08.00/0
© 1995 ISWA
208
L. Y Maystre & E Viret
different waste categories. Sampling over 24 h provides no indication about weekly or seasonal variations. (3) Direct sorting of waste. In order to avoid the criticism mentioned above, a sampling technique was developed by the Institute for Environmental Engineering at EPFL to reduce the fraction of fine indeterminable material to less than 2% of the total waste. The techniques and procedures are described in detail elsewhere (Maystre et al. 1994).
2. Sampling procedure At present in Switzerland, waste is normally collected in plastic bags. The specific weight of the bags lies between 0.08 and 0.12 kgl -~. If a bag is opened and sorted before being compressed and shredded, it is possible to make a very detailed hand sorting. This was tested during a 1-month preliminary campaign: about 200 bags with a total weight of about 800 kg were collected just before the regular truck collection and hand sorted in "status nascendi". Forty-seven categories of waste could thus be identified and weighted for each bag. The unidentifiable category of dusts was 2% by weight. The cumulated percentages were calculated for each category. The standard deviation of the cumulated percentages diminished steadily and remained nearly constant above 300 kg of total weight of waste. In other words, 300 kg was found to be the minimum weight for a sample to give reliable data of the percentages of each category. If waste is normally collected twice weekly, it is necessary to analyse samples from the same origin on the 2 week days because waste is collected domestically in weekly cycles. Thus the minimum "quantum" of waste from one given origin to be sorted to obtain reliable data is about 600 kg. A l-year campaign was undertaken in 1986 in the metropolitan area of Geneva: 52 tonnes of waste were collected during four periods of 5 weeks, in various areas of differing housing types and were hand sorted and weighted in 47 different categories (Diserens & Maystre 1988, Maystre & Diserens 1989, Leroy el al. 1992). Socio-economic status proved to be insignificant (tin cans containing sardines and tin cans containing caviar are both tin cans!), but housing type proved to be a significant parameter--the content of grass and leaves from areas of individual housing varies seasonally. Some categories appeared to be inadequate, thus additional campaigns were made in 1988 and 1989 with identification of 52 categories (some of the previous 47 being merged, others split). The results presented in this paper refer to these 52 categories.
3. Analytical procedures The main advantage of sorting waste into a large number of categories is the production of truly homogeneous categories. Small samples can thus be analysed at reasonable cost, with the confidence of getting realistic and reproducible data regarding the content of particular elements. From each category of waste, three samples of I00-500 g were taken and dried at 105°C for 24h, then ground to 0.2ram. The parts of the RENTSCH 2M1 grinder in contact with the sample were made of Cr-Ni, thus no bias is possible, since the investigated elements were five metals (Cu, Zn, Cd, Hg and Pb) and two anions (F and Cl) which are currently considered deleterious to the environment. The 0.2 mm powder samples were dissolved in nitric acid for the determination of
Goal-oriented characterization o f urban waste
209
Cu, Zn, Cd and Pb by flame atomic absorption, and through cold vapour atomic absorption for Hg. For F and C1, the samples were burnt with Oz (Sch6ninger method) and the eluant was analysed using ionic chromatography. The precision of the results depends on the quantity of a waste category put into solution and analysed, as well as on the dilution factor. For the determination of F, the dilution factor was systematically high and therefore the analytical threshold was 50 ppm for most waste categories. For the determination of the concentration of Hg, the threshold was, in most cases, 1 ppm. The concentrations of the other elements were nearly always above the corresponding threshold value. 4. Results
The results of Table 1 refer to the weighted average of waste from the regular collection of housing and small trade urban areas. Waste from large department stores and from industries are not included in this table--they were investigated separately for the purpose of the research. Table 2 converts the percentages and concentrations into quantities expressed in gtonne -~, e.g. 2.27g Cd in waste (about 40% of 5.84gtonne -~) are to be found in waste category number 37 (toys, ball-point pens, plastic cups, buckets, disposable shavers, etc.). Disposable nappies contribute for: 0.033 weight fraction × (l -0.534) dry part x (0.15 x 2900+0.85 ×1850) =30.6 g CI per tonne of waste as collected.
of CI
5. Discussion
The reliability of the data of Table 2 can be tested through an input-output balance of a WTE plant. Direct sampling was carried out at the WTE plant of Geneva, during a period of 9 h on 27 May 1986 (Baccini & Diener 1986). Six 90-min sampling periods produced six series of results which are presented in Table 3. Between 1986 and 1989, the percentages in weight of the waste categories changed by less than 20%, many of them by less than 10%. Therefore, a comparison of the global outputs on 27 May 1986 with the inputs as determined in the 1989 campaign may be accepted, granted a weaker accuracy is tolerated. Input flows are calculated as weighted averages of the data of Table 2 (for housing and small trade urban areas) and the corresponding data for large department stores and for industrial areas, which are not reproduced in this paper. Values have been rounded off and an uncertainty interval of 30% selected for the calculation of the probable minimum and maximum data for input flows (g tonne-~) of waste as collected. This 30% uncertainty combines an estimated 10% uncertainty regarding the hand sorting, an estimated 10% uncertainty about the analytical results (only three samples for each determination), and a 10% uncertainty concerning moisture content. For outputs, the adopted minimum and maximum values are equal to the average values of Table 3 _+ 1 S.D. (rounded values). Maximum and minimum values for inputs and outputs are presented in Table 4. The concentration of F (Table 1) is below the analytical threshold for most waste categories. Therefore, the input value for F should be considered as unreliable and the output value is probably closer to reality. For the other chemical elements, the intervals overlap but it is not possible to certify that output values are closer to reality than input values, or the contrary. This is due to at least three reasons:
2 3 4 5 6 7 7a 7b 8 9 9a 9b 9c 10 11 12 13 14 15 16 16a 16b 16c 16d 16e 16f 17 18 19
1
N
Vegetable and foodstuffs Meat scraps Natural tissues Synthetic tissues Nylon stockings Unweaved sanitary Disposable nappies Polyethylene Cellulose Various textiles Glass Lead capsules Aluminium capsules Plastic capsules Newspaper Packing paper Other paper Other cardboard Packing cardboard Household aluminium Aluminium aerosols Lacquers without C F C s Deodorants with CFCs Shaving foam without CFCs Various products without CFCs Lacquers with CFCs Aluminium Aluminium tubes Aluminium pastry trays Aluminium covers
I 2 3 4 5 6
16a 16b E E 25a 20 18 18 19
29 50a 4 9 B 20 29 10 11 12 13 14 15
Class or material
N*
0.009 0.011 0.066 0.019 0.037 0.858
0.997 0.002 0.001 0.000
0.150 0.850
Fraction of material
0.247 0.211 0.274
0.001 0.001 0.001
0.121 0.011 0.116 0.032 0.032 0.002 0.001
0.170 0.204 0.166 0.289 0.172 0.303 -
0.005 0.096
0.261 0.017 0.006 0.007 0.00 I 0.002 0.033
Composition
0.231 0.005
0.360 0.534
0.114
0.739 0.450 0.205 0.231
Humidity
% by weight
-
0 200 4,700 4,700 6,950
-
0 0 0 0 0
200 2,900 2,267 2,633 3,267 2,300 2,300 2,700
2,900 1,850 1,700 200
3,733 23,000 1,867 1,700 2,000 2,700
CI (thousands)
-
0 0 0 0 0 0 0 0
-
0 0 500 0
0 0 0 500 0 0
F
5.0 39.0 9.0 9.0 4.7
5.0
5.0
39.0 14.6 12.0 44.3 280.0 72.0 84.3 12.0
14.6 13.0 8.7 7.9
28.3 23.6 57.7 8.7 9.0 12.0
Cu
4.4 37.0 29.0 29.0 14.0
116.0
•4.0
37.0 57.5 41.0 26.7 35.0 75.3 59.7 44.0
57.5 70.5 42.9 3.6
74.0 95.7 104.3 42.9 55.0 41.5
Zn
0 0 0 0 0
0
5.2 1.4 0.5 0.5 2.3
0
3.0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0
Hg
4.4
1.5 2.0 2.2 0.8 1.4 1.5 2.5 2.1 8.4 2.3 2.2 3.6
3.2 3.9 2.0 2.2 1.0 3.5
Cd
Average concentration of chemical elements (ppm)
TABLE 1 Mass and composition of 52 waste categories analysed in MSW from Geneva
39 82 24 19 10 28
continued
30 18 27 27 72
30 30
74 309 19 11 999,000 18 74 23 316 39 70 43 24
Pb
t,o
26 27 28 29 30 30a 30b 31 32 33 34 35 36
2O 21 22 22a 22b 22c 23 24 25 25a 25b 25c 25d 25e
30a 30b 31 32 33 34 35 36
25a 25b 25c 25d 25e 26 26 27 28 29
22a A 28 23 26
20 21
N*
Aluminium beverage cans Aluminium scraps Non-ferrous metals Non-ferrous metals Copper (electrical cables) Chlorinated plast. (elect. sheaths) Iron food cans Iron covers Iron aerosols Lacquers with CFCs Dusting products without CFCs Ironing products without CFCs Oven detergents without C F C s Paints without CFCs Iron Iron beverage cans Iron scraps Plastic bottles (PVC) Polyethylene bottles Solid moulded boxes PVC PE Rubbish bags Supermarket bags Over-packing Plastics from foodstuffs Rigid pots (yoghurts) Polystyrene
Class or material
0.210 0.790
0.008 0.033 0.039 0.019 0.013 0.888
0.930 0.035 0.035
Fraction of material
0.038 0,237 0.064 0.087 0.188 0.113
0.032 0.030 0.059 0.060 0.072
0.074 0.031 0.050
0.156 0.100 0.070
Humidity
% by weight
0.011 0.006 0.010 0.012 0.009 0.002
0.001 0.016 0.006 0.006 0.005
0.013 0.002 0.001
0.002 0.001 0.003
Composition 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0
0 0 0 0
F
583,333 1,000 4,100 2,600 35,500 126,000 1,450 1,500
500 500 0 223,333 2,900
0 223,333 750 500
200 2,200
CI (thousands)
4.1 80.0 200.0 91.0 17.5 54.5 41.0 8.7
5.0 5.0 9.5 5.0 5.0 313.0 313.0 7.0 4.6 14.6
1,792.0 999,500 4.6 199.0 313.0
39.0 2.0
Cu
15.7 77.5 362.5 435.0 45.0 69.0 267.0 45.5
4.4 12.0 1.8 1.0 20.0 328.5 328.5 7.3 21.7 57.5
21.7 202.0 328.5
46,827
37.0 17.0
Zn
1.2 1.8 5.8 6. l 8.6 5.2 4.6 5.2
5.2 1,1 1.1 1.0 3.5 4.1 4,1 1.0 0.7 1.5
0.7 3.0 4.1
10,0
1.4 53.0
Cd
18 84
21 24 89 10
0 0 0 0
continued
8 16 470
30 30 30 30 30 520 520 15 8 74
8 380 520
30,010
Pb
1.1 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0
0
0 0
Hg
Average concentration of chemical elements (ppm)
T A B L E 1 (continued) M a s s a n d c o m p o s i t i o n o f 52 w a s t e c a t e g o r i e s a n a l y s e d in M S W f r o m G e n e v a
to
7
44 45 46 46a 46b 47 47a
43
42
39 40 41
37a 37b
37 37a 37b 38
47a
46a 46b
15 10 44 45
33 15 10
32 15
14 33 15 C D
N*
N
Plastic scraps Synthetic mousse Moulded pieces Cigarette packets Cardboard Plastic Aluminium Tetra Brik without aluminium Tetra Brik with aluminium Packaging composites AI + plastic Polyethylene Aluminium Pack. comp. AI + plast. + paper Polyethylene Aluminium Paper Packaging composites AI + paper Aluminium Paper Paper + paraffin wax Cardboard + paraffin wax Batteries Zinc-carbon batteries Alkaline batteries Medicament packaging Solid medicaments (medications)
Class or material
0.100
0.440 0.560
0.400 0.600
0.600 0.100 0.300
0.900 0.100
0.810 0.020 0.170
0.079 0.921
Fraction of material
0.087
0.173 0.195 0.030
0.136
0,128
0.065 0.096 0.121
0.002
0.003 0.001 0.002
0.002
0.001
0.004 0.007 0.001
0.002
0.019
0.070
0.177
Composition
Humidity
% by weight
0 0
0
0 0
0 0 0 0
0 0 0
0 0
0 0 0 40 40
F
4,267
32,551 593
2,700 2,267 1,933 1,633
35,500 2,700 2,267
2,600 2,700
2,300 35,500 2,700 300 400
91,000 2,450
CI (thousands)
6.8
2,724.7 8,097.7
12.0 12.0 209.7 12.3
34.0
95,305 114,881
44.0 41.0 77.3 23.3
45.0 44.0 41.0
435.0 44.0
91.0 12.0
17.5 12.0 12.0
59.7 45.0 44.0 50.0 50.0
283.0 39.4
Zn
84.3 17.5 12.0 15.0 15.0
155.0 19.0
Cu
1.4
5.3 19.6
3.6 2.5 4.4 1.7
8.6 3.6 2.5
6.1 3.6
2.2 8.6 3.6 0.0 0.0
7.9 138.0
Cd
0
72 836
0 0 0 0
0 0 0
0 0
0 0 0 0 0
0 0
Hg
Average concentration of chemical elements (ppm)
T A B L E 1 (continued) M a s s a n d c o m p o s i t i o n o f 52 w a s t e c a t e g o r i e s a n a l y s e d in M S W f r o m G e n e v a
c'onthlued
102 15
24 23 263 15
21 24 23
590 24
43 21 24 3 3
288 259
Pb
~'
.~ .~
Liquid medicaments (medications) Glass Plastic Paper/cardboard Aluminium Electronic material Toxics Cleaning products Paints Various products Polyethylene PVC Glass Tin plate Wood-leather-rubber scraps Wood Leather Rubber Inert materials Others
Class or material
0.810 0.054 0.136
0.470 0.180 0.100 0.150 0.010 0.040 0.050
0.380 0.280 0.160 0.020 0.060
Fraction of material
0.275 0.369
0.150
0.030 0.080
Humidity
0.057 0.024
0.017
0.003 0.006
Composition
0 0 0 867 0
0 0 0 0 0 0 0
867 0 0 0 0 0
F
1,850 4,600 13,000 1,733 3,500
2,500 1,300 4,400 2,900 223,333 200 500
1,300 200 2,900 2,300 6,950 7,567
CI (Thousands)
13.0 74.5 28.0 35.3 112.0
0.7 1.9 0.6 14.6 4.6 7.9 313.0
1.0 7.9 14.6 84.3 4.7 30,333
Cu
70.5 436.5 7,028.0 97.0 324.3
906.0 4.3 18.0 57.5 21.7 3.6 328.5
15.3 3.6 57.5 59.7 14.0 17,689
Zn
2.0 4.9 8.4 2.5 4.5
1.2 0.2 0.2 1.5 0.7 0.8 4.1
0.8 0.8 1.5 2.2 2.3 509.0
Cd
0 0 0 0 0.7
0 0.6 0 0 0 0
0 0 0 0 0 0
Hg
Average concentration of chemical elements (ppm)
309 372 197 2,055 311
8 11 1 74 8 11 520
4 11 74 43 72 29,805
Pb
N, rank number of waste category: N*. number of the waste category of reference: A. B, pure metal: C, D, chemical composition indicated by manufacturer: E. chemical analysis could not be made; 0, concentration below threshold of applied analytical technique; -. no determination made: concentrations are given in ppm with the exception of CI (given in thousands); a-g, subclasses of a category: CFC. chlorofluorocarbons: PVC, polyvinyl chloride: PE, polyethylene.
50a 50b 50c 51 52
49a 49b 49c 29 28 9 26
47b 9 29 13 19 48
47b
48 49 49a 49b 49c 49d 49e 49f 49g 50 50a 50b 50c 51 52
N*
N
% by weight
T A B L E 1 (continued) M a s s a n d c o m p o s i t i o n o f 52 w a s t e c a t e g o r i e s a n a l y s e d in M S W f r o m G e n e v a
,7"
b~ ta~
~"
~.
.,, ,.~ ~.
~.
~"
Class or material
Vegetable and foodstuffs Meat scraps Natural tissues Synthetic tissues Nylon stockings Unweaved sanitary Disposable nappies Various textiles Glass Newspaper Packing paper Other paper Other cardboard Packing cardboard Household aluminium Aluminium aerosols Aluminium tubes Aluminium pastry boats Aluminium covers Aluminium beverage cans Aluminium scraps Non-ferrous metals Iron food cans Iron covers Iron aerosols Iron beverage cans Iron scraps PVC bottles
N
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 0.261 0.017 0.006 0.007 0.001 0.002 0.033 0.005 0.096 0.121 0.011 0.116 0.032 0.032 0.002 0.001 0.001 0.001 0.001 0.002 0.001 0.003 0.013 0.002 0.001 0.001 0.016 0.006
Composition 0 0 0 2.65 0 0 0 1.92 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
F 253.9 215.1 9.5 9.0 1.2 3.1 30.6 6.5 19.1 228.0 23.1 316.8 53.0 60.2 4.0 0.1 3.9 4.4 3.5 0.4 1.2 21.8 8.9 1.2 0.6 0.3 0.0 1239.9
CI 1.93 0.22 0.29 0.05 0.01 0.01 0.20 0.03 0.75 1.21 0.39 27.16 1.66 2.21 0.02 0.02 0.01 0.01 0.00 0.07 0.00 102.25 2.36 0.73 0.37 0.18 0.11 0.03
Cu 5.03 0.89 0.53 0.23 0.03 0.05 1.04 0.16 0.34 4.12 0.23 3.39 1.74 1.56 0.06 0.2 0.02 0.03 0.01 0.07 0.01 121.50 2.39 0.76 0.39 0.19 0.11 0.12
Zn 0.218 0.036 0.010 0.012 0.001 0.004 0.029 0.008 0.079 0.251 0.018 0.812 0.053 0.058 0.005 0.001 0.000 0.000 0.001 0.003 0.029 0.026 0.035 0.009 0.005 0.002 0.016 0.004
Cd 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Hg
Standardized flux of chemical elements (g tonne-~)
TABLE 2 Contribution of 52 waste categories to the total flux of elements in MSW from Geneva
continued
2.64 0.77 0.12 0.10 O.Ol 0.03 4.17 0.07 181.38 2.35 2.77 3.73 1.60 1.13 0.04 0.01 0.02 0.03 0.04 0.03 0.05 77.87 4.50 1.21 0.62 0.30 0.23 0.04
Pb
7~
bJ
Polyethylene bottles Solid moulded boxes Rubbish bags Supermarket bags Over-packing Plastics from foodstuffs Rigid pots (yoghurts) Polystyrene Plastic scraps Cigarette packets Tetra Brik without A1 Tetra Brik with AI Packaging comp. A1 + plastic Pack. comp. AI + plast. + paper Pack. composites AI + paper Paper + paraffin wax Cardboard + paraffin wax Batteries Medicament (medications) packaging Electronic material Toxics Wood-leather-rubber scraps Inert material Others
29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
N, rank number of waste category.
Total for the stratum considered
Class or material
N
1.000
0.006 0.005 0.011 0.006 0,010 0.012 0.009 0.002 0.019 0.002 0.004 0.007 0.001 0.001 0.002 0.003 0.001 0.002 0.002 0.003 0.006 0.017 0.057 0.024
Composition
41.4
0 0 0 0 0 0 0 0 0 0 0.15 0.24 0 0 0 0 0 0 0.72 0 0 0 35.69 0
F
5289
15.8 560.6 44.6 12.1 345.6 1322.9 10.4 2.3 167.8 5.5 1.1 2.4 2.3 21.3 4.4 4.8 1.2 21.3 4.2 19. I 25.1 50.8 71.4 52.6
C1
236.1
0.08 0.29 2.17 0.42 0.17 0.57 0.29 0.01 0.53 0.13 0.05 0.09 0.07 0.01 0.02 0.52 0.01 8.34 0.02 76.50 0.10 0.27 1.46 1.68
Cu
382.7
0.31 0.29 3.94 2.02 0.44 0.72 1.91 0.07 1.04 0.10 0.18 0.30 0.35 0.04 0.08 0.19 0.02 154.62 0.05 44.61 2.50 14.98 3.99 4.87
Zn
5.84
0.008 0.008 0.063 0.028 0.084 0.054 0.033 0.008 2.269 0.005 0 0 0.005 0.006 0.005 0.011 0.001 0.019 0.002 1.284 0.006 0.044 0.102 0.068
Cd
0.74
0 0.0011 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.7275 0 0 0.0003 0 0 0.0110
Hg
Standardized flux of chemical elements (g tonne -~)
T A B L E 2 (continued) Contribution of 52 waste categories to the total flux of elements in MSW from Geneva
470.3
0.40 0.07 5.10 2.74 0.20 0.25 0.63 0.02 4.64 0.07 0.01 0.02 0.47 0.02 0.04 0.65 0.01 0.08 0.05 75.17 0.24 4.29 84.62 4.68
Pb
I'J
.,.t
e~
reed s med s
S
0.04 0.01 1.00 0.!4
0 7203 967
137 24
6292 953 690 148 176 76 7 2 37
C1
0
54 12 36 7 46 20 0.7 0.2
F
207 38
0
.
0.8 0.3 20 6 185 37 I 0.5 -0.01
Cu
.
545 89
0
13 3 317 63 209 63 6 3 -0.04
Zn
.
7 1.6
0
.
0.4 0.2 5.9 1.5 1.1 0.3 0.11 0.06 - I E-05
Cd
.
1.2 0.5
0
0.7 0.5 0.39 0.13 0.05 0.02 0.02 0.004 0
Hg
337 63
0
6 1 11 24 216 58 3 2 0.01
Pb
• no analysis was made: 0, flow was considered to be nil: med, mean: dif, calculated from the differences in concentration over a l-day period: s, standard deviation.
Scrap iron and large objects 11=6 Total u r b a n waste 11=6
0.78 0.18 0.02 0.00 0.16 0.03 0.0005 0.0001 -
Smoke n=6 Filter dust n=6 Clinker (dust & u n b u r n t n=6 Economizer 11=6 Cooling tub
reed s reed s med s med s dif
Final mass
Incineration products
Flux of chemical elements (g t o n n e ~)
TABLE 3 O u t p u t flows of WTE, G e n e v a
.t'-,
1-o
217
Goal-oriented characterization o f urban waste
TABLE 4 Input and output (g tonne-~) of waste as collected Elements
F
C1
Cu
Zn
Cd
Hg
Pb
Input
min max
25 50
3600 6600
150 270
250 470
4.0 7.0
0.4 0.9
310 570
Output
min max
110 165
6200 8200
170 250
450 630
5.5 8.5
0.7 1.7
280 400
(1) Chemical analyses of some categories may be biased, but it is impossible to know which ones; (2) It is impossible to know if the waste composition of 27 May 1986 was similar to the annual average; (3) Slight changes in the composition of waste certainly occurred between 1986 and 1989, but it is difficult to evaluate their influence. The reliability of output values is an important issue, since they are used to evaluate the environmental impact of W T E plants (Pictet et al. 1992). New products brought on to the market inevitably change the composition of waste, with a lag of a few weeks to 1 year. The comparison between 3 years has shown that this change was not very rapid. However, it is likely that the new trends for more "ecological" products, for example, the introduction of new labels such as the German "Blue Angel", will change the waste composition over the next 5 years. New collection practices change the waste composition, e.g. collection of non-mixed waste (glass, paper and cardboard, plastics, etc.). In addition, the obligation to bring back waste to selling points (e.g. batteries) or to special deposit centres (e.g. refrigerators, neon tubes, etc.), will also considerably modify the composition of the remaining mixed waste. Conclusion The investigation made in Geneva has helped define a new strategy for waste management with more intensive recycling (Simos 1990), and will remain a valuable point of comparison for future investigations of waste characterization. References Baccini, P. & Diener, H. P. (1986) Etude de la gestion des d~chets du canton de Gen~ve, Flux des substances (Waste Management in Geneva: Material balance study of municipal incineration). EA WAG-project 30-330, Dtibendorf, Switzerland. Brunner, Paul H. & Ernst, W. R. (1986) Alternative methods for the analysis of municipal solid waste. Waste Management & Research 4, 147-160. Diserens, Th. & Maystre, L. Y. (1988) Les emballages plastiques dans les d6chets (Plastic packaging materials in wastes). Sn,iss Plastics 5, 18-21. Leroy, D., Giovannoni, J. M. & Maystre, L. Y. (1992) Sampling method to determine a household waste composition variance. Waste Management & Research 10, 3-12. Maystre, L. Y. & Diserens, Th. (1989) Analyse de la composition des d6chets m6nagers et assimil~s du canton de Gen~ve (Analysis of the composition of MSW in Geneva). Techniques, Sciences, Mbthodes 3, 179-185.
218
L. Y. Maystre & E Viret
Maystre, L. Y. et al. (1994) DOchets Urbahls, Nature et Caractkrisation (Urban Wastes, Nature and Characterization). Presses Polytechniques et Universitaires Romandes, Switzerland. Pictet, J., Giovannoni, J. M. & Maystre, L. Y. (1992) Impact assessment of urban waste processing systems using a multibox model. Water, Air and Soil Pollution 63, 155-178. Simos, J. (1990) Evaluer I'Impact sur I'Environnement (Evahtation of the hnpact on the Envh'onment). Presses Polytechniques et Universitaires Romandes, Switzerland.