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INNOVATIVE EVALUATION OF ECONOMIC DATA ON SOURCE SEPARATION SCHEMES IN LOMBARDY, ITALY M. Giavini1, C. Garaffa2, A. Ribaudo3, G. Ghiringhelli1 1 Ars Ambiente Srl, Gallarate, Italy 2 Novamont Spa, Novara, Italy 3 Regione Lombardia, D.G. Reti e Servizi di Pubblica Utilità, Milan, Italy Contact: Dr. Michele Giavini, Ars Ambiente Srl, V. Carlo Noè 45, 21013 Gallarate, Italy. Tel: +39 0331777991, E-mail: EXECUTIVE SUMMARY Intensive source separation of organics (ISSO) represents a strategic decision, and is Italy’s key factor for reaching an overall high performance of residential recycling schemes. It both maximizes organics diversion from landfill, and reduces the amount of putrescible materials inside residual waste to less than 10 percent. These ISSO results are directly related to high collection frequencies for organics, and tools sets provided to the citizens. Specifially, small kitchen buckets and yearly supplies of compostable bags for collecting the food waste help citizens overcome the “yuck factor,” and secure high participation rates. This paper presents an economic evaluation of the main separate collection schemes already in place in Italy, based on data processed by the author and published in a recent report by Lombardy Region. A detailed analysis was conducted on overall costs for municipal waste management in 2008, using the comprehensive raw data reported by all the municipalities of Lombardy Region. Municipalities are required to report this information using an on-line database managed by the regional Environmental Agency. This dataset is interesting both for the high number of municipalities accounted (1.546, with about 9.700.000 inhabitants), and the presence in the same region of both main types of collection scheme used in Italy: “fetch” curbside schemes (typically ISSO) and “bring” schemes based on large centralized containers placed on the roads. This survey introduces a new comprehensive indicator, which expresses normalized overall costs for waste collection and treatment per equivalent inhabitant, and strongly lessens the bias and the variability that was present in raw data expressed using the traditional total cost per inhabitant. The main outcomes from this survey can be summarized as follows:  As already acknowledged, average diversion rate of municipalities performing curbside collection, mostly with ISSO, is significantly higher than those still adopting centralized road container schemes (averaging 53.2 percent compared to 30.5 percent).  The analysis with a variability plot on overall costs for subsets of municipalities with the same recyclables diversion rate shows that they remain unchanged, or even decrease with higher diversion;  With higher diversion rates, collection costs slightly increase (especially with over 60 percent diversion), but not as much as was commonly thought before this study; treatment and disposal costs decrease.  The use of the new indicator reduces the influence of geographic or demographic parameters showing that costs don’t change much between densely and sparsely populated areas. These results give a consistent support to the local authorities involved in waste management planning, especially thinking about setting up ISSO schemes. They act as a guideline when it comes to think about optimization tools and strategies, because they highlight many municipalities with best practices that succeeded in reaching diversion rates up to 70 percent while keeping overall costs low.



Intensive source separation of organics (ISSO) increasingly plays a pivotal role in Italian waste collection schemes. It started in the northern part of the country in the mid-1990s, with two driving forces: lack of space in landfills and (consequently) increasing tipping fees. The model of source separation that developed is characterized by specific features and tools that allow for high diversion rates, low contamination of organics and strong participation by citizens. The Italian ISSO model achieves impressive diversion rates, and is catching on in Spain and the UK. Until now, most concern was about the assessment of the economic viability of this scheme. Recent data processed by the author and published in a recent report by Lombardy Region, Italy give a statistical evidence of the force of this scheme.


The ISSO scheme features

Compared to the “bring” scheme still in use in many parts of Italy, which is based on large centralized containers placed on the roads, ISSO is a “fetch” scheme and has some distinctive features that boost the quality and diversion rate of recyclable fractions. All of the waste fractions (organics, dry recyclables and residual waste) are collected at the curbside, focusing mainly on the collection of food waste in small, certified compostable bags. Unlike Central European schemes, garden waste curbside collection is discouraged to address waste minimization and maximize food waste diversion, limiting it to seasonal collection services linked to PAYT systems and promoting home composting when possible. Recent research done by WRAP in the UK confirms this (WRAP, 2010). In terms of collection frequency, the Italian integration approach calls for high frequency collections of food waste, in order to keep organics low in the residual waste stream. Organics collection typically ranges from two to three times a week, depending on the Mediterranean/Continental climate and season. This allows the use of smaller (3 to 5 m3 capacity), quicker, cheaper and more environmentally friendly collection trucks, without compaction. There is also manual tipping of 30-litres bins for single houses, which allows for reduced pick-up time compared to mechanical tipping of larger carts (condos are still provided with larger 120- to 240-litres carts, serving 10 to 20 households each). A final feature of ISSO is the use of indoor household tools for maximizing ease of use and increasing participation. Typically 6- to 10-litres vented kitchen buckets and yearly supplies of compostable bags (Figure 1) are given to each household (bags are certified according to European compostability standard EN 13432).

Figure 1 –


A key feature of the ISSO scheme: vented kitchen buckets with breathable compostable bags

The Lombardy Region survey

Economic viability is a key aspect of ISSO. Although initial studies showed the general benefits (Favoino et al., 2002), an important survey was completed in March 2010 (Regione Lombardia, 2010) that focused on the economics of collection schemes in the Region of Lombardy, in northern Italy. Milan is the capital of Lombardy, and the region contains one-sixth of Italy’s population. The survey was based on detailed economic data reported by all 1.546 municipalities in the region. All municipalities in Lombardy are required to enter detailed data about waste collection in a web-based application (O.R.SO.) approved by the Regional Environmental Agency (ARPA). This database is constantly checked and validated at

many levels by the Provinces and by ARPA, but up to now it has been used mostly for performing statistics and evaluations at a quantitative level (e.g. diversion rates, captures of recyclables, trends over years etc.); economic data wasn’t monitored so deeply because of lack of data and bias in data during the first years of the implementation of this on-line monitoring method. The Region was recently urged to go deeply into economic evaluations, so followed the idea of seeing inside this huge dataset with a statistical approach, possibly with a method to clearly identify incomplete or faulty economic data and to avoid the bias generated by them. According to this database, about 850 municipalities in the region are collecting with the ISSO model, about 300 municipalities collect food waste using centralized road containers and the remaining communities do not collect food waste at all.

2 RESULTS AND DISCUSSION 2.1 A new indicator for overall costs 2.1.1 The bias of dividing costs by overall waste production To compare economic data from municipalities with a different population, it’s necessary to divide the overall cost value by a quantity strictly related to the size of the municipality. Often similar surveys (Federambiente, 2009) adopted the indicator calculated by specific costs, dividing total cost by total waste produced (Euro per ton), but lately many researches addressed this evaluation as biased. Actually it penalizes the benefit resulting, for instance, from waste reduction policies, so it’s not advisable when comparing collection schemes with different overall waste production like road containers vs. curbside. The use of the cost per inhabitant indicator is more correct, but it suffers from another bias; it’s usually calculated using the resident population, not taking into account the effect of other waste producers such as non-residents (tourism, people living in rented households, non residential producers such as small industries whose waste production is accounted into the municipal waste, etc.). Using simply the resident population, for instance, tourism areas show higher costs expressed per capita. To deal with this issue, the survey introduced the parameter “equivalent population” explained as follows. 2.1.2 Equivalent population The equivalent population has been calculated merging data already present in the O.R.SO. database, that is the number of residential households, and of the industries producing municipal waste, both registered because they pay the waste tax to the municipality. Also the indication of the “tourism months”, highlighted in the on-line form, was taken into account. The calculation of this indicator is based on some assumptions, specified as follows:  The standard value of the number of people for a residential household was set to 2,4, calculating it as an average from municipalities not affected by tourism;  Non residential producers (small industries) were accounted as though they were a household with 3 people. This value is a compromise that avoids excessive unbalance in the calculation in case of a high industrial presence. Then the indicator comes out this way:  Dividing the resident population by 2,4, we obtain the Resident Domestic Households;  The difference between the total residential households stated in the on-line form and that resulting from the above calculation was addressed to be related to temporary living people (tourism), so it was transformed into equivalent inhabitants by multiplying it by 2,4, then by an average residency factor of 3 months over 12. This value is the Equivalent Population related to tourism;  Multiplying the number of non residential units by 3, the obtained value is the Equivalent Population related to small industrial and commercial producers;

The Total Equivalent Inhabitants value comes from the sum of the resident population and the equivalent inhabitants related to tourism and non residential units.

2.1.3 Breaking down road cleaning costs Road cleaning activity, performed by the municipalities both mechanically and manually, produces waste that is taken into account as municipal waste. Of course this activity bears a cost, which is indeed well specified in the detailed economic section of the O.R.SO. forms filled by the municipalities. This fact made us consider the possibility of subtracting this cost from the overall waste management cost, not accounting for it. Actually, this cost in not related to the specificity of the waste collection scheme, but only to urban and territorial parameters (i.e. road cleaning is performed typically in densely populated towns with high urbanization). 2.1.4 The final indicator After these considerations, the survey proposed a new indicator called “Normalized Overall Costs” which represents the sum of all detailed costs for waste management including collection, transport, disposal and recycling fees for both recyclables and residual waste, general costs, excluding road cleaning, divided by the equivalent population as calculated above.


Reduction of variability

2.2.1 Keeping off the outliers The survey also tackles the issues of avoiding faulty or error biased data to affect the sample statistical analysis. Actually, although the on-line O.R.SO. forms are well reviewed by the Waste Monitoring Offices which are part of the Provinces, these economic data are sometimes not filled in properly by the municipalities. Nonetheless, 100% of the 1.546 municipalities filled the forms, so this high number allow the exclusions of some cases considered as outliers in situations such as :  Abnormal variation in total costs with respect to the previous year (153 cases above 95 th or below 5th percentiles with respect to the regional average were excluded);  Overall cost per capita considered outlier after performing statistical tests (interval µ ± 2σ, so excluding other 55 cases); 2.2.2 Effect of the reduction of variability After this data pre-processing (normalization with the new indicator, elimination of outliers), the first important result is the reduction of the overall variability in the sample, as shown in Figure 2. The box and whisker plot gives a visual representation of the variability of the sample after the different steps of normalization, summarized as follows:  Step 0: raw data for overall costs expressed per inhabitant  Step 1: elimination of cases with anomalies in variation of costs vs. previous year  Step 2: normalization by equivalent population as described in par. 2.1.2  Step 3: elimination of outliers as in the second point of par. 2.2.1  Step 4: elimination of road cleaning costs.

Box & Whisker Plot Normalization steps

Overall costs per inhabitant . year

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Step 4 Step 3

Mean Mean±SD Mean±1,96*SD

Effect of the reduction of variability after normalization steps

This representation gives strength to the choice of the new indicator, which corresponds to the normalization step 4. The variability (expressed as standard deviation, SD) was reduced of almost 65 percent, as shown in Table 1. After these normalization steps, it was possible to evaluate the normality of values distribution, with a statistical test like KolmogorovSmirnov.

Table 1 –


Sample (n) Average Min Max St. Dev. Raw data 1532 97,35 15,32 775,45 46,93 Normalization step 1 1380 97,38 28,49 588,76 40,89 Normalization step 2 1376 77,10 19,79 367,97 23,10 Normalization step 3 1314 75,72 42,79 128,22 17,53 Final indicator (normalization step 4) 1312 70,77 31,65 126,84 16,62 Numeric values related to the normalization steps. All data expressed in €/inhabitant/year.


2.3.1 Geographical and demographic parameters A first remarkable consideration concerns the possible correlation between overall normalized costs and features related to the territory, such as population density expressed in inhabitants per square kilometre. There is a lack of such a relationship, meaning that total waste management costs don’t change much between densely and sparsely populated areas. This is due to the fact that every municipality succeeded in fitting the general collection model to its specific circumstances (e.g. collection frequencies optimization) without increase of cost. With the use of the new normalized indicator, highly urbanized municipalities like those in the hinterland of Milan are shown to bear the same costs as those in rural areas, although considering the residual variability between cases belonging to these subsets. 2.3.2 Collection schemes: curbside vs. road containers Lombardy is an interesting case study because of the existence of both waste collection schemes in different municipalities of the same region (see Figure 3). . According to the O.R.SO. database, in Lombardy 1099 municipalities use the curbside collection, of which about 850 municipalities apply ISSO model, 447 municipalities use road container schemes, and among them about 300 collect also food waste using these containers.

Figure 3 –

Road containers and curbside collection schemes

The consistency of this database allow for making a statistic comparison between these two schemes, detailed in table 2. As already acknowledged, average diversion rate of municipalities performing curbside collection mostly with ISSO are significantly higher than those still adopting centralized road container schemes (averaging 53.2 percent compared to 30.5 percent). Also, another confirmed aspect is the higher overall waste using big road containers; a major benefit of ISSO is indeed an overall decrease in residential waste generation, due to limits on curbside setouts. Nonresidential waste is also reduced because it can no longer be dropped off anonymously in centralized roadside containers. As for the economic comparison between the two schemes, again a high variability emerges but, on average, curbside collection costs are slightly cheaper. –

Average – road containers

Standard deviation – curbside

Standard deviation – road containers

Diversion rate





Overall waste capture (kg/inhabitant/year)





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Normalized overall costs (€/eq. inhabitant/year) Table 2 -

Comparison between 1099 municipalities adopting curbside collection and 447 with road containers scheme

2.3.3 Overall costs vs. diversion rate An “evergreen” graphic representation is the scatterplot in which one looks for a possible relationship between overall costs and the diversion rate for a set of municipalities.

r 2 = 0,0085

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Overall Normalized Costs

Often these plots results in a very dispersed cloud of dots without a clear correlation; in this survey the chart is represented in Figure 4. A more powerful visualization is the variability plot (Figure 5), in which data are categorized into sets with the same range in terms of diversion rate. Statistically speaking, it’s possible to say that there is no difference between average costs in all the subsets, but the visualization of the variability plot highlights a certain decreasing trend in costs with increasing diversion rate.

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Figure 4 – Scatterplot of overall costs vs. diversion rate for the two considered subsets of municipalities

Figure 5 – Variability plot with overall standardized costs for subsets of municipalities in Lombardy with the same percent diversion rate of recyclables

2.3.4 Breaking down overall costs Another impressive outcome, shown in Figure 6, illustrates the different costs for collection and treatment/disposal, using subsets of municipalities with the same recyclables diversion rate. It is clear that overall treatment costs decrease with higher diversion rates, because of the lower tipping fees for most recyclables and consequently avoided gate fees for disposal. Collection costs increase slightly but only over 60 percent diversion, because of the most labour intensive scheme, but not as much as was commonly thought before this study. This is the result of collection frequency optimization performed by municipalities after years of experience with the first pilot areas.

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Figure 6 - Total decrease in the sum of disposal/treatment and collection costs, for groups of municipalities with the same range of diversion rate of recyclables



The survey from Regione Lombardia provided some important evaluations, starting from a huge and validated dataset and using statistical analysis. Pre-processing of data with many normalization steps proved to be an important phase in order to have a sharper focus on economic differences strictly related to the collection schemes, and the introduction of a new indicator to express overall costs, gives interesting outcomes. From this survey the main consideration is that a higher diversion rate doesnâ&#x20AC;&#x2122;t necessarily lead to higher overall costs and is due to the fact that the ISSO scheme is based completely on optimization tools and strategies that help keep costs low, such as reduction of the collection frequency for residual waste. Nevertheless, data show a great variability which, especially for curbside schemes, can be often explained with the different choices implemented by the municipalities (e.g. food waste collection ranges from once to three times a week). Municipalities with diversion rate higher than 70 %, experience a certain increase in collection costs, which leaves room for optimizations that can be achieved looking at the best practices in other municipalities. Overall, ISSO schemes in Italy have been widely successful, and continue to influence trends in Italy and other countries as well. For instance, the model is spreading to Spain and the UK, in particular in areas where some concurrent elements are present: lack of landfill space and increasing tipping fees, available or planned composting or anaerobic digestion capacity, regional regulations mandating separate collection of organic waste and adoption of the diversion targets given by the EU Landfill Directive 99/31/EC. With increasing data on the Italian model, it will be easier to be implemented in new locations, with confidence that diversion rates will increase without incurring extra costs.

REFERENCES E. Favoino, M. Ricci F. Giro i Fontanals (2002): Myth and reality about cost of separate collection schemes, Workshop of the EC "biological treatment of biodegradable waste: technical aspects, Brussels Federambiente (2009): Analisi dei costi della raccolta differenziata dei rifiuti urbani. Bain & Company, Rome. Regione Lombardia (2010): Valutazione Statistico â&#x20AC;&#x201C; economoica dei modelli di gestione dei rifiuti urbani in Lombardia. In: WRAP, Waste and Resources Action Programme (2010): Performance analysis of mixed food and garden waste collection schemes â&#x20AC;&#x201C; Final report

Giavini - Innovative evaluation of economic data on source separation schemes in Lombardy - 2010  
Giavini - Innovative evaluation of economic data on source separation schemes in Lombardy - 2010