Subido por loguemiemiliano

Methodology to design a municipal solid waste pre-collection

Waste Management 36 (2015) 1–11
Contents lists available at ScienceDirect
Waste Management
journal homepage:
Methodology to design a municipal solid waste pre-collection
system. A case study
A. Gallardo, M. Carlos ⇑, M. Peris, F.J. Colomer
Dept. Mechanical Engineering and Construction, Jaume I University, Av. de Vicent Sos Baynat s/n, 12071 Castelló de la Plana, Spain
a r t i c l e
i n f o
Article history:
Received 18 June 2014
Accepted 8 November 2014
Available online 28 November 2014
a b s t r a c t
The municipal solid waste (MSW) management is an important task that local governments as well as
private companies must take into account to protect human health, the environment and to preserve natural resources. To design an adequate MSW management plan the first step consists in defining the waste
generation and composition patterns of the town. As these patterns depend on several socio-economic
factors it is advisable to organize them previously. Moreover, the waste generation and composition patterns may vary around the town and over the time. Generally, the data are not homogeneous around the
city as the number of inhabitants is not constant nor it is the economic activity. Therefore, if all the information is showed in thematic maps, the final waste management decisions can be made more efficiently.
The main aim of this paper is to present a structured methodology that allows local authorities or private
companies who deal with MSW to design its own MSW management plan depending on the available
data. According to these data, this paper proposes two ways of action: a direct way when detailed data
are available and an indirect way when there is a lack of data and it is necessary to take into account bibliographic data. In any case, the amount of information needed is considerable. This paper combines the
planning methodology with the Geographic Information Systems to present the final results in thematic
maps that make easier to interpret them. The proposed methodology is a previous useful tool to organize
the MSW collection routes including the selective collection. To verify the methodology it has been successfully applied to a Spanish town.
Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction
In a municipal solid waste (MSW) management system, selective collection is divided into two stages: pre-collection and collection. Pre-collection includes the activities which involve the
handling of the waste at origin (separation, storage and pre-processing) in order to gather it together to facilitate its collection.
In some cases, this stage also involves modifying some of the physical characteristics of the waste material such as its density, moisture, etc. Collection is the activity that consists in transferring the
MSW from the primary disposal site to a treatment plant. To define
the selective collection system, it is necessary to take into account
an important number of technical, economic, environmental and
legal factors related to the place where the activity will be carried
out (Rada, 2013; Baltes et al., 2009; Toso and Alem, 2014). Therefore, there is no single, universal model valid for all towns and
⇑ Corresponding author. Tel.: +34 964728114.
E-mail addresses: [email protected] (A. Gallardo), [email protected] (M. Carlos),
[email protected] (M. Peris), [email protected] (F.J. Colomer).
0956-053X/Ó 2014 Elsevier Ltd. All rights reserved.
The active role of citizens in the pre-collection stage, as waste
generators and service users, means that the social factor is of great
importance in designing it. Thus, Bolaane (2006) highlighted that
the citizens’ participation is one of the main factors to be considered
when several selective collection alternatives are analyzed. There
are a number of practical reasons why citizens might not participate in a selective collection system (Castagna et al., 2013;
González-Torre and Adenso-Díaz, 2005). Some of these reasons
include the distance to the collection point, overflowing bins, the
lack of space at home, a distrust of correct management of the
recovered materials, the presence of family members who are not
willing to participate, the low number of recyclable products generated or poor knowledge of the selective collection system if they are
new neighbors in the zone (Berné et al., 2000; Keramitsoglou and
Tsagarakis, 2013; Martin et al., 2006; Wagner, 2013; GonzálezTorre et al., 2003; McDonald and Oates, 2003). However, other studies show that a higher participation in the recycling system by
citizens is related to their environmental awareness and to their
considering that it is everybody’s responsibility (Vicente and Reis,
2008; Rada et al., 2014a,b). In fact, Mueller (2013) found an increase
in the separation ratios when the investment in recycling education
A. Gallardo et al. / Waste Management 36 (2015) 1–11
programs increased. The methodology usually employed to assess
the degree of acceptance in a new selective collection system or
the implementation of certain measures to enhance the separation
ratio is to conduct a citizens’ survey (Bolaane, 2006; Karousakis and
Birol, 2008; Keramitsoglou and Tsagarakis, 2013).
Another important point to be taken into account when designing a waste pre-collection system is the economic factor, which
involves studying the investment and system management costs
(Munizaga Plaza and Lobo García de Cortázar, 2013). Selective collection costs may represent 70% of the total cost of MSW management and can vary depending on the pre-collection system applied
(Tavares et al., 2009; Rada et al., 2013). Several studies have analyzed the costs of the selective collection of MSW (Zsigraiova
et al., 2013; McLeod and Cherrett, 2008). Some of them compare
the economic costs of management systems that include selective
collection with those without waste separation (Tonjes and
Mallikarjun, 2013; Lavee, 2007), results varying from one study
to another. Lavee (2007) established that selective collection is
economically viable in medium-sized and large towns, whereas
Tonjes and Mallikarjun (2013) pointed out that selective collection
is not efficient if environmental factors are not taken into account.
One of the aims of selective collection is to improve the environmental conditions, as MSW reutilization and recycling reduces
the extraction of resources required to obtain new materials
(Margallo et al., 2010; Rada et al., 2014a,b; Raicu et al., 2011). Additionally, the recovery of nutrients and materials also reduces
greenhouse gas emissions (Menikpura et al., 2013). Along similar
lines, De Feo and Malvano (2009) showed that with the same
MSW treatment, the scenario with a higher percentage of selective
collection is environmentally better.
Nevertheless, the environmental impact will vary depending on
how the pre-collection is carried out (Ionescu et al., 2013;
Giugliano et al., 2011; Ghiani et al., 2012). For example, drop-off
sites will cause less environmental impact than door-to-door collection or pneumatic collection (Iriarte et al., 2009). Large-volume
containers will also generate less environmental impact than doorto-door collection (Rives et al., 2010).
Legislation is another important factor to be considered when
MSW pre-collection is being designed. MSW management is ruled
by international, national, regional and local regulations. Moreover,
regulations can condition the generation of certain kinds of waste,
like the generation of plastic bags, especially in those countries
where regulations are more developed (Mazzanti et al., 2008). In
Europe, Directive 2008/98/EC addresses the aims of waste recovery
and recycling. In Spain, this Directive has been entirely transposed
by the law Ley 22/2011 (BOE, 2011). In Flanders, the aim of the
‘‘Implementation plan for household waste 2003–2007 and sustainable management 2010–2015’’ is to reduce and maintain waste
generation at 150 kg inh1 year1 (Gellynck et al., 2011). In Denmark, the Waste Strategy 2005–2008 was developed to reach the
aims established in Directive 2004/12/EC about the selective collection of packaging (Larsen et al., 2010). Similar regulations can
be found in other European countries.
In addition, there are political programs to boost the reduction
of waste, a more adequate handling of waste or greater recycling of
materials. These objectives have been developed as plans which
involve instruments offering incentives to manage MSW properly,
to encourage selective collection or to punish excess waste generation. André-García and Cerdá Tena (2006) sorted these instruments into three classes: A payment proportional to the rate of
generation, a tax applied to the packaging of products, and incentives on recovering and recycling. Some industrial sectors have
committed themselves to achieving recycling goals as set out in
the European Declaration on Paper Recycling 2011–2015. Hence,
in 2015, a recycling rate of 70% must be attained by the European
Union member countries. To achieve this aim, waste pre-collection
and collection require a process design. In fact, the pre-collection
design must define all its main elements (like the waste fraction
rate, the storage level, the type of bin, etc.) as well as the relations.
For example, the model proposed by Coutinho-Rodrigues et al.
(2012) determines the number of facilities to be opened, their
respective capacities, their locations, their respective shares of
the total demand, and the population that is assigned to each of
the candidate sites to be opened. Furthermore, they must be
adapted to the characteristics of the geographic zone where the
pre-collection will be carried out (Gellynck et al., 2011). For all
these reasons, several authors have developed different methodologies that allow selective waste collection to be designed accurately. Correct distribution and size of the disposal points are
essential to achieve the desired level of source separation, to offer
a good service (disposal points without spilling and with low visual
impact), and to facilitate waste collection. These methodologies
establish a wide range of goals: optimization of the collection
routes (Zamorano et al., 2009); estimation of MSW generation over
time, and the weekly and daily peak hours (Zafra, 2009), in order to
minimize the distance the user must walk to the collection bin and
to maximize the number of users covered (Gautam and Kumar,
2005; Bautista and Pereira, 2006), or to highlight the relevance of
regular system monitoring as a service assessment tool (Teixeira
et al., 2014).
In the literature there are also several specific studies about
how to carry out pre-selective collection in small towns (less than
50,000 inhabitants), like Churriana de la Vega (Zamorano et al.,
2009) and Aranjuez (López Alvarez et al., 2009), and in big towns,
like Hsinchu (Kao and Lin, 2002). Other authors compare different
pre-collection scenarios in a zone. Tanskanen and Kaila (2001) analyzed the efficiency of six pre-collection scenarios in Helsinki,
while Larsen et al. (2010) compared the influence of the rate of
at-source separation in five pre-collection schemes in Aarhaus
The main aim of the present paper is to present a general methodology for designing MSW pre-collection and its application in a
case study. The methodology detailed here is flexible so as to allow
waste pre-collection design in towns with different characteristics.
Geographic Information System (GIS) tools are also used as a
support in the methodology because they are extremely useful in
work that needs to analyze and treat spatial data (for example,
to measure distances, to optimize collection routes, to analyze
the collection points and to allocate them, etc.) and it is an interactive decision support system (Tralhão et al., 2010). The methodology proposed in this paper can be a suitable tool for enterprises
and administrations that deal with MSW management.
2. Methodology
In order to manage the MSW in a specific geographical area correctly it is essential to have previously defined an adequate precollection system. The methodology proposed here takes into
account technical, economic, environmental and legal factors,
among others, that affect every stage of the pre-collection design.
In fact, when the specific characteristics of an area are considered,
the pre-collection must be perfectly adapted to the socio-demographic, economic, cultural and geographic characteristics of the
environment where the collection is to be carried out. Fig. 1 shows
a schematic representation of the stages of the methodology proposed and the factors that affect each of them.
The purpose of the methodology is to help waste managers to
locate the minimum number of MSW collection points in a town
and determine the number of bins needed, taking into account
some variables like the storage level (SL), the frequency of collection, the bin volume, etc.
A. Gallardo et al. / Waste Management 36 (2015) 1–11
- MSW Composition
- Treatment methods
- MSW separation
- Current regulations
- Users requirements
Number of waste
fractions selection
- Current regulations
- Population density
- Costs
- Fractioning rate
Storage level selection
- Fractioning rate
- Maximum distance to source
- MSW daily generation rate
- Inhabitants per generation point
- Collection frequency
- Coefficient of utilization
- Space availability
- Urban environment
- Density
Location of the MSW
disposal points
Volume of the MSW
disposal points and
bins selection
Maps of the disposal
point distribution for
each fraction
Fig. 1. Schematic representation of the methodology.
The first stage of the methodology consists in selecting the
number of waste fractions (NWF), which is the number of waste
fractions the MSW is divided into at source. This figure will determine the number of waste streams that will be collected separately
by the collection services.
This decision should be made by the waste managers and it will
depend on the objectives proposed in each case.
In the second stage, the level of storage of each waste fraction
must be selected. Hence, the factors that affect the SL must be analyzed first. Afterwards, an adequate SL must be defined for each
waste fraction. The SL refers to the distance that the citizen must
walk to the disposal point.
In the third step of the methodology, the location of the storage
point will be chosen. The location points depend mainly on the
previously selected SL and the recovery rate of the different materials (glass, paper and cardboard, light packaging, etc.) that we
want to achieve. This stage is developed in a GIS environment
and, therefore, it is advisable to select software capable of performing network analyses.
In the fourth stage, the storage volume at each point must be
defined for each waste fraction. Additionally, the type of bin must
be selected and the number of bins in each location must be
defined, taking into account the collection system, the urban environment, and the possible annual bin overflows that have been
previously set.
Finally, a map with the pre-collection points will be drawn for
each waste fraction using GIS tools with all the information
explained above.
2.1. Waste fraction selection
Citizens can perform several waste pre-treatments at home to
reduce the volume of waste, to recover materials and to change
their physical shape. From all these possibilities, the most
extended pre-treatment is the separation of materials and its main
aim is to take advantage of the recovered materials (Lavee and
Nardiya, 2013). The factors that affect the NWF are the composition of the waste, the waste valorization method, the difficulty
involved in waste separation, the restrictions imposed by regulations, and the market requirements (Gallardo, 2000). Depending
on all these factors, the waste manager must select the most suitable NWF in the area under study.
The heterogeneous composition of MSW can give rise to materials pollution that can become even higher as the materials
remain more time together. For that reason, waste separation at
source depending on the type of material makes it possible to
improve materials valorization. In fact, it allows higher quality
materials to be obtained, as Huerta-Pujol et al. demonstrated in
2011 in the case of compost or Miranda et al. (2013) in the case
of paper. In this sense, the valorization method that will be applied
to MSW will affect the NWF. In addition, the method of separating
the materials must be simple to facilitate this task for citizens so
that they can separate the materials correctly and the number of
inappropriate materials will be as low as possible. Furthermore,
the sub-products market demands, on an ever-increasing basis,
recovered materials of higher quality.
The country regulations can also set an NWF value, the recovery
percentage or a particular type of treatment. For example, European Directive 2008/98/CE (DOUE, 2008) specifies that at least
paper, plastic, metals and glass fractions must be collected separately before 2015 and that 50% of the overall weight of these
materials must be separated out to be reused and recycled in 2020.
Depending on the factors mentioned above, there can be a wide
range of NWF, from zero, which means a mass or ‘‘all-in-one’’ collection, to a high rate of waste separation by type of material. In
Spain, waste is divided into four or five fractions; glass, paper
and cardboard, light packaging, organic matter and non-segregated
(Gallardo et al., 2010, 2013). In Portugal, glass, paper and plastic/
metals are separated at source (Magrinho et al., 2006), and in Sweden waste is separated into eight fractions (newsprint, glass, paper,
A. Gallardo et al. / Waste Management 36 (2015) 1–11
metal, plastic film, hard plastics, biowaste and residual waste) and,
depending on the town, citizens leave them in kerbside bins or at
drop-off sites.
Therefore, in the first step of the methodology the user should
select the NWF depending on the factors described in this section.
2.2. Storage level selection
Once the waste has been separated at source, it must be stored
either at home or at a street disposal point. Depending on the distance to the street disposal point, different SL can be defined
(Table 1). In order to select the SL, several factors must be taken
into account such as the current regulations, the population density, the costs, and the fractioning rate (FR).
The local regulations generally set the guidelines on MSW collection design, such as the distance to the bins, their size, their
design, etc. In other cases, regulations point out the desirable separation percentage for each material present in the MSW (for
example, European Directive 2008/98/CE), which affects the SL.
The FR is the relation between the amount of waste collected in
a container of a particular waste fraction j (paper, glass, etc.) and
the total amount of MSW.
The distance to the disposal point greatly influences the FR, as
Gallardo et al. (2010) pointed out for the case of selective collection
at drop-off sites. Therefore, depending on the desirable FR, the
most suitable SL will be set. Another factor that affects the SL is
the population density. Consequently, the storage points in dense
towns (or vertical towns) are usually nearer the user than in towns
with a low population density (or horizontal towns).
Moreover, the economic factor must also be taken into account
because the management costs will vary depending on the SL. In
fact, the points which are nearer the citizen (door-to-door or kerbside) are more expensive than the ones which are farther away. In
this latter case, shorter collecting routes, as well as less time and
fewer workers, are required than in the first case. Nonetheless, in
each city the costs must be analyzed since they can vary according
to the characteristics of the town, such as its demographic, physical
or geographic characteristics (Lavee and Nardiya, 2013). Di Maria
and Micale (2013) considered that in their area it was economically
more sustainable to collect high density waste door-to-door and to
collect low density waste at drop-off sites.
Table 1 shows the main characteristics of the SL that can take
place in MSW pre-collection. By combining the NWF and the SL,
a great number of pre-collection alternatives can be obtained. In
Spain, this combination results in eight pre-collection systems, as
pointed out by Gallardo et al. (2012). In all those systems, four or
five fractions, depending on the town, are separated at source,
but the materials and the SL of each one are different.
In this second stage, the user should define the SL taking into
account the selection made in the first stage as well as all the variables mentioned above and depending on the objectives and
restrictions of the case study.
2.3. Location of the MSW disposal points
At this stage, the storage points are distributed within the area
under study. The distribution will depend on the SL selected in the
previous stage. Fig. 2 shows the design requirements proposed to
locate and to calculate the volume of the storage points.
Geographical Information Systems (GIS) allow the user to locate
the storage points as they work with spatial data associated to databases. The GIS tool used must be capable of building the street
network and analyzing it in order to define the location points in
accordance with the factors mentioned above. Several authors
(Valeo et al., 1998; Kao and Lin, 2002; Gautam and Kumar, 2005;
Zamorano et al., 2009) have used the Location-Allocation tool to
locate the selective collection bins.
In this third stage, the user should distribute the collection
points in the area. Fig. 2 shows the maximum recommended distances between the citizen’s home and the disposal point, and
the variables that should be taken into account to define the disposal points at each SL.
2.4. Volume of the MSW disposal points and selection of bins
Once the disposal points have been located (see Fig. 3), the following step consists in defining the bin volume needed to store the
waste until the collection truck arrives.
The definition of the volume of the disposal points consists in
calculating the bin volume needed to receive the waste that will
be deposited at each storage point. Afterwards, the number of bins
needed will be calculated according to the bin size that has been
Table 1
Characteristics of the different storage levels.
Storage level
Door to door
– Bins or containers are located in each door, interior courtyards or other accessible zone in the house or the building
– The citizen must walk a minimum distance
– Usual use: towns with low population density
– Advantage: effortless for the citizen
door to door
– Disadvantage: waste is collected on a fixed schedule and high collection cost
– The disposal points are placed in the street within a aradius of the buffer zone between 20 and 30 m
– Disposal points separation varies between 40–60 m
– Usual use: towns with high population density
– Advantage: the collection is agile, quick and its costs are lower than door to door costs
– Disadvantage: the distance that citizens must walk to the disposal point
– The disposal points are placed in the streets with a radius of the buffer zone between 100 and 300 m
– Disposal points separation varies between 200–400 m
– Usual use: selective collection of light packaging, paper/cardboard and glass
– Advantage: lower costs in the collection compared to kerbside collection, waste disposal with flexible schedule
– Disadvantage: citizen must do a greater effort than in kerbside collection
– The disposal points are placed in establishments within a radius of the buffer zone that varies depending on the number of
establishments that cooperate with the collection
– Usual use: hazardous waste collection (such as batteries, fluorescents tubes or medicinal products)
– Advantage: elimination of the hazardous waste from the other waste fractions
– The disposal points are placed in facilities located at a distance less than 4 km or 15 min
– Usual use: especial waste pre-collection (such as bulky, inert or hazardous)
– Advantage: controlled collection of the especial waste
Kerbside bins
25 m
Drop-off sites
150 m
250 m
Green points
The radius of the buffer zone is the maximum distance that a citizen must walk in a straight line to the disposal point.
A. Gallardo et al. / Waste Management 36 (2015) 1–11
distance to source
Drop off sites
Depends on the
ti i rate
100-300 m
Depends on the
town verticality.
30-40 m
- Inhabitants/housing
- Housings/collecting points
- Daily collection rate
- Utilization coefficient
- Waste fraction density
- Collection frequency
Door to door
Green points
At source
Depends on the
number of the
establishments that
cooperate in the
management system
Distance less than
4km to the town
centre and at a
travel time of less
than 15 minutes
- Inhabitants/housing
- Daily collection rate
- Utilization coefficient
- Waste fraction
- Collection frequency
- Number of
- Number of
inhabitants in the
collection area
- Daily collection rate
- Number of
inhabitants in the
buffer zone
- Daily collection
- Number of
collected materials
Fig. 2. Location and volume of the storage points.
Fig. 3. Example of the location of doorways in some streets in Castellón.
chosen. To calculate the storage volume, the maximum generation
days (such as weekends, holidays, etc.) must be taken into account.
In this way, the bin capacity will be oversized compared to the one
needed under normal operating conditions. The disposal volume at
each point will be defined by Eq. (1):
V ij ¼ ðHbi DGRmsw FRj Cf j Cuj Þ=Dj
where Vij is the bin volume needed (m3 day1) at each disposal
point i and for each fraction j; Hbi is the number of inhabitants
per disposal point; DGRmsw is the daily rate of MSW generation
(kg inh1 day1); FRj is the fractioning rate of fraction j; Cfj is the
coefficient of the collection frequency of fraction j. It is the result
of dividing the period of time considered (one week, two weeks,
etc.) by the number of collection days over that period for each
waste fraction; Cuj is the coefficient of utilization of fraction j;
and Dj is the fraction j waste density in the bin (kg m3).
Coefficient Cf may contribute to increase or decrease the waste
volume stored at each disposal point. When there is daily waste
collection in a town, Cf = 1, this means that there would be a lower
volume of waste at the collection point. If Cf = 3.5, it means that
waste collection is performed twice a week and logically the waste
volume at the disposal point will be higher.
The Cu is used to increase the bin volume needed in order to
take into account the situations which imply greater generation,
A. Gallardo et al. / Waste Management 36 (2015) 1–11
and allows the user to control the number of annual overflows.
Hence, a higher value of Cu will lead to a lower number of bin overflows. This coefficient must be calculated considering the generation of each waste fraction over one year and the maximum
number of overflows selected by the user in that year. For example,
Cu can be defined as follows:
Cuj ¼ Monthly maximum collection of fraction j
=Monthly average collection of fraction j
A high value of Cu means that more bins would be needed in the
streets, but there would be fewer bin overflows. Again, waste managers must decide whether to vary this coefficient or not. For example, if glass generation in the month of August is 20% higher than
the annual average glass generation and the Cu value is defined
as 1.2, there will be no bin overflows in the rest of the months. In
these months, however, there will be too many bins. If Cu = 1, the
number of bins needed will be lower but there will be bin overflows
in the months when glass generation is higher than the annual average. Waste managers must decide on the best solution in each particular case.
The fraction density Dj will vary depending on the size of the
bin where it is placed, and therefore it is necessary to set the bin
volume. For this purpose, the waste density is needed and it can
be defined from different sources such as Tanskanen and Kaila
(2001), Di Maria and Micale (2013), Ecovidrio (2010), WRAP
(2009), the Spanish Ministry of the Environment (2004) or
Zamorano et al. (2009).
The characteristics and the operation of the green points mean
that the way to calculate the capacity needed to design them is different in each case. Other parameters such as the number of inhabitants, the type of waste, etc. must also be taken into account.
The selection of the bin size will depend on the characteristics
of the streets. Nowadays, the most frequently used presentation
and containers are bags or disposable sacks, garbage bins, twowheel containers, four-wheel containers, large-capacity containers,
selective collection bins or buried bins (Mecati and Gros, 2007;
Gallardo, 2000). Once the bin size has been selected, the number
of bins for each disposal point must be determined. To do so, the
disposal point volume is divided by the selected bin volume. Nevertheless, different types of bins can be used in a city, depending on
the design requirements.
At this point, and in accordance with the procedure explained
above, the bin volume will be defined, and the number of bins
needed at each point and in the entire town will be calculated.
2.5. Maps of the distribution of disposal points for each fraction
Finally, in the last step of the methodology the processed information should be integrated into maps. A GIS tool can help to analyze and represent the data spatially. This way of showing the
results will help the user of the methodology make decisions to
improve MSW management. Therefore, maps showing features
such as the location of doorways in the town and the proposed
location of the disposal point (door-to-door, kerbside, drop-off
points or establishments) must first be represented and then analyzed to ensure successful implementation.
3. Case study
To validate the methodology, it was applied to Castellón (Spain).
The results are shown step-by-step on maps and in tables to make
them easier to understand. Castellón is located on the east coast of
Spain, in the Comunidad Valenciana. In this town there are two settlements, the main one is the urban center and the other one is the
maritime district, which is 5 km from the first. Castellón has a pop-
ulation of 180,204 inhabitants, covers an area of 108.8 km2 and has
an average population density of 1655.7 inh km2 (IVE, 2012). The
study area is the urban center, which has a population of 156,221
This paper proposes the design of the pre-collection of paper
and cardboard, light packaging, glass, and mixed waste fractions
in the study area. It also proposes the design for the pre-collection
of medicinal products. This fraction has been included as it represents a good example of the door-to-door collection system.
3.1. Selection of the number of waste fractions
Taking into account European Directive 2008/98/CE (DOUE,
2008), and the Spanish regulations RD 252/2006 (BOE, 2006) and
Ley 22/2011 (BOE, 2011), the proposed NWF consists in: papercardboard, glass, light packaging (plastics, beverage packages and
metal), and mixed waste. To show how to organize pre-collection
in establishments, we present the case of a particular type of
waste, namely, expired medicinal products and their packaging,
which are considered hazardous waste in the regulations.
3.2. Selection of the storage level
In order to select the SL for each waste fraction, the Integrated
Waste Plan (IWP) of the Comunidad Valenciana in Spain was taken
into account (DOGV, 2004). According to the IWP, until the year
2017, mixed waste pre-collection must be carried out at the kerbside and the paper and cardboard, the glass and the light packages
fractions at drop-off points. Thus, taking into account the current
regulations and in an attempt to include all the possible SL, two
scenarios were proposed at this stage to design the selective waste
pre-collection in Castellón. Scenario A, on the one hand, considers
that mixed waste (organic and reject fraction) will be collected
door-to-door, paper-cardboard, light packaging and glass will be
collected at drop-off sites, and medicines will be collected at the
pharmacies, which means door-to-door collection. On the other
hand, Scenario B considers that mixed waste will be collected in
kerbside bins (street bins), paper-cardboard, light packaging and
glass will be collected at drop-off sites located in the streets, and
finally medicines will be collected at the pharmacies as in scenario
A. The main difference between the two scenarios is that the mixed
waste fraction in scenario A will be deposited in containers located
at the front door of the buildings, while in scenario B it will be
deposited in kerbside containers at a maximum distance from
the citizens of 30 m. In both scenarios, paper-cardboard, glass
and light packaging fractions will be deposited at drop-off sites
and a maximum distance of 150 m is suggested. At these dropoff sites, the different fractions will be placed in separate containers. Finally, expired medicinal products and their packaging will be
deposited in bins located at the drugstores. Since 2001, in Spain,
there has been an integrated waste management system (IWMS)
for empty medicinal product packaging and expired medicinal
products, also called IPWCMS (an integrated packaging waste collection management system), which undertakes the collection and
treatment of this kind of waste.
3.3. Location of the MSW disposal points
The location of the disposal points was established with ArcGIS
10.1., as this software satisfies the requirements set by this methodology. It contains the Network Analyst tool, which allows the
user to analyze the street network.
The spatial information required to carry out the case-study
was obtained from the Spanish National Geographic Institute
(IGN, 2012), the Register of Inhabitants (2010), and Castellón Town
Council. The IGN offers the street network in a shapefile. This infor-
A. Gallardo et al. / Waste Management 36 (2015) 1–11
mation has been updated and further data that were needed, such
as the direction of the traffic in streets, were added because they
are essential to be able to locate the disposal points. Therefore,
other types of information like one- or two-way streets, pedestrian
streets or streets that allow trucks to pass through them were
introduced. Castellón Town Council shared information like the
main use of the land (commercial, residential or industrial) and
the number and location of the doorways of buildings. A total of
13,771 doorways were marked on a map. Each doorway, however,
contains a different number of inhabitants depending on the number of households in each building.
On the same map, the possible locations of disposal points were
marked taking into account several factors, such as access for
trucks and citizens, the distance between adjacent containers, the
distance to the doorways, etc. Once all the possible disposal points
have been located, the final number of disposal points is minimized in accordance with a predefined requirement. The minimum
number of disposal points was determined taking into account the
fact that the maximum distance between the user and the disposal
point must be less than 30 m in the case of kerbside disposal and
150 m in the case of the drop-off sites. Finally, the real distance
between each doorway and the disposal point was calculated.
3.3.1. Door-to-door storage level pre-collection
On the door-to-door SL, the disposal points overlap the doorways. Fig. 4 shows an example distribution of the 13,771 doorways
in the town, which corresponds to the mixed waste disposal points
in scenario A.
3.3.2. Kerbside storage level pre-collection
The optimum sites to locate the kerbside waste disposal points
are in streets in which vehicles can pass through. These points usually correspond to street crossings in the case of street segments
between 60 and 120 m. Furthermore, when streets are longer than
120 m, intermediate points are located equidistantly, at a maxi-
mum distance of 60 m between points. Moreover, in two-way
streets, disposal points are located on both sides of the sidewalk.
After applying all these requirements, the final number of possible
disposal points for the mixed waste fraction in scenario B is 3694.
The next step is to limit the distance that the citizen must walk to
the disposal point to 30 m. This condition means that the final
number of possible disposal points is reduced to 2098 as shown
in Fig. 4.
However, 8% of the doorways do not satisfy this requirement.
These doorways are usually located in streets that are closed to
traffic where containers cannot be located or on the outskirts of
the city, where houses are far away from the street network. To
know the distance from each doorway to the disposal points, the
closest facility analysis in ArcGis 10.1 was used. The results in
Table 2 show that most of the doorways are located at the recommended distance of 30 m from the disposal point, and consequently 95% of the citizens have a disposal point at a distance of
less than 30 m. Only 4% of the doorways or, to put it another
way, 2% of the users will have the containers at a distance of more
than 60 m. Finally, 1% of the users will have to walk distances of up
to 100 m.
3.3.3. Drop-off sites storage level pre-collection
The optimum points to locate the drop-off sites will also be
placed in streets allowing the passage of traffic. The selected points
are crossroads, the midpoint of a street when its length is between
300 and 600 m, or intermediate points in streets whose length is
greater than 600 m. In this last type of streets, the intermediate
points are equidistant and the distance between two consecutive
points is less than 300 m.
Consequently, after applying all these requirements to the Castellón street network, the number of possible drop-off sites is 1520.
Considering that the maximum distance to be walked by users
from their doorway to the drop-off site must be less than 150 m,
the final number of possible drop-off sites is 273. Fig. 5 shows
Fig. 4. Proposed location of the mixed waste containers at curbside.
A. Gallardo et al. / Waste Management 36 (2015) 1–11
Table 2
Distance (m) from the doorways to the mixed waste disposal points at kerbside.
Distance (m)
% doorways
% inhabitants
the distribution of these 273 drop-off sites around the town. Table 5
displays the number and distribution of the drop-off sites that
allow 13,470 doorways to be within a distance of less than 150 m.
As a result, only the inhabitants of 301 doorways (which represent 0.23% of the doorways) must walk at least 150 m. Again, the
real distance from each doorway to the nearest drop-off site was
calculated using ArcGis 10.1. The results in Table 3 show that only
0.01% of the citizens will have to walk a distance greater than
200 m.
3.3.4. Establishment storage level: medicinal products waste disposal
at pharmacies
Citizens must dispose of their expired medicinal products and
drug packages at pharmacies. Fig. 5 shows the location of the 69
drugstores in Castellón. The distance between any two pharmacies
varies from 34 to 540 m, although many of them are at a distance
from the nearest establishment of between 100 and 250 m. In the
historical town center, these establishments are closer together,
while the greater distances belong to the ones located on the outskirts of the town.
Table 4 shows that approximately 84% of the doorways have a
pharmacy within less than 300 m, where citizens will be able to
dispose of this specific waste. Nevertheless, some citizens will have
to walk distances of more than 1215 m to reach the nearest
3.4. Volume of disposal points and bin selection
In this section, the volume needed at each disposal point is calculated using the ArcGis 10 application. The Location-Allocation
tool is used to calculate the number of inhabitants that will be able
to place the waste at each disposal point. Therefore, it would be
useful to know the number of inhabitants per doorway. This information is not available, and thus had to be estimated. According to
the land registry, the town is divided into 97 sections. The number
of inhabitants and the number of doorways in each section are
known, and these data were used to calculate the number of inhabitants per doorway in each section. Eq. (1) was used to calculate the
volume required for the bins at each point, taking into account the
waste generation and composition data in Castellón, shown in
Table 5, and the number of inhabitants per disposal point.
The daily generation rate of MSW in Castellón is 0.96 kg inh1 day1. This figure was calculated using Town Council data for the
year 2012. The FR values were obtained from Gallardo et al.
(2012), the density values of the different fractions used are bibliographic data provided by Di Maria and Micale (2013), and the Cu
(shown in Table 7) was calculated using equation 2 and the collection data for Castellón in 2012.
3.4.1. Door-to-door storage level volume
The required bin volume was calculated for each doorway. As it
is impossible to list all the points, Table 6 shows their average values. The collection frequency used is 7/7, which means that Cf = 1
seven days a week (or daily collection). This is the most common
collection frequency in Spain due to the characteristics of its
In Table 6, the standard deviation is so high due to the fact that
the number of inhabitants per doorway is not a homogeneous
value. The type of bin that is best suited for use in door-to-door
Fig. 5. Location of the drop-off sites for the selective waste fractions (paper-cardboard, glass, and light packaging).
A. Gallardo et al. / Waste Management 36 (2015) 1–11
Table 3
Distribution of the doorways and inhabitants depending on the distance to the
nearest drop-off sites.
Number of
Number of
No assigned
Table 4
Distribution of doorways according to the distance to the nearest drugstore.
Distance (m)
% doorways
% accumulated doorways
Table 5
Data to calculate the bin volume needed at each disposal point.
rate (FR) (%)
(kg m3)
Light packaging
Mixed waste (door
to door and
pre-collection is the two-wheel bin. Nowadays, there are different
bin sizes, such as 0.06, 0.08, 0.12, 0.24 and 0.34 m3. Taking into
account these bin sizes, Table 7 shows the most suitable size for
each doorway. However, several small bins could also be used
instead of large-sized bins (for example, two 0.06 m3 bins instead
of one 0.12 m3 bin).
Table 7
Number of bins needed to cater for the mixed waste fraction in doorways and at
Number of doorways
N° of
(1 bin)
Number of bins at kerbside
Volume generated
per disposal point
N° of
Number of
Furthermore, there are 137 doorways where the required bin
volume is greater than 0.34 m3, which is even higher than the largest available bin. In this case, more than one bin is necessary to
allocate all the waste generated in that neighborhood.
3.4.2. Kerbside storage level volume
The Location-Allocation ArcGis tool is applied (minimize
impedance method) to calculate the volume needed at each disposal point, to allocate the doorways to the disposal point, and to
know the exact number of inhabitants associated to them. In this
case, the distance (or impedance) is not limited in order to consider
those doorways whose distance to the disposal point is greater
than 30 m (which represents 8% of the total), as the tool allocates
the inhabitants to the nearest disposal point.
The required bin volume for each disposal point (2098 in total)
was calculated taking into account a daily collection frequency.
Table 6 shows the average values obtained for the disposal points
in the area studied.
To determine the number of bins at each point and consequently the total number of containers that are needed, first it is
necessary to select the size of the bin. In this case study, the bin
size is 1.1 m3, as this is the usual volume in middle-sized towns
like Castellón. Table 7 presents the number of disposal points that
should be endowed with 1, 2, 3, 4 or 5 bins. As a result, the final
number of containers possibly needed in this town is 2290.
3.4.3. Drop-off sites storage level volume
Using the same methodology and GIS tools, the number of
inhabitants related to each drop-off site is calculated. As in the case
of the kerbside pre-collection, the distance (or impedance) is not
limited so as to take into consideration the contribution of those
doorways located at a distance greater than 150 m from the
drop-off site (which represent 0.23% of the total number of
In Spain, towns like Castellón usually have 3.2 m3 containers for
the selective fractions at drop-off sites. This is the reason why this
container volume was selected. In this case study several collection
frequencies were assessed in order to optimize the container volume and hence ensure the best collection frequency allowing just
one bin per waste fraction to be located at each drop-off site.
Table 8 shows the number of bins at drop-off sites for the paper-
Table 6
Statistical parameters for mixed waste generation (kg) and bin volume needed at each disposal point for door-to-door and kerbside collection.
Mixed waste in door to door
St. Dvt.
Mixed waste at kerbside
Inhabitants per
Daily disposal per
doorway (kg)
Volume per doorway
Inhabitants per disposal
Daily disposal per
point (kg)
Volume per disposal
point (m3)
A. Gallardo et al. / Waste Management 36 (2015) 1–11
Table 8
Number of containers per drop-off site for paper-cardboard, light packaging, and glass.
N° bins per drop-off (volume)
1 (<3.2 m3)
2 (3.2–6.4 m3)
3 (6.4–9.6 m3)
Lightweight packaging
2 per week
1 per week
3 per week
2 per week
1 per week
2 per week
1 per week
1 per 2 weeks
Table 9
Statistical values of the waste disposed of in each pharmacy.
St. Dvt.
3 per week
Number of inhabitants per
Amount of waste per year
cardboard, light packaging, and glass fractions. The most appropriate collection frequency is three times per week for paper-cardboard (Cf = 2.3), twice a week (Cf = 3.5) for light packaging, and
once every two weeks for glass (Cf = 14).
3.4.4. Establishment storage level volume
As in the previous analyses, the number of citizens per establishment was determined using the ArcGis 10.1 Location-Allocation tool, with the method of minimum impedance. The annual
rate of waste collected at pharmacies in Spain in 2012 was
79.80 g inh1 year1 (SIGRE, 2014). With all these data, the amount
of waste placed in each drugstore was obtained. Table 9 summarizes the average values of the waste deposited in the 69 pharmacies in Castellón.
In this special case, the container volume needed at each disposal point cannot be calculated as there is no information available about the size of the bins or the waste density in the bins.
Moreover, the distribution of the pharmacies in the town is not
uniform and neither is the amount of waste deposited in each
drugstore. As a result, a collection frequency must be defined for
each establishment.
4. Conclusions
To ensure suitable MSW management in a town, the problem
must be addressed from its roots. Studying the waste pre-collection
in a town will make it possible to lay the foundations on which to
organize the subsequent collection. Waste collection represents
an important part of the total waste management costs. At the same
time, proper organization of the waste disposal points in a town
will improve the later waste collection routes by optimizing them,
it will make the disposal of waste an effortless task for citizens, and
it will contribute to build a healthier and more sustainable town.
This paper presents a structured methodology that allows local
authorities or private companies that deal with MSW, to design
their own MSW pre-collection systems in order to facilitate the citizens’ waste disposal, increase the selective recovery of materials,
and improve the job of waste collection.
To decide on the number of pre-collection containers and their
location all over the town it is crucial to design an MSW management system, as the distribution of the containers affects collection
routes and waste management, as well as other urban activities.
Hence, the methodology proposed in this paper attempts to minimize the number of containers, which in turn will contribute to
reduce the length of the collection routes and, as a result, their final
The first step of the methodology is based on defining the number of waste fractions. Once this number has been defined, the SL of
each fraction must be selected. Five possible levels have been proposed in this paper, as they are the most common forms of waste
storage: door-to-door, kerbside, drop-off sites, establishment, and
green point. Each fraction can have its own SL. This work also
explains the characteristics, advantages and disadvantages of each
SL in order to provide the final user with a wider range of decision
With the aid of GIS, and more specifically with the ArcGis 10.1
software application, some keys to locating the storage points have
been presented. Moreover, the volume of the disposal points has
been calculated taking into account several parameters, such as
the number of inhabitants per disposal point, the daily generation
rate, the fractioning rate (which is sometimes set by regulations),
the collection frequency, a utilization coefficient to avoid overflows, and the waste density in the bins.
Furthermore, this methodology implicitly considers the objectives of selective collection, since they will be used to define the
final distance that the inhabitants must walk to reach the disposal
To verify the methodology, it has been applied to a real case. In
the selected town two scenarios, which take into account four SL,
were selected. Thus, the paper offers several examples of how to
organize the pre-collection of selective fractions.
For all these reasons, this methodology will be a useful tool for
distributing the storage points in the study zone. Literature related
to the distribution of bins in a town is scarce despite being a key
step in designing a waste management system. In fact, there are
plenty of methodologies to assess and optimize the waste collection routes, but there are no studies on the type of storage and
the distribution of bins. In this respect, this study tries to fill the
gap in the scientific literature in terms of this kind of studies.
André-García, F.J., Cerdá Tena, E., 2006. Gestión de residuos sólidos urbanos: análisis
económico y políticas públicas. Cuad. Econ. ICE 71, 71–91.
Baltes, L., Draghici, C., Manea, C., Ceausescu, D., Tierean, M., 2009. Trends in
selective collection of the household waste. Environ. Eng. Manage. J. 8 (4), 985–
Bautista, J., Pereira, J., 2006. Modeling the problem of locating collection areas for
urban waste management. An application to the metropolitan area of
Barcelona. Omega 34, 617–629.
Berné, C., Garcés, C., Lafuente, A., Pedraja, M., Rivera, P., 2000. Problemática
medioambiental y participación ciudadana: una aplicación al caso de los
residuos urbanos. GAPP 17–18, 93–103.
BOE, 2006. Real Decreto 252/2006 de 3 de marzo, por el que se revisan los objetivos
de reciclado y valorización establecidos en la Ley 11/1997, de 24 de abril, de
Envases y Residuos de Envases, y por el que se modifica el Reglamento para su
desarrollo y ejecución, aprobado por el Real Decreto 782/1998, de 30 de abril.
Boletín Oficial del Estado 54, 8961–8967 (4 de marzo de 2006).
BOE, 2011. Ley 22/2011, de 28 de julio, de residuos y suelos contaminados. Boletín
Oficial del Estado 181, 85650–85705 (29 de julio de 2011).
Bolaane, B., 2006. Constraints to promoting people centred approaches in recycling.
Habitat Int. 30, 731–740.
Castagna, A., Casagrande, M., Zeni, A., Girelli, E., Rada, E.C., Ragazzi, M., Apostol, T.,
2013. 3R’ from citizen point of view and their proposal: a case-study. UPB Sci.
Bull. Ser. D 75 (4), 253–264.
Coutinho-Rodrigues, J., Tralhão, L., Alçada-Almeida, L., 2012. A bi-objective
modeling approach applied to an urban semi-desirable facility location
problem. Eur. J. Oper. Res. 223 (1), 203–213.
A. Gallardo et al. / Waste Management 36 (2015) 1–11
De Feo, G., Malvano, C., 2009. The use of LCA in selecting the best MSW
management system. Waste Manage. 29, 1901–1915.
Di Maria, F., Micale, C., 2013. Impact of source segregation intensity of solid waste
on fuel consumption and collection. Waste Manage. 33, 2170–2176.
DOGV, 2004. Orden de 2 de diciembre de 2004, del conseller de Territorio y
Vivienda, por la que se aprueba el Plan Zonal de residuos de las Zonas II, IV y V.
DOGV 4907, 32686–32718 (21.12.2004).
de 19 de noviembre de 2008 sobre los residuos y por la que se derogan
determinadas Directivas. Off. J. Eur. Union L 312, 3–30 (22.11.2008).
ECOVIDRIO, 2010. Informe técnico sobre contenedores de recogida de residuos de
envases de vidrio.
Gallardo, A. 2000. Metodología para el diseño de redes de recogida selectiva de RSU
utilizando sistema de Información Geográfica. Creación de una Base de datos
aplicable a España (Thesis Ph). Universidad Politécnica de Valencia.
Gallardo, A., Bovea, M.D., Colomer, F., Prades, M., Carlos, M., 2010. Comparison of
different collection systems for sorted household waste in Spain. Waste
Manage. 30, 2430–2439.
Gallardo, A., Bovea, M.D., Colomer, F., Prades, M., 2012. Analysis of collection
systems for sorted household waste in Spain. Waste Manage. 32, 1623–1633.
Gallardo, A., Gómez, A., Bovea, M.D., Colomer Mendoza, F.J., Carlos, M., 2013.
Influencia del nivel de ingresos económicos en la recogida selectiva de residuos
urbanos. Rev. Int. Contam. Ambie. 29, 19–24.
Gautam, A.K., Kumar, S., 2005. Strategic planning of recycling options by multiobjective programming in a GIS environment. Clean Technol. Environ. Policy 7,
Gellynck, X., Jacobsen, R., Verhelst, P., 2011. Identifying the key factors in increasing
recycling and reducing residual household waste: a case study of the Flemish
region of Belgium. J. Environ. Manage. 92, 2683–2690.
Ghiani, G., Laganà, D., Manni, E., Triki, C., 2012. Capacitated location of collection
sites in an urban waste management system. Waste Manage. 32 (7), 1291–
Giugliano, M., Cernuschi, S., Grosso, M., Rigamonti, L., 2011. Material and energy
recovery in integrated waste management systems. An evaluation based on life
cycle assessment. Waste Manage. 31 (9–10), 2092–2101.
González-Torre, P.L., Adenso-Díaz, B., 2005. Influence of distance on the motivation
and frequency of household recycling. Waste Manage. 25 (1), 15–23.
González-Torre, P.L., Adenso-Díaz, B., Ruiz-Torres, A., 2003. Some comparative
factors regarding recycling collection systems in regions of the USA and Europe.
J. Environ. Manage. 69, 129–138.
Huerta-Pujol, O., Gallart, M., Soliva, M., Martínez-Farré, F.X., López, M., 2011. Effect
of collection system on mineral content of biowaste. Resour. Conserv. Recy. 55,
IGN. 2012. CartoCiudad en centro de descargas. Centro Nacional de Información
<> (3.02.2014).
Ionescu, G., Rada, E.C., Ragazzi, M., Marculescu, C., Badea, A., Apostol, T., 2013.
Integrated municipal solid waste scenario model using advanced pretreatment
and waste to energy processes. Energy Convers. Manage. 76, 1083–1092.
Iriarte, A., Gabarrell, X., Rieradevall, J., 2009. LCA of selective waste collection
systems in dense urban areas. Waste Manage. 29, 903–914.
IVE, 2012. Ficha municipal de Castellón de la Plana. Actualización 2012. Institut
Valencià d’Estadística.
Kao, J.-J., Lin, T.-I., 2002. Shortest service location model for planning waste pickup
locations. J. Air Waste Manage. Assoc. 52 (5), 585–592.
Karousakis, K., Birol, E., 2008. Investigating household preferences for kerbside
recycling services in London: a choice experiment approach. J. Environ. Manage.
88, 1099–1108.
Keramitsoglou, K.M., Tsagarakis, K.P., 2013. Public participation in designing a
recycling scheme towards máximum public acceptance. Resour. Conserv. Recy.
70, 53–67.
Larsen, A.W., Merrild, H., Moller, J., Christensen, T.H., 2010. Waste collection
systems for recyclables: an environmental and economic assessment for the
municipality of Aarhus (Denmark). Waste Manage. 30, 744–754.
Lavee, D., 2007. Is municipal solid waste recycling economically efficient? Environ.
Manage. 40, 926–943.
Lavee, D., Nardiya, S., 2013. A cost evaluation method for transferring municipalities
to solid waste source-separated system. Waste Manage. 33, 1064–1072.
López Alvarez, J.V., Aguilar Larrucea, M., Soriano Santandreu, F., Fernando de Fuentes,
A., 2009. Containerization of the selective collection of light packaging waste
material: the case of small cities in advanced economies. Cities 26, 339–348.
Magrinho, A., Didelet, F., Semiao, V., 2006. Municipal solid waste disposal in
Portugal. Waste Manage. 26, 1477–1489.
Margallo, M., Aldaco, R., Bala, A., Fullana, P., Irabien, Á., 2010. Implementation of the
selective collection in small villages of less than 50 inhabitants in Cantabria
region (Spain): preliminary viability study. Chem. Eng. Trans. 21, 733–738.
Martin, M., Williams, I.D., Clark, M., 2006. Social, cultural and structural influences
on household waste recycling: a case study. Resour. Conserv. Recy. 48, 357–395.
Mazzanti, M., Montini, A., Zoboli, R., 2008. Municipal waste generation and
socioeconomic drivers evidence from comparing northern and southern Italy.
J. Environ. Dev. 17 (1), 51–69.
McDonald, S., Oates, C., 2003. Reasons for non-participation in a kerbside recycling
scheme. Resour. Conserv. Recy. 39, 369–385.
McLeod, F., Cherrett, T., 2008. Quantifying the transport impacts of domestic waste
collection strategies. Waste Manage. 28, 2271–2278.
Mecati, L., Gros directors, J., 2007. Gestión de residuos municipales y limpieza viaria.
Guía Técnica. Red Española de Ciudades por el Clima y FEMP.
Menikpura, S.N.M., Sang-Arun, J., Bengtsson, M., 2013. Integrated solid waste
management: an approach for enhancing climate co-benefits through resource
recovery. J. Cleaner Prod. 58 (1), 34–42.
Ministry of the Environment, 2004. Appendix 4. Documentation of the MSW
expenditure functions. In: The FEASIBLE Model, Version 2. User Manual and
Documentation. DANCEE ref. No. 124/000-0184. p. 113.
Miranda, R., Monte, M.C., Blanco, A., 2013. Analysis of the quality of the recovered
paper from commingled collection systems. Resour. Conserv. Recy. 72, 60–66.
Mueller, W., 2013. The effectiveness of recycling policy options: waste diversion or
just diversions? Waste Manage. 33, 508–518.
Munizaga Plaza, J.A., Lobo García de Cortázar, A., 2013. Generación de residuos
domésticos y su variabilidad en comunidades de tamaño intermedio. Rev. Int.
Contam. Ambie. 29, 9–17.
Rada, E.C., 2013. Effects of MSW selective collection on waste-to-energy strategies.
WIT Trans. Ecol. Environ. 176, 215–223.
Rada, E.C., Ragazzi, M., Fedrizzi, P., 2013. Web-GIS oriented systems viability for
municipal solid waste selective collection optimization in developed and
transient economies. Waste Manage. 33 (4), 785–792.
Rada, E.C., Zatelli, C., Mattolin, P., 2014a. MSW selective collection and tourism?
WIT Trans. Ecol. Environ. 180, 187–957.
Rada, E.C., Ragazzi, M., Fedrizzi, P., 2014b. Selective collection as a pretreatment for
indirect solid recovered fuel generation. Waste Manage. 34 (2), 291–297.
Raicu, S., Costescu, D., Rosßca, E., Popa, M., 2011. Optimal planning of selective waste
collection. WIT Trans. Ecol. Environ. 150, 785–794.
Register of Inhabitants, 2010. Dades estadístiques de població de la ciutat de
Castelló de la Plana, resultant del tancament numèric realitzat per l’Ajuntament
a data d’1 de gener de 2010.
Rives, J., Rieradevall, J., Gabarrell, X., 2010. LCA comparison of container systems in
municipal solid waste management. Waste Manage. 30, 949–957.
SIGRE, 2014. SIGRE Medicamento y Medio Ambiente, Url <
Tanskanen, J.-H., Kaila, J., 2001. Comparison of methods used in the collection of
source-separated household waste. Waste Manage. Res. 19, 486–497.
Tavares, G., Zsigraiova, Z., Semiao, V., Carvalho, M.G., 2009. Optimisation of MSW
collection routes for minimum fuel consumption using 3D GIS modelling.
Waste Manage. 29, 1176–1185.
Teixeira, C.A., Avelino, C., Ferreira, F., Bentes, I., 2014. Statistical analysis in MSW
collection performance assessment. Waste Manage. 34 (9), 1584–1594.
Tonjes, D.J., Mallikarjun, S., 2013. Cost effectiveness of recycling: a systems model.
Waste Manage. 33, 2548–2556.
Toso, E.A.V., Alem, D., 2014. Effective location models for sorting recyclables in
public management. Eur. J. Oper. Res. 234 (3), 839–860.
Tralhão, L., Coutinho-Rodrigues, J., Alçada-Almeida, L., 2010. A multiobjective
modeling approach to locate multi-compartment containers for urban-sorted
waste. Waste Manage. 30, 2418–2429.
Valeo, C., Baetz, B., Tsanis, I., 1998. Location of recycling depots with GIS. J. Urban
Plann. Dev. 124 (2), 93–99.
Vicente, P., Reis, E., 2008. Factors influencing households’ participation in recycling.
Waste Manage. Res. 26, 140–146.
Wagner, T.P., 2013. Examining the concept of convenient collection: an application
to extended producer responsibility and product stewardship frameworks.
Waste Manage. 33 (3), 499–507.
WRAP, 2009. Summary Report-Material Bulk Densities, Report prepared by
Resource Futures.
Zafra, C.A., 2009. Metodología de diseño para la recogida de residuos sólidos
urbanos mediante factores punta de generación: sistemas de caja fija (SCF). Rev.
Ing. Invest. 29 (2), 119–126.
Zamorano, M., Molero, E., Grindlay, A., Rodríguez, M.L., Hurtado, A., Calvo, F.J., 2009.
A planning scenario for the application of geographical information systems in
municipal waste collection: a case of Churriana de la Vega (Granada, Spain).
Resour. Conserv. Recy. 54, 123–133.
Zsigraiova, Z., Semiao, V., Beijoco, F., 2013. Operation costs and pollutant emissions
reduction by definition of new collection scheduling and optimization of MSW
collection routes using GIS. The case study of Barreiro, Portugal. Waste Manage.
33, 793–806.