Waste Management 36 (2015) 1–11 Contents lists available at ScienceDirect Waste Management journal homepage: www.elsevier.com/locate/wasman 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 Keywords: MSW Generation Composition Map GIS Methodology 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 cities. ⇑ Corresponding author. Tel.: +34 964728114. E-mail addresses: gallardo@uji.es (A. Gallardo), mcarlos@uji.es (M. Carlos), perism@uji.es (M. Peris), fcolomer@uji.es (F.J. Colomer). http://dx.doi.org/10.1016/j.wasman.2014.11.008 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 2 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 (Denmark). 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. 3 A. Gallardo et al. / Waste Management 36 (2015) 1–11 FACTORS STAGES - 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 GIS selection 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, 4 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 Characteristics 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 Establishment 250 m Green points a The radius of the buffer zone is the maximum distance that a citizen must walk in a straight line to the disposal point. 5 A. Gallardo et al. / Waste Management 36 (2015) 1–11 Location: Maximum distance to source Volume Drop off sites Kerbside Depends on the F ti i rate t Fractioning 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 Establishments 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 density - Collection frequency - Number of collection establishments - Number of inhabitants in the collection area - Daily collection rate - Number of inhabitants in the buffer zone - Daily collection rate - 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 ð1Þ 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, 6 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 ð2Þ 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 inhabitants. 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- 7 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. 8 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 % doorways Inhabitants % inhabitants 0–10 10–20 20–30 30–40 40–50 50–60 60–80 80–100 >100 5068 5587 2016 217 203 157 212 140 164 36.80 40.57 14.64 1.58 1.47 1.14 1.54 1.02 1.19 56,630 63,675 26,740 1590 1549 1117 1288 808 1101 36.65 41.21 17.31 1.03 1.00 0.72 0.83 0.52 0.71 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 drugstore. 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 climate. 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). 9 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. Distance (m) Number of doorways % doorways Number of inhabitants % inhabitants 0–50 50–100 100–150 150–200 200–250 No assigned Total 4450 6394 2896 19 5 7 13,771 32.31 46.43 21.03 0.14 0.04 0.05 100 51,758 67,005 35,643 79 12 189 154,686 33.46 43.32 23.04 0.05 0.01 0.12 100 Table 4 Distribution of doorways according to the distance to the nearest drugstore. Distance (m) Doorways % doorways % accumulated doorways 0–50 50–100 100–150 150–200 200–250 250–300 300–350 350–400 400–450 450–500 500–600 600–700 700–800 800–900 900–1000 1000–1100 1100–1200 1200–1300 1155 2339 3600 2791 1105 490 374 296 225 215 327 338 230 109 68 64 30 2 8.40 17.00 26.17 20.29 8.03 3.56 2.72 2.15 1.64 1.56 2.38 2.46 1.67 0.79 0.49 0.47 0.22 0.01 25.4 51.57 71.86 79.89 83.45 86.17 88.32 89.96 91.52 93.9 96.36 98.03 98.82 99.31 99.78 100.00 100.01 Total 13,757 Table 5 Data to calculate the bin volume needed at each disposal point. Fraction Fractioning rate (FR) (%) Density (kg m3) Utilization coefficient (Cu) Collection frequency (Cf) Paper-cardboard Glass Light packaging Mixed waste (door to door and kerbside) 6.80 4.86 3.08 85.27 90 364 80 120 1.17 1.29 1.08 1.08 2.3 14 3.5 1 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 kerbside. Number of doorways Bin size (m3) N° of doorways (1 bin) 0.060 0.080 0.120 0.240 0.340 >0.340 2122 689 2086 215 137 Number of bins at kerbside Bin size (m3) Volume generated per disposal point (m3) N° of bins Number of disposal points 1.1 1.1 1.1 1.1 1.1 0–1.1 1.1–2.2 2.2–3.3 3.3–4.4 4.4–5.5 1 2 3 4 5 1,916 176 3 2 1 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 doorways). 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 Min. Max. Average St. Dvt. Mixed waste at kerbside Inhabitants per doorway Daily disposal per doorway (kg) Volume per doorway (m3) Inhabitants per disposal point Daily disposal per point (kg) Volume per disposal point (m3) 2.42 88.09 11.31 10.80 1.98 72.11 9.26 8.90 0.014 0.531 0.068 0.065 3.83 634.13 73.82 55.46 3.14 519.09 60.42 45.40 0.03 4.67 0.54 0.41 10 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) Paper-cardboard 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 268 5 0 243 30 0 142 126 5 273 0 0 273 0 0 247 26 0 273 0 0 273 0 0 264 9 0 273 273 273 273 273 273 273 273 273 Table 9 Statistical values of the waste disposed of in each pharmacy. Min. Max. Average St. Dvt. Glass 3 per week Number of inhabitants per establishment Amount of waste per year (kg) 41 6716 2237 1470 3.28 535.91 178.51 117.28 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 cost. 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 tools. 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 point. 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. 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