1. Introduction

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ChooseTop of pageAbstract1.Introduction <<2.MSW in HK3.MSW in Asian cities4.Research procedures and...5.Finding and results6.Conclusion

Municipal solid wastes (MSWs) are those substances discarded within the municipal area (Wei et al., 2017). The main sources of MSW vary but include commercial, residential, industrial or institutional; each of these can be further segregated into different categories based on the physical composition of wastes (Baawain et al., 2017; Lavee and Khatib, 2010). MSW is a significant issue for Hong Kong (HK) as the MSW amount is increasing at a rapid rate (Ling, 2015). The composition and amount of MSW are determined by factors such as population, income, household size, emigration rate and economic conditions (Cai et al., 2014). The land area in HK is less than 259 square kilometres, but is home to about 7·18 million people. Currently, HK has only three operating landfills and 13 closed landfills (Hong et al., 2010). In 1998, the HK government published a framework on waste reduction to set-out initiatives for the reduction of waste in the city (Chung et al., 2010). After some trials testing the effectiveness of different waste management strategies, a territory-wide programme was developed in 2005 to facilitate the separation of waste in buildings (Chung et al., 2010). The waste disposal ordinance in 1980 provided the statutory framework to manage all types of wastes in HK, which offers licenses for waste collection and disposal facilities (Chan, 2001). The government of HK also developed and enacted the product eco-responsibility legislation in 2008 to manage MSW in the city (Chen et al., 2013). MSW refers to the waste generated by humans in their daily lives (Lee et al., 2016) excluding construction and demolition waste, chemical waste and some special industrial wastes (Prades et al., 2014). The increasing population results in an increase in waste so that the projection of waste generation becomes a critical issue for many cities (Wang et al., 2011). With fast economic development, humans tend to generate more waste, especially when people can spend more and consumption increases (Hong et al., 2017). MSW is piled up and is gradually becoming a major problem due to the complexity in collection and treatment (Lavee and Khatib, 2010). The rapid increase in MSW has stirred up problems such as public health and environmental changes (Antmann et al., 2013).

One of the most common methods used to deal with MSW is landfilling, which has been adopted by many cities around the world leading to the lack of sufficient lands and a strong emergence of landfill gases (Bernstad, 2014). The landfill emissions lead to odour pollution and respiratory diseases (Chowdhury, 2009). HK set the target to raise the MSW recovery from 34% in 2002 to 36% in 2004, 40% in 2007 and then 50% in 2015. As a comparison, Florida in the USA has decided to increase the MSW recovery rate to 75% by 2020 (Liyanage et al., 2015). The Environmental Protection Department (EPD) of HK keeps regular statistics on each type of waste. The analysis of these statistics is important as it allows evaluation of whether the system is working properly. System dynamics (SD) is a robust tool that can use these statistics and provide a comprehensive simulation of the waste management process (Kollikkathara et al., 2009). According to Machowski et al. (2008), SD focuses on the feedforward and feedback relationships, and it develops relationships between rate variables and stock variables. SD analyses problems and allows analysis of complex, non-linear relationships aided by computer simulations to conceptualise and to rationally analyse structures and interactions and to prognosticate their effects in a holistic way (Inghels and Dullaert, 2010). The HK's daily domestic waste generation rate per capita is much higher than that of other Asian cities such as Shanghai and Singapore. HK is running out of landfilling spaces earlier than planned and the current landfills will be exhausted by 2020 (Liyanage et al., 2015). There is an urgent need to forecast the rapid increasing MSW in HK and to provide accurate modelling for control purposes. In the past, researchers focused on gross domestic product (GDP) as the only indicator of waste generation; however, according to Lam and Chan (2014), other factors such as infant mortality, labour force size, population density and life expectancy should be included. By analysing the historical and current MSW statistics in HK and other Asian cities such as Singapore and Shanghai through interviews and documentation research, this study develops a SD simulation to forecast the future MSW generation in HK for control purposes. A comparison and contrast of MSW analysis between HK, Singapore and Shanghai are provided.

2. MSW in HK

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ChooseTop of pageAbstract1.Introduction2.MSW in HK <<3.MSW in Asian cities4.Research procedures and...5.Finding and results6.Conclusion

The MSW loads in HK were increasing since the year 1986. HK's MSW comprises of over 70% solid waste, and the daily waste disposal has reached 311 t (Han et al., 2014). Waste recycling is more complex than its reduction. In 1998, the HK government launched the Waste Reduction Framework Plan, which provided a variety of initiatives to reduce waste and recommended a series of measures to promote MSW separation and segregation in HK (Jaillon et al., 2009). The plan was to improve the overall MSW recovery rate from 34% in 2004 to 40% in 2007 and to increase the household waste recovery rate from 8% in 2004 to 20% in 2007. The HK government published the first sustainable development strategy in 2005, including a policy framework for MSW management in HK (Zhang et al., 2012), which proposes a simple and effective tool to create incentives for the community to recycle more and to discard less (Han et al., 2014). For example, the government levies a scheme to direct the economic incentives to reduce the use of plastic shopping bags in the city (Lu and Yuan, 2013).

According to Yu et al. (2013), the EPD in HK manages collecting, treating, disposing and transferring MSW in the city; more than HK$10 billion (HK$1 = £0·10) has been invested in MSW facilities to manage the waste. The waste disposal ordinance was used to control the waste disposal including export and import (Yu et al., 2013). The three operating landfills are located in the new territories, namely: Nim Wang, Tseung Kwan O and Ta Kwu Ling. Thirteen out of 16 landfills in HK have been closed and restored for several uses to minimise potential health risks. For example, some were landscaped to offer green zones and recreational uses such as golf driving ranges, grass pitches and ecological parks.

There are seven refuse transfer stations located in different areas but with centralised collection points. The waste from smaller refuse collection trucks is compacted and transferred into containers and shipped to landfills through lorries. The chemical waste treatment centre on Tsing Yi Island accepts different chemical and clinical waste. The Sha Ling Composting Plant in the northern new territories accepts livestock waste and composts it into soil suitable for the use in the city. With the efforts of the government and community, the waste recovery rate in HK has been increasing, and over 80% of the HK population has been involved in the waste separation programme (Yau, 2010). Materials in MSW such as paints, plastics, disposed goods and inks are considered hazardous (Wei et al., 2017), and the waste management occupies the uppermost rung in the hierarchy of waste management (Zhou et al., 2015). The hierarchy refers to those activities undertaken with an item before it is perceived as waste, which includes the decrease of total waste produced, the decrease in the associated environmental impacts on the public and the decreased quantity of noxious objects (Gidarakos, 2015). Some effective methods for waste reduction include adjustments in the usage of raw materials and the adoption of a suitable production process (Gidarakos, 2015).

3. MSW in Asian cities

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ChooseTop of pageAbstract1.Introduction2.MSW in HK3.MSW in Asian cities <<4.Research procedures and...5.Finding and results6.Conclusion

Asian cities such as HK, Singapore, Shanghai, Taiwan and Beijing are among the leading cities regarding both economic development and waste generation. The city GDP per capita in some Asian megacities such as Bangkok, Shanghai, Jakarta, Manila, Beijing and Kuala Lumpur is two- to five-times higher than other cities. The estimates of expected typical values for MSW in some Asian cities are listed in Table 1. High- and middle-income cities (such as HK, Singapore, Tokyo, Taipei, Seoul, Bangkok, Kuala Lumpur, Beijing and Shanghai) have a daily material consumption from 4000 to 14 000 t and this creates a daily MSW at around 250–750 t. On the other hand, low-income cities such as Manila and Jakarta have a much lower daily material consumption and a MSW generation. The middle- and low-income rural regions have a daily material consumption ranged from 500 to 2000 t, and MSW generation from 120 to 200 t (Ali and Sion, 2014). Table 2 shows that HK has higher agriculture, forest, marine and urban density than other cities such as Guangzhou, Bangkok and Beijing.

Table 1. Estimated material consumption and waste generating in Asian cities (Ali and Sion, 2014)

Table 2. HK compared with some Asian cities (Ali and Sion, 2014)

4. Research procedures and steps to develop system dynamics model

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ChooseTop of pageAbstract1.Introduction2.MSW in HK3.MSW in Asian cities4.Research procedures and... <<5.Finding and results6.Conclusion

SD is a robust process used to analyse complex systems aided by computer simulation. SD can accommodate internal feedback loops and time delays, such as required when forecasting on MSW generation and control. The process of a SD model starts with identifying the parameters; in this study, the parameters refer to those factors for waste generation (Liu and Li, 2015). In the past, researchers only focused on GDP as an indicator for waste generation, but Lam and Chan (2014) have suggested that additional factors should be included, particularly (a) population, (b) household size, (c) standard of living and (d) purchasing power. Hong et al. (2010) conceptually describe the relationship between these parameters and MSW generation as higher economic growth leads to higher public spending, which increases the waste generation; higher income leads to higher waste generation; and, more population generates more MSW. HK is a highly populated city with 6650 persons per square kilometre. The median monthly domestic household income is around HK$22 400, and it is increasing; the total labour force is around 3·86 million people (Cai et al., 2014). In this study, data for SD modelling were collected from semi-structured interviews and official reports in the EPD of HK, Shanghai Environmental Protection Agency and the National Environmental Agency Singapore, which regularly provide statistics on daily/monthly/annual waste outputs in their cities. The Vensim 6.0 software package was used to simulate the dynamic process of the system.

The first step in generating the dynamic simulation was developing the stock-and-flow diagram by defining the variables influencing on MSW generation using the box variable function and rate variable function in Vensim 6.0 as shown in Figure 1. MSW generation is the box variable, and MSW increase rate and MSW decrease rate are the rate variables. The second step was to identify the variables influencing the values. Step 3 is based on the causal loop diagram among variables such as household waste increasing rate, MSW generation per household and household spending per capita rate. The MSW decrease rate was determined in step 4. Step 5 develops causal loop diagram towards the MSW disposal volume, resulting in the decrease in the landfill rate. MSW disposal volume is the starting point followed by MSW recovery rate, total waste disposed and MSW disposal. Step 6 defines the stock-and-flow diagram for landfill in HK, where landfill is a box variable. The simulation as developed at this step could determine the amount of waste disposed at landfills to forecast future waste. Step 7 integrates causal loop diagrams and stock-and-flow diagrams to finalise the SD model.

Figure 1. A seven-step SD modelling for MSW forecasting

6. Conclusion

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ChooseTop of pageAbstract1.Introduction2.MSW in HK3.MSW in Asian cities4.Research procedures and...5.Finding and results6.Conclusion <<

Historical data regarding MSW generation in HK (including MSW volume rate, landfill rate for landfill capacity, MSW disposal volume, population and household spending) were used to determine coefficients in the SD modelling to project the future waste generation in HK. A system-based MSW prediction and response model was developed in this study using a seven-step SD model. The SD simulation forecasts the MSW generation and recycling in HK, which shows that in the near future the MSW will increase based on the current growth rates, and along with that the waste recycling will also improve. The strategies developed by the HK government regarding MSW disposal provide scope for further improvement because HK will experience more severe MSW conditions in the future as its landfills are expected to be closed earlier than planned. Compared with Singapore and Shanghai, HK has a higher MSW generation rate due to less effective planning measures and government policies. Recommendations for HK to support the management of MSW generation were derived according to the experiences of Singapore and Shanghai. HK could learn from Singapore and start programmes to provide education and consultation to school students on reducing, reusing and recycling of waste to shape and influence the behaviours of future generations. HK could also implement the strategies learnt from Shanghai to allocate special funds for waste management. Future studies are recommended to simulate the MSW generation and recycling in all these cities so that accurate comparison can be made that will allow the development of an effective solution for HK as well as the other two cities.