# Data-Driven Recovery Potential Analysis and Modeling for Batteries Recovery Operations in Electric Bicycle Industry

Authors: Ping Zhang; Guangfu Liu
Journal: Discrete Dynamics in Nature and Society
 (2018)

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## Abstract

To help the government manage waste lead-acid batteries in a more targeted and sustainable way, accurately forecasting the number of waste lead-acid batteries and analyzing their recovery potential play a key role. In China, electric bicycles are one of the most common means of transportation. As of the end of 2017, the social holding quantity of electric bicycles in China was over 250 million and that of electric tricycles was over 50 million. The quantity is equal to the total number of electric bicycles manufactured between 2011 and 2017. Currently, 90% of electric bicycles adopt lead-acid batteries as their power batteries. However, there are a few studies on the lead-acid batteries used in electric bicycles as power batteries. In this paper, we have selected lead-acid batteries used in electric bicycles as the subject of research as such kind of batteries enjoys the widest user base, the most single-battery consumption volume, and the strongest mobility. Based on the output and sales of electric bicycles, we have obtained the quantity of power lead-acid batteries. We have then estimated the annual waste quantity of lead-acid batteries used in electric bicycles in 2000-2022 using the “market supply A model” and the “Stanford Model”, respectively, and based on the proportion of raw materials contained in lead-acid batteries and the proportion between reclaimed and discarded lead-acid batteries, we have estimated the recovery potential of discarded lead-acid batteries in 2000-2022. We estimate that the lead-acid batteries used in electric bicycles only have great recovery potential and there are abundant potential resources for recovery. The research data and results can help decision-makers make more effective and more accurate management measures and policies.


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## Body

## 1. Overview of Waste Lead-Acid Batteries

On May 15, 2018, the mandatory national standardTechnical Code for Safety of Electric Bicycles (hereinafter referred to asTechnical Code) was approved for issuance by the State Administration for Market Regulation and the Standardization Administration of the People’s Republic of China through Standard Notice of the People’s Republic of China (No. 72018) and will be officially implemented since April 15, 2019. TheTechnical Code states that electric bicycles shall have pedal power, the maximum design speed shall be no more than 25km/h, the total weight (including battery) shall be no more than 55kg, the motor power shall be no more than 400W, and the nominal battery voltage shall be no more than 48V. The period from May 15, 2018, to April 14, 2019, is the transitional period, during which manufacturers are encouraged to organize production according to theTechnical Code, sales companies to sell products that meet the requirements specified in theTechnical Code, and consumers to buy products that meet the requirements specified in theTechnical Code. After theTechnical Code is officially implemented, products that do not meet the requirements specified in theTechnical Code shall not be manufactured, sold, or imported. The issuance of theTechnical Code has not only accelerated the transformation and upgrading of the electric bicycle industry, but also greatly simulated the demand of the electric bicycle industry for the small, light lithium batteries with stable voltage because of mandatory norms on speed, motor power, and voltage, especially regulations on the weight of batteries. In the meantime, as the absolute dominate products, lead-acid batteries account for over 90% of battery products in the electric bicycle market [1]. The cheap but large and heavy lead-acid batteries as power batteries of electric bicycles are faced with accelerated replacement or direct elimination. To properly recycle and process large quantities of waste lead-acid batteries will be a big challenge.In foreign countries, waste lead-acid batteries have become a hot topic in circular economy because of its relatively high recycling value. On the other hand, if they are improperly handled, they can easily cause serious environmental pollution and threaten our health. Therefore, waste lead-acid batteries are internationally recognized as hazardous waste. As early as in the 1990s, the EU issued Directive 91/157/EEC on batteries containing hazardous substances, which include lead-acid batteries. The Directive sets relevant directive on battery labeling, margin system and environmental protection input, and so on [2]. Nowadays the recovery rate of lead-acid batteries in developed countries has basically reached 100% [3]. Developed countries attach great importance to the recycling of waste batteries and the production of secondary lead. The average annual output of secondary lead enterprises in developed countries is as high as more than 70,000 tons. In 1998, the total lead output in Western countries was 4.896 million tons, of which that of secondary lead was 2.846 million tons, accounting for 58.13% of the total lead output; the total lead output of the United States was 1.422 million tons, of which that of secondary lead was 1.083 million tons, accounting for 76.3%; the output density of secondary lead in countries like Germany, France, and Sweden was all over 50% [4]. In the 1960s, the world output of primary lead started to decline, while that of secondary lead gradually rose. In the 1990s, the world output of secondary lead exceeded that of primary lead. The main raw materials used to manufacture secondary lead are used lead-acid batteries. Currently lead-acid batteries already account for over 85% of raw materials of secondary lead [2]. In 2017, the global lead-acid battery market size was about USD42.9 billion, up 1% YoY. The lead consumption of lead-acid batteries in the United States accounts for over 95% of the country’s total lead consumption. Thanks to sound regulations and effective management, the lead emission from manufacturing of lead-acid batteries accounts for only 1.5% of total emissions. In 2008, the US government removed lead-acid battery manufacturing from main lead pollution sources [5].China is the largest manufacturer and seller of electric bicycles and also the world’s largest manufacturer and consumer of lead accumulators. According to the data of the National Bureau of Statistics, by the end of 2017, the number of electric bicycles registered or in use was over 250 million, and that of electric tricycles was over 50 million (Ye. X. H. 2018) [6]. Since 2011, the production of electric bicycles has grown by 30 million to 37 million per year and that of electric tricycles by 7.6 million to 10 million a year [7]. The newly increased production of the two each year is nearly 40 million to 50 million. For a long time over 95% of the power batteries used in electric bicycles in China are lead-acid batteries. Currently lead-acid batteries are still the primary power batteries in the electric bicycle industry. Even though lithium batteries are better in performance, energy density, and service life, as their prices are relatively high, the proportion of lithium batteries in commercially available vehicle models is less than 10% [8].The service life of the lead-acid batteries used as power batteries of electric bicycles is generally 1 to 3 years and the average service cycle is 2 years. With increasing production of lead-acid batteries and increasing number of electric bicycles registered or in use, the number of scrapped and replaced lead-acid batteries is huge. According to incomplete statistics, the total weight of waste lead-acid batteries in China every year is around 4 million tons and it is growing at an annual rate of about 15% (Li X. Z. 2016) [9]. Around 2000, about 50 million lead-acid batteries or over 300,000 tons were scrapped in China every year (Ma Y. G. 2000) [10]; the weight of waste lead batteries produced in 2015 was more than 2.6 million tons [11]; in 2016 there were about 3.5 million tons of waste batteries [12], 11.7 times that in 2000, and the annual growth rate of waste lead-acid batteries in 2016 was over 30%. However, according to statistics, the number of waste lead-acid batteries recycled with proper methods is less than 30% [13]. That is to say, over 70% of waste lead-acid batteries are illegally recycled and dismantled.The acid solution in lead-acid batteries contains various heavy metals such as lead, zinc, manganese, and cadmium. Improperly dismantling or processing waste lead-acid batteries can cause lead dust pollution and blood lead poisoning (acute or chronic injection of lead into the body can cause nerve metabolic, reproductive, and mental diseases and can even result in death). As for improper pouring of waste lead solution, the heavy metals resolved from the acid solution and toxic waste solution will cause severe pollution to soil, plants, rivers, surface water, ground water, air, etc., seriously threatening ecological balance and human health.On the other hand, seen from the global lead consumption structure, 86% of the downstream lead demands are used to manufacture batteries, while those used in paint, boards, and alloy account for 5%, 4%, and 2%, respectively. Therefore, the battery industry is the main downstream application of secondary lead [14]. In China around 80% of refined lead production is used to manufacture lead-acid batteries every year (Li S. L. 2018) [15]. The Chinese secondary lead industry developed slowly. In the 1950s, the annual production of secondary lead hovered around the thousand tonnage. In 1990 its production was 28,200 tons, in 1994 it reached 95,000 tons, and in 1995 it broke 100,000 tons. Between 1990 and 1993, the production of secondary lead accounted for about 10% of the total production of refined lead, and it increased to around 20% since 1994 (Ma Y. G. 2000) [16]. In 2013, the production of secondary lead in China was 1.5 million tons, up 7.1% year on year, and it is estimated that it accounted for over 30% [17] of the consumption of refined lead that year. In 2015, the production of refined lead in China was about 4.7 million tons and that of secondary lead was about 1.6 million tons, and the proportion of secondary lead production was about 35% [18]. This shows that after nearly 30 years’ development, the use ratio of secondary lead has only increased from 10% in the early 1990s to about 35% today. Waste lead-acid batteries are main raw materials of secondary lead. According to incomplete statistics, the use ratio of secondary lead is 90% in the United States, 85% in Japan and 80%-90% in Europe, while in China the ratio of secondary lead actually used is less than 50% (Xue X. 2016) [19].Moreover, waste lead batteries are composed of 74% lead and its compound, 20% sulfuric acid, and 6% plastics, which have relatively high resource recovery value [24]. According to statistics, in 2012 the global battery market size was USD75.975 billion, of which the market size of lead-acid batteries was USD39.294 billion, which was the largest. And 97% of the lead in lead-acid batteries can be recycled, making them the consumables with the highest reclamation rate (Lv X. L. 2013) [25].Therefore, if we can further improve the recovery of waste lead-acid batteries and increase the use ratio of secondary lead, the “urban mine” of waste lead-acid batteries will have irreplaceable strategic significance to our protection of primary metal resources, utilization of secondary metal resources, development of the secondary lead industry, and national metal resource security.


## 2. Related Works

With low prices, simple production technology, high recovery rate, great recovery value, and a high use ratio of secondary lead, lead-acid batteries have incomparable advantages in the secondary battery field. Renowned lead-acid battery scientist Detchko Pavlov writes in the preface of his bookLead-acid Batteries: Science and Technology that because they use a high proportion of secondary lead and are easy to produce, lead-acid batteries are currently the lowest-cost chemical power source. For decades lead-acid batteries have taken up 65%-70% (Pavlov D. 2015) [26] of global chemical power source production. Lead-acid batteries are cheap, easy to produce, and easy to recycle, and the resources for their manufacture are practically unlimited (Pavlov D. 2015) [27]. Waste lead-acid batteries have very high recovery value. The grids in waste lead-acid batteries and the lead slime containing PbO2 and PbSO4 are main sources of secondary lead. In China over 85% of the raw materials of secondary lead are from waste lead-acid batteries, and 50% of secondary lead is used to produce storage batteries (Zhu S.R. 2002) [28]. Therefore, to be able to reasonably, scientifically, and accurately predict the generation amount of waste lead-acid batteries and estimate the amount of secondary lead and other renewable resources recycled from waste lead-acid batteries is of great significance to the waste metal resource recovery, ecological environment protection, metal resource safety, and sustainable development of the (secondary) lead industry of China.As lead-acid batteries are very similar and comparable to electronic and electrical products in service characteristics, scrapping cycle, and recovery method, the studies that mainly use waste electronic and electrical products as the subject of forecast can be used for reference. Liu Xiaoli et al. (2005) [29] estimated the annual waste quantity of five major categories of electronic and electrical products in 2000-2010 in China using the Stanford Model. Liang Xiaohui et al. (2009) [30] forecasted the waste quantity, recovery amount, storage amount, circulating amount, and filling amount of five categories of electronic products in 2008-2012 using the Carnegie Mellon Model. Tang Hongxia (2009) [31] forecasted the generation amount of waste electrical and electronic products in Shanghai using the “expert estimation” model. Tong Xin et al.(2013) [32] compared the forecast results of the generation amount of electronic waste in China based on the Stanford Model and the holding quantity coefficient method with the actual recovery data in the pilot areas of the “old for new” activity of home appliances in China. Wang Qi et al. (2014) [33] conducted a comparative study of the four most representative estimation models for waste electronic products, namely, the Carnegie Mellon Model, the market supply model, the Stanford Model, and the time sequence model, and presented concrete calculation examples to show their advantages, disadvantages, and applicable scope. Zhang Han et al. (2016) [34] established a model and estimated and compared the annual waste quantity of primary batteries, lead-acid batteries, lithium batteries, and Ni-MH batteries in China between 2011 and 2020.Meanwhile, researchers have conducted meaningful studies with various research methods to forecast the amounts of different wastes in the world. For example, V. P. Ulnikovica et al. (2012) [35] presented a methodology for the assessment of waste material quantities that was developed as part of the Technological Development Project TR 21037 of the Republic of Serbia. Required information on the amount of traffic, vessel types, and numbers as well as the number of dockings was extracted from questionnaires and interviews with watermen and researchers to determine the quantity of vessel-generated waste. V. Bijayashree et al. (2014) [36] forecasted municipal solid waste quantity and composition, respectively, through a multiple linear regression model and system dynamics model and forecasted the generation rate, amount, and waste stream of solid waste in India’s capital Delhi in 2011-2014. R. Intharathirat et al. (2015) [37] forecasted MSW collected in Thailand with prediction interval in long term period by using the optimized multivariate grey model which is the mathematical approach. Li Xin et al. (2017) [38] by setting the consumption intensity, recovery intensity, and life distribution functions of minerals and analyzing the historical experience of industrialized countries such as the United States, the United Kingdom, Germany, Japan, and China on the consumption, storage, and recovery of metal products between 1949 and 2015, taking copper, steel, and aluminum as examples, predicted the consumption and waste recovery variation trend of the three metals in China between 2016 and 2030. P. van Der Werf et al. (2018) [39] adopted direct measurement of waste streams through waste composition studies to estimate the quantity of food waste disposed in the garbage stream by households in southern Ontario, Canada, and determine if this common methodology could be expanded and serve as the basis of a standardized and rigorous household food waste measurement methodology. A. K. Awasthi et al. (2018) [40] revealed the presence of a strong linear correlation among global e-waste generation and Gross Domestic Product by comparing the best fit for data relationship between e-waste collected volumes and GDP PPS. They also held that because e-waste contains valuable metals such as copper, gold, and silver and their content is higher in precious metals than in mineral ores, the better collection of e-waste acts an important role concerning the circular economy.Regarding “recovery potential” of waste, scholars also have studied it from multiple aspects. Some scholars studied the quantity of resources with recovery value in municipal solid waste and the economic benefit they can bring. Some scholars estimated the content of precious metals in waste pipes and cables that remain underground in cities and concluded that they have great potential for urban mining. Some scholars studied the types and recovery potential of landfill mined plastic wastes and determined the feasibility of landfill mining projects based on that. Some scholars determined the theoretical recovery potential of 57 elements a complete survey of the sewage sludge ash (SSA) from monoincineration facilities and concluded that SSA is an important secondary resource of P. M. Alamgir et al. (2007) [41] analyzed the contents of components in solid waste such as organics, paper, and plastic, evaluated the potential for recovery and reduction based on the waste characteristics, and predicted the economic benefit that can be earned from recycling and composting of municipal solid waste, based on the study of the types and generation amount of solid waste in six major cities in Bangladesh in 2005. B. Wallsten et al. (2013) [42] analyzed the pipes and cables that remain in the ground after being taken out of use or disconnected for a number of reasons using the GIS-based MFA method and found that they contain rich mineral resources such as copper, aluminum, and iron. They believe that these infrastructures “cold spots” are hibernating stock with a significant potential for urban mining. C. Zhou. et al. (2014) [43] study the characteristics of the landfill mined plastic wastes and their recovery potential to determine the feasibility of landfill mining project. O. Krüger C. Adam (2015) [44] conducted a complete survey of the sewage sludge ash (SSA) from German monoincineration facilities and determined the theoretical recovery potential of 57 elements. German SSA contains up to 19,000t/a P which equals approximately 13% of phosphorus applied in the German agriculture in form of phosphate rock based mineral fertilizers. Thus, SSA is an important secondary resource of P. Stijn van Ewijk et al. (2018) [45] estimated the recovery potential of waste in global paper life cycle using the life-cycle assessment method, and they evaluated the use of global paper materials and the ideal waste recovery potential using the “recovery potential” index.Life-cycle assessment (LCA) is a standardized method (Ciroth A et al. 2011) [46] to assess environmental impacts associated with all the stages of a product’s, process’s or activity’s life from raw material extraction through materials processing, manufacture, distribution, use, recovery, maintenance, and disposal. Its research focus is to establish the life-cycle environmental impact assessment model and collect data or use LCA database data to analyze the environmental impacts of the subject of study in its whole life-cycle. For example, H. A. Arafat et al. (2015) [47] assessed the environmental impacts of five municipal solid waste (MSW) treatment processes using the life-cycle assessment (LCA) tool.As far as the subject is concerned, there are almost no studies on the subject of the waste quantity of lead-acid batteries in China, especially the lead-acid batteries used as power batteries in electric bicycles. In terms of research methods, the common estimation models used to estimate waste quantity are the market supply model, the market supply A model, the Stanford Model, the Carnegie Mellon Model, the time sequence model, the expert estimation model, the holding quantity coefficient method, the ICER model, etc. Due to limited data, early researcher obtained some data needed for calculation from indirect calculation of other data that they could collect at that time. Moreover, with the development of society, some key data needed for calculation such as product service life were adjusted due to rapid social development, quick changes in industries and the issue of particular policies. Currently the holding quantity of electric bicycles (including tricycles) in China is more than 300 million [7], and annual sales volume is nearly 40 million [7]. Each electric bicycle is equipped with 3 to 4 battery sets, while over 90% of electric bicycles use lead-acid batteries as power batteries. Therefore, lead-acid batteries take up a huge market share, no matter in production, sales or holding quantity, and waste quantity and have great recovery potential and, meanwhile, will face a seriously pollution prevention situation. It is thus strongly necessary to study the lead-acid batteries used in electric bicycles, adopt the latest statistical data, and select the optimal estimation model to forecast and study their waste quantity and provide scientific support for waste recovery and reclamation in China.


## 3. Research Method and Data Source

### 3.1. Research Method

#### 3.1.1. Introduction to Estimation Models

In the estimation of the waste quantity of an electronic product, the production, sales, and service life of the product are generally considered. There are mainly 7 estimation models (Simon W. et al. 2011) [48].(1) Market supply model: the model is a method to estimate electronic waste based on product sales data and average service life. The assumption is that the sold electronic product is completely discarded at the end of its service life and can still be used before the end of its service life and the average service life of the product is relatively stable. The estimation formula of the annual waste quantity of a certain electronic product using the model is(1)Qw=SnQ w is quantity of electronic waste; Sn is sales of the electronic product n years ago; n is average service life of the electronic product.(2) Market supply A model (Yamasue E et al. 2006) [49]: on the basis of the market supply model, the model adopts the distribution value of average service life of a product. It is assumed that the product is subject to several different service lives every year and gives each service life a certain proportion. According to relevant research, the service lives of the product are in normal distribution around the average service life. The estimation formula of electronic waste using the market supply A model is(2)Qw=∑i=0nSiPiQ w is quantity of electronic waste; Si is sales of the electronic product i years ago beginning this year; Pi is percentage of the electronic product with i years of service life; i is time life of the electronic product.(3) Stanford Model (Yang and Williams 2009) [50]: the model uses the changes in the sales in a certain period of time after entering society and the social holding quantity in that period of time to calculate the quantity of electronic waste. Its calculation method is similar to that of the market supply A model, except that Pi in the market supply A model is a constant value while Pi in the Stanford Model is variable. The model assumes that every year the product that is being sold is subject to several different service lives according to its usage. The formula is(3)Qw=∑i=0nSiPiQ w is quantity of electronic waste; Si is sales of the electronic product i years ago beginning this year; Pi is the percentage of the electronic product with i years of service life; i is the time life of the electronic product.(4) Carnegie Melon Model: the model has corrected the market supply method by taking into account the disposal methods after discarding. When making forecast, it takes into account how consumers treat and handle unused electronic products. On the basis of analyzing consumers’ handling of electronic waste, it has set four different handling scenarios when an electronic product is obsolete, namely, refurbishing and reselling it, laying it aside, dismantling and restoring it, and disposing it as waste, and gives each handling method a certain proportion. The Carnegie Melon Model is suitable for large waste electrical appliances with a relatively longer service life.(5) Time gradient model: the model starts with holding quantity, takes into account the number of home appliances entering and exiting the holding quantity statistics, and estimates waste production based on sales data and private holding quantity and industrial holding quantity level. The formula is(4)Pt=∑i=t1tSn-∑i=t1tPn-Ht-Ht1,t1<tP t is production of electronic waste in the t year; Pn is production of electronic waste in the n year; Sn is sales of the electronic product in the n year; Ht is social stock of electronic production in the t year; Ht1 is social stock of electronic production in the t1 year.(6) “Estimation” model: It mainly adopts social holding quantity and average service life. The estimation formula is(5)Qw=Holdingquantityprivate+industrialnQ w is quantity of electronic waste; n is average service life of the electronic product.(7) ICER model: the model uses the replacement rate of the estimated product to estimate its waste quantity. On the basis of the market supply model and the Stanford Model, Chinese scholars have established a prediction model based on the production of waste electronic information products in fixed and dynamic cycles.The aforesaid models are mainly used to estimate the waste quantity of electronics and electric appliances. We suggest selecting a suitable model to estimate the quantity of waste lead-acid batteries based on the service cycle and waste characteristics of lead-acid batteries.


#### 3.1.2. Selection of Prediction Model

(  1) Types and Characteristics of Lead-Acid Batteries. Based on their field of application, lead-acid batteries can be divided into four types: starting batteries, power batteries, standby batteries, and energy storage batteries (see Table 1). The service life of lead-acid batteries varies depending on their purpose of use. Therefore, the discarding time and annual discarding quantity also vary. Taking the statistical data in 2012, for example, the production of lead-acid batteries used in electric bicycles as power batteries accounted for less than 37% of the production of the whole lead-acid battery industry. However, some scholars (Zhang H. et al. 2016) [34] did not make such a strict distinction. When estimating the quantity of waste lead-acid batteries, they adopted the data of the whole industry as the production and sales data for calculation, while only adopting the service life of a certain type of batteries for calculation, which can easily lead to deviation of estimation data.Table 1
Types and recovery management characteristics of lead-acid batteries.
Battery type Application field Battery production (2012) [20] (10,000 KVAH) Proportion Service life (year) Recovery management characteristics Starting battery Used as storage batteries for starting, ignition and lighting (SLI) and so on in vehicles with an internal combustion engine such as buses, trucks and motorcycles and other vehicles 7495 52% 1.5-3 The users are widely distributed. The production is high, the single use quantity is relatively huge, and most of such batteries are replaced through distributors or maintenance service providers. The recovery management focuses are distributors and maintenance service providers.  Power battery Used as power batteries in electric vehicles such as electric bicycles, electric special-purpose vehicles (electric sightseeing buses, golf carts, patrol cars, forklifts, etc.), low-speed electric passenger cars and hybrid electric vehicles 5320 37% 1-3 The users are especially disperse, the production is relatively large, the single use quantity is large and the replacement frequency is high, but the recovery is irregular. Illegal recovery vendors are main clients. The recovery management focuses are consumers, distributors and maintenance service providers.  Standby battery Used as standby power in telecommunication base stations, UPS, emergency lighting power and other standby power 1601 11% 3-6 The batteries have built-in GPS, the production is low, but the single use quantity is huge. They can be recycled through proper channels and are easy to manage. Recovery management focuses are distributors and maintenance service providers. Energy storage battery Used as storage batteries in solar power generation equipment, wind turbines and other renewable energy resourcesGlobally starting lead-acid batteries take up the largest proportion, which is 48%, followed by power lead-acid batteries with 28%. The proportion of standby and energy storage lead-acid batteries is 15%, and that of other lead-acid batteries is 9% (Lu L.Q. 2018) [51]. The proportions of the four types of lead-acid batteries are similar to those in the Chinese market.In addition, in terms of waste recovery, lead-acid batteries in different application fields are faced different recovery dilemmas (see Table1). The lead-acid batteries used as power batteries are the focus and difficulty in recovery management, while the lead-acid batteries used in electric bicycles as power batteries are inevitably the priority in research.(  2) Selection of Prediction Model. The aforesaid 7 models are mainly applicable to the estimation of the quantity of waste electronic and electrical products, including TVs, refrigerators, air conditioners, computers, washing machines, and mobile phones (Gao Y. N. et al. 2010) [52]. Because of the generality between battery-using products and electronic and electrical products in terms of service cycle, discarding cycle and replacement frequency, some scholars used some of the models to estimate the quantity of waste batteries, including primary batteries, lead-acid batteries, lithium batteries, and Ni-MH batteries.In view of the characteristics of lead-acid batteries, especially the power batteries used in electric bicycles as the subject of study of the thesis, we have selected the “market supply A model” and the “Stanford Model” to forecast the waste quantity of power batteries used in electric bicycles.


### 3.2. Source of Data

#### 3.2.1. Calculation of Sales of Lead-Acid Batteries Used in Electric Bicycles as Power Batteries

Both the “market supply A model” and the “Stanford Model” adopt product sales (Si), product service life (i), and service life distribution (Pi) as the calculation basis to estimate waste quantity.In this thesis, we have adopted the annual production of electric bicycles and electric tricycles as the basis data to estimate the waste quantity of power lead-acid batteries used in electric bicycles. We have collected and sorted out the overall data of the electric bicycle industry, and based on the industry structure, we have obtained the annual net increment of electric bicycles (including electric tricycles) using lead-acid batteries as power using formula (6). Based on the annual net increment of lead-acid battery powered electric bicycles (according to national regulations, a common electric bicycle generally uses four 48V12ah or four 48V20ah batteries), we have then obtained the annual increment of lead-acid batteries through calculation and have used it as the annual newly increased sales of power lead-acid batteries used in electric bicycles.(6)Annual  net  increment  of__lead-acid  battery  powered  electric  bicyclesincluding  tricycles=production  of  electric  bicycles+production  of  electric  tricycles-production  of  lithium  battery  powered  bicycles+import  volume  of  electric  bicycles-export  volume  of  electric  bicycles(  1) Calculation of Sales-Output Ratios of Three Types of Electric Bicycles. According to the acquired data, calculation, and analysis, the average sales-output ratio of electric bicycles in 2015-2017 (see Table 2) is 96%, that of electric tricycles in 2014-2017 (see Table 3) is 85%, and that of lithium battery powered bicycles (see Table 4) is 87%. The three types of electric bicycles basically ensured dynamic balance between sales and output. Therefore, the output of the three types of electric bicycles is deemed equal to their sales in this thesis.Table 2
Sales-output ratio of electric bicycles in 2015-2017 (unit: 10,000 sets.).
Year Output of electric bicycles Sales of electric bicycles Sales-output ratio 2015 3257 3398 104.3% 2016 3215 2600 80.9% 2017 3113 3200 102.8% Source: National Bureau of Statistics (www.stats.gov.cn) and www.chyxx.com.Table 3
Sales-output ratio of electric tricycles in 2014-2017 (unit: 10,000 sets).
Year Output of electric tricycles Sales of electric tricycles Sales-output ratio 2014 1122 898 80% 2015 1163 980 84.2% 2016 1153 930 80.7% 2017 850 800 94.1% Source:www.chyxx.com.Table 4
Sales-output ratio of lithium battery powered bicycles in 2006-2015 (unit: 10,000 sets).
Year Output of lithium battery powered bicycles Sales of lithium battery powered bicycles Sales-output ratio 2006 5 5 100% 2007 13.5 8 59.2% 2008 22.3 12 53.8% 2009 29.84 17 57% 2010 40.2 25 62% 2011 65 70 107% 2012 149.9 160 106% 2013 231.1 231.1 100% 2014 301 350 116% 2015 292 300 106% Source:www.evtimes.cn/, www.escn.com.cn/, and www.chyxx.com/industry/201702/493958.html.(  2) Calculation of Import Volume of Electric Bicycles. Due to limited data and influence of domestic policy and international market, the import and export data of electric bicycles have been fluctuating widely over the years. To ensure the accuracy and coherence of estimation data, regarding the missing import data of electric bicycles in 2016 and 2017, we have excluded the data in abnormal years (2012, 2013, and 2014) and adopted the average value of the remaining data as the import volume of electric bicycles in 2016 and 2017 (see Table 5).Table 5
Import and export volume of electric bicycles (unit: 10,000 sets.).
Year Export volume of electric bicycles Import volume of electric bicycles 2009 122.4 457 2010 163.4 488 2011 141.1 435 2012 128.9 835 2013 151.9 2456 2014 211.3 886 2015 649.4 441 2016 133.9 (455) 2017 730.1 (455) Source: General Administration of Customs (www.customs.gov.cn/), www.chinaidr.com/news/2017-02/110769.html, and www.chinaidr.com/news/2017-02/110770.html.(  3) Calculation of Output of Lithium Battery Powered Bicycles. Due to limited data, the output of lithium battery powered bicycles in 2017 is missing. Through the analysis of the data on lithium battery powered bicycles over the years, we have found that the proportion of the output of lithium battery powered bicycles in the bicycle industry is on a rising trend since 2006. The fitted equation on the proportion of lithium battery powered bicycles in electric bicycles in 2006-2016 is(7)y=-0.00022x3+0.00477x2-0.01925x+0.02324R2=0.96559With the equation, we have obtained that the proportion in 2017 is 9.90%, which is highly consistent with industry experts’ forecast on the proportion of lithium battery powered bicycles in 2017, which is that “seen from data performance, the market share of lithium battery powered bicycles is increasing year by year. Even though official data is currently unavailable, we can be sure that the market share of the sales of lithium battery powered bicycles in 2017 is around one tenth” [53]. Based on that, we have obtained the output of lithium battery powered bicycles in 2017, which is 3.0806 million (see Table 6).Table 6
Output of lithium battery powered bicycles (unit: 10,000 sets.).
Year Output of electric bicycles Output of lithium battery powered bicycles Proportion of lithium battery powered bicycles in electric bicycles 2006 1950 5 0.26% 2007 2138 13.5 0.63% 2008 2188 22.3 1.02% 2009 2369 29.84 1.26% 2010 2954 40.2 1.36% 2011 3096 65 2.10% 2012 3505 149.9 4.28% 2013 3695 231.1 6.25% 2014 3551 301 8.48% 2015 3257 292 8.97% 2016 3215 282 8.77% 2017 3113 (308.06) (9.90%) Source:www.evtimes.cn/ and www.escn.com.cn/.(  4) Calculation of Annual Net Increment of Lead-Acid Battery Powered Bicycles (Including Tricycles). The annual net increment of lead-acid battery powered bicycles (including tricycles) in 2000-2017 is obtained using formula (6) (see Table 7).Table 7
Annual net increment of lead-acid battery powered bicycles (including tricycles) in 2000-2017 (unit: 10,000 sets).
Year Output of electric bicycles Output of electric tricycles Output of lithium battery powered bicycles Export volume of electric bicycles Import volume of electric bicycles Annual net increment of lead-acid battery powered bicycles (including tricycles) 2000 29 - - - - 29.00 2001 59 - - - - 59.00 2002 159 - - - - 159.00 2003 400 - - - - 400.00 2004 676 - - - - 676.00 2005 1211 - - - - 1211.00 2006 1950 - 5 - - 1945.00 2007 2138 - 13.5 - - 2124.50 2008 2188 - 22.3 - - 2165.70 2009 2369 603 29.84 122.4 457 3276.77 2010 2954 678 40.2 163.4 488 3916.36 2011 3096 761 65 141.1 435 4085.92 2012 3505 892 149.9 128.9 835 4953.22 2013 3695 1021 231.1 151.9 2456 6788.98 2014 3551 1122 301 211.3 886 5046.71 2015 3257 1163 292 649.4 441 3919.60 2016 3215 1153 282 133.9 (455) 4407.10 2017 3113 850 (308.06) 730.1 (455) 3379.84 Source: National Bureau of Statistics (www.stats.gov.cn/).(  5) Forecast of Annual Net Increment of Lead-Acid Battery Powered Bicycles (Including Tricycles) in 2018-2022. Based on the data change in the annual net increment of lead-acid battery powered bicycles in 2000-2017, we have analyzed its characteristics and variation trend and selected the annual net increment of lead-acid batteries in the last five years (2013-2017). We have adopted the fitted equation:(8)y=1,973.54328ln⁡x+6,598.11029R2=0.90909To estimate the annual net increment of lead-acid battery powered bicycles (including tricycles) in 2018-2022 (see Table8), based on the fact that the most common electric bicycle uses four 48V12ah storage batteries and the weight of each storage battery is about 4.3±0.2kg, we have forecasted the annual net increment of lead-acid batteries used in electric bicycles in 2000-2022 (see Table 9).Table 8
Annual net increment of lead-acid battery powered bicycles (including tricycles) in 2018-2022 (unit: 10,000 sets.).
Year Annual net increment of lead-acid battery powered bicycles (including tricycles) 2013 6788.98 2014 5046.71 2015 3919.60 2016 4407.10 2017 3379.84 2018 3062.00 2019 2757.77 2020 2494.24 2021 2261.79 2022 2053.86Table 9
Annual net increment of lead-acid batteries used in electric bicycles in 2000-2022.
Year Annual net increment of lead-acid battery powered bicycles (including tricycles) (unit: 10,000 sets.) Annual net increment of lead-acid batteries used in electric bicycles (10,000 sets.) (10,000 t) (10,000 KVAH) 2000 29 116.0 0.5 66.8 2001 59 236.0 1.0 135.9 2002 159 636.0 2.7 366.3 2003 400 1600.0 6.9 921.6 2004 676 2704.0 11.6 1557.5 2005 1211 4844.0 20.8 2790.1 2006 1945 7780.0 33.5 4481.3 2007 2124.5 8498.0 36.5 4894.8 2008 2165.7 8662.8 37.3 4989.8 2009 3276.8 13107.1 56.4 7549.7 2010 3916.4 15665.4 67.4 9023.3 2011 4085.9 16343.7 70.3 9414.0 2012 4953.2 19812.9 85.2 11412.2 2013 6789.0 27155.9 116.8 15641.8 2014 5046.7 20186.8 86.8 11627.6 2015 3919.6 15678.4 67.4 9030.8 2016 4407.1 17628.4 75.8 10154.0 2017 3379.8 13519.4 58.1 7787.1 2018 3062.0 12248.0 52.7 7054.8 2019 2757.8 11031.1 47.4 6353.9 2020 2494.2 9977.0 42.9 5746.7 2021 2261.8 9047.2 38.9 5211.2 2022 2053.9 8215.4 35.3 4732.1


#### 3.2.2. Estimation with “Market Supply A Model”

During our visit and interview, an owner who has been selling electric bicycles (including old for new business of storage batteries) for more than a decade said that even though the motives to buy an electric bicycle (household use, delivering goods, and express delivery) and the using frequency and time (the frequency is 2-6 times a day when using it to go to and get off work or take children to school or pick them up from school, and the using time is about 1-1.5 hours; for delivery of goods and parcels, the frequency is over 30 times a day, and the using time is more than 4 hours) vary, most storage batteries (lead-acid batteries) used in electric bicycles need to be replaced in 2 years if they are properly used. Through the survey of the families using electric bicycles in the surroundings, we have found that most families buy electric bicycles as a means of transportation to go to and get off work and send their children to school or pick them up by the way they generally use them for no more than 30 minutes in a single time and 2-3 times a day and replace batteries in 2-3 years.Take a 48V12ah lead-acid battery for example. According to the product information when the storage battery is sold, the cycle index is 400-600. If it is charged once a day, which means 1 cycle a day, it can be used for 1-1.5 years; if it is charged once in two days, it can be used for 2-3.5 years; if it is charged once in three days, it can be used for 3-5 years.According to industry standard, the service life of the lead-acid batteries used in electric bicycles should ensure 350 times of discharging based on 70% nominal capacity. However, in actual use, the cycle life of some batteries is as high as 600 cycles, the total capacity released is 6151ah, and the corresponding accumulative mileage is about 24,600km. Based on that, it can be used for over 2 years (Guo Z.Q. 2003) [54].Therefore, through social research and literature reading, we have found that the average service life of the lead-acid batteries powering electric bicycles is 2 years and the lead-acid batteries with a service life under 1 year or above 4 years are in the minority; that is, most lead-acid batteries are discarded after used for 2-3 years. We have selected the average valueX=2 of the service life of lead-acid batteries as the μ value and obtained σ=63, σ2=2/3 using the equation σ=Xi+X¯2/n. After the service life of lead-acid batteries complies with the normal distribution N2,2/3, we can obtain the service life distribution proportion of lead-acid batteries by querying the normal distribution table: the lead-acid batteries with a service life < 1 year account for 11.12%; those with a service life of 1-2 years account for 38.88%; those with a service life of 2-3 years account for 38.88%, and those with a service life > 3 years account for 11.12%; that is, P1=11.12%, P2=38.88%, P3=38.88%, and P4=11.12%.After puttingSi, Pi in the market supply A model, respectively, we have obtained the waste quantity of lead-acid batteries used in electric bicycles in 2000-2022 (see Table 10).Table 10
“Market supply A model” based annual waste quantity of lead-acid batteries used in electric bicycles in 2000-2022.
Year Annual waste quantityof lead-acid batteries used in electric bicycles (10,000 sets.) (10,000 t) (10,000 KVAH) 2000 - - - 2001 12.9 0.1 7.4 2002 71.3 0.3 41.1 2003 207.6 0.9 119.6 2004 529.9 2.3 305.2 2005 1196.3 5.1 689.1 2006 2282.8 9.8 1314.9 2007 3977.7 17.1 2291.2 2008 6153.9 26.5 3544.6 2009 7830.8 33.7 4510.6 2010 8994.8 38.7 5181.0 2011 11151.1 47.9 6423.0 2012 13967.5 60.1 8045.3 2013 16105.9 69.3 9277.0 2014 18819.4 80.9 10840.0 2015 22323.7 96.0 12858.4 2016 22353.5 96.1 12875.6 2017 18924.4 81.4 10900.5 2018 16697.8 71.8 9617.9 2019 15215.7 65.4 8764.2 2020 13205.3 56.8 7606.2 2021 11663.7 50.2 6718.3 2022 10536.0 45.3 6068.7


#### 3.2.3. Estimation Using “Stanford Model”

(  1) Model Assumption. The main difference between the Stanford Model and the market supply A model lies in that the Stanford Model mainly adopts the service life of products and service life distribution proportion to estimate waste quantity. That is to say, the Pi (percentage of waste) in the market supply A model is a constant value while the Pi (percentage of waste) in the Stanford Model is variable. According to the literature (Liu M. L. et al. 2015) [55], the model is based on the following assumptions.First, the lead-acid battery used in the eclectic bicycle is always being used till the end of its service life, and it is completely discarded after its service life ends. Second, the service life of the annual net incremental lead-acid batteries used in electric bicycles is in normal distribution centering on the average service life by different proportions. Third, the service life of the annual net incremental lead-acid batteries used in electric bicycles remains unchanged.To the lead-acid batteries studied in this thesis, we have assumed that the probability of discarding of the lead-acid batteries aftern1,n2,…,nm years is p1,p2,…,pm and we have used the annual net increment of lead-acid batteries used in electric bicycles obtained through calculation to forecast the future waste quantity. If the longest service life of the lead-acid batteries used in electric bicycles is M, the waste quantity is St in the t year and the scrap rate is Pk after k years, then the waste quantity Qj in the year j is(9)Qj=∑kMSj-kPk(  2) Model Calculation. On the basis of social survey, literature search and study of product use information, and the use characteristics of the lead-acid batteries used in electric bicycles, we have determined the service life, discarding time, and scrap rate of such lead-acid batteries every year (see Table 11).Table 11
Service life distribution proportion of lead-acid batteries powering electric bicycles.
Year Annual net increment of lead-acid batteries used in electric bicycles (10,000 sets) Average service life (year) Service life distribution (%) of lead-acid batteries P 4 P 3 P 2 P 1 2000 116.0 2.3 10% 30% 40% 20% 2001 236.0 2.3 10% 30% 40% 20% 2002 636.0 2.3 10% 30% 40% 20% 2003 1600.0 2.3 10% 30% 40% 20% 2004 2704.0 2.3 10% 30% 40% 20% 2005 4844.0 2.3 10% 30% 40% 20% 2006 7780.0 2.5 15% 35% 35% 15% 2007 8498.0 2.5 15% 35% 35% 15% 2008 8662.8 2.5 15% 35% 35% 15% 2009 13107.1 2.5 15% 35% 35% 15% 2010 15665.4 2.5 15% 35% 35% 15% 2011 16343.7 2.5 15% 35% 35% 15% 2012 19812.9 2.7 20% 40% 30% 10% 2013 27155.9 2.7 20% 40% 30% 10% 2014 20186.8 2.7 20% 40% 30% 10% 2015 15678.4 2.7 20% 40% 30% 10% 2016 17628.4 2.7 20% 40% 30% 10% 2017 13519.4 2.7 20% 40% 30% 10% 2018 12248.0 2.7 20% 40% 30% 10% 2019 11031.1 2.7 20% 40% 30% 10% 2020 9977.0 2.7 20% 40% 30% 10% 2021 9047.2 2.7 20% 40% 30% 10% 2022 8215.4 2.7 20% 40% 30% 10%After putting the data in Table11 into the Stanford Model for calculation, we have obtained the waste quantity of lead-acid batteries used in electric bicycles in 2000-2022 (see Table 12).Table 12
“Stanford Model” based annual waste quantity of lead-acid batteries used in electric bicycles in 2000-2022.
Year Annul waste quantity of lead-acid batteries used in electric bicycles (10,000 sets) (10,000 t) (10,000 KVAH) 2000 - - - 2001 - - - 2002 - - - 2003 - - - 2004 656.8 2.8 378.3 2005 1395.2 6.0 803.6 2006 2594.0 11.2 1494.1 2007 4075.8 17.5 2347.7 2008 5721.3 24.6 3295.5 2009 7481.1 32.2 4309.1 2010 9139.3 39.3 5264.3 2011 11244.0 48.3 6476.5 2012 13821.4 59.4 7961.1 2013 15150.6 65.1 8726.7 2014 16729.6 71.9 9636.2 2015 20542.2 88.3 11832.3 2016 22448.8 96.5 12930.5 2017 19972.3 85.9 11504.0 2018 16949.2 72.9 9762.7 2019 15467.6 66.5 8909.4 2020 13710.9 59.0 7897.5 2021 11910.1 51.2 6860.2 2022 10759.8 46.3 6197.7


## 3.1. Research Method

### 3.1.1. Introduction to Estimation Models

In the estimation of the waste quantity of an electronic product, the production, sales, and service life of the product are generally considered. There are mainly 7 estimation models (Simon W. et al. 2011) [48].(1) Market supply model: the model is a method to estimate electronic waste based on product sales data and average service life. The assumption is that the sold electronic product is completely discarded at the end of its service life and can still be used before the end of its service life and the average service life of the product is relatively stable. The estimation formula of the annual waste quantity of a certain electronic product using the model is(1)Qw=SnQ w is quantity of electronic waste; Sn is sales of the electronic product n years ago; n is average service life of the electronic product.(2) Market supply A model (Yamasue E et al. 2006) [49]: on the basis of the market supply model, the model adopts the distribution value of average service life of a product. It is assumed that the product is subject to several different service lives every year and gives each service life a certain proportion. According to relevant research, the service lives of the product are in normal distribution around the average service life. The estimation formula of electronic waste using the market supply A model is(2)Qw=∑i=0nSiPiQ w is quantity of electronic waste; Si is sales of the electronic product i years ago beginning this year; Pi is percentage of the electronic product with i years of service life; i is time life of the electronic product.(3) Stanford Model (Yang and Williams 2009) [50]: the model uses the changes in the sales in a certain period of time after entering society and the social holding quantity in that period of time to calculate the quantity of electronic waste. Its calculation method is similar to that of the market supply A model, except that Pi in the market supply A model is a constant value while Pi in the Stanford Model is variable. The model assumes that every year the product that is being sold is subject to several different service lives according to its usage. The formula is(3)Qw=∑i=0nSiPiQ w is quantity of electronic waste; Si is sales of the electronic product i years ago beginning this year; Pi is the percentage of the electronic product with i years of service life; i is the time life of the electronic product.(4) Carnegie Melon Model: the model has corrected the market supply method by taking into account the disposal methods after discarding. When making forecast, it takes into account how consumers treat and handle unused electronic products. On the basis of analyzing consumers’ handling of electronic waste, it has set four different handling scenarios when an electronic product is obsolete, namely, refurbishing and reselling it, laying it aside, dismantling and restoring it, and disposing it as waste, and gives each handling method a certain proportion. The Carnegie Melon Model is suitable for large waste electrical appliances with a relatively longer service life.(5) Time gradient model: the model starts with holding quantity, takes into account the number of home appliances entering and exiting the holding quantity statistics, and estimates waste production based on sales data and private holding quantity and industrial holding quantity level. The formula is(4)Pt=∑i=t1tSn-∑i=t1tPn-Ht-Ht1,t1<tP t is production of electronic waste in the t year; Pn is production of electronic waste in the n year; Sn is sales of the electronic product in the n year; Ht is social stock of electronic production in the t year; Ht1 is social stock of electronic production in the t1 year.(6) “Estimation” model: It mainly adopts social holding quantity and average service life. The estimation formula is(5)Qw=Holdingquantityprivate+industrialnQ w is quantity of electronic waste; n is average service life of the electronic product.(7) ICER model: the model uses the replacement rate of the estimated product to estimate its waste quantity. On the basis of the market supply model and the Stanford Model, Chinese scholars have established a prediction model based on the production of waste electronic information products in fixed and dynamic cycles.The aforesaid models are mainly used to estimate the waste quantity of electronics and electric appliances. We suggest selecting a suitable model to estimate the quantity of waste lead-acid batteries based on the service cycle and waste characteristics of lead-acid batteries.


### 3.1.2. Selection of Prediction Model

(  1) Types and Characteristics of Lead-Acid Batteries. Based on their field of application, lead-acid batteries can be divided into four types: starting batteries, power batteries, standby batteries, and energy storage batteries (see Table 1). The service life of lead-acid batteries varies depending on their purpose of use. Therefore, the discarding time and annual discarding quantity also vary. Taking the statistical data in 2012, for example, the production of lead-acid batteries used in electric bicycles as power batteries accounted for less than 37% of the production of the whole lead-acid battery industry. However, some scholars (Zhang H. et al. 2016) [34] did not make such a strict distinction. When estimating the quantity of waste lead-acid batteries, they adopted the data of the whole industry as the production and sales data for calculation, while only adopting the service life of a certain type of batteries for calculation, which can easily lead to deviation of estimation data.Table 1
Types and recovery management characteristics of lead-acid batteries.
Battery type Application field Battery production (2012) [20] (10,000 KVAH) Proportion Service life (year) Recovery management characteristics Starting battery Used as storage batteries for starting, ignition and lighting (SLI) and so on in vehicles with an internal combustion engine such as buses, trucks and motorcycles and other vehicles 7495 52% 1.5-3 The users are widely distributed. The production is high, the single use quantity is relatively huge, and most of such batteries are replaced through distributors or maintenance service providers. The recovery management focuses are distributors and maintenance service providers.  Power battery Used as power batteries in electric vehicles such as electric bicycles, electric special-purpose vehicles (electric sightseeing buses, golf carts, patrol cars, forklifts, etc.), low-speed electric passenger cars and hybrid electric vehicles 5320 37% 1-3 The users are especially disperse, the production is relatively large, the single use quantity is large and the replacement frequency is high, but the recovery is irregular. Illegal recovery vendors are main clients. The recovery management focuses are consumers, distributors and maintenance service providers.  Standby battery Used as standby power in telecommunication base stations, UPS, emergency lighting power and other standby power 1601 11% 3-6 The batteries have built-in GPS, the production is low, but the single use quantity is huge. They can be recycled through proper channels and are easy to manage. Recovery management focuses are distributors and maintenance service providers. Energy storage battery Used as storage batteries in solar power generation equipment, wind turbines and other renewable energy resourcesGlobally starting lead-acid batteries take up the largest proportion, which is 48%, followed by power lead-acid batteries with 28%. The proportion of standby and energy storage lead-acid batteries is 15%, and that of other lead-acid batteries is 9% (Lu L.Q. 2018) [51]. The proportions of the four types of lead-acid batteries are similar to those in the Chinese market.In addition, in terms of waste recovery, lead-acid batteries in different application fields are faced different recovery dilemmas (see Table1). The lead-acid batteries used as power batteries are the focus and difficulty in recovery management, while the lead-acid batteries used in electric bicycles as power batteries are inevitably the priority in research.(  2) Selection of Prediction Model. The aforesaid 7 models are mainly applicable to the estimation of the quantity of waste electronic and electrical products, including TVs, refrigerators, air conditioners, computers, washing machines, and mobile phones (Gao Y. N. et al. 2010) [52]. Because of the generality between battery-using products and electronic and electrical products in terms of service cycle, discarding cycle and replacement frequency, some scholars used some of the models to estimate the quantity of waste batteries, including primary batteries, lead-acid batteries, lithium batteries, and Ni-MH batteries.In view of the characteristics of lead-acid batteries, especially the power batteries used in electric bicycles as the subject of study of the thesis, we have selected the “market supply A model” and the “Stanford Model” to forecast the waste quantity of power batteries used in electric bicycles.


## 3.1.1. Introduction to Estimation Models

In the estimation of the waste quantity of an electronic product, the production, sales, and service life of the product are generally considered. There are mainly 7 estimation models (Simon W. et al. 2011) [48].(1) Market supply model: the model is a method to estimate electronic waste based on product sales data and average service life. The assumption is that the sold electronic product is completely discarded at the end of its service life and can still be used before the end of its service life and the average service life of the product is relatively stable. The estimation formula of the annual waste quantity of a certain electronic product using the model is(1)Qw=SnQ w is quantity of electronic waste; Sn is sales of the electronic product n years ago; n is average service life of the electronic product.(2) Market supply A model (Yamasue E et al. 2006) [49]: on the basis of the market supply model, the model adopts the distribution value of average service life of a product. It is assumed that the product is subject to several different service lives every year and gives each service life a certain proportion. According to relevant research, the service lives of the product are in normal distribution around the average service life. The estimation formula of electronic waste using the market supply A model is(2)Qw=∑i=0nSiPiQ w is quantity of electronic waste; Si is sales of the electronic product i years ago beginning this year; Pi is percentage of the electronic product with i years of service life; i is time life of the electronic product.(3) Stanford Model (Yang and Williams 2009) [50]: the model uses the changes in the sales in a certain period of time after entering society and the social holding quantity in that period of time to calculate the quantity of electronic waste. Its calculation method is similar to that of the market supply A model, except that Pi in the market supply A model is a constant value while Pi in the Stanford Model is variable. The model assumes that every year the product that is being sold is subject to several different service lives according to its usage. The formula is(3)Qw=∑i=0nSiPiQ w is quantity of electronic waste; Si is sales of the electronic product i years ago beginning this year; Pi is the percentage of the electronic product with i years of service life; i is the time life of the electronic product.(4) Carnegie Melon Model: the model has corrected the market supply method by taking into account the disposal methods after discarding. When making forecast, it takes into account how consumers treat and handle unused electronic products. On the basis of analyzing consumers’ handling of electronic waste, it has set four different handling scenarios when an electronic product is obsolete, namely, refurbishing and reselling it, laying it aside, dismantling and restoring it, and disposing it as waste, and gives each handling method a certain proportion. The Carnegie Melon Model is suitable for large waste electrical appliances with a relatively longer service life.(5) Time gradient model: the model starts with holding quantity, takes into account the number of home appliances entering and exiting the holding quantity statistics, and estimates waste production based on sales data and private holding quantity and industrial holding quantity level. The formula is(4)Pt=∑i=t1tSn-∑i=t1tPn-Ht-Ht1,t1<tP t is production of electronic waste in the t year; Pn is production of electronic waste in the n year; Sn is sales of the electronic product in the n year; Ht is social stock of electronic production in the t year; Ht1 is social stock of electronic production in the t1 year.(6) “Estimation” model: It mainly adopts social holding quantity and average service life. The estimation formula is(5)Qw=Holdingquantityprivate+industrialnQ w is quantity of electronic waste; n is average service life of the electronic product.(7) ICER model: the model uses the replacement rate of the estimated product to estimate its waste quantity. On the basis of the market supply model and the Stanford Model, Chinese scholars have established a prediction model based on the production of waste electronic information products in fixed and dynamic cycles.The aforesaid models are mainly used to estimate the waste quantity of electronics and electric appliances. We suggest selecting a suitable model to estimate the quantity of waste lead-acid batteries based on the service cycle and waste characteristics of lead-acid batteries.


## 3.1.2. Selection of Prediction Model

(  1) Types and Characteristics of Lead-Acid Batteries. Based on their field of application, lead-acid batteries can be divided into four types: starting batteries, power batteries, standby batteries, and energy storage batteries (see Table 1). The service life of lead-acid batteries varies depending on their purpose of use. Therefore, the discarding time and annual discarding quantity also vary. Taking the statistical data in 2012, for example, the production of lead-acid batteries used in electric bicycles as power batteries accounted for less than 37% of the production of the whole lead-acid battery industry. However, some scholars (Zhang H. et al. 2016) [34] did not make such a strict distinction. When estimating the quantity of waste lead-acid batteries, they adopted the data of the whole industry as the production and sales data for calculation, while only adopting the service life of a certain type of batteries for calculation, which can easily lead to deviation of estimation data.Table 1
Types and recovery management characteristics of lead-acid batteries.
Battery type Application field Battery production (2012) [20] (10,000 KVAH) Proportion Service life (year) Recovery management characteristics Starting battery Used as storage batteries for starting, ignition and lighting (SLI) and so on in vehicles with an internal combustion engine such as buses, trucks and motorcycles and other vehicles 7495 52% 1.5-3 The users are widely distributed. The production is high, the single use quantity is relatively huge, and most of such batteries are replaced through distributors or maintenance service providers. The recovery management focuses are distributors and maintenance service providers.  Power battery Used as power batteries in electric vehicles such as electric bicycles, electric special-purpose vehicles (electric sightseeing buses, golf carts, patrol cars, forklifts, etc.), low-speed electric passenger cars and hybrid electric vehicles 5320 37% 1-3 The users are especially disperse, the production is relatively large, the single use quantity is large and the replacement frequency is high, but the recovery is irregular. Illegal recovery vendors are main clients. The recovery management focuses are consumers, distributors and maintenance service providers.  Standby battery Used as standby power in telecommunication base stations, UPS, emergency lighting power and other standby power 1601 11% 3-6 The batteries have built-in GPS, the production is low, but the single use quantity is huge. They can be recycled through proper channels and are easy to manage. Recovery management focuses are distributors and maintenance service providers. Energy storage battery Used as storage batteries in solar power generation equipment, wind turbines and other renewable energy resourcesGlobally starting lead-acid batteries take up the largest proportion, which is 48%, followed by power lead-acid batteries with 28%. The proportion of standby and energy storage lead-acid batteries is 15%, and that of other lead-acid batteries is 9% (Lu L.Q. 2018) [51]. The proportions of the four types of lead-acid batteries are similar to those in the Chinese market.In addition, in terms of waste recovery, lead-acid batteries in different application fields are faced different recovery dilemmas (see Table1). The lead-acid batteries used as power batteries are the focus and difficulty in recovery management, while the lead-acid batteries used in electric bicycles as power batteries are inevitably the priority in research.(  2) Selection of Prediction Model. The aforesaid 7 models are mainly applicable to the estimation of the quantity of waste electronic and electrical products, including TVs, refrigerators, air conditioners, computers, washing machines, and mobile phones (Gao Y. N. et al. 2010) [52]. Because of the generality between battery-using products and electronic and electrical products in terms of service cycle, discarding cycle and replacement frequency, some scholars used some of the models to estimate the quantity of waste batteries, including primary batteries, lead-acid batteries, lithium batteries, and Ni-MH batteries.In view of the characteristics of lead-acid batteries, especially the power batteries used in electric bicycles as the subject of study of the thesis, we have selected the “market supply A model” and the “Stanford Model” to forecast the waste quantity of power batteries used in electric bicycles.


## 3.2. Source of Data

### 3.2.1. Calculation of Sales of Lead-Acid Batteries Used in Electric Bicycles as Power Batteries

Both the “market supply A model” and the “Stanford Model” adopt product sales (Si), product service life (i), and service life distribution (Pi) as the calculation basis to estimate waste quantity.In this thesis, we have adopted the annual production of electric bicycles and electric tricycles as the basis data to estimate the waste quantity of power lead-acid batteries used in electric bicycles. We have collected and sorted out the overall data of the electric bicycle industry, and based on the industry structure, we have obtained the annual net increment of electric bicycles (including electric tricycles) using lead-acid batteries as power using formula (6). Based on the annual net increment of lead-acid battery powered electric bicycles (according to national regulations, a common electric bicycle generally uses four 48V12ah or four 48V20ah batteries), we have then obtained the annual increment of lead-acid batteries through calculation and have used it as the annual newly increased sales of power lead-acid batteries used in electric bicycles.(6)Annual  net  increment  of__lead-acid  battery  powered  electric  bicyclesincluding  tricycles=production  of  electric  bicycles+production  of  electric  tricycles-production  of  lithium  battery  powered  bicycles+import  volume  of  electric  bicycles-export  volume  of  electric  bicycles(  1) Calculation of Sales-Output Ratios of Three Types of Electric Bicycles. According to the acquired data, calculation, and analysis, the average sales-output ratio of electric bicycles in 2015-2017 (see Table 2) is 96%, that of electric tricycles in 2014-2017 (see Table 3) is 85%, and that of lithium battery powered bicycles (see Table 4) is 87%. The three types of electric bicycles basically ensured dynamic balance between sales and output. Therefore, the output of the three types of electric bicycles is deemed equal to their sales in this thesis.Table 2
Sales-output ratio of electric bicycles in 2015-2017 (unit: 10,000 sets.).
Year Output of electric bicycles Sales of electric bicycles Sales-output ratio 2015 3257 3398 104.3% 2016 3215 2600 80.9% 2017 3113 3200 102.8% Source: National Bureau of Statistics (www.stats.gov.cn) and www.chyxx.com.Table 3
Sales-output ratio of electric tricycles in 2014-2017 (unit: 10,000 sets).
Year Output of electric tricycles Sales of electric tricycles Sales-output ratio 2014 1122 898 80% 2015 1163 980 84.2% 2016 1153 930 80.7% 2017 850 800 94.1% Source:www.chyxx.com.Table 4
Sales-output ratio of lithium battery powered bicycles in 2006-2015 (unit: 10,000 sets).
Year Output of lithium battery powered bicycles Sales of lithium battery powered bicycles Sales-output ratio 2006 5 5 100% 2007 13.5 8 59.2% 2008 22.3 12 53.8% 2009 29.84 17 57% 2010 40.2 25 62% 2011 65 70 107% 2012 149.9 160 106% 2013 231.1 231.1 100% 2014 301 350 116% 2015 292 300 106% Source:www.evtimes.cn/, www.escn.com.cn/, and www.chyxx.com/industry/201702/493958.html.(  2) Calculation of Import Volume of Electric Bicycles. Due to limited data and influence of domestic policy and international market, the import and export data of electric bicycles have been fluctuating widely over the years. To ensure the accuracy and coherence of estimation data, regarding the missing import data of electric bicycles in 2016 and 2017, we have excluded the data in abnormal years (2012, 2013, and 2014) and adopted the average value of the remaining data as the import volume of electric bicycles in 2016 and 2017 (see Table 5).Table 5
Import and export volume of electric bicycles (unit: 10,000 sets.).
Year Export volume of electric bicycles Import volume of electric bicycles 2009 122.4 457 2010 163.4 488 2011 141.1 435 2012 128.9 835 2013 151.9 2456 2014 211.3 886 2015 649.4 441 2016 133.9 (455) 2017 730.1 (455) Source: General Administration of Customs (www.customs.gov.cn/), www.chinaidr.com/news/2017-02/110769.html, and www.chinaidr.com/news/2017-02/110770.html.(  3) Calculation of Output of Lithium Battery Powered Bicycles. Due to limited data, the output of lithium battery powered bicycles in 2017 is missing. Through the analysis of the data on lithium battery powered bicycles over the years, we have found that the proportion of the output of lithium battery powered bicycles in the bicycle industry is on a rising trend since 2006. The fitted equation on the proportion of lithium battery powered bicycles in electric bicycles in 2006-2016 is(7)y=-0.00022x3+0.00477x2-0.01925x+0.02324R2=0.96559With the equation, we have obtained that the proportion in 2017 is 9.90%, which is highly consistent with industry experts’ forecast on the proportion of lithium battery powered bicycles in 2017, which is that “seen from data performance, the market share of lithium battery powered bicycles is increasing year by year. Even though official data is currently unavailable, we can be sure that the market share of the sales of lithium battery powered bicycles in 2017 is around one tenth” [53]. Based on that, we have obtained the output of lithium battery powered bicycles in 2017, which is 3.0806 million (see Table 6).Table 6
Output of lithium battery powered bicycles (unit: 10,000 sets.).
Year Output of electric bicycles Output of lithium battery powered bicycles Proportion of lithium battery powered bicycles in electric bicycles 2006 1950 5 0.26% 2007 2138 13.5 0.63% 2008 2188 22.3 1.02% 2009 2369 29.84 1.26% 2010 2954 40.2 1.36% 2011 3096 65 2.10% 2012 3505 149.9 4.28% 2013 3695 231.1 6.25% 2014 3551 301 8.48% 2015 3257 292 8.97% 2016 3215 282 8.77% 2017 3113 (308.06) (9.90%) Source:www.evtimes.cn/ and www.escn.com.cn/.(  4) Calculation of Annual Net Increment of Lead-Acid Battery Powered Bicycles (Including Tricycles). The annual net increment of lead-acid battery powered bicycles (including tricycles) in 2000-2017 is obtained using formula (6) (see Table 7).Table 7
Annual net increment of lead-acid battery powered bicycles (including tricycles) in 2000-2017 (unit: 10,000 sets).
Year Output of electric bicycles Output of electric tricycles Output of lithium battery powered bicycles Export volume of electric bicycles Import volume of electric bicycles Annual net increment of lead-acid battery powered bicycles (including tricycles) 2000 29 - - - - 29.00 2001 59 - - - - 59.00 2002 159 - - - - 159.00 2003 400 - - - - 400.00 2004 676 - - - - 676.00 2005 1211 - - - - 1211.00 2006 1950 - 5 - - 1945.00 2007 2138 - 13.5 - - 2124.50 2008 2188 - 22.3 - - 2165.70 2009 2369 603 29.84 122.4 457 3276.77 2010 2954 678 40.2 163.4 488 3916.36 2011 3096 761 65 141.1 435 4085.92 2012 3505 892 149.9 128.9 835 4953.22 2013 3695 1021 231.1 151.9 2456 6788.98 2014 3551 1122 301 211.3 886 5046.71 2015 3257 1163 292 649.4 441 3919.60 2016 3215 1153 282 133.9 (455) 4407.10 2017 3113 850 (308.06) 730.1 (455) 3379.84 Source: National Bureau of Statistics (www.stats.gov.cn/).(  5) Forecast of Annual Net Increment of Lead-Acid Battery Powered Bicycles (Including Tricycles) in 2018-2022. Based on the data change in the annual net increment of lead-acid battery powered bicycles in 2000-2017, we have analyzed its characteristics and variation trend and selected the annual net increment of lead-acid batteries in the last five years (2013-2017). We have adopted the fitted equation:(8)y=1,973.54328ln⁡x+6,598.11029R2=0.90909To estimate the annual net increment of lead-acid battery powered bicycles (including tricycles) in 2018-2022 (see Table8), based on the fact that the most common electric bicycle uses four 48V12ah storage batteries and the weight of each storage battery is about 4.3±0.2kg, we have forecasted the annual net increment of lead-acid batteries used in electric bicycles in 2000-2022 (see Table 9).Table 8
Annual net increment of lead-acid battery powered bicycles (including tricycles) in 2018-2022 (unit: 10,000 sets.).
Year Annual net increment of lead-acid battery powered bicycles (including tricycles) 2013 6788.98 2014 5046.71 2015 3919.60 2016 4407.10 2017 3379.84 2018 3062.00 2019 2757.77 2020 2494.24 2021 2261.79 2022 2053.86Table 9
Annual net increment of lead-acid batteries used in electric bicycles in 2000-2022.
Year Annual net increment of lead-acid battery powered bicycles (including tricycles) (unit: 10,000 sets.) Annual net increment of lead-acid batteries used in electric bicycles (10,000 sets.) (10,000 t) (10,000 KVAH) 2000 29 116.0 0.5 66.8 2001 59 236.0 1.0 135.9 2002 159 636.0 2.7 366.3 2003 400 1600.0 6.9 921.6 2004 676 2704.0 11.6 1557.5 2005 1211 4844.0 20.8 2790.1 2006 1945 7780.0 33.5 4481.3 2007 2124.5 8498.0 36.5 4894.8 2008 2165.7 8662.8 37.3 4989.8 2009 3276.8 13107.1 56.4 7549.7 2010 3916.4 15665.4 67.4 9023.3 2011 4085.9 16343.7 70.3 9414.0 2012 4953.2 19812.9 85.2 11412.2 2013 6789.0 27155.9 116.8 15641.8 2014 5046.7 20186.8 86.8 11627.6 2015 3919.6 15678.4 67.4 9030.8 2016 4407.1 17628.4 75.8 10154.0 2017 3379.8 13519.4 58.1 7787.1 2018 3062.0 12248.0 52.7 7054.8 2019 2757.8 11031.1 47.4 6353.9 2020 2494.2 9977.0 42.9 5746.7 2021 2261.8 9047.2 38.9 5211.2 2022 2053.9 8215.4 35.3 4732.1


### 3.2.2. Estimation with “Market Supply A Model”

During our visit and interview, an owner who has been selling electric bicycles (including old for new business of storage batteries) for more than a decade said that even though the motives to buy an electric bicycle (household use, delivering goods, and express delivery) and the using frequency and time (the frequency is 2-6 times a day when using it to go to and get off work or take children to school or pick them up from school, and the using time is about 1-1.5 hours; for delivery of goods and parcels, the frequency is over 30 times a day, and the using time is more than 4 hours) vary, most storage batteries (lead-acid batteries) used in electric bicycles need to be replaced in 2 years if they are properly used. Through the survey of the families using electric bicycles in the surroundings, we have found that most families buy electric bicycles as a means of transportation to go to and get off work and send their children to school or pick them up by the way they generally use them for no more than 30 minutes in a single time and 2-3 times a day and replace batteries in 2-3 years.Take a 48V12ah lead-acid battery for example. According to the product information when the storage battery is sold, the cycle index is 400-600. If it is charged once a day, which means 1 cycle a day, it can be used for 1-1.5 years; if it is charged once in two days, it can be used for 2-3.5 years; if it is charged once in three days, it can be used for 3-5 years.According to industry standard, the service life of the lead-acid batteries used in electric bicycles should ensure 350 times of discharging based on 70% nominal capacity. However, in actual use, the cycle life of some batteries is as high as 600 cycles, the total capacity released is 6151ah, and the corresponding accumulative mileage is about 24,600km. Based on that, it can be used for over 2 years (Guo Z.Q. 2003) [54].Therefore, through social research and literature reading, we have found that the average service life of the lead-acid batteries powering electric bicycles is 2 years and the lead-acid batteries with a service life under 1 year or above 4 years are in the minority; that is, most lead-acid batteries are discarded after used for 2-3 years. We have selected the average valueX=2 of the service life of lead-acid batteries as the μ value and obtained σ=63, σ2=2/3 using the equation σ=Xi+X¯2/n. After the service life of lead-acid batteries complies with the normal distribution N2,2/3, we can obtain the service life distribution proportion of lead-acid batteries by querying the normal distribution table: the lead-acid batteries with a service life < 1 year account for 11.12%; those with a service life of 1-2 years account for 38.88%; those with a service life of 2-3 years account for 38.88%, and those with a service life > 3 years account for 11.12%; that is, P1=11.12%, P2=38.88%, P3=38.88%, and P4=11.12%.After puttingSi, Pi in the market supply A model, respectively, we have obtained the waste quantity of lead-acid batteries used in electric bicycles in 2000-2022 (see Table 10).Table 10
“Market supply A model” based annual waste quantity of lead-acid batteries used in electric bicycles in 2000-2022.
Year Annual waste quantityof lead-acid batteries used in electric bicycles (10,000 sets.) (10,000 t) (10,000 KVAH) 2000 - - - 2001 12.9 0.1 7.4 2002 71.3 0.3 41.1 2003 207.6 0.9 119.6 2004 529.9 2.3 305.2 2005 1196.3 5.1 689.1 2006 2282.8 9.8 1314.9 2007 3977.7 17.1 2291.2 2008 6153.9 26.5 3544.6 2009 7830.8 33.7 4510.6 2010 8994.8 38.7 5181.0 2011 11151.1 47.9 6423.0 2012 13967.5 60.1 8045.3 2013 16105.9 69.3 9277.0 2014 18819.4 80.9 10840.0 2015 22323.7 96.0 12858.4 2016 22353.5 96.1 12875.6 2017 18924.4 81.4 10900.5 2018 16697.8 71.8 9617.9 2019 15215.7 65.4 8764.2 2020 13205.3 56.8 7606.2 2021 11663.7 50.2 6718.3 2022 10536.0 45.3 6068.7


### 3.2.3. Estimation Using “Stanford Model”

(  1) Model Assumption. The main difference between the Stanford Model and the market supply A model lies in that the Stanford Model mainly adopts the service life of products and service life distribution proportion to estimate waste quantity. That is to say, the Pi (percentage of waste) in the market supply A model is a constant value while the Pi (percentage of waste) in the Stanford Model is variable. According to the literature (Liu M. L. et al. 2015) [55], the model is based on the following assumptions.First, the lead-acid battery used in the eclectic bicycle is always being used till the end of its service life, and it is completely discarded after its service life ends. Second, the service life of the annual net incremental lead-acid batteries used in electric bicycles is in normal distribution centering on the average service life by different proportions. Third, the service life of the annual net incremental lead-acid batteries used in electric bicycles remains unchanged.To the lead-acid batteries studied in this thesis, we have assumed that the probability of discarding of the lead-acid batteries aftern1,n2,…,nm years is p1,p2,…,pm and we have used the annual net increment of lead-acid batteries used in electric bicycles obtained through calculation to forecast the future waste quantity. If the longest service life of the lead-acid batteries used in electric bicycles is M, the waste quantity is St in the t year and the scrap rate is Pk after k years, then the waste quantity Qj in the year j is(9)Qj=∑kMSj-kPk(  2) Model Calculation. On the basis of social survey, literature search and study of product use information, and the use characteristics of the lead-acid batteries used in electric bicycles, we have determined the service life, discarding time, and scrap rate of such lead-acid batteries every year (see Table 11).Table 11
Service life distribution proportion of lead-acid batteries powering electric bicycles.
Year Annual net increment of lead-acid batteries used in electric bicycles (10,000 sets) Average service life (year) Service life distribution (%) of lead-acid batteries P 4 P 3 P 2 P 1 2000 116.0 2.3 10% 30% 40% 20% 2001 236.0 2.3 10% 30% 40% 20% 2002 636.0 2.3 10% 30% 40% 20% 2003 1600.0 2.3 10% 30% 40% 20% 2004 2704.0 2.3 10% 30% 40% 20% 2005 4844.0 2.3 10% 30% 40% 20% 2006 7780.0 2.5 15% 35% 35% 15% 2007 8498.0 2.5 15% 35% 35% 15% 2008 8662.8 2.5 15% 35% 35% 15% 2009 13107.1 2.5 15% 35% 35% 15% 2010 15665.4 2.5 15% 35% 35% 15% 2011 16343.7 2.5 15% 35% 35% 15% 2012 19812.9 2.7 20% 40% 30% 10% 2013 27155.9 2.7 20% 40% 30% 10% 2014 20186.8 2.7 20% 40% 30% 10% 2015 15678.4 2.7 20% 40% 30% 10% 2016 17628.4 2.7 20% 40% 30% 10% 2017 13519.4 2.7 20% 40% 30% 10% 2018 12248.0 2.7 20% 40% 30% 10% 2019 11031.1 2.7 20% 40% 30% 10% 2020 9977.0 2.7 20% 40% 30% 10% 2021 9047.2 2.7 20% 40% 30% 10% 2022 8215.4 2.7 20% 40% 30% 10%After putting the data in Table11 into the Stanford Model for calculation, we have obtained the waste quantity of lead-acid batteries used in electric bicycles in 2000-2022 (see Table 12).Table 12
“Stanford Model” based annual waste quantity of lead-acid batteries used in electric bicycles in 2000-2022.
Year Annul waste quantity of lead-acid batteries used in electric bicycles (10,000 sets) (10,000 t) (10,000 KVAH) 2000 - - - 2001 - - - 2002 - - - 2003 - - - 2004 656.8 2.8 378.3 2005 1395.2 6.0 803.6 2006 2594.0 11.2 1494.1 2007 4075.8 17.5 2347.7 2008 5721.3 24.6 3295.5 2009 7481.1 32.2 4309.1 2010 9139.3 39.3 5264.3 2011 11244.0 48.3 6476.5 2012 13821.4 59.4 7961.1 2013 15150.6 65.1 8726.7 2014 16729.6 71.9 9636.2 2015 20542.2 88.3 11832.3 2016 22448.8 96.5 12930.5 2017 19972.3 85.9 11504.0 2018 16949.2 72.9 9762.7 2019 15467.6 66.5 8909.4 2020 13710.9 59.0 7897.5 2021 11910.1 51.2 6860.2 2022 10759.8 46.3 6197.7


## 3.2.1. Calculation of Sales of Lead-Acid Batteries Used in Electric Bicycles as Power Batteries

Both the “market supply A model” and the “Stanford Model” adopt product sales (Si), product service life (i), and service life distribution (Pi) as the calculation basis to estimate waste quantity.In this thesis, we have adopted the annual production of electric bicycles and electric tricycles as the basis data to estimate the waste quantity of power lead-acid batteries used in electric bicycles. We have collected and sorted out the overall data of the electric bicycle industry, and based on the industry structure, we have obtained the annual net increment of electric bicycles (including electric tricycles) using lead-acid batteries as power using formula (6). Based on the annual net increment of lead-acid battery powered electric bicycles (according to national regulations, a common electric bicycle generally uses four 48V12ah or four 48V20ah batteries), we have then obtained the annual increment of lead-acid batteries through calculation and have used it as the annual newly increased sales of power lead-acid batteries used in electric bicycles.(6)Annual  net  increment  of__lead-acid  battery  powered  electric  bicyclesincluding  tricycles=production  of  electric  bicycles+production  of  electric  tricycles-production  of  lithium  battery  powered  bicycles+import  volume  of  electric  bicycles-export  volume  of  electric  bicycles(  1) Calculation of Sales-Output Ratios of Three Types of Electric Bicycles. According to the acquired data, calculation, and analysis, the average sales-output ratio of electric bicycles in 2015-2017 (see Table 2) is 96%, that of electric tricycles in 2014-2017 (see Table 3) is 85%, and that of lithium battery powered bicycles (see Table 4) is 87%. The three types of electric bicycles basically ensured dynamic balance between sales and output. Therefore, the output of the three types of electric bicycles is deemed equal to their sales in this thesis.Table 2
Sales-output ratio of electric bicycles in 2015-2017 (unit: 10,000 sets.).
Year Output of electric bicycles Sales of electric bicycles Sales-output ratio 2015 3257 3398 104.3% 2016 3215 2600 80.9% 2017 3113 3200 102.8% Source: National Bureau of Statistics (www.stats.gov.cn) and www.chyxx.com.Table 3
Sales-output ratio of electric tricycles in 2014-2017 (unit: 10,000 sets).
Year Output of electric tricycles Sales of electric tricycles Sales-output ratio 2014 1122 898 80% 2015 1163 980 84.2% 2016 1153 930 80.7% 2017 850 800 94.1% Source:www.chyxx.com.Table 4
Sales-output ratio of lithium battery powered bicycles in 2006-2015 (unit: 10,000 sets).
Year Output of lithium battery powered bicycles Sales of lithium battery powered bicycles Sales-output ratio 2006 5 5 100% 2007 13.5 8 59.2% 2008 22.3 12 53.8% 2009 29.84 17 57% 2010 40.2 25 62% 2011 65 70 107% 2012 149.9 160 106% 2013 231.1 231.1 100% 2014 301 350 116% 2015 292 300 106% Source:www.evtimes.cn/, www.escn.com.cn/, and www.chyxx.com/industry/201702/493958.html.(  2) Calculation of Import Volume of Electric Bicycles. Due to limited data and influence of domestic policy and international market, the import and export data of electric bicycles have been fluctuating widely over the years. To ensure the accuracy and coherence of estimation data, regarding the missing import data of electric bicycles in 2016 and 2017, we have excluded the data in abnormal years (2012, 2013, and 2014) and adopted the average value of the remaining data as the import volume of electric bicycles in 2016 and 2017 (see Table 5).Table 5
Import and export volume of electric bicycles (unit: 10,000 sets.).
Year Export volume of electric bicycles Import volume of electric bicycles 2009 122.4 457 2010 163.4 488 2011 141.1 435 2012 128.9 835 2013 151.9 2456 2014 211.3 886 2015 649.4 441 2016 133.9 (455) 2017 730.1 (455) Source: General Administration of Customs (www.customs.gov.cn/), www.chinaidr.com/news/2017-02/110769.html, and www.chinaidr.com/news/2017-02/110770.html.(  3) Calculation of Output of Lithium Battery Powered Bicycles. Due to limited data, the output of lithium battery powered bicycles in 2017 is missing. Through the analysis of the data on lithium battery powered bicycles over the years, we have found that the proportion of the output of lithium battery powered bicycles in the bicycle industry is on a rising trend since 2006. The fitted equation on the proportion of lithium battery powered bicycles in electric bicycles in 2006-2016 is(7)y=-0.00022x3+0.00477x2-0.01925x+0.02324R2=0.96559With the equation, we have obtained that the proportion in 2017 is 9.90%, which is highly consistent with industry experts’ forecast on the proportion of lithium battery powered bicycles in 2017, which is that “seen from data performance, the market share of lithium battery powered bicycles is increasing year by year. Even though official data is currently unavailable, we can be sure that the market share of the sales of lithium battery powered bicycles in 2017 is around one tenth” [53]. Based on that, we have obtained the output of lithium battery powered bicycles in 2017, which is 3.0806 million (see Table 6).Table 6
Output of lithium battery powered bicycles (unit: 10,000 sets.).
Year Output of electric bicycles Output of lithium battery powered bicycles Proportion of lithium battery powered bicycles in electric bicycles 2006 1950 5 0.26% 2007 2138 13.5 0.63% 2008 2188 22.3 1.02% 2009 2369 29.84 1.26% 2010 2954 40.2 1.36% 2011 3096 65 2.10% 2012 3505 149.9 4.28% 2013 3695 231.1 6.25% 2014 3551 301 8.48% 2015 3257 292 8.97% 2016 3215 282 8.77% 2017 3113 (308.06) (9.90%) Source:www.evtimes.cn/ and www.escn.com.cn/.(  4) Calculation of Annual Net Increment of Lead-Acid Battery Powered Bicycles (Including Tricycles). The annual net increment of lead-acid battery powered bicycles (including tricycles) in 2000-2017 is obtained using formula (6) (see Table 7).Table 7
Annual net increment of lead-acid battery powered bicycles (including tricycles) in 2000-2017 (unit: 10,000 sets).
Year Output of electric bicycles Output of electric tricycles Output of lithium battery powered bicycles Export volume of electric bicycles Import volume of electric bicycles Annual net increment of lead-acid battery powered bicycles (including tricycles) 2000 29 - - - - 29.00 2001 59 - - - - 59.00 2002 159 - - - - 159.00 2003 400 - - - - 400.00 2004 676 - - - - 676.00 2005 1211 - - - - 1211.00 2006 1950 - 5 - - 1945.00 2007 2138 - 13.5 - - 2124.50 2008 2188 - 22.3 - - 2165.70 2009 2369 603 29.84 122.4 457 3276.77 2010 2954 678 40.2 163.4 488 3916.36 2011 3096 761 65 141.1 435 4085.92 2012 3505 892 149.9 128.9 835 4953.22 2013 3695 1021 231.1 151.9 2456 6788.98 2014 3551 1122 301 211.3 886 5046.71 2015 3257 1163 292 649.4 441 3919.60 2016 3215 1153 282 133.9 (455) 4407.10 2017 3113 850 (308.06) 730.1 (455) 3379.84 Source: National Bureau of Statistics (www.stats.gov.cn/).(  5) Forecast of Annual Net Increment of Lead-Acid Battery Powered Bicycles (Including Tricycles) in 2018-2022. Based on the data change in the annual net increment of lead-acid battery powered bicycles in 2000-2017, we have analyzed its characteristics and variation trend and selected the annual net increment of lead-acid batteries in the last five years (2013-2017). We have adopted the fitted equation:(8)y=1,973.54328ln⁡x+6,598.11029R2=0.90909To estimate the annual net increment of lead-acid battery powered bicycles (including tricycles) in 2018-2022 (see Table8), based on the fact that the most common electric bicycle uses four 48V12ah storage batteries and the weight of each storage battery is about 4.3±0.2kg, we have forecasted the annual net increment of lead-acid batteries used in electric bicycles in 2000-2022 (see Table 9).Table 8
Annual net increment of lead-acid battery powered bicycles (including tricycles) in 2018-2022 (unit: 10,000 sets.).
Year Annual net increment of lead-acid battery powered bicycles (including tricycles) 2013 6788.98 2014 5046.71 2015 3919.60 2016 4407.10 2017 3379.84 2018 3062.00 2019 2757.77 2020 2494.24 2021 2261.79 2022 2053.86Table 9
Annual net increment of lead-acid batteries used in electric bicycles in 2000-2022.
Year Annual net increment of lead-acid battery powered bicycles (including tricycles) (unit: 10,000 sets.) Annual net increment of lead-acid batteries used in electric bicycles (10,000 sets.) (10,000 t) (10,000 KVAH) 2000 29 116.0 0.5 66.8 2001 59 236.0 1.0 135.9 2002 159 636.0 2.7 366.3 2003 400 1600.0 6.9 921.6 2004 676 2704.0 11.6 1557.5 2005 1211 4844.0 20.8 2790.1 2006 1945 7780.0 33.5 4481.3 2007 2124.5 8498.0 36.5 4894.8 2008 2165.7 8662.8 37.3 4989.8 2009 3276.8 13107.1 56.4 7549.7 2010 3916.4 15665.4 67.4 9023.3 2011 4085.9 16343.7 70.3 9414.0 2012 4953.2 19812.9 85.2 11412.2 2013 6789.0 27155.9 116.8 15641.8 2014 5046.7 20186.8 86.8 11627.6 2015 3919.6 15678.4 67.4 9030.8 2016 4407.1 17628.4 75.8 10154.0 2017 3379.8 13519.4 58.1 7787.1 2018 3062.0 12248.0 52.7 7054.8 2019 2757.8 11031.1 47.4 6353.9 2020 2494.2 9977.0 42.9 5746.7 2021 2261.8 9047.2 38.9 5211.2 2022 2053.9 8215.4 35.3 4732.1


## 3.2.2. Estimation with “Market Supply A Model”

During our visit and interview, an owner who has been selling electric bicycles (including old for new business of storage batteries) for more than a decade said that even though the motives to buy an electric bicycle (household use, delivering goods, and express delivery) and the using frequency and time (the frequency is 2-6 times a day when using it to go to and get off work or take children to school or pick them up from school, and the using time is about 1-1.5 hours; for delivery of goods and parcels, the frequency is over 30 times a day, and the using time is more than 4 hours) vary, most storage batteries (lead-acid batteries) used in electric bicycles need to be replaced in 2 years if they are properly used. Through the survey of the families using electric bicycles in the surroundings, we have found that most families buy electric bicycles as a means of transportation to go to and get off work and send their children to school or pick them up by the way they generally use them for no more than 30 minutes in a single time and 2-3 times a day and replace batteries in 2-3 years.Take a 48V12ah lead-acid battery for example. According to the product information when the storage battery is sold, the cycle index is 400-600. If it is charged once a day, which means 1 cycle a day, it can be used for 1-1.5 years; if it is charged once in two days, it can be used for 2-3.5 years; if it is charged once in three days, it can be used for 3-5 years.According to industry standard, the service life of the lead-acid batteries used in electric bicycles should ensure 350 times of discharging based on 70% nominal capacity. However, in actual use, the cycle life of some batteries is as high as 600 cycles, the total capacity released is 6151ah, and the corresponding accumulative mileage is about 24,600km. Based on that, it can be used for over 2 years (Guo Z.Q. 2003) [54].Therefore, through social research and literature reading, we have found that the average service life of the lead-acid batteries powering electric bicycles is 2 years and the lead-acid batteries with a service life under 1 year or above 4 years are in the minority; that is, most lead-acid batteries are discarded after used for 2-3 years. We have selected the average valueX=2 of the service life of lead-acid batteries as the μ value and obtained σ=63, σ2=2/3 using the equation σ=Xi+X¯2/n. After the service life of lead-acid batteries complies with the normal distribution N2,2/3, we can obtain the service life distribution proportion of lead-acid batteries by querying the normal distribution table: the lead-acid batteries with a service life < 1 year account for 11.12%; those with a service life of 1-2 years account for 38.88%; those with a service life of 2-3 years account for 38.88%, and those with a service life > 3 years account for 11.12%; that is, P1=11.12%, P2=38.88%, P3=38.88%, and P4=11.12%.After puttingSi, Pi in the market supply A model, respectively, we have obtained the waste quantity of lead-acid batteries used in electric bicycles in 2000-2022 (see Table 10).Table 10
“Market supply A model” based annual waste quantity of lead-acid batteries used in electric bicycles in 2000-2022.
Year Annual waste quantityof lead-acid batteries used in electric bicycles (10,000 sets.) (10,000 t) (10,000 KVAH) 2000 - - - 2001 12.9 0.1 7.4 2002 71.3 0.3 41.1 2003 207.6 0.9 119.6 2004 529.9 2.3 305.2 2005 1196.3 5.1 689.1 2006 2282.8 9.8 1314.9 2007 3977.7 17.1 2291.2 2008 6153.9 26.5 3544.6 2009 7830.8 33.7 4510.6 2010 8994.8 38.7 5181.0 2011 11151.1 47.9 6423.0 2012 13967.5 60.1 8045.3 2013 16105.9 69.3 9277.0 2014 18819.4 80.9 10840.0 2015 22323.7 96.0 12858.4 2016 22353.5 96.1 12875.6 2017 18924.4 81.4 10900.5 2018 16697.8 71.8 9617.9 2019 15215.7 65.4 8764.2 2020 13205.3 56.8 7606.2 2021 11663.7 50.2 6718.3 2022 10536.0 45.3 6068.7


## 3.2.3. Estimation Using “Stanford Model”

(  1) Model Assumption. The main difference between the Stanford Model and the market supply A model lies in that the Stanford Model mainly adopts the service life of products and service life distribution proportion to estimate waste quantity. That is to say, the Pi (percentage of waste) in the market supply A model is a constant value while the Pi (percentage of waste) in the Stanford Model is variable. According to the literature (Liu M. L. et al. 2015) [55], the model is based on the following assumptions.First, the lead-acid battery used in the eclectic bicycle is always being used till the end of its service life, and it is completely discarded after its service life ends. Second, the service life of the annual net incremental lead-acid batteries used in electric bicycles is in normal distribution centering on the average service life by different proportions. Third, the service life of the annual net incremental lead-acid batteries used in electric bicycles remains unchanged.To the lead-acid batteries studied in this thesis, we have assumed that the probability of discarding of the lead-acid batteries aftern1,n2,…,nm years is p1,p2,…,pm and we have used the annual net increment of lead-acid batteries used in electric bicycles obtained through calculation to forecast the future waste quantity. If the longest service life of the lead-acid batteries used in electric bicycles is M, the waste quantity is St in the t year and the scrap rate is Pk after k years, then the waste quantity Qj in the year j is(9)Qj=∑kMSj-kPk(  2) Model Calculation. On the basis of social survey, literature search and study of product use information, and the use characteristics of the lead-acid batteries used in electric bicycles, we have determined the service life, discarding time, and scrap rate of such lead-acid batteries every year (see Table 11).Table 11
Service life distribution proportion of lead-acid batteries powering electric bicycles.
Year Annual net increment of lead-acid batteries used in electric bicycles (10,000 sets) Average service life (year) Service life distribution (%) of lead-acid batteries P 4 P 3 P 2 P 1 2000 116.0 2.3 10% 30% 40% 20% 2001 236.0 2.3 10% 30% 40% 20% 2002 636.0 2.3 10% 30% 40% 20% 2003 1600.0 2.3 10% 30% 40% 20% 2004 2704.0 2.3 10% 30% 40% 20% 2005 4844.0 2.3 10% 30% 40% 20% 2006 7780.0 2.5 15% 35% 35% 15% 2007 8498.0 2.5 15% 35% 35% 15% 2008 8662.8 2.5 15% 35% 35% 15% 2009 13107.1 2.5 15% 35% 35% 15% 2010 15665.4 2.5 15% 35% 35% 15% 2011 16343.7 2.5 15% 35% 35% 15% 2012 19812.9 2.7 20% 40% 30% 10% 2013 27155.9 2.7 20% 40% 30% 10% 2014 20186.8 2.7 20% 40% 30% 10% 2015 15678.4 2.7 20% 40% 30% 10% 2016 17628.4 2.7 20% 40% 30% 10% 2017 13519.4 2.7 20% 40% 30% 10% 2018 12248.0 2.7 20% 40% 30% 10% 2019 11031.1 2.7 20% 40% 30% 10% 2020 9977.0 2.7 20% 40% 30% 10% 2021 9047.2 2.7 20% 40% 30% 10% 2022 8215.4 2.7 20% 40% 30% 10%After putting the data in Table11 into the Stanford Model for calculation, we have obtained the waste quantity of lead-acid batteries used in electric bicycles in 2000-2022 (see Table 12).Table 12
“Stanford Model” based annual waste quantity of lead-acid batteries used in electric bicycles in 2000-2022.
Year Annul waste quantity of lead-acid batteries used in electric bicycles (10,000 sets) (10,000 t) (10,000 KVAH) 2000 - - - 2001 - - - 2002 - - - 2003 - - - 2004 656.8 2.8 378.3 2005 1395.2 6.0 803.6 2006 2594.0 11.2 1494.1 2007 4075.8 17.5 2347.7 2008 5721.3 24.6 3295.5 2009 7481.1 32.2 4309.1 2010 9139.3 39.3 5264.3 2011 11244.0 48.3 6476.5 2012 13821.4 59.4 7961.1 2013 15150.6 65.1 8726.7 2014 16729.6 71.9 9636.2 2015 20542.2 88.3 11832.3 2016 22448.8 96.5 12930.5 2017 19972.3 85.9 11504.0 2018 16949.2 72.9 9762.7 2019 15467.6 66.5 8909.4 2020 13710.9 59.0 7897.5 2021 11910.1 51.2 6860.2 2022 10759.8 46.3 6197.7


## 4. Analysis of Predictions

In this thesis we have adopted the “market supply A model” and the “Stanford Model” to predict the annual waste quantity of lead-acid batteries used in electric bicycles in 2000-2022. As shown in Tables10 and 12, the use quantity of lead-acid batteries changes with the sales or annual net increment of electric bicycles, while the waste quantity of lead-acid batteries is closely related to their service life. By analyzing the sales of lead-acid battery powered electric bicycles in 2000-2017, we have found that the sales of lead-acid batteries increased steadily as the sales of electric bicycles increased in 2000-2004, saw explosive growth in 2005-2013, reached the peak in 2013, and steadily fell down since 2013 till 2017 in which the sales are close to that in 2010. The forecast of the sales of lead-acid battery powered electric bicycles also shows that the downward trend will last till 2022. By comparing and analyzing the results of the two prediction models, we have found that because the Pi in the Stanford Model is variable and the model has higher requirements on data and is more comprehensive, the quantity of waste lead-acid batteries estimated with the model is slightly smaller than that estimated using the market supply A model; however, the predictions of the two models on the overall trend of the waste are consistent.Moreover, due to the issuance and implementation of the mandatory national standardTechnical Code for Safety of Electric Bicycles (GB17761-2018) since May 15, 2018, lead-acid battery powered electric bicycles will certainly be faced with either situation: to innovate own technology or to be replaced by lithium battery powered bicycles on a large scale. If lead-acid batteries are replaced by lithium batteries on a large scale, the sales of new electric bicycles powered by lead-acid batteries will reduce significantly, while the quantity of waste lead-acid batteries will increase sharply. Therefore, the lead-acid battery industry will be faced with industry transformation or technology upgrading, and recovery and processing enterprises of waste lead-acid batteries will be faced with new opportunities.


## 5. Analysis of Recovery Potential of Waste Lead-Acid Batteries

The average service life of the lead-acid batteries used in electric bicycles is about 2 years. Generally each electric bicycle is equipped with four 48V12ah lead-acid batteries. According to the prediction above, the waste quantity of lead-acid batteries used in electric bicycles only in 2017 will be nearly 200 million, and the weight 850,000 tons. Because in each lead-acid battery, 73.26% is lead and 11.46% is pure sulfuric acid, the 850,000-ton waste lead-acid batteries will contain 620,000 tons of lead and 9.74 million tons of pure sulfuric acid.We have studied the list of raw materials needed in the production phase of lead-acid batteries and the list of treatment links of waste lead-acid batteries based on the life-cycle assessment (LCA) method. The LCA method can be used to not only assess the environmental impacts and the consumption of environmental resources in the production, sales, transportation and use, and disposal and treatment of lead-acid batteries but also forecast the recovery potential of lead-acid batteries in the ideal state.The materials used to manufacture lead-acid batteries mainly include lead (73.26%), pure sulfuric acid (11.46%), plastic (12.09%), antimony, arsenic, tin (2.51%), rubber (0.35%), copper (0.35%), etc. (see Table14). Based on Table 10 (“Market supply A model” based annual waste quantity of lead-acid batteries used in electric bicycles in 2000-2022), Table 12 (“Stanford Model” based annul waste quantity of lead-acid batteries used in electric bicycles in 2000-2022), Table 13 (List of raw materials of lead-acid batteries), and Table 14 (Recovery list of disposal link of lead-acid batteries), we have obtained the recovered resource amount of lead-acid batteries used in electric bicycles as power batteries in 2000-2022 (see Tables 15 and 16) through calculation.Table 13
List of raw materials of lead-acid batteries (Yu Y. J. et al. 2010 [21]; Zhang H. et al. 2013 [22]).
Name of raw material Mass of raw material contained in 1000 KVAH lead-acid batteries (kg) Ratio of mass of raw material in total mass Lead 26.85 73.26% Pure sulfuric acid 4.20 11.46% Plastic 4.43 12.09% Antimony, arsenic, tin 0.92 2.51% Rubber 0.13 0.35% Copper 0.12 0.35%Table 14
Recovery list of disposal link of lead-acid batteries (Zhang H. Wang et al. 2013) [23].
Type Name Quantity (1,000kg) Unit Recovered material Lead 636.91 Kg Total sulfur (100% sulfuric acid) 97.41 Kg Plastic recovery quantity 106.06 Kg  Energy Coal 138.23 Kg Electric power 21.40 Kg  Emission Lead fume 12.88 Kg Residue-containing lead 10.55 Kg SO2 emission 267.07 KgTable 15
Recovery quantity of lead-acid batteries used in electric bicycles as power batteries in 2000-2022 (market supply A model).
Year Annual waste quantity and recovery quantity of lead-acid batteries used in electric bicycles Waste quantity (10,000 KVAH) Lead (t) Pure sulfuric acid (t) Plastic (t) Antimony, arsenic, tin (t) Rubber (t) Copper (t) 2000 - 2001 7.4 2.0 0.3121 0.3291 0.0684 0.0097 0.0089 2002 41.1 11.0 1.7 1.8 0.3781 0.0534 0.0493 2003 119.6 32.1 5.0 5.3 1.1 0.1554 0.1435 2004 305.2 81.9 12.8 13.5 2.8 0.3968 0.3662 2005 689.1 185.0 28.9 30.5 6.3 0.8958 0.8269 2006 1314.9 353.0 55.2 58.2 12.1 1.7 1.6 2007 2291.2 615.2 96.2 101.5 21.1 3.0 2.7 2008 3544.6 951.7 148.9 157.0 32.6 4.6 4.3 2009 4510.6 1211.1 189.4 199.8 41.5 5.9 5.4 2010 5181.0 1391.1 217.6 229.5 47.7 6.7 6.2 2011 6423.0 1724.6 269.8 284.5 59.1 8.3 7.7 2012 8045.3 2160.2 337.9 356.4 74.0 10.5 9.7 2013 9277.0 2490.9 389.6 411.0 85.3 12.1 11.1 2014 10840.0 2910.5 455.3 480.2 99.7 14.1 13.0 2015 12858.4 3452.5 540.1 569.6 118.3 16.7 15.4 2016 12875.6 3457.1 540.8 570.4 118.5 16.7 15.5 2017 10900.5 2926.8 457.8 482.9 100.3 14.2 13.1 2018 9617.9 2582.4 404.0 426.1 88.5 12.5 11.5 2019 8764.2 2353.2 368.1 388.3 80.6 11.4 10.5 2020 7606.2 2042.3 319.5 337.0 70.0 9.9 9.1 2021 6718.3 1803.9 282.2 297.6 61.8 8.7 8.1 2022 6068.7 1629.4 254.9 268.8 55.8 7.9 7.3Table 16
Recovery quantity of lead-acid batteries used in electric bicycles as power batteries in 2000-2022 (Stanford Model).
Year Annual waste quantity and recovery quantity of lead-acid batteries used in electric bicycles Waste quantity (10,000 KVAH) Lead (t) Pure sulfuric acid (t) Plastic (t) Antimony, arsenic, tin (t) Rubber (t) Copper (t) 2000 - - - - - - - 2001 - - - - - - - 2002 - - - - - - - 2003 - - - - - - - 2004 378.3 101.6 15.9 16.8 3.5 0.4918 0.4540 2005 803.6 215.8 33.8 35.6 7.4 1.04 0.9644 2006 1494.1 401.2 62.8 66.2 13.7 1.9 1.8 2007 2347.7 630.3 98.6 104.0 21.6 3.1 2.8 2008 3295.5 884.8 138.4 146.0 30.3 4.3 4.0 2009 4309.1 1157.0 181.0 190.9 39.6 5.6 5.2 2010 5264.3 1413.5 221.1 233.2 48.4 6.8 6.3 2011 6476.5 1738.9 272.0 286.9 59.6 8.4 7.8 2012 7961.1 2137.6 334.4 352.7 73.2 10.3 9.6 2013 8726.7 2343.1 366.5 386.6 80.3 11.3 10.5 2014 9636.2 2587.3 404.7 426.9 88.7 12.5 11.6 2015 11832.3 3177.0 497.0 524.2 108.9 15.4 14.2 2016 12930.5 3471.8 543.1 572.8 119.0 16.8 15.5 2017 11504.0 3088.8 483.2 509.6 105.8 15.0 13.8 2018 9762.7 2621.3 410.0 432.5 89.8 12.7 11.7 2019 8909.4 2392.2 374.2 394.7 82.0 11.6 10.7 2020 7897.5 2120.5 331.7 349.9 72.7 10.3 9.5 2021 6860.2 1842.0 288.1 303.9 63.1 8.9 8.2 2022 6197.7 1664.1 260.3 274.6 57.0 8.1 7.4Recovery potential is the ratio between the recoverable mass of each material of waste lead-acid batteries and the mass of the raw material contained in lead-acid batteries. It can be used to access the recovery value of waste lead-acid batteries.The recovery potential of each material of lead-acid batteries can be obtained based on the data in Tables13 and 14: the recovery potential of lead is 86.9%, that of pure sulfuric acid is 85%, and that of plastic is 87.7%.Taking 2017, for example, the waste quantity of lead-acid batteries used in electric bicycles is about 110 million KVAH, which contains 3,000 tons of lead. As the recovery potential of lead is 86.9%, recoverable lead is 2,607 tons. According to the international lead price of USD2, 600 per ton in 2017, the economic value is over USD6.7 million. The lead-acid battery recovery industry thus has enormous economic benefit.


## 6. Conclusions

In the thesis, through statistical analysis of the data in the electric bicycle industry, with the output of electric bicycles as the entry point, we have collected import and export data of electric tricycles, lithium battery powered bicycles, and electric bicycles. And based on the characteristics of the electric bicycle industry, as there are currently two main power batteries used in the electric bicycle industry, lead-acid batteries and lithium batteries, we have eliminated the output of lithium battery powered electric bicycles and taken into account the import and export value of electric bicycles and have finally obtained the annual net increment of lead-acid battery powered electric bicycles through calculation. With the annual net increment of lead-acid battery powered electric bicycles as the basic data to study the lead-acid batteries used in electric bicycles, we have then obtained the annual net increment of lead-acid batteries used in electric bicycles and forecasted increment in 2018-2022. Then, with the “market supply A model” and the “Stanford Model”, we have estimated the quantity of discarded lead-acid batteries used in electric bicycles between 2000 and 2022, respectively, and based on the proportion of raw materials contained in lead-acid batteries and the proportion between reclaimed and discarded lead-acid batteries, we have estimated the recovery potential of waste lead-acid batteries in 2000-2022. We estimate that the lead-acid batteries used in electric bicycles only have great recovery potential and there are abundant potential resources for recovery.(1) Based on the forecast of the output of lead-acid batteries in 2018-2022, the output of lead-acid batteries tends to fall significantly. As shown by the data, due to restrictions of economic environment and environmental protection policy, the electric bicycles using lead-acid batteries as power will be faced with a big risk of elimination, while the lithium battery powered bicycles that currently only account for 10% of the output of the electric bicycle industry show great development momentum. The storage battery manufacturers that mainly produce lead-acid batteries supplied to electric bicycles will face transformation and upgrading.(2) The implementation of the mandatory national standardTechnical Code for Safety of Electric Bicycles and the rise of lithium battery powered electric bicycles will jointly force lead-acid battery powered electric bicycles to make technological innovation. Lithium batteries will gradually replace lead-acid batteries and become main power source of electric bicycles, and a large number of waste lead-acid batteries will (before end of service life) be eliminated and discarded. How to properly recycle and dispose waste lead-acid batteries will be a big challenge.(3) According to the research data presented in the thesis, waste lead-acid batteries have great economic benefit and environmental protection benefit. However, the recovery industry is currently faced with the dilemma of how to get rid of the recovery of lead-acid batteries used in electric bicycles by “irregulars” such as petty dealers, eliminate illegal smelting of secondary lead and improper disposal of waste sulfuric acid, improve the recovery quantity by regular secondary enterprises through regular channels, increase circulation of lead resources, and ensure normal development of secondary lead enterprises. Those will be difficulties in government management. “Extended Producer Responsibility” (EPR) [56] will play one of the most important roles to solve those difficulties.


## 7. Limitations and Prospects

Limited by data, the calculation results in the thesis are not obtained directly using the data of lead-acid batteries, so there is still some uncertainty in the waste quantity of lead-acid batteries and the forecast of their recovery potential, and the deviation between the waste quantity of lead-acid batteries forecasted using models and the actual generation data is unavoidable. Moreover, the service life of lead-acid batteries is critical to the forecast of waste quantity. However, their service life is affected by many factors such as whether the charger is matched, whether the user uses the battery correctly and the quality of the battery itself. In future research, we will further improve data accuracy and adjust the adaptability of models.



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*Source: 6783190-2018-11-11.xml*